diff --git a/teachopencadd/talktorials/018_machine_learning_splitting_schemes/data/EGFR_compounds_lipinski_timeseries.csv b/teachopencadd/talktorials/018_machine_learning_splitting_schemes/data/EGFR_compounds_lipinski_timeseries.csv
new file mode 100644
index 00000000..722b3f86
--- /dev/null
+++ b/teachopencadd/talktorials/018_machine_learning_splitting_schemes/data/EGFR_compounds_lipinski_timeseries.csv
@@ -0,0 +1,4494 @@
+,molecule_chembl_id,IC50,units,document_year,smiles,pIC50,molecular_weight,n_hba,n_hbd,logp,ro5_fulfilled
+0,CHEMBL63786,3,nM,1996.0,Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1,11.522878745280336,349.021459484,3,1,5.289100000000002,True
+1,CHEMBL53711,6,nM,1998.0,CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,11.221848749616356,343.04325754800004,5,1,3.5969000000000015,True
+2,CHEMBL35820,6,nM,1997.0,CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC,11.221848749616356,387.05823891599994,5,1,4.933300000000004,True
+3,CHEMBL66031,8,nM,1999.0,Brc1cccc(Nc2ncnc3cc4[nH]cnc4cc23)c1,11.096910013008056,339.01195742000004,4,2,4.012200000000001,True
+4,CHEMBL53753,8,nM,1999.0,CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,11.096910013008056,329.02760748400004,5,2,3.572600000000002,True
+5,CHEMBL176582,0.01,nM,1996.0,Cn1cnc2cc3ncnc(Nc4cccc(Br)c4)c3cc21,11.0,353.027607484,5,1,4.0226000000000015,True
+6,CHEMBL174426,25,nM,1996.0,Cn1cnc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,10.602059991327963,353.02760748400004,5,1,4.022600000000002,True
+7,CHEMBL29197,25,nM,1997.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OC,10.602059991327963,359.02693878799994,5,1,4.153100000000003,True
+8,CHEMBL1243316,0.03,nM,2010.0,C#CCNC/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cc1OCC,10.522878745280336,477.13678081200004,6,3,4.758780000000003,True
+9,CHEMBL363815,0.037000000000000005,nM,2005.0,C=CC(=O)Nc1ccc2ncnc(Nc3cc(Cl)c(Cl)cc3F)c2c1,10.431798275933003,376.029394552,4,2,4.943800000000002,True
+10,CHEMBL3613702,0.037000000000000005,nM,2015.0,C=CC(=O)Nc1ccc2ncnc(Nc3cc(F)c(Cl)c(Cl)c3)c2c1,10.431798275933003,376.029394552,4,2,4.943800000000001,True
+11,CHEMBL275762,0.07,nM,2005.0,O=C(CCl)Nc1ccc2ncnc(Nc3cc(Cl)c(Cl)cc3F)c2c1,10.154901959985743,397.9904222,4,2,4.996600000000002,True
+12,CHEMBL327307,0.07200000000000001,nM,1996.0,COc1cc2ncnc(Nc3ccc(Br)c(Br)c3)c2cc1OC,10.142667503568733,436.937450856,5,1,4.915600000000003,True
+13,CHEMBL53428,0.09,nM,1997.0,CN(C)c1cc2ncnc(Nc3cccc(Br)c3)c2cn1,10.045757490560677,343.04325754800004,5,1,3.5969000000000015,True
+14,CHEMBL55729,0.1,nM,1996.0,Nc1ccc2cncnc2c1,10.0,145.063997224,3,1,1212,True
+15,CHEMBL420624,0.1,nM,1997.0,Nc1ccc2c(Nc3cccc(Br)c3)ncnc2c1,10.0,314.01670845200005,4,2,3.7181000000000015,True
+16,CHEMBL190094,0.11,nM,2005.0,CN(C)C/C=C/C(=O)Nc1ccc2ncnc(Nc3cc(Cl)c(Cl)cc3F)c2c1,9.958607314841776,433.087243776,5,2,4.875600000000003,True
+17,CHEMBL328216,0.12,nM,1995.0,Nc1cc2ncnc(Nc3cccc(Br)c3)c2cc1N,9.920818753952377,329.02760748400004,5,3,3.300300000000001,True
+18,CHEMBL3930620,0.12,nM,2017.0,O=C(CCCCCCn1cc(-c2ccc3ncnc(Nc4cccc(Cl)c4F)c3c2)nn1)NO,9.920818753952377,483.1585788760001,8,3,4.880300000000003,True
+19,CHEMBL193160,0.12,nM,2005.0,O=C(CCl)Nc1ccc2ncnc(Nc3cccc(I)c3)c2c1,9.920818753952377,437.97443668399995,4,2,4.155300000000002,True
+20,CHEMBL3892310,0.13,nM,2015.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCC1C2COCC21,9.886056647693165,511.178645624,7,2,4.493400000000002,True
+21,CHEMBL51853,0.13,nM,1998.0,Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.886056647693165,315.01195742000004,5,2,3.113100000000001,True
+22,CHEMBL54400,0.13,nM,1997.0,CNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,9.886056647693165,329.02760748400004,5,2,3.5726000000000013,True
+23,CHEMBL417478,0.16,nM,2000.0,C=CC(=O)Nc1nc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1/C=C/CCN1CCOCC1,9.795880017344077,482.16332990800004,7,2,4.420900000000004,True
+24,CHEMBL3357641,0.16,nM,2014.0,CN(C)C/C=C(\F)C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,9.795880017344077,503.153573748,7,2,4.687100000000003,True
+25,CHEMBL93032,0.17,nM,1995.0,Oc1cc2ncnc(Nc3cccc(Br)c3)c2cc1O,9.769551078621726,330.99563865999994,5,3,3.5471000000000017,True
+26,CHEMBL592617,0.17,nM,2010.0,N#CCC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.769551078621726,381.022522104,5,2,3.988080000000002,True
+27,CHEMBL418967,0.17,nM,1996.0,CCCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCCC,9.769551078621726,415.08953904399993,5,1,5.713500000000004,True
+28,CHEMBL2031302,0.18,nM,2012.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCC,9.744727494896694,386.094581652,5,2,4.6891000000000025,True
+29,CHEMBL166093,0.18,nM,1998.0,OCC(O)CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.744727494896694,389.0487368520001,7,4,2.2959999999999994,True
+30,CHEMBL166154,0.19,nM,1998.0,CNc1cc2c(Nc3cccc(Cl)c3)ncnc2cn1,9.721246399047173,285.078123064,5,2,3.4635000000000007,True
+31,CHEMBL165864,0.19,nM,1998.0,OCCNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.721246399047173,359.0381721680001,6,3,2.9351000000000003,True
+32,CHEMBL3357634,0.2,nM,2014.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C(F)=C/CN(C)C,9.69897000433602,447.127359,6,2,4.528000000000004,True
+33,CHEMBL437879,0.20800000000000002,nM,2005.0,COc1cc2ncnc(Nc3cc(Cl)c(Cl)cc3F)c2cc1OC,9.681936665037238,367.02906020399996,5,1,4.836500000000003,True
+34,CHEMBL161956,0.22,nM,1998.0,CN(CCO)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.657577319177793,373.0538222320001,6,2,2.9594000000000005,True
+35,CHEMBL2031300,0.23,nM,2012.0,CN1CCN(CCC(=O)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)CC1,9.638272163982409,468.12732152,6,2,3.7119000000000018,True
+36,CHEMBL127041,0.24,nM,1997.0,OCCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,9.619788758288394,359.038172168,6,3,2.9351000000000003,True
+37,CHEMBL316064,0.24,nM,1996.0,COc1cc2ncnc(Nc3cccc(C(F)(F)F)c3)c2cc1OC,9.619788758288394,349.10381134799997,5,1,4.409400000000002,True
+38,CHEMBL328955,0.25,nM,1996.0,Nc1ccc2c(Nc3cccc(Cl)c3)ncnc2c1,9.602059991327963,270.067224032,4,2,3.609000000000001,True
+39,CHEMBL52913,0.25,nM,1999.0,C=CC(=O)Nc1ccc2c(Nc3cccc(Cl)c3)ncnc2c1,9.602059991327963,324.07778871600004,4,2,4.151300000000002,True
+40,CHEMBL3357639,0.26,nM,2014.0,O=C(Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1)/C(F)=C/CN1CCOCC1,9.585026652029182,545.1641384320001,8,2,4.4577000000000035,True
+41,CHEMBL3360608,0.26,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc(OCCCCn4ccnc4[N+](=O)[O-])c(OC)cc23)c1,9.585026652029182,458.170253184,9,1,4.327200000000003,True
+42,CHEMBL3929484,0.27,nM,2017.0,O=C(CCCCCn1cc(-c2ccc3ncnc(Nc4cccc(Cl)c4F)c3c2)nn1)NO,9.568636235841012,469.1429288120001,8,3,4.490200000000002,True
+43,CHEMBL152905,0.27,nM,1999.0,Nc1ccc2sc3c(Nc4cccc(Br)c4)ncnc3c2c1,9.568636235841012,369.9887794520001,5,2,4.932800000000002,True
+44,CHEMBL2031303,0.27,nM,2012.0,CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)CCN(C)C,9.568636235841012,431.15243087600004,6,2,4.454800000000003,True
+45,CHEMBL3357635,0.27,nM,2014.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C(F)=C/CN1CCCCC1,9.568636235841012,487.158659128,6,2,5.452300000000005,True
+46,CHEMBL2031298,0.27,nM,2012.0,O=C(CCN1CCCCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.568636235841012,453.116422488,5,2,4.950400000000004,True
+47,CHEMBL128468,0.28,nM,1997.0,O=C(O)CCCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,9.55284196865778,401.048736852,6,3,3.8076000000000016,True
+48,CHEMBL2031297,0.28,nM,2012.0,CN(C)CCC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.55284196865778,413.08512236,5,2,4.026100000000001,True
+49,CHEMBL355816,0.28,nM,1998.0,O=C(O)CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.55284196865778,373.0174367240001,6,3,3.027400000000001,True
+50,CHEMBL426580,0.29,nM,1996.0,Cc1nc2cc3c(Nc4cccc(Br)c4)ncnc3cc2[nH]1,9.537602002101043,353.02760748400004,4,2,4.320620000000002,True
+51,CHEMBL2031305,0.29,nM,2012.0,CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)CCN1CCOCC1,9.537602002101043,473.16299556,7,2,4.225400000000003,True
+52,CHEMBL203644,0.3,nM,2006.0,CC#CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,9.522878745280336,355.0636158720001,5,2,3.5227000000000013,True
+53,CHEMBL3623290,0.3,nM,2015.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OC(=O)N1CCN(C)C[C@H]1C,9.522878745280336,459.147345496,7,1,4.309200000000003,True
+54,CHEMBL3357644,0.3,nM,2014.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C(F)=C\CN1CCOCC1,9.522878745280336,489.137923684,7,2,4.298600000000003,True
+55,CHEMBL4290812,0.3,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N1CCN(C)CC1,9.522878745280336,509.2539232320001,8,2,4.4189000000000025,True
+56,CHEMBL3357642,0.31,nM,2014.0,CN(C)C/C=C(/F)C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,9.508638306165727,503.153573748,7,2,4.687100000000003,True
+57,CHEMBL3360603,0.31,nM,2014.0,COc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCCn1ccnc1[N+](=O)[O-],9.508638306165727,486.12185902,9,1,5.138400000000003,True
+58,CHEMBL3360606,0.32,nM,2014.0,COc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCOCCn1ccnc1[N+](=O)[O-],9.494850021680094,502.11677363999996,10,1,4.374800000000003,True
+59,CHEMBL366580,0.34,nM,1996.0,Brc1cccc(Nc2ncnc3cc4c[nH]nc4cc23)c1,9.468521082957745,339.01195742000004,4,2,4.012200000000001,True
+60,CHEMBL163369,0.35,nM,1998.0,OCCN(CCO)CCCNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.455931955649724,460.1222361400001,8,4,2.6194999999999995,True
+61,CHEMBL91980,0.35,nM,1996.0,Nc1ccc2c(Nc3cccc(I)c3)ncnc2c1,9.455931955649724,362.00284435200007,4,2,3.560200000000001,True
+62,CHEMBL603266,0.36,nM,2010.0,O=C(Cn1sccc1=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.443697499232712,455.00515778799996,7,2,3.9978000000000016,True
+63,CHEMBL39320,0.37,nM,1997.0,Cn1ncc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,9.431798275933003,353.02760748400004,5,1,4.022600000000002,True
+64,CHEMBL599863,0.37,nM,2010.0,O=C(CNC(=O)Oc1ccccc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.431798275933003,491.0593015360001,6,3,4.863000000000003,True
+65,CHEMBL3895468,0.37,nM,2015.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCC12COCC1C2,9.431798275933003,511.178645624,7,2,4.637500000000003,True
+66,CHEMBL2447950,0.38,nM,2005.0,CCOc1cc2ncnc(Nc3cccc(Cl)c3)c2cc1OCC.Cl,9.42021640338319,379.085432208,5,1,5.246000000000004,True
+67,CHEMBL2029434,0.38,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C(C)C)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,9.42021640338319,556.2910370120001,8,2,4.587200000000004,True
+68,CHEMBL4282543,0.4,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1OCCN1CCN(C)CC1,9.397940008672037,553.28013798,9,2,4.293300000000003,True
+69,CHEMBL3901622,0.4,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccc(NCCN(C)C)cc3)cc12)c1ccccc1,9.397940008672037,401.221560484,6,2,5.036400000000004,True
+70,CHEMBL51741,0.4,nM,1999.0,C=CC(=O)Nc1ccc2ncnc(N3CCc4ccc(Br)cc43)c2c1,9.397940008672037,394.0429232,4,1,4.211000000000003,True
+71,CHEMBL3759317,0.4,nM,2016.0,COc1cc(C(=O)NCCN(C)C)cc(OC)c1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,9.397940008672037,505.2147608520001,8,2,4.840000000000004,True
+72,CHEMBL4112924,0.4,nM,2015.0,CO[C@@H]1COC2C1OC[C@H]2Oc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C)C,9.397940008672037,557.1841249280001,9,2,3.7822000000000013,True
+73,CHEMBL2029429,0.41,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(OC)c4)nc32)c1,9.387216143280265,528.2597368840001,8,2,3.808600000000003,True
+74,CHEMBL1204199,0.41,nM,2005.0,CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC.Cl,9.387216143280265,423.03491662799996,5,1,5.355100000000004,True
+75,CHEMBL31815,0.42,nM,2000.0,C=CC(=O)Nc1ccc2ncnc(Nc3cccc(C)c3)c2c1,9.3767507096021,304.132411132,4,2,3.8063200000000013,True
+76,CHEMBL2029428,0.43,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4)nc32)c1,9.366531544420411,498.2491722000001,7,2,3.8000000000000025,True
+77,CHEMBL188762,0.43,nM,2008.0,CCC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.366531544420411,370.0429232,4,2,4.484400000000003,True
+78,CHEMBL39337,0.44,nM,1997.0,Brc1cccc(Nc2ncnc3cc4[nH]ncc4cc23)c1,9.356547323513812,339.01195742,4,2,4.012200000000001,True
+79,CHEMBL40734,0.44,nM,1997.0,Brc1cccc(Nc2ncnc3cc4[nH]ccc4cc23)c1,9.356547323513812,338.01670845200005,3,2,4.617200000000001,True
+80,CHEMBL351629,0.44,nM,1998.0,CN(CC(=O)O)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.356547323513812,387.0330867880001,6,2,3.051700000000001,True
+81,CHEMBL162821,0.45,nM,1998.0,CNc1cc2c(Nc3cccc(C)c3)ncnc2cn1,9.346787486224656,265.13274548,5,2,3.118520000000001,True
+82,CHEMBL443523,0.45,nM,1999.0,C=CC(=O)Nc1ccc2c(Nc3cccc(Br)c3)ncnc2c1,9.346787486224656,368.0272731360001,4,2,4.260400000000002,True
+83,CHEMBL304271,0.45,nM,2002.0,CCN(CC)CC(O)CNC(=O)c1cc(C)c(/C=C2\C(=O)Nc3ncnc(Nc4ccc(F)c(Cl)c4)c32)[nH]1,9.346787486224656,541.2004436880001,7,5,3.57442,True
+84,CHEMBL3355875,0.47,nM,2015.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCCn1ccnc1[N+](=O)[O-],9.327902142064282,486.12185902,9,1,5.138400000000003,True
+85,CHEMBL539822,0.47,nM,1999.0,Cl.Nc1ccc2c(c1)sc1c(Nc3cccc(Br)c3)ncnc12,9.327902142064282,405.96545716400004,5,2,5.354600000000002,True
+86,CHEMBL3818015,0.47,nM,2016.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1NC(=O)[C@@H]1COC(=O)N1,9.327902142064282,457.03856609199994,7,3,3.1914000000000007,True
+87,CHEMBL3360609,0.47,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc(OCCCCCn4ccnc4[N+](=O)[O-])c(OC)cc23)c1,9.327902142064282,472.185903248,9,1,4.717300000000003,True
+88,CHEMBL54088,0.48,nM,1999.0,C=CC(=O)Nc1cc2c(Nc3cccc(C)c3)ncnc2cn1,9.318758762624412,305.12766010000007,5,2,3.201320000000001,True
+89,CHEMBL2021576,0.49,nM,2010.0,O=C(O)[C@H]1O[C@@H]1C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.309803919971486,428.01201699600006,6,3,2.9264,True
+90,CHEMBL3355881,0.49,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(OCCCCCn4ccnc4[N+](=O)[O-])cc23)c1,9.309803919971486,472.185903248,9,1,4.717300000000003,True
+91,CHEMBL3360617,0.49,nM,2014.0,COc1cc2c(Nc3cccc(Br)c3)ncnc2cc1OCCCn1ccnc1[N+](=O)[O-],9.309803919971486,498.06511518800005,9,1,4.718300000000004,True
+92,CHEMBL203599,0.5,nM,2006.0,CN1CCN(CCC#CC(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3cn2)CC1,9.30102999566398,467.1636642560001,7,2,3.1403000000000016,True
+93,CHEMBL3758582,0.5,nM,2016.0,COc1ccc(C(=O)NCCN(C)C)cc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,9.30102999566398,475.20419616800007,7,2,4.831400000000004,True
+94,CHEMBL4071474,0.5,nM,2018.0,C=CC(=O)N1CC[C@H](N2C(=O)N(c3ccccc3Cl)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,9.30102999566398,586.25715004,7,1,4.667320000000004,True
+95,CHEMBL2021575,0.5,nM,2010.0,O=C(O)[C@@H]1O[C@H]1C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.30102999566398,428.01201699600006,6,3,2.9264,True
+96,CHEMBL2347958,0.5,nM,2018.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@@H]1CCOC1,9.30102999566398,485.16299556,7,2,4.389900000000002,True
+97,CHEMBL3758770,0.5,nM,2016.0,COc1cc(C(=O)NCCN(C)C)ccc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,9.30102999566398,475.20419616800007,7,2,4.831400000000004,True
+98,CHEMBL3355882,0.5,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(OCCCCCCn4ccnc4[N+](=O)[O-])cc23)c1,9.30102999566398,486.201553312,9,1,5.107400000000005,True
+99,CHEMBL2031304,0.51,nM,2012.0,CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)CCN1CCCCC1,9.292429823902065,471.18373100400004,6,2,5.379100000000005,True
+100,CHEMBL126791,0.51,nM,1997.0,Brc1cccc(Nc2ncnc3cc(NCCCn4ccnc4)ncc23)c1,9.292429823902065,423.0807056760001,7,2,4.229600000000001,True
+101,CHEMBL2031299,0.51,nM,2012.0,O=C(CCN1CCOCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.292429823902065,455.09568704400004,6,2,3.796700000000002,True
+102,CHEMBL3901296,0.51,nM,2015.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC[C@@]12COC[C@@H]1C2,9.292429823902065,511.178645624,7,2,4.637500000000003,True
+103,CHEMBL3357643,0.53,nM,2014.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C(F)=C/CN1CCOCC1,9.275724130399214,489.137923684,7,2,4.298600000000003,True
+104,CHEMBL49986,0.54,nM,1999.0,C=CC(=O)Nc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,9.267606240177033,369.022522104,5,2,3.655400000000002,True
+105,CHEMBL3360611,0.54,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc(OCCOCCn4ccnc4[N+](=O)[O-])c(OC)cc23)c1,9.267606240177033,474.16516780399996,10,1,3.5636000000000028,True
+106,CHEMBL3355880,0.56,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(OCCCCn4ccnc4[N+](=O)[O-])cc23)c1,9.251811972993801,458.170253184,9,1,4.327200000000003,True
+107,CHEMBL165547,0.56,nM,1998.0,CN(CC(O)CO)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.251811972993801,403.0643869160001,7,3,2.3202999999999996,True
+108,CHEMBL3360610,0.57,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc(OCCCCCCn4ccnc4[N+](=O)[O-])c(OC)cc23)c1,9.244125144327509,486.201553312,9,1,5.107400000000005,True
+109,CHEMBL2029435,0.58,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C3CC3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,9.236572006437065,554.2753869480001,8,2,4.341200000000003,True
+110,CHEMBL4282954,0.6,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N1CCOCC1,9.221848749616356,496.222288756,8,2,4.503700000000003,True
+111,CHEMBL378144,0.6,nM,2006.0,C#CC(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.221848749616356,367.0068720400001,5,2,3.1026000000000016,True
+112,CHEMBL3891846,0.6,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccc(NCCN4CCCCC4)cc3)cc12)c1ccccc1,9.221848749616356,441.252860612,6,2,5.960700000000005,True
+113,CHEMBL4105621,0.6,nM,2017.0,C=CC(=O)Nc1cc(Cl)cc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,9.221848749616356,559.2098655000001,9,2,4.371020000000003,True
+114,CHEMBL127086,0.61,nM,1997.0,O=C(O)CCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,9.214670164989233,387.033086788,6,3,3.4175000000000013,True
+115,CHEMBL1204262,0.64,nM,2005.0,CCOc1cc2ncnc(Nc3cccc(I)c3)c2cc1OCC.Cl,9.193820026016114,471.021052528,5,1,5.197200000000003,True
+116,CHEMBL162622,0.65,nM,1998.0,Brc1cccc(Nc2ncnc3cnc(NCCN4CCOCC4)cc23)c1,9.187086643357144,428.096021392,7,2,3.2750000000000012,True
+117,CHEMBL3360607,0.65,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc(OCCCn4ccnc4[N+](=O)[O-])c(OC)cc23)c1,9.187086643357144,444.15460312,9,1,3.9371000000000027,True
+118,CHEMBL3920583,0.65,nM,2017.0,O=C(CCCCCn1cc(-c2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)nn1)NO,9.187086643357144,469.1429288120001,8,3,4.490200000000003,True
+119,CHEMBL1204168,0.66,nM,2005.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OC.Cl,9.18045606445813,395.00361649999996,5,1,4.574900000000003,True
+120,CHEMBL3355878,0.66,nM,2015.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCCCn1ccnc1[N+](=O)[O-],9.18045606445813,498.065115188,9,1,4.718300000000004,True
+121,CHEMBL3814257,662,nM,2016.0,CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,9.1791420105603,330.06836690399996,4,2,4.124300000000002,True
+122,CHEMBL317925,0.67,nM,1996.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2c(OC)c1OC,9.173925197299171,389.0375034719999,6,1,4.161700000000003,True
+123,CHEMBL3357636,0.67,nM,2014.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C(F)=C\CN1CCCCC1,9.173925197299171,487.158659128,6,2,5.452300000000005,True
+124,CHEMBL2031307,0.68,nM,2012.0,CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)CCN(C)C,9.167491087293763,455.15243087600004,6,2,4.931480000000004,True
+125,CHEMBL3957055,0.69,nM,2017.0,O=C(CCCCCCn1cc(-c2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)nn1)NO,9.161150909262744,483.1585788760001,8,3,4.880300000000004,True
+126,CHEMBL92937,0.69,nM,1996.0,CNc1cc2ncnc(Nc3cccc(Br)c3)c2cc1N,9.161150909262744,343.04325754800004,5,3,3.759800000000001,True
+127,CHEMBL280757,0.69,nM,2000.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Br)c3)c2c1,9.161150909262744,386.01785132400005,4,2,4.399500000000002,True
+128,CHEMBL4279016,0.7,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N1CCC(N2CCN(C)CC2)CC1,9.154901959985743,592.32742252,9,2,4.883300000000004,True
+129,CHEMBL3909201,0.7,nM,2012.0,C=CC(=O)N1CC(Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C1,9.154901959985743,446.09572452400005,6,1,4.0892000000000035,True
+130,CHEMBL4294211,0.7,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N1CCC(N2CCOCC2)CC1,9.154901959985743,579.295788044,9,2,4.968100000000004,True
+131,CHEMBL4293145,0.7,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1O[C@H]1CCOC1,9.154901959985743,497.206304344,8,2,4.834800000000003,True
+132,CHEMBL4287401,0.7,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1OCCN1CCOCC1,9.154901959985743,540.248503504,9,2,4.3781000000000025,True
+133,CHEMBL4284071,0.71,nM,2017.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(CN4CCOCC4)cc3)ncc2Cl)c1,9.148741651280924,464.17275172,7,3,4.573900000000003,True
+134,CHEMBL289213,0.72,nM,1997.0,CN(CC(=O)O)Cc1c[nH]c2cc3ncnc(Nc4cccc(Br)c4)c3cc12,9.142667503568733,439.06438691600005,5,3,4.133600000000002,True
+135,CHEMBL54091,0.72,nM,1999.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Br)c3)ncnc2cn1,9.142667503568733,387.0131002920001,5,2,3.794500000000002,True
+136,CHEMBL339416,0.74,nM,1997.0,[O-][N+]1(CCCNc2cc3ncnc(Nc4cccc(Br)c4)c3cn2)CCOCC1,9.130768280269024,458.10658607600004,7,2,3.6777000000000024,True
+137,CHEMBL28418,0.75,nM,2000.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2n1,9.1249387366083,343.06361587200007,5,2,3.6854000000000013,True
+138,CHEMBL31373,0.75,nM,2000.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,9.1249387366083,342.068366904,4,2,4.290400000000002,True
+139,CHEMBL3360602,0.77,nM,2014.0,COc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCn1ccnc1[N+](=O)[O-],9.113509274827518,472.106208956,9,1,4.748300000000003,True
+140,CHEMBL53555,0.77,nM,1999.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,9.113509274827518,343.06361587200007,5,2,3.6854000000000013,True
+141,CHEMBL3814882,772,nM,2016.0,O=C(NCCN1CCCCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,9.112382699664265,468.12732152,5,3,4.743300000000003,True
+142,CHEMBL162142,0.78,nM,1998.0,Brc1cccc(Nc2ncnc3cnc(NCCc4c[nH]cn4)cc23)c1,9.10790539730952,409.06505561200004,6,3,3.9086,True
+143,CHEMBL53300,0.79,nM,1996.0,Nc1ccc2ncncc2c1,9.102372908709556,145.063997224,3,1,1212,True
+144,CHEMBL4087740,0.8,nM,2017.0,C=CC(=O)Nc1cc(F)cc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,9.096910013008056,543.2394160400002,9,2,3.856720000000003,True
+145,CHEMBL3633143,0.8,nM,2017.0,C=CC(=O)Nc1cccc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,9.096910013008056,525.2488378520001,9,2,3.717620000000003,True
+146,CHEMBL1243345,0.8,nM,2010.0,CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C)CCF,9.096910013008056,499.158659128,6,2,5.437280000000004,True
+147,CHEMBL36727,0.8,nM,1997.0,Cn1ccc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,9.096910013008056,352.03235851600004,4,1,4.627600000000002,True
+148,CHEMBL3814959,0.8029999999999999,nM,2016.0,NC(=O)Nc1ccc2ncnc(Nc3ccc(Br)cc3)c2c1,9.095284454721321,357.022522104,4,3,3.626500000000002,True
+149,CHEMBL3360620,0.82,nM,2014.0,COc1cc2c(Nc3cccc(Br)c3)ncnc2cc1OCCOCCn1ccnc1[N+](=O)[O-],9.086186147616283,528.075679872,10,1,4.344800000000004,True
+150,CHEMBL3814211,0.8540000000000001,nM,2016.0,NC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,9.068542129310996,331.063615872,4,3,3.656500000000001,True
+151,CHEMBL3355874,0.89,nM,2015.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCn1ccnc1[N+](=O)[O-],9.050609993355089,472.106208956,9,1,4.748300000000003,True
+152,CHEMBL96065,0.89,nM,1996.0,COc1cc2ncnc(Nc3cccc(I)c3)c2cc1OC,9.050609993355089,407.01307468799996,5,1,3.9952000000000023,True
+153,CHEMBL205059,0.9,nM,2006.0,O=C(C#CCCN1CCCCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,9.045757490560677,452.15276522400006,6,2,4.378800000000003,True
+154,CHEMBL3759199,0.9,nM,2016.0,COc1cccc(OC)c1-c1cc2c(N[C@H](CO)c3ccccc3)ncnc2s1,9.045757490560677,407.13036253200005,7,2,4.521000000000002,True
+155,CHEMBL3759369,0.9,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3cccc(C(=O)NCCN(C)C)c3)cc12)c1ccccc1,9.045757490560677,445.19363148400004,6,2,4.8228000000000035,True
+156,CHEMBL3233785,0.9,nM,2014.0,O=C(/C=C/CN1CC2CCC1C(=O)C2)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,9.045757490560677,485.108851812,7,2,4.775500000000003,True
+157,CHEMBL3622664,0.9,nM,2015.0,CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CNC1CC1,9.045757490560677,455.15243087600004,6,3,4.811300000000004,True
+158,CHEMBL3946096,0.9,nM,2012.0,C=CC(=O)N1CC[C@@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@@H]1C(=O)NC,9.045757490560677,531.148488368,7,2,3.9840000000000027,True
+159,CHEMBL53690,0.91,nM,1999.0,C=CC(=O)Nc1ccc2ncnc(Nc3cccc(C(F)(F)F)c3)c2c1,9.040958607678906,358.10414569600005,4,2,4.516700000000002,True
+160,CHEMBL338114,0.91,nM,1997.0,Brc1cccc(Nc2ncnc3cc(NCCc4c[nH]cn4)ncc23)c1,9.040958607678906,409.0650556120001,6,3,3.9086,True
+161,CHEMBL126372,0.92,nM,1997.0,OCC(O)CNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,9.036212172654443,389.048736852,7,4,2.2960000000000003,True
+162,CHEMBL165630,0.93,nM,1998.0,OCCN(CCO)CCNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,9.031517051446064,446.1065860760001,8,4,2.229399999999999,True
+163,CHEMBL189779,0.94,nM,2005.0,CN(C)C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(I)c3)c2c1,9.0268721464003,473.07125826,5,2,4.034300000000003,True
+164,CHEMBL31816,0.95,nM,2000.0,C=CC(=O)Nc1nc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,9.022276394711152,373.07418055600004,6,2,3.6940000000000017,True
+165,CHEMBL328106,0.96,nM,1996.0,COc1cc2ncnc(Nc3ccc(Br)cc3)c2cc1OC,9.017728766960431,359.02693878799994,5,1,4.153100000000003,True
+166,CHEMBL31570,0.97,nM,2000.0,C=CC(=O)Nc1nc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCOC,9.013228265733757,417.100395304,7,2,3.710600000000002,True
+167,CHEMBL3655347,1.0,nM,2013.0,CC(C)N(C)C/C=C/C(=O)N1CCc2c(oc3ncnc(Nc4ccc(F)c(Cl)c4)c23)C1,9.0,457.16808094000004,6,1,4.540000000000004,True
+168,CHEMBL3655342,1.0,nM,2013.0,CN(C)C(=O)N1CCN(C/C=C/C(=O)N2CCc3c(sc4ncnc(Nc5ccc(F)c(Cl)c5)c34)C2)CC1,9.0,557.1776000680001,7,1,3.967500000000002,True
+169,CHEMBL3655341,1.0,nM,2013.0,COCCN(C/C=C/C(=O)N1CCc2c(sc3ncnc(Nc4ccc(F)c(Cl)c4)c23)C1)CCOC,9.0,533.166366688,8,1,4.263100000000003,True
+170,CHEMBL3655340,1.0,nM,2013.0,CN1CCC[C@H]1/C=C/C(=O)N1CCc2c(sc3ncnc(Nc4ccc(F)c(Cl)c4)c23)C1,9.0,471.12958725600004,6,1,4.762500000000004,True
+171,CHEMBL271705,1.0,nM,2008.0,Clc1cc(Nc2ncnc3[nH]nc(OCCN4CCOCC4)c23)ccc1OCc1ccccn1,9.0,481.162915308,9,2,3.4349000000000016,True
+172,CHEMBL312753,1.0,nM,2004.0,OCc1ccc(-c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,9.0,372.10448213200004,5,3,5.075500000000003,True
+173,CHEMBL3655350,1.0,nM,2013.0,CC(C)C(C)C/C=C/C(=O)N1CCc2c(sc3ncnc(Nc4cc(O)cc(Cl)c4)c23)C1,9.0,470.15432478400004,6,2,5.917000000000006,True
+174,CHEMBL308498,1.0,nM,2004.0,CC(C)(CO)NCc1ccc(-c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,9.0,443.17798142000004,6,4,5.443700000000003,True
+175,CHEMBL3655338,1.0,nM,2013.0,CC(C)(CN1CCOCC1)NC/C=C/C(=O)N1CCc2c(sc3ncnc(Nc4ccc(F)c(Cl)c4)c23)C1,9.0,558.1980011640001,8,2,4.368700000000002,True
+176,CHEMBL3655336,1.0,nM,2013.0,O=C(/C=C/CN1CCCOCC1)N1CCc2c(sc3ncnc(Nc4ccc(F)c(Cl)c4)c23)C1,9.0,501.1401519400001,7,1,4.390600000000004,True
+177,CHEMBL3416592,1.0,nM,2015.0,COc1ccccc1-c1cc2c(N[C@H](CO)c3ccccc3)ncnc2s1,9.0,377.11979784800013,6,2,4.512400000000002,True
+178,CHEMBL30432,1.0,nM,2001.0,CN(C)c1cc2c(Nc3ccc4c(cnn4Cc4ccccc4)c3)ncnc2cn1,9.0,395.1858436720001,7,1,4.232400000000002,True
+179,CHEMBL3678946,1.0,nM,2015.0,CC(C)n1c(Nc2ccccc2)nc2cnc(Nc3ccc(C(=O)NC4CCN(C)CC4)cc3)nc21,9.0,484.269907644,8,3,4.7184000000000035,True
+180,CHEMBL4095447,1.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3cccc4ccccc34)c3c(N)ncnc32)C1,9.0,398.18550932400007,6,1,3.5782000000000016,True
+181,CHEMBL4090601,1.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc4ccccc4c3)c3c(N)ncnc32)C1,9.0,398.18550932400007,6,1,3.5782000000000016,True
+182,CHEMBL4064942,1.0,nM,2017.0,CN(C)C(=O)CSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,9.0,447.15290954400007,5,2,5.201700000000004,True
+183,CHEMBL4126630,1.0,nM,2018.0,C=CC(=O)Nc1cccc(-n2c(=O)n(C(C)C)c(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)c1,9.0,554.2753869480002,10,2,3.451620000000002,True
+184,CHEMBL213007,1.0,nM,2006.0,COc1cc2ncnc(Nc3cc(Cl)ccc3F)c2cc1OC1CCN(S(C)(=O)=O)CC1,9.0,480.10343208399996,7,1,3.977300000000003,True
+185,CHEMBL3674150,1.0,nM,2015.0,CC(C)n1c(Nc2ccccc2)nc2cnc(Nc3ccc(C(=O)NN4CCN(C)CC4)cc3F)nc21,9.0,503.2557348,9,3,3.9257000000000017,True
+186,CHEMBL121954,1.0,nM,1997.0,Oc1cccc(Nc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)c1,9.0,352.083936716,6,4,4.199100000000001,True
+187,CHEMBL3357640,1.0,nM,2014.0,O=C(Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1)/C(F)=C\CN1CCOCC1,9.0,545.1641384320001,8,2,4.4577000000000035,True
+188,CHEMBL76751,1.0,nM,2004.0,c1csc(-c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)c1,9.0,348.05033838400004,5,2,5.644700000000002,True
+189,CHEMBL3741490,1.0,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OCCO)c(OCCOC)cc23)c1,9.0,379.153206152,7,2,2.7510000000000012,True
+190,CHEMBL310853,1.0,nM,2004.0,c1csc(-c2cc3nccc(Nc4ccc5[nH]ccc5c4)c3s2)c1,9.0,347.055089416,4,2,6.2497000000000025,True
+191,CHEMBL415738,1.0,nM,1999.0,Cc1cccc(Nc2cc(NCCO)ncn2)c1,9.0,244.132411132,5,3,1.9328199999999995,True
+192,CHEMBL165574,1.0,nM,1998.0,Brc1cccc(Nc2ncnc3cnc(NCCCN4CCOCC4)cc23)c1,9.0,442.111671456,7,2,3.6651000000000016,True
+193,CHEMBL431977,1.0,nM,2004.0,NC(=O)C1CCN(Cc2ccc(-c3cc4nccc(Nc5ccc6[nH]ccc6c5)c4s3)cc2)CC1,9.0,481.19363148400004,5,3,5.885500000000004,True
+194,CHEMBL153573,1.0,nM,1999.0,Nc1cc2sc3c(Nc4cccc(Br)c4)ncnc3c2cc1F,9.0,387.97935764000005,5,2,5.071900000000001,True
+195,CHEMBL79215,1.0,nM,2004.0,c1ccc(NCCN(c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)n2cccc2)cc1,9.0,465.173564736,7,3,6.099500000000004,True
+196,CHEMBL2031296,1.01,nM,2016.0,CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.995678626217357,356.027273136,4,2,4.094300000000001,True
+197,CHEMBL1204305,1.05,nM,2005.0,COc1cc2ncnc(Nc3cccc(I)c3)c2cc1OC.Cl,8.978810700930062,442.9897524,5,1,4.4170000000000025,True
+198,CHEMBL3818547,1.06,nM,2016.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)[C@@H]1COC(=O)N1,8.97469413473523,431.07965986,7,3,3.221400000000001,True
+199,CHEMBL3814956,1.06,nM,2016.0,O=C(NCCN1CCCCC1)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,8.97469413473523,442.168415288,5,3,4.773300000000003,True
+200,CHEMBL3355879,1.08,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(OCCCn4ccnc4[N+](=O)[O-])cc23)c1,8.96657624451305,444.15460312,9,1,3.9371000000000027,True
+201,CHEMBL4099329,1.1,nM,2017.0,COc1ccc(N(C)c2nc(N)nc3c(Cc4ccccc4)c[nH]c23)cc1,8.958607314841776,359.17461029200007,5,2,3.9074000000000018,True
+202,CHEMBL4091569,1.1,nM,2017.0,OCCSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,8.958607314841776,406.12636044800007,5,3,5.105800000000004,True
+203,CHEMBL4209019,1.1,nM,2018.0,CN(C)C1CCN(c2ccc(Nc3cc4c(N5CCC(CO)CC5)nc(Nc5ccc(F)cc5)nc4cn3)nc2)CC1,8.958607314841776,571.3183350560001,10,3,4.785200000000004,True
+204,CHEMBL264382,1.1,nM,2002.0,Cc1cc(C(=O)NCCN2CCOCC2)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc4c(ccn4Cc4ccccc4)c3)c21,8.958607314841776,602.2753869480002,8,4,4.4144200000000025,True
+205,CHEMBL165788,1.1,nM,1998.0,CNc1cc2c(Nc3cccc(C(F)(F)F)c3)ncnc2cn1,8.958607314841776,319.104480044,5,2,3.8289000000000017,True
+206,CHEMBL358934,1.1,nM,1999.0,CCO.CNc1ccc2sc3c(Nc4cccc(Br)c4)ncnc3c2c1,8.958607314841776,430.0462943280001,6,3,5.390900000000002,True
+207,CHEMBL296168,1.1,nM,1999.0,C=CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2n1,8.958607314841776,369.022522104,5,2,3.655400000000002,True
+208,CHEMBL3970231,1.1,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)CC1,8.958607314841776,474.12702465200005,6,1,4.869400000000004,True
+209,CHEMBL3663926,1.1,nM,2015.0,C=CC(=O)Nc1cccc(Oc2cnc(C(N)=O)c(Nc3ccc(N4CCN(C)CC4)cc3)n2)c1,8.958607314841776,473.2175377240001,8,3,2.987700000000001,True
+210,CHEMBL162034,1.1,nM,1998.0,CN(C)CCNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.958607314841776,386.0854567080001,6,2,3.5044000000000004,True
+211,CHEMBL4206716,1.1,nM,2018.0,CN1CCN(c2ccc(Nc3cc4c(N5CCCCC5)nc(Nc5ccccc5)nc4cn3)nc2)CC1,8.958607314841776,495.28589205600014,9,2,4.649100000000003,True
+212,CHEMBL3663925,1.1,nM,2015.0,C=CC(=O)N1CCC(c2nc(Nc3ccc(N4CCC(N5CCN(C)CC5)CC4)c(C)c3)c(C(N)=O)nc2CC)CC1,8.958607314841776,574.3743727120001,8,2,3.2981200000000026,True
+213,CHEMBL437890,1.1,nM,2006.0,CN1CCN(CCC#CC(=O)Nc2cc3c(Nc4ccc(F)c(Br)c4)ncnc3cn2)CC1,8.958607314841776,511.11314867600015,7,2,3.2494000000000014,True
+214,CHEMBL3960853,1.1,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccc(NCCN4CCOCC4)cc3)cc12)c1ccccc1,8.958607314841776,443.232125168,7,2,4.807000000000004,True
+215,CHEMBL3655337,1.1,nM,2013.0,O=C(/C=C/CN1C2CCC1CC2)N1CCc2c(sc3ncnc(Nc4ccc(F)c(Cl)c4)c23)C1,8.958607314841776,497.1452373200001,6,1,5.295100000000005,True
+216,CHEMBL2032376,1.16,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.935542010773082,528.2597368840001,8,2,3.808600000000003,True
+217,CHEMBL69358,1.2,nM,2002.0,CCN(CC)CCNC(=O)c1cc(C)c(/C=C2\C(=O)Nc3ncnc(Nc4ccc(F)c(Cl)c4)c32)[nH]1,8.920818753952375,511.1898790040001,6,4,4.213520000000002,True
+218,CHEMBL3622645,1.2,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(O[C@H]4CCOC4)c(NC(=O)/C=C/CN(C)C)cc23)c1,8.920818753952375,457.211389724,7,2,3.578700000000002,True
+219,CHEMBL3622639,1.2,nM,2015.0,COCCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C)C,8.920818753952375,473.16299556000007,7,2,4.2474000000000025,True
+220,CHEMBL3622632,1.2,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(NC(=O)/C=C/CN(C)C)cc23)c1,8.920818753952375,445.211389724,7,2,3.436200000000002,True
+221,CHEMBL166358,1.2,nM,1998.0,CN(C)CCCNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.920818753952375,400.1011067720001,6,2,3.8945000000000016,True
+222,CHEMBL53665,1.2,nM,1999.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Br)c3)c2n1,8.920818753952375,387.0131002920001,5,2,3.794500000000002,True
+223,CHEMBL127058,1.2,nM,1997.0,OCCN(CCO)CCCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.920818753952375,460.1222361400001,8,4,2.6194999999999995,True
+224,CHEMBL4091276,1.2,nM,2017.0,C=CC(=O)Nc1cccc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)C(C)C5)cc4OC)nc32)c1,8.920818753952375,539.264487916,9,2,4.106120000000003,True
+225,CHEMBL3663923,1.2,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3)c(C(N)=O)nc2CC)c1C,8.920818753952375,515.264487916,8,3,3.858520000000002,True
+226,CHEMBL4096021,1.2,nM,2017.0,C=CC(=O)Nc1cc(Nc2cc(-c3cn4c5c(cccc35)CCC4)ncn2)c(OC)cc1N(C)CCN(C)C,8.920818753952375,525.28522336,8,2,4.919000000000003,True
+227,CHEMBL162223,1.2,nM,1998.0,Brc1cccc(Nc2ncnc3cnc(NCCc4ccccn4)cc23)c1,8.920818753952375,420.06980664400004,6,2,4.580500000000002,True
+228,CHEMBL3663927,1.2,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(OC)c(N4CCN(C)CC4)c3)c(C(N)=O)nc2CC)c1,8.920818753952375,531.259402536,9,3,3.558700000000001,True
+229,CHEMBL3663936,1.2,nM,2015.0,C=CC(=O)N1CCC[C@@H](Oc2nc(Nc3ccc(N4CCC(N5CCN(C)CC5)CC4)c(C)c3)c(C(N)=O)nc2CC)C1,8.920818753952375,590.3692873320001,9,2,2.961920000000002,True
+230,CHEMBL4288246,1.2,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN1CCOCC1,8.920818753952375,553.28013798,9,2,4.435500000000003,True
+231,CHEMBL3663934,1.2,nM,2015.0,CCC(=O)N1CC[C@@H](Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3)c(C(N)=O)nc2CC)C1,8.920818753952375,481.28013798000006,8,2,2.0229999999999997,True
+232,CHEMBL153206,1.2,nM,1999.0,COc1ccc2[nH]c3ncnc(Nc4cccc(Br)c4)c3c2c1,8.920818753952375,368.027273136,4,2,4.625800000000003,True
+233,CHEMBL2437462,1.21,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(N5CCN(C)CC5)cc4)nc32)c1,8.917214629683551,482.2178720720001,9,2,2.7956000000000003,True
+234,CHEMBL598007,1.24,nM,2010.0,O=C(Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)[C@@H]1O[C@H]1CN1CCCCC1,8.906578314837763,481.111337108,6,2,4.327700000000003,True
+235,CHEMBL153525,1.24,nM,1999.0,Brc1cccc(Nc2ncnc3ccc4cc[nH]c4c23)c1,8.906578314837763,338.01670845200005,3,2,4.617200000000001,True
+236,CHEMBL2441568,1.29,nM,2013.0,Fc1ccc(Nc2ncnc3cc4c(cc23)NCCO4)cc1Cl,8.88941028970075,330.06836690399996,5,2,3.970200000000002,True
+237,CHEMBL3663935,1.3,nM,2015.0,C=CC(=O)N1CCC[C@@H](Oc2nc(Nc3ccc(N4CCC(N5CCN(C)CC5)CC4)cc3)c(C(N)=O)nc2CC)C1,8.886056647693161,576.353637268,9,2,2.653500000000002,True
+238,CHEMBL3663933,1.3,nM,2015.0,C=CC(=O)N1CCC(c2nc(Nc3ccc(N4CCC(N5CCN(C)CC5)CC4)cc3)c(C(N)=O)nc2CC)CC1,8.886056647693161,560.358722648,8,2,2.989700000000002,True
+239,CHEMBL203661,1.3,nM,2006.0,O=C(C#CCCN1CCOCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,8.886056647693161,454.13202978000004,7,2,3.225100000000001,True
+240,CHEMBL3663930,1.3,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3cnn(C4CCN(C)CC4)c3)c(C(N)=O)nc2C(C)C)c1,8.886056647693161,504.25973688400006,9,3,3.8225000000000016,True
+241,CHEMBL3916927,1.3,nM,2012.0,C=CC(=O)N1CC(Oc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3cc2OC)C1,8.886056647693161,428.105146336,6,1,3.9501000000000026,True
+242,CHEMBL3663921,1.3,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3)c(C(N)=O)nc2CC)c1,8.886056647693161,501.24883785200007,8,3,3.5501000000000014,True
+243,CHEMBL161895,1.3,nM,1998.0,Cc1cccc(Nc2ncnc3cnc(NCCc4c[nH]cn4)cc23)c1,8.886056647693161,345.17019360800003,6,3,3.4545200000000014,True
+244,CHEMBL3545154,1.3,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4ccc(Cl)c(Cl)c4F)ncnc3cc2OC)CC1,8.886056647693161,490.09747411200004,6,1,5.383700000000005,True
+245,CHEMBL176891,1.32,nM,1996.0,CN(C)CCn1cnc2cc3ncnc(Nc4cccc(Br)c4)c3cc21,8.87942606879415,410.085456708,6,1,4.047200000000003,True
+246,CHEMBL3972316,1.39,nM,2016.0,C=CC(=O)N1CCCC[C@@H](n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cccc(C)c32)C1,8.856985199745905,470.1929607,4,1,5.355420000000004,True
+247,CHEMBL3663928,1.4,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(CC)CC4)cc3)c(C(N)=O)nc2CC)c1,8.853871964321762,515.264487916,8,3,3.9402000000000017,True
+248,CHEMBL128467,1.4,nM,1997.0,O=S(=O)(O)CCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.853871964321762,423.00007240800005,7,3,2.8306000000000004,True
+249,CHEMBL3929060,1.4,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@H]1C(N)=O,8.853871964321762,517.1328383040001,7,2,3.723300000000002,True
+250,CHEMBL3932784,1.4,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@H]1C(=O)NCCSC,8.853871964321762,591.151859496,8,2,4.717200000000004,True
+251,CHEMBL3655344,1.4,nM,2013.0,CC(C)N(C)C/C=C/C(=O)N1Cc2sc3ncnc(Nc4ccc(Cl)c(Cl)c4)c3c2C1,8.853871964321762,475.10003671600003,6,1,5.480300000000005,True
+252,CHEMBL127082,1.4,nM,1997.0,CNc1cc2ncnc(Nc3cccc(C)c3)c2cn1,8.853871964321762,265.13274548,5,2,3.118520000000001,True
+253,CHEMBL4286318,1.4,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,8.853871964321762,511.2695732960001,8,2,4.664900000000003,True
+254,CHEMBL3663922,1.4,nM,2015.0,CCc1nc(C(N)=O)c(Nc2ccc(N3CCN(C)CC3)cc2)nc1Oc1cccc(NC(=O)/C=C/CN(C)C)c1,8.853871964321762,558.306687076,9,3,3.481900000000002,True
+255,CHEMBL1916891,1.4,nM,2011.0,Cc1ccccc1Nc1nc2cc(F)c(N(C)C(=O)/C=C/CN(C)C)cc2n2cncc12,8.853871964321762,432.2073876400001,6,1,4.154220000000003,True
+256,CHEMBL4086000,1.4,nM,2017.0,C=CC(=O)Nc1cccc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)nc4)nc32)c1,8.853871964321762,496.2335221360001,9,2,3.104020000000001,True
+257,CHEMBL2138625,1.4,nM,2017.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1C#CC(C)(C)N1CCN(C)CC1,8.853871964321762,506.19971541600006,6,2,4.667900000000004,True
+258,CHEMBL202411,1.4,nM,2006.0,O=C(C#CCO)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,8.853871964321762,370.063281524,5,3,3.1001000000000003,True
+259,CHEMBL3814320,1.43,nM,2016.0,O=C(NCCN1CCOCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.844663962534938,470.10658607600004,6,3,3.589600000000001,True
+260,CHEMBL2031306,1.46,nM,2012.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cc1OCC,8.835647144215566,410.09458165200004,5,2,5.165780000000003,True
+261,CHEMBL2032380,1.47,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCCN(C)CC5)cc4OC)nc32)c1,8.832682665251824,542.2753869480001,8,2,4.198700000000003,True
+262,CHEMBL3663937,1.5,nM,2015.0,C=CC(=O)Nc1ccc(F)c(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3)c(C(N)=O)nc2CC)c1,8.823908740944319,519.23941604,8,3,3.6892000000000014,True
+263,CHEMBL165731,1.5,nM,1998.0,Cc1cccc(Nc2ncnc3cnc(NCCN4CCOCC4)cc23)c1,8.823908740944319,364.20115938799995,7,2,2.820920000000001,True
+264,CHEMBL3759480,1.5,nM,2016.0,COc1cc(C(N)=O)ccc1-c1cc2c(N[C@H](CO)c3ccccc3)ncnc2s1,8.823908740944319,420.1256115000001,7,3,3.6113000000000017,True
+265,CHEMBL3759359,1.5,nM,2016.0,COc1c(CO)cccc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,8.823908740944319,391.13544791200013,6,2,5.032300000000004,True
+266,CHEMBL3919609,1.5,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccc(O)cc3)cc12)c1ccccc1,8.823908740944319,331.132076784,5,2,4.768500000000003,True
+267,CHEMBL338175,1.5,nM,1997.0,O=C(O)CNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.823908740944319,373.017436724,6,3,3.027400000000001,True
+268,CHEMBL3663924,1.5,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3)c(C(N)=O)nc2C(C)C)c1,8.823908740944319,515.264487916,8,3,4.111100000000002,True
+269,CHEMBL165508,1.5,nM,1998.0,Brc1cccc(Nc2ncnc3cnc(NCc4cccnc4)cc23)c1,8.823908740944319,406.05415658000004,6,2,4.538000000000001,True
+270,CHEMBL27688,1.5,nM,2000.0,C=CC(=O)Nc1cc2c(Nc3cccc(C)c3)ncnc2cc1OCCCN1CCOCC1,8.823908740944319,447.227039788,7,2,3.907420000000003,True
+271,CHEMBL31656,1.5,nM,2000.0,C=CC(=O)Nc1nc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCOCC1,8.823908740944319,486.158244528,8,2,3.786500000000002,True
+272,CHEMBL204638,1.5,nM,2006.0,O=C(C#CCCN1CCOCC1)Nc1cc2c(Nc3ccc(F)c(Br)c3)ncnc2cn1,8.823908740944319,498.0815142000001,7,2,3.334200000000001,True
+273,CHEMBL3939913,1.51,nM,2016.0,Cc1cccc2nc(NC(=O)c3ccnc(C(F)(F)F)c3)n([C@@H]3CCCCN(C(=O)/C=C/CN(C)C)C3)c12,8.821023052706831,528.2460588920001,6,1,4.682220000000004,True
+274,CHEMBL4071827,1.52,nM,2017.0,C=CC(=O)Nc1cccc(-c2c[nH]c3nccc(-c4[nH]c(CCCO)nc4-c4ccc(F)cc4)c23)c1,8.818156412055227,481.191403228,4,4,5.475500000000005,True
+275,CHEMBL297968,1.6,nM,1999.0,C=CC(=O)Nc1ccc2c(Nc3cccc(C)c3)ncnc2c1,8.795880017344075,304.132411132,4,2,3.8063200000000013,True
+276,CHEMBL53637,1.6,nM,1999.0,C=CC(=O)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,8.795880017344075,324.077788716,4,2,4.151300000000002,True
+277,CHEMBL3898690,1.6,nM,2012.0,C=CC(=O)N1CC(Oc2cc3c(Nc4cccc(Cl)c4)ncnc3cc2OC)C1,8.795880017344075,410.11456814800005,6,1,3.8110000000000017,True
+278,CHEMBL202360,1.6,nM,2006.0,C#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.795880017344075,366.011623072,4,2,3.707600000000001,True
+279,CHEMBL416611,1.6,nM,1997.0,OCC(O)Cn1ccc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,8.795880017344075,412.0534878840001,6,3,3.4438000000000013,True
+280,CHEMBL516979,1.66,nM,2009.0,COC[C@H]1Oc2cc3ncnc(Nc4cccc(I)c4)c3cc2O[C@@H]1COC,8.779891911959945,493.04985411999996,7,1,3.779200000000002,True
+281,CHEMBL1089524,1.7,nM,2010.0,CN(C)CCCC(=O)Nc1ccc2nccc(Nc3cccc(Br)c3)c2c1,8.769551078621726,426.10552345600007,4,2,5.021200000000004,True
+282,CHEMBL173498,1.7,nM,1996.0,Brc1cccc(Nc2ncnc3cc4nccnc4cc23)c1,8.769551078621726,351.01195742000004,5,1,4.079100000000001,True
+283,CHEMBL32079,1.7,nM,2000.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCOCCCCO,8.769551078621726,474.14701114799993,7,3,4.458300000000004,True
+284,CHEMBL204085,1.7,nM,2006.0,O=C(C#CCCN1CCOCC1)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,8.769551078621726,453.13678081200004,6,2,3.8301000000000016,True
+285,CHEMBL203645,1.7,nM,2006.0,CCCC#CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,8.769551078621726,383.0949160000001,5,2,4.302900000000003,True
+286,CHEMBL32844,1.7,nM,2000.0,C=CC(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cc1OCCCN1CCN(C)CC1,8.769551078621726,524.153536268,7,2,4.2767000000000035,True
+287,CHEMBL162981,1.7,nM,1998.0,Brc1cccc(Nc2ncnc3cnc(NCCCn4ccnc4)cc23)c1,8.769551078621726,423.08070567600004,7,2,4.229600000000001,True
+288,CHEMBL4062543,1.7,nM,2017.0,C=CC(=O)NCCSc1nc(-c2ccccc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,8.769551078621726,441.1623313560001,5,3,5.276600000000004,True
+289,CHEMBL3663932,1.7,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)[C@H](C)C4)cc3)c(C(N)=O)nc2CC)c1,8.769551078621726,515.264487916,8,3,3.938600000000002,True
+290,CHEMBL4126810,1.7,nM,2018.0,CN1CCN(c2ccc(Nc3cc4c(N[C@H]5CCCN(C)C5)nc(Nc5ccccc5)nc4cn3)nc2)CC1,8.769551078621726,524.3124411520001,10,3,4.164900000000003,True
+291,CHEMBL166255,1.7,nM,1998.0,CN(CCO)CCNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.769551078621726,416.09602139200007,7,3,2.8669000000000002,True
+292,CHEMBL4086056,1.79,nM,2017.0,COc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1C[C@H](O)[C@@H](O)[C@H](O)[C@H]1CO,8.747146969020108,522.1681405159999,10,5,1.702599999999999,True
+293,CHEMBL356850,1.8,nM,1999.0,Brc1cccc(Nc2ncnc3c2sc2ccccc23)c1,8.744727494896694,354.97788041999996,4,1,5.350600000000002,True
+294,CHEMBL349070,1.8,nM,1998.0,CN(C)CCCCNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.744727494896694,414.1167568360001,6,2,4.284600000000003,True
+295,CHEMBL3622617,1.8,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(NC(=O)C=C)cc23)c1,8.744727494896694,388.15354049999996,6,2,3.504400000000002,True
+296,CHEMBL4064475,1.8,nM,2017.0,C=CC(=O)Nc1cccc(-n2c(=O)cc(C)c3cnc(Nc4cnn(C5CCN(C)CC5)c4)nc32)c1,8.744727494896694,484.2335221360001,9,2,3.420420000000002,True
+297,CHEMBL4078120,1.8,nM,2017.0,C=CC(=O)Nc1cc(C)cc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.744727494896694,539.264487916,9,2,4.026040000000003,True
+298,CHEMBL3663931,1.8,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)[C@@H](C)C4)cc3)c(C(N)=O)nc2CC)c1,8.744727494896694,515.264487916,8,3,3.938600000000002,True
+299,CHEMBL67003,1.8,nM,2002.0,Cc1cc(C(=O)N2CCOCC2)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c21,8.744727494896694,560.2284367560002,8,3,4.219820000000002,True
+300,CHEMBL27685,1.8,nM,2000.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Br)c3)ncnc2cc1OCCCN1CCOCC1,8.744727494896694,529.11247998,7,2,4.500600000000004,True
+301,CHEMBL4095439,1.8,nM,2017.0,C=CC(=O)Nc1cc(Br)cc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.744727494896694,603.1593499200002,9,2,4.480120000000003,True
+302,CHEMBL3985465,1.8,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@H]1C(=O)NCCO,8.744727494896694,561.1590530520001,8,3,3.346500000000002,True
+303,CHEMBL382073,1.8,nM,2006.0,CCN(CC)CCC#CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,8.744727494896694,439.157516256,5,2,4.839700000000004,True
+304,CHEMBL162508,1.8,nM,1998.0,Cc1cccc(Nc2ncnc3cnc(NCCCN4CCOCC4)cc23)c1,8.744727494896694,378.21680945199995,7,2,3.2110200000000013,True
+305,CHEMBL251125,1.8,nM,2007.0,CCOc1cc2ncnc(C#Cc3c[nH]nc3-c3ccc(F)cc3)c2cc1OCC,8.744727494896694,402.149204068,5,1,4.356200000000004,True
+306,CHEMBL3815163,1.81,nM,2016.0,S=C(NCCN1CCOCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.742321425130816,486.08374245600004,6,3,3.754500000000001,True
+307,CHEMBL1243283,1.81,nM,2010.0,CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CNCc1cn(CCF)nn1,8.742321425130816,566.17570616,9,3,4.8867800000000035,True
+308,CHEMBL31276,1.9,nM,2004.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)c(C#N)cnc2cn1,8.721246399047171,450.08037132800007,6,2,4.063880000000002,True
+309,CHEMBL126623,1.9,nM,1997.0,Brc1cccc(Nc2ncnc3cc(NCCCN4CCOCC4)ncc23)c1,8.721246399047171,442.11167145600007,7,2,3.6651000000000016,True
+310,CHEMBL4070707,1.9,nM,2017.0,C=CC(=O)N1CCC[C@H]1CSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,8.721246399047171,499.18420967200007,5,2,6.290500000000005,True
+311,CHEMBL2048903,1.9,nM,2012.0,OCCn1ccc2ncnc(Nc3ccc(Oc4cccc5[nH]ncc45)c(Cl)c3)c21,8.721246399047171,420.11015146400007,7,3,4.489200000000003,True
+312,CHEMBL2029432,1.95,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4C)nc32)c1,8.709965388637482,512.2648222640001,7,2,4.108420000000003,True
+313,CHEMBL3818062,1.98,nM,2016.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)[C@H]1NC(=O)O[C@@H]1C,8.703334809738468,445.095309924,7,3,3.6099000000000014,True
+314,CHEMBL596754,1.99,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1SCCCCCCC(=O)NO,8.701146923590294,478.124167528,7,3,5.722500000000004,True
+315,CHEMBL3678960,2.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2ncc3nc(Nc4ccccc4)n(C(C)C)c3n2)c1,8.698970004336019,413.19640835600006,7,3,5.018900000000003,True
+316,CHEMBL3671498,2.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN(C)C,8.698970004336019,530.107728948,7,3,3.456100000000002,True
+317,CHEMBL3806248,2.0,nM,2016.0,CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2c2c1OCCO2,8.698970004336019,375.07859723999997,6,1,4.3358000000000025,True
+318,CHEMBL3758376,2.0,nM,2016.0,CN(C)CCNC(=O)c1ccc(-c2cc3c(N[C@H](CO)c4ccccc4)ncnc3s2)cc1,8.698970004336019,461.18854610400007,7,3,3.795200000000003,True
+319,CHEMBL56936,2.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCNCCN(C)C,8.698970004336019,433.16808094000004,7,2,3.704500000000002,True
+320,CHEMBL31622,2.0,nM,2000.0,C=CC(=O)Nc1cc2c(Nc3cccc(C)c3)ncnc2cc1OCCCN1CCN(C)CC1,8.698970004336019,460.25867426400004,7,2,3.8226200000000023,True
+321,CHEMBL3952953,2.0,nM,2014.0,COCCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/[C@@H]1CCCN1C,8.698970004336019,499.17864562400007,7,2,4.780000000000004,True
+322,CHEMBL3545308,2.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(C(C)=O)CC4)cc3OC)ncc2C(F)(F)F)c1,8.698970004336019,555.220572416,8,3,4.784200000000004,True
+323,CHEMBL3604943,2.0,nM,2015.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N1CCN(C)CC1,8.698970004336019,497.2539232320001,8,2,4.2638000000000025,True
+324,CHEMBL3759961,2.0,nM,2016.0,COc1cccc(OC)c1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,8.698970004336019,391.13544791200013,6,1,5.548600000000004,True
+325,CHEMBL3928512,2.0,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccccc3O)cc12)c1ccccc1,8.698970004336019,331.132076784,5,2,4.768500000000004,True
+326,CHEMBL3671496,2.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)NCC,8.698970004336019,516.0920788840001,6,4,4.097400000000003,True
+327,CHEMBL3758351,2.0,nM,2016.0,COc1cc(CO)ccc1-c1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.698970004336019,415.0557536200001,6,2,5.395300000000003,True
+328,CHEMBL3758800,2.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3ccc(C(=O)NCCN(C)C)cc3)cc12)c1ccccc1,8.698970004336019,445.19363148400004,6,2,4.822800000000004,True
+329,CHEMBL3758278,2.0,nM,2016.0,COc1cc(C(N)=O)ccc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,8.698970004336019,404.1306968800001,6,2,4.638900000000002,True
+330,CHEMBL418909,2.0,nM,2004.0,CC(=O)NCCNCc1ccc(-c2cc3nccc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,8.698970004336019,455.17798142000004,5,4,5.4139000000000035,True
+331,CHEMBL3898077,2.0,nM,2012.0,C=C(CN(C)C)C(=O)N1CC(Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C1,8.698970004336019,503.153573748,7,1,4.021000000000002,True
+332,CHEMBL3950549,2.0,nM,2016.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C(C)C)C(C)C,8.698970004336019,485.19938106800004,6,2,5.788000000000006,True
+333,CHEMBL126192,2.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4nccs4)c3)c2cc1OCC,8.698970004336019,392.13069687999996,7,1,5.294300000000003,True
+334,CHEMBL310740,2.0,nM,2004.0,OCCNCc1ccc(-c2cc3nccc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,8.698970004336019,414.15143232400004,5,4,5.270100000000003,True
+335,CHEMBL3930316,2.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,8.698970004336019,374.094581652,5,2,4.523000000000003,True
+336,CHEMBL93966,2.0,nM,1996.0,Nc1ccc2c(Nc3cccc(F)c3)ncnc2c1,8.698970004336019,254.096774572,4,2,3.0947000000000005,True
+337,CHEMBL3647422,2.0,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/[C@H]1CCCN1C,8.698970004336019,499.17864562400007,7,2,4.780000000000004,True
+338,CHEMBL3655339,2.0,nM,2013.0,O=C(/C=C/[C@@H]1CCCN1)N1CCc2c(sc3ncnc(Nc4ccc(F)c(Cl)c4)c23)C1,8.698970004336019,457.11393719200004,6,2,4.420300000000003,True
+339,CHEMBL3674148,2.0,nM,2015.0,CC(C)n1c(Nc2ccc(F)c(Cl)c2)nc2cnc(Nc3ccc(C(=O)NN4CCN(C)CC4)cc3)nc21,8.698970004336019,537.216762448,9,3,4.579100000000004,True
+340,CHEMBL3671486,2.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCNC(=O)CN(C)C,8.698970004336019,544.1233790120001,7,3,3.8462000000000023,True
+341,CHEMBL3671491,2.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(C)=O,8.698970004336019,487.06552978800005,6,3,3.9144000000000023,True
+342,CHEMBL332906,2.0,nM,1997.0,Nc1ccc(-c2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,8.698970004336019,336.089022096,5,3,3.999100000000001,True
+343,CHEMBL3961553,2.0,nM,2016.0,OC[C@@H](Nc1ncnc2oc(-c3ccc(O)cc3)cc12)c1ccccc1,8.698970004336019,347.126991404,6,3,3.7409000000000026,True
+344,CHEMBL94062,2.0,nM,2001.0,O=C(C#CCO)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.698970004336019,396.022187756,5,3,3.070100000000001,True
+345,CHEMBL3968417,2.0,nM,2016.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,8.698970004336019,400.12146509600007,6,2,3.6172000000000004,True
+346,CHEMBL250132,2.0,nM,2007.0,C[C@H](CN(C)C(=O)CO)Oc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12,8.698970004336019,507.167331992,8,2,4.2188000000000025,True
+347,CHEMBL387265,2.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OC1CCN(S(C)(=O)=O)CC1,8.698970004336019,480.10343208399996,7,1,3.977300000000003,True
+348,CHEMBL3233779,2.0,nM,2014.0,COC(CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1)OC,8.698970004336019,479.119416496,8,2,4.272800000000002,True
+349,CHEMBL4068047,2.0,nM,2017.0,C=CC(=O)Nc1cc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)cc(C(F)(F)F)c1,8.698970004336019,593.23622248,9,2,4.736420000000004,True
+350,CHEMBL213874,2.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OCC1CCN(C)CC1,8.698970004336019,430.157181908,6,1,4.895100000000004,True
+351,CHEMBL4103201,2.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3cnc4[nH]ccc4c3)c3c(N)ncnc32)C1,8.698970004336019,388.17600726000006,7,2,2.3013000000000003,True
+352,CHEMBL4094959,2.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3cn(C)c4ccccc34)c3c(N)ncnc32)C1,8.698970004336019,401.1964083560001,7,1,2.9167000000000005,True
+353,CHEMBL218677,2.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OC1CCN(CC(N)=O)CC1,8.698970004336019,459.147345496,7,2,3.503000000000002,True
+354,CHEMBL2087358,2.0,nM,2012.0,Clc1cccc(Nc2ncnc3cc4c(cc23)OCCOCCOCCO4)c1,8.698970004336019,401.1142337999999,7,1,3.8312000000000026,True
+355,CHEMBL214798,2.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OC1CCN(C)CC1,8.698970004336019,416.141531844,6,1,4.6475000000000035,True
+356,CHEMBL587723,2.0,nM,2011.0,CCN1CCN(Cc2ccc(-c3cc4c(N[C@H](C)c5ccccc5)ncnc4[nH]3)cc2)CC1,8.698970004336019,440.2688450240001,5,2,4.935500000000003,True
+357,CHEMBL3233795,2.0,nM,2014.0,O=C(/C=C/CN1CCC2(CC1)OCCO2)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.698970004336019,503.11941649600004,8,2,4.5610000000000035,True
+358,CHEMBL2087361,2.0,nM,2012.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)OCCOCCOCCO4)c1,8.698970004336019,391.15320615199994,7,1,3.1591000000000014,True
+359,CHEMBL3040861,2.0,nM,2014.0,c1ccc(-c2cccc(Nc3ncnc4cc5c(cc34)OCO5)c2)cc1,8.698970004336019,341.11642672,5,1,4.769100000000003,True
+360,CHEMBL2419760,2.0,nM,2013.0,Cl.c1ccc(-c2cccc(Nc3ncnc4cc5c(cc34)OCO5)c2)cc1,8.698970004336019,377.0931044319999,5,1,5.190900000000002,True
+361,CHEMBL2087360,2.0,nM,2012.0,Fc1ccc(Nc2ncnc3cc4c(cc23)OCCOCCOCCO4)cc1Cl,8.698970004336019,419.10481198799994,7,1,3.9703000000000035,True
+362,CHEMBL2031309,2.02,nM,2012.0,CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)CCN1CCOCC1,8.694648630553376,497.16299556,7,2,4.702080000000003,True
+363,CHEMBL3815074,2.04,nM,2016.0,C#Cc1cccc(Nc2ncnc3ccc(NC(C)=O)cc23)c1,8.690369832574099,302.116761068,4,2,3.3131000000000013,True
+364,CHEMBL4215080,2.1,nM,2018.0,CN(C)C1CCN(c2ccc(Nc3cc4c(N5CCOCC5)nc(Nc5ccc(F)cc5F)nc4cn3)nc2)CC1,8.67778070526608,561.2776131160001,10,2,4.552200000000004,True
+365,CHEMBL597773,2.1,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)CCCCCCC(=O)NO,8.67778070526608,489.15791018,7,4,4.959000000000002,True
+366,CHEMBL4206288,2.1,nM,2018.0,CN1CCN(c2ccc(Nc3cc4c(N5CCOCC5)nc(Nc5ccccc5)nc4cn3)nc2)CC1,8.67778070526608,497.2651566120001,10,2,3.495400000000002,True
+367,CHEMBL3622665,2.1,nM,2015.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CNC1CC1,8.67778070526608,441.13678081200004,6,3,4.4212000000000025,True
+368,CHEMBL155278,2.1,nM,1999.0,Cc1cccc(Nc2ncnc3c2sc2ccc(N)cc23)c1,8.67778070526608,306.093917448,5,2,4.478720000000003,True
+369,CHEMBL3960167,2.11,nM,2016.0,Cc1cc(C(=O)Nc2nc3cccc(C)c3n2[C@@H]2CCCCN(C(=O)/C=C/CN(C)C)C2)ccn1,8.675717544702309,474.27432432800003,6,1,3.971840000000003,True
+370,CHEMBL4071012,2.2,nM,2017.0,C=CC(=O)NCCSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,8.657577319177793,459.15290954400007,5,3,5.415700000000004,True
+371,CHEMBL4085842,2.2,nM,2017.0,C=CC(=O)Nc1cc(Nc2cc(-c3cn(C)c4ccccc34)ncn2)c(OC)cc1N(C)CCN(C)C,8.657577319177793,499.2695732960001,8,2,4.509800000000003,True
+372,CHEMBL2031308,2.21,nM,2012.0,CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)CCN1CCCCC1,8.655607726314889,495.18373100400004,6,2,5.855780000000005,True
+373,CHEMBL3814447,2.22,nM,2016.0,C#Cc1cccc(Nc2ncnc3ccc(NC(N)=O)cc23)c1,8.653647025549361,303.112010036,4,3,2.8453,True
+374,CHEMBL3814445,2.25,nM,2016.0,Fc1ccc(Nc2ncnc3ccc(NC(=S)NCCN4CCOCC4)cc23)cc1Cl,8.647817481888637,460.124836224,6,3,3.784500000000002,True
+375,CHEMBL3910496,2298,nM,2015.0,C=CC(=O)N1CCC[C@H]1Cn1nc(-c2ccc(Oc3ccccc3)cc2)c2c(N)ncnc21,8.638649975647732,440.19607400800004,7,1,4.044800000000002,True
+376,CHEMBL53299,2.3,nM,1996.0,COc1ccc(CNc2cc3c(Nc4cccc(Br)c4)ncnc3cn2)cc1,8.638272163982407,435.0694722960001,6,2,5.151600000000003,True
+377,CHEMBL4083486,2.3,nM,2017.0,C=CC(=O)Nc1cc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)ccc1C,8.638272163982407,539.264487916,9,2,4.026040000000003,True
+378,CHEMBL4225166,2.3,nM,2018.0,C=CC(=O)Nc1cc(Nc2ncc3ncn(-c4ccc(F)c(Br)c4)c3n2)c(OC)cc1N(C)CCN(C)C,8.638272163982407,582.150262456,9,2,4.591600000000003,True
+379,CHEMBL4209801,2.3,nM,2018.0,CN1CCN(c2ccc(Nc3cc4c(N5CCCC5)nc(Nc5ccccc5)nc4cn3)nc2)CC1,8.638272163982407,481.2702419920001,9,2,4.259000000000003,True
+380,CHEMBL4060996,2.3,nM,2017.0,COc1ccc(N(C)c2nc(C)nc3c(Cc4ccccc4)cn(C)c23)cc1.Cl,8.638272163982407,408.17168910000004,5,0,5.065820000000005,True
+381,CHEMBL3622675,2.4,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OCC)c(NC(=O)/C=C/CN(C)C4CC4)cc23)c1,8.619788758288394,441.21647510400004,6,2,4.342300000000003,True
+382,CHEMBL598797,2.4,nM,2010.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(OCCCCCCC(=O)NO)cc23)c1,8.619788758288394,434.19540531199993,7,3,4.198000000000002,True
+383,CHEMBL139095,2.4,nM,2001.0,C=CS(=O)(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.619788758288394,404.9895077240001,6,2,3.416100000000001,True
+384,CHEMBL4207750,2.4,nM,2018.0,CCS(=O)(=O)Nc1cc(-c2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)cnc1OC,8.619788758288394,487.088116368,7,2,4.9981000000000035,True
+385,CHEMBL4079861,2.4,nM,2017.0,C=CC(=O)Nc1cc(C(C)C)cc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.619788758288394,567.2957880440001,9,2,4.841020000000004,True
+386,CHEMBL3219127,2.45,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)C3CCCCN3C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.610833915635467,596.2859516320001,9,2,3.778100000000003,True
+387,CHEMBL4063421,2.5,nM,2017.0,C=CC(=O)Nc1cccc(-n2c(=O)cc(C)c3cnc(Nc4nc5c(s4)CN(C)CC5)nc32)c1,8.602059991327963,473.1633939760001,9,2,3.401620000000001,True
+388,CHEMBL4215076,2.5,nM,2018.0,CN(C)C1CCN(c2ccc(Nc3cc4c(N5CCOCC5)nc(Nc5ccc(F)cc5)nc4cn3)nc2)CC1,8.602059991327963,543.2870349280001,10,2,4.413100000000004,True
+389,CHEMBL321494,2.5,nM,2017.0,CSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,8.602059991327963,376.11579576400004,4,2,5.743300000000003,True
+390,CHEMBL592216,2.53,nM,2010.0,C#CCCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,8.596879478824183,385.09933268400005,5,1,4.966700000000003,True
+391,CHEMBL53062,2.6,nM,1996.0,COc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.585026652029184,330.0116230720001,5,1,3.539500000000002,True
+392,CHEMBL4099682,2.6,nM,2017.0,COc1ccc(Nc2nc(C)nc3c(Cc4ccccc4)cn(C)c23)cc1.Cl,8.585026652029184,394.15603903600004,5,1,5.041520000000004,True
+393,CHEMBL4081860,2.6,nM,2017.0,NCCSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,8.585026652029184,405.14234486000004,5,3,5.072200000000003,True
+394,CHEMBL3357654,2.6,nM,2014.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1NC(=O)/C(F)=C/CN(C)C,8.585026652029184,473.086265232,6,2,4.498000000000003,True
+395,CHEMBL287007,2.6,nM,1997.0,CN(C)Cc1c[nH]c2cc3ncnc(Nc4cccc(Br)c4)c3cc12,8.585026652029184,395.074557676,4,2,4.6788000000000025,True
+396,CHEMBL341319,2.6,nM,1997.0,CN(CCO)c1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.585026652029184,373.053822232,6,2,2.9594000000000005,True
+397,CHEMBL4171764,2.61,nM,2017.0,Brc1cccc(Nc2ncnc3sc4c(c23)CCCC4)c1,8.58335949266172,359.00918054799996,4,1,5.076200000000002,True
+398,CHEMBL281543,2.7,nM,2000.0,C=CC(=O)Nc1nc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1CCCCN1CCOCC1,8.568636235841014,484.17897997200004,7,2,4.340300000000003,True
+399,CHEMBL136511,2.7,nM,2001.0,C=CS(=O)(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.568636235841014,403.994258756,5,2,4.0211000000000015,True
+400,CHEMBL3622672,2.7,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(NC(=O)/C=C/CN4CCCCC4)cc23)c1,8.568636235841014,441.21647510400004,6,2,4.343900000000003,True
+401,CHEMBL3952157,2.7,nM,2016.0,COc1ccc(-c2cc3c(N[C@H](CO)c4ccccc4)ncnc3o2)cc1,8.568636235841014,361.142641468,6,2,4.043900000000002,True
+402,CHEMBL285063,2.7,nM,2001.0,C=CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.568636235841014,368.027273136,4,2,4.260400000000002,True
+403,CHEMBL4227201,2.7,nM,2018.0,C=CC(=O)Nc1cc(Nc2ncc3nc(Nc4ccccc4)n(C)c3n2)c(OC)cc1N(C)CCN(C)C,8.568636235841014,515.275721296,10,3,3.9814000000000025,True
+404,CHEMBL151593,2.7,nM,1999.0,CO.Nc1cccc2c1sc1c(Nc3cccc(Br)c3)ncnc12,8.568636235841014,402.0149942000001,6,3,4.5413000000000014,True
+405,CHEMBL163188,2.8,nM,1998.0,Cc1cccc(Nc2ncnc3cnc(N(C)C)cc23)c1,8.55284196865778,279.148395544,5,1,3.1428200000000013,True
+406,CHEMBL2048795,2.8,nM,2012.0,O=C1Cc2cccc(Oc3ccc(Nc4ncnc5ccn(CCO)c45)cc3Cl)c2N1,8.55284196865778,435.109817116,7,3,4.107500000000001,True
+407,CHEMBL305246,2.8,nM,2002.0,Cc1cc(C(=O)N2CCN(C)CC2)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc(F)c(Cl)c3)c21,8.55284196865778,495.1585788760001,6,3,3.5295200000000007,True
+408,CHEMBL2048906,2.9,nM,2012.0,CC(=O)NCCn1ccc2ncnc(Nc3ccc(Oc4cccc5sncc45)c(Cl)c3)c21,8.537602002101043,478.097872528,8,2,5.366400000000003,True
+409,CHEMBL3815161,2.92,nM,2016.0,O=C(NCCN1CCOCC1)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,8.534617148551582,444.14767984400004,6,3,3.619600000000001,True
+410,CHEMBL1336,2.96,nM,2016.0,CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)cc2)ccn1,8.528708288941061,464.086302712,4,3,5.549700000000003,True
+411,CHEMBL3828269,2.97,nM,2016.0,Cn1cc(-c2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)cn1,8.527243550682787,353.08435131600004,5,1,4.5664000000000025,True
+412,CHEMBL3114700,3.0,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(C(=O)/C=C/CN2CCCC2)CCO4)c1,8.522878745280337,439.20082504,6,1,3.7321000000000026,True
+413,CHEMBL3114690,3.0,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(C(=O)/C=C/CN(C)C)CCO4)c1,8.522878745280337,413.185174976,6,1,3.1979000000000024,True
+414,CHEMBL3671500,3.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNCC(C)=O,8.522878745280337,501.08117985200005,7,3,3.9569000000000027,True
+415,CHEMBL3935492,3.0,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@H]1C(=O)NCCS(C)(=O)=O,8.522878745280337,623.1416887360001,9,2,3.3988000000000014,True
+416,CHEMBL79206,3.0,nM,2004.0,CN(CCO)Cc1ccc(-c2cc3nccc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,8.522878745280337,428.16708238800004,5,3,5.612300000000003,True
+417,CHEMBL80540,3.0,nM,2004.0,c1cc(Nc2ccc3[nH]ccc3c2)c2sc(-c3ccc(CNCCN4CCNCC4)cc3)cc2n1,8.522878745280337,482.22526596000006,6,4,5.183000000000004,True
+418,CHEMBL3233773,3.0,nM,2014.0,CS(=O)(=O)CCNC/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.522878745280337,483.0601873680001,8,3,3.356300000000001,True
+419,CHEMBL214857,3.0,nM,2006.0,COCCN1CCC(Oc2cc3c(Nc4cccc(Cl)c4F)ncnc3cc2OC)CC1,8.522878745280337,460.167746592,7,1,4.664100000000003,True
+420,CHEMBL4060919,3.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(Cc3ccccc3)c3c(N)ncnc32)C1,8.522878745280337,362.18550932400007,6,1,2.3488000000000007,True
+421,CHEMBL3622640,3.0,nM,2015.0,COCCOc1cc2ncnc(Nc3ccc(Br)cc3F)c2cc1NC(=O)/C=C/CN(C)C,8.522878745280337,517.11247998,7,2,4.356500000000003,True
+422,CHEMBL4072299,3.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc(O)cc3)c3c(N)ncnc32)C1,8.522878745280337,364.16477388000004,7,2,2.1305999999999994,True
+423,CHEMBL3671490,3.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCNC,8.522878745280337,473.0862652320001,6,3,4.387800000000003,True
+424,CHEMBL215786,3.0,nM,2006.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCC1CCN(C)CC1,8.522878745280337,430.157181908,6,1,4.895100000000004,True
+425,CHEMBL3961848,3.0,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4cccc(C=C)c4)ncnc3cc2OC)CC1,8.522878745280337,430.200490692,6,1,4.5808000000000035,True
+426,CHEMBL3233792,3.0,nM,2014.0,O=C(/C=C/CN1CCOCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.522878745280337,447.093201748,7,2,4.054300000000002,True
+427,CHEMBL4214567,3.0,nM,2018.0,O=C(Nc1nccs1)C(c1cc(F)ccc1O)N1Cc2ccccc2C1=O,8.522878745280337,383.07399052799997,5,2,3.3236000000000017,True
+428,CHEMBL258940,3.0,nM,2007.0,CN1CCC(Nc2ncc3ncnc(Nc4ccc(F)c(Cl)c4)c3n2)CC1,8.522878745280337,387.13744950800003,7,2,3.4620000000000015,True
+429,CHEMBL258270,3.0,nM,2008.0,CC(=O)N1CCN(CCOc2n[nH]c3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c23)CC1,8.522878745280337,522.189464404,9,2,3.266800000000001,True
+430,CHEMBL203725,3.0,nM,2006.0,CN1CCC(Oc2cccc3ncnc(Nc4ccc(F)c(Cl)c4)c23)CC1,8.522878745280337,386.13096716,5,1,4.638900000000004,True
+431,CHEMBL125086,3.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4ccco4)c3)c2cc1OCC,8.522878745280337,375.15829153199996,6,1,5.430800000000004,True
+432,CHEMBL250130,3.0,nM,2007.0,C[C@H](COc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12)N(C)C(=O)CO,8.522878745280337,507.16733199199996,8,2,4.218800000000003,True
+433,CHEMBL3759986,3.0,nM,2016.0,OCc1cccc(-c2cc3c(N[C@H](CO)c4ccccc4)ncnc3s2)c1,8.522878745280337,377.11979784800013,6,3,3.996100000000002,True
+434,CHEMBL3760082,3.0,nM,2016.0,COc1ccc(C=O)cc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,8.522878745280337,389.11979784800013,6,1,5.352500000000004,True
+435,CHEMBL3085376,3.0,nM,2007.0,CCN(CC)[C@@](C)(C#Cc1ncnc2cc(OC)c(OC)cc12)Cc1ccccc1,8.522878745280337,403.225977168,5,0,4.341700000000004,True
+436,CHEMBL473428,3.0,nM,2009.0,OCc1ccc(-c2cc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3s2)o1,8.522878745280337,481.06631830399994,7,2,6.558700000000003,True
+437,CHEMBL3759725,3.0,nM,2016.0,COc1c(C(=O)NCCN(C)C)cccc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,8.522878745280337,475.20419616800007,7,2,4.831400000000004,True
+438,CHEMBL4113919,3.0,nM,2015.0,CC(C)n1c(Nc2ccccc2)nc2cnc(Nc3ccc(C(=O)N[N+]4=CCN(C)CC4)cc3)nc21,8.522878745280337,484.25678300009,8,3,3.5679000000000016,True
+439,CHEMBL3633929,3.0,nM,2015.0,CC(=O)Nc1ccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c2c1,8.522878745280337,419.114902496,6,2,4.959200000000003,True
+440,CHEMBL4165894,3.0,nM,2018.0,COc1cc2ncnc(N3CCc4ccccc43)c2cc1NC(=O)/C=C/CN1CCCC1,8.522878745280337,429.21647510400004,6,1,3.9231000000000025,True
+441,CHEMBL286343,3.0,nM,2000.0,C=CC(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cc1OCCCn1ccnc1,8.522878745280337,492.0909360120001,7,2,4.926000000000004,True
+442,CHEMBL3965391,3.0,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C1,8.522878745280337,460.11137458800005,6,1,4.479300000000004,True
+443,CHEMBL2048796,3.0,nM,2012.0,O=C1Cc2c(cccc2Oc2ccc(Nc3ncnc4ccn(CCO)c34)cc2Cl)N1,8.522878745280337,435.109817116,7,3,4.107500000000001,True
+444,CHEMBL3355873,3.05,nM,2015.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCn1ccnc1[N+](=O)[O-],8.515700160653214,458.090558892,9,1,4.358200000000003,True
+445,CHEMBL52882,3.1,nM,1996.0,CNC1=CC2N=CN(C)/C(=N\c3cccc(Br)c3)C2C=N1,8.508638306165727,345.05890761200004,4,1,2.5828000000000007,True
+446,CHEMBL598377,3.1,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCCCCC(=O)NO,8.508638306165727,462.14701114799993,7,3,5.009200000000003,True
+447,CHEMBL373207,3.1,nM,2006.0,CCN(CC)CC#CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,8.508638306165727,425.141866192,5,2,4.449600000000003,True
+448,CHEMBL165495,3.1,nM,1998.0,Cc1cccc(Nc2ncnc3cnc(N)cc23)c1,8.508638306165727,251.11709541599998,5,2,2.65902,True
+449,CHEMBL202556,3.1,nM,2006.0,O=C(C#CCN1CCOCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,8.508638306165727,440.11637971600004,7,2,2835,True
+450,CHEMBL4245415,3.1,nM,2018.0,Cc1coc2ncnc(N(C)c3ccc(N(C)C)cc3)c12,8.508638306165727,282.148061196,5,0,3.3651200000000028,True
+451,CHEMBL2048797,3.1,nM,2012.0,OCCn1ccc2ncnc(Nc3ccc(Oc4cccc5[nH]ccc45)c(Cl)c3)c21,8.508638306165727,419.114902496,6,3,5.094200000000003,True
+452,CHEMBL4105329,3.1,nM,2017.0,Cc1n[nH]c2ccc(-c3cc(N[C@@H](CO)c4ccccc4)cnc3-c3cc(Cl)ccc3O)cc12,8.508638306165727,470.150953656,5,4,6.104820000000005,True
+453,CHEMBL53156,3.1,nM,1996.0,CNc1ccc2ncnc(Nc3cccc(Br)c3)c2n1,8.508638306165727,329.02760748400004,5,2,3.5726000000000013,True
+454,CHEMBL4061473,3.1,nM,2017.0,C=CC(=O)N1CCC[C@@H]1CSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,8.508638306165727,499.18420967200007,5,2,6.290500000000005,True
+455,CHEMBL591038,3.16,nM,2010.0,C=C=CCCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O,8.500312917381597,385.09933268400005,5,2,5.3716000000000035,True
+456,CHEMBL4279227,3.2,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3c[nH]c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,8.494850021680094,497.2539232320001,7,3,4.654500000000003,True
+457,CHEMBL4225863,3.2,nM,2018.0,C=CC(=O)Nc1cc(Nc2ncc3ncn(-c4ccc(F)cc4)c3n2)c(OC)cc1N(C)CCN(C)C,8.494850021680094,504.23975038800006,9,2,3.829100000000002,True
+458,CHEMBL4206166,3.2,nM,2018.0,CN(C)C1CCN(c2ccc(Nc3cc4c(N5CCC(CO)CC5)nc(Nc5ccccc5)nc4cn3)nc2)CC1,8.494850021680094,553.327756868,10,3,4.646100000000004,True
+459,CHEMBL4127809,3.2,nM,2018.0,C=CC(=O)N[C@H]1CCN(c2nc(Nc3ccccc3)nc3cnc(Nc4ccc(N5CCN(C)CC5)cn4)cc23)C1,8.494850021680094,550.2917057080001,10,3,3.5397000000000025,True
+460,CHEMBL127611,3.2,nM,1997.0,CN(CC(O)C(O)C(O)C(O)CO)c1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.494850021680094,493.0960809680001,10,6,0.40300000000000075,True
+461,CHEMBL4071058,3.2,nM,2017.0,CC(C)(C)OC(=O)NCC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.494850021680094,471.09060166399996,6,3,4.599100000000003,True
+462,CHEMBL128987,3.2,nM,1997.0,Brc1cccc(Nc2ncnc3cc(NCCN4CCOCC4)ncc23)c1,8.494850021680094,428.09602139200007,7,2,3.2750000000000012,True
+463,CHEMBL340700,3.2,nM,1997.0,CN(CC(O)CO)c1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.494850021680094,403.064386916,7,3,2.3202999999999996,True
+464,CHEMBL4102224,3.2,nM,2017.0,CCC(=O)NCCSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,8.494850021680094,461.16855960800007,5,3,5.639700000000004,True
+465,CHEMBL4072048,3.3,nM,2017.0,C=CC(=O)Nc1cccc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CC(C)N(C)C(C)C5)cc4OC)nc32)c1,8.481486060122112,553.28013798,9,2,4.494620000000004,True
+466,CHEMBL2035810,3.3,nM,2012.0,C=CC(=O)NCc1coc(-c2c(N)ncnc2Nc2ccc(OCc3ccccn3)c(Cl)c2)n1,8.481486060122112,477.13161518000004,9,3,3.8870000000000013,True
+467,CHEMBL1914461,3.3,nM,2011.0,Br.Oc1ccc(-c2cc3c(NCc4ccccc4)ncnc3[nH]2)cc1,8.481486060122112,396.05857326400013,4,3,4.520500000000004,True
+468,CHEMBL105053,3.3,nM,2011.0,C[C@@H](Nc1[nH]cnc2nc(-c3ccccc3)cc1-2)c1ccccc1,8.481486060122112,314.153146576,3,2,4.749600000000004,True
+469,CHEMBL3622674,3.3,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(NC(=O)/C=C/CN(C)C4CC4)cc23)c1,8.481486060122112,427.20082504000004,6,2,3.952200000000003,True
+470,CHEMBL433205,3.3,nM,1996.0,Nc1ccc2c(Nc3cccc(C(F)(F)F)c3)ncnc2c1,8.481486060122112,304.093581012,4,2,3.974400000000002,True
+471,CHEMBL1916897,3.35,nM,2011.0,Cc1ccc(F)cc1Nc1nc2cc(Cl)c(N(C)C(=O)/C=C/CN(C)C)cc2n2cncc12,8.474955192963153,466.168415288,6,1,4.807620000000004,True
+472,CHEMBL51659,3.4,nM,2001.0,C=CC(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.468521082957745,369.0225221040001,5,2,3.655400000000002,True
+473,CHEMBL39715,3.4,nM,1997.0,COC(=O)CN(C)Cc1c[nH]c2cc3ncnc(Nc4cccc(Br)c4)c3cc12,8.468521082957745,453.08003698000005,6,2,4.222000000000002,True
+474,CHEMBL4102389,3.4,nM,2017.0,C=CC(=O)Nc1cc(CC)cc(-n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.468521082957745,553.2801379800001,9,2,4.280020000000003,True
+475,CHEMBL598163,3.4,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCCCC(=O)NO,8.468521082957745,448.13136108399993,7,3,4.619100000000003,True
+476,CHEMBL3403517,3.4,nM,2015.0,COc1ccc2c(c1)CCCN2c1nc(C)nc2oc(C)cc12,8.468521082957745,309.147726848,5,0,3.932540000000003,True
+477,CHEMBL3355888,3.43,nM,2015.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCn1c([N+](=O)[O-])cnc1C,8.46470587995723,486.12185902,9,1,5.056720000000004,True
+478,CHEMBL4227091,3.5,nM,2018.0,C=CC(=O)Nc1cc(Nc2ncc3ncn(-c4ccc(I)cc4)c3n2)c(OC)cc1N(C)CCN(C)C,8.455931955649724,612.145820168,9,2,4.294600000000003,True
+479,CHEMBL340898,3.5,nM,1997.0,Cc1cccc(Nc2ncnc3cc(NCCCn4ccnc4)ncc23)c1,8.455931955649724,359.18584367200003,7,2,3.775520000000002,True
+480,CHEMBL36164,3.5,nM,1997.0,OCCN(CCO)Cc1c[nH]c2cc3ncnc(Nc4cccc(Br)c4)c3cc12,8.455931955649724,455.09568704400004,6,4,3.4038000000000004,True
+481,CHEMBL2029425,3.52,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCC(N(C)C)CC5)cc4OC)nc32)c1,8.453457336521868,556.2910370120001,8,2,4.587200000000005,True
+482,CHEMBL3828021,3.58,nM,2016.0,C#Cc1cccc(Nc2ncnc3ccc(-c4cnn(C)c4)cc23)c1,8.446116973356126,325.13274548,5,1,3.755200000000002,True
+483,CHEMBL31419,3.6,nM,2000.0,C=CC(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cc1OCCCN1CCOCC1,8.443697499232712,511.121901792,7,2,4.361500000000004,True
+484,CHEMBL430571,3.6,nM,1999.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(OCc4ccccc4)cc3)c2c1,8.443697499232712,396.15862588,5,2,5.076900000000003,True
+485,CHEMBL3805859,3.6,nM,2016.0,CCOc1cc2ncnc(Nc3ccc(C)cc3)c2c2c1OCCO2,8.443697499232712,337.14264146799997,6,1,3.851720000000002,True
+486,CHEMBL4168235,3.62,nM,2017.0,COc1cc2c(Nc3ccc(C#N)cc3)ncnc2cc1OCCCN1CCC(c2ccccc2)CC1,8.441291429466835,493.24777523200004,7,1,5.902180000000006,True
+487,CHEMBL3814694,3.7,nM,2016.0,Fc1ccc(Nc2ncnc3ccc(NC(=S)NCCN4CCCCC4)cc23)cc1Cl,8.431798275933005,458.145571668,5,3,4.938200000000004,True
+488,CHEMBL40130,3.7,nM,1997.0,Brc1cccc(Nc2ncnc3cc4c(ccn4CCN4CCOCC4)cc23)c1,8.431798275933005,451.100772424,6,1,4.422800000000003,True
+489,CHEMBL38199,3.7,nM,1997.0,Brc1cccc(Nc2ncnc3cc4c(cnn4CCN4CCOCC4)cc23)c1,8.431798275933005,452.09602139200007,7,1,3.817800000000002,True
+490,CHEMBL1914653,3.7,nM,2011.0,Br.C[C@@H](Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12)c1ccccc1,8.431798275933005,410.074223328,4,3,5.081500000000004,True
+491,CHEMBL1914654,3.8,nM,2011.0,Br.C[C@@H](Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12)c1ccc(F)cc1,8.42021640338319,428.064801516,4,3,5.220600000000004,True
+492,CHEMBL96780,3.8,nM,1996.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1N,8.42021640338319,344.027273136,5,2,3.726700000000002,True
+493,CHEMBL94431,3.8,nM,1996.0,COc1cc2ncnc(Nc3cccc(F)c3)c2cc1OC,8.42021640338319,299.10700490799996,5,1,3.529700000000002,True
+494,CHEMBL3980793,3.8,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@H]1C(=O)NCCOC,8.42021640338319,575.174703116,8,2,4.000600000000003,True
+495,CHEMBL2437469,3.82,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.41793663708829,512.2284367560001,10,2,2.8042000000000007,True
+496,CHEMBL166307,3.9,nM,1998.0,CN1CCN(NCCCNc2cc3c(Nc4cccc(Br)c4)ncnc3cn2)CC1,8.4089353929735,470.1542049640001,8,3,3.084900000000001,True
+497,CHEMBL4228672,3.9,nM,2018.0,C=CC(=O)Nc1cc(Nc2ncc3ncn(-c4ccc(Cl)cc4)c3n2)c(OC)cc1N(C)CCN(C)C,8.4089353929735,520.210199848,9,2,4.343400000000003,True
+498,CHEMBL31588,3.9,nM,2000.0,C=CC(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cc1OCCCCN(C)C,8.4089353929735,483.12698717200004,6,2,4.981000000000004,True
+499,CHEMBL4217992,3.9,nM,2018.0,CN(C)C1CCN(c2ccc(Nc3cc4c(N5CCOCC5)nc(Nc5ccccc5)nc4cn3)nc2)CC1,8.4089353929735,525.2964567400002,10,2,4.274000000000003,True
+500,CHEMBL3892567,3.9,nM,2016.0,OC[C@@H](Nc1ncnc2oc(-c3ccccc3)cc12)c1ccccc1,8.4089353929735,331.132076784,5,2,4.035300000000003,True
+501,CHEMBL3814846,3.96,nM,2016.0,CC(=O)Nc1ccc2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2c1,8.402304814074487,436.110231716,5,2,5.703300000000003,True
+502,CHEMBL250923,4.0,nM,2007.0,COc1cc2ncnc(/C=C/CCc3ccccc3)c2cc1OC,8.397940008672037,320.15247787999994,4,0,4.293000000000004,True
+503,CHEMBL1914665,4.0,nM,2011.0,Br.CC[C@@H](Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12)c1ccccc1,8.397940008672037,424.089873392,4,3,5.471600000000004,True
+504,CHEMBL78018,4.0,nM,2004.0,NCc1ccc(-c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,8.397940008672037,371.120466544,5,3,5.041900000000003,True
+505,CHEMBL421326,4.0,nM,2004.0,OCCOCCNCc1ccc(-c2cc3nccc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,8.397940008672037,458.17764707199996,6,4,5.286700000000004,True
+506,CHEMBL3760071,4.0,nM,2016.0,COC(=O)c1cc(OC)c(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3s2)c(OC)c1,8.397940008672037,449.140927216,8,1,5.335200000000004,True
+507,CHEMBL65250,4.0,nM,2002.0,C#Cc1cc(Nc2ncnc3cc(OC)c(OC)cc23)ccc1F,8.397940008672037,323.10700490799996,5,1,3.511000000000002,True
+508,CHEMBL3895411,4.0,nM,2012.0,C=C(CN1CCOCC1)C(=O)N1CC(Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C1,8.397940008672037,545.1641384320001,8,1,3.7916000000000025,True
+509,CHEMBL470219,4.0,nM,2009.0,Fc1ccc(Nc2ncnc3nc(Nc4ccc(CN5CCCC5)cc4)sc23)cc1Cl,8.397940008672037,454.11427153999995,7,2,5.961800000000004,True
+510,CHEMBL3114688,4.0,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(C(=O)/C=C/CN2CCCCC2)CCO4)c1,8.397940008672037,453.216475104,6,1,4.122200000000004,True
+511,CHEMBL3233786,4.0,nM,2014.0,O=C(/C=C/CN1CCC(F)CC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.397940008672037,463.10451538000007,6,2,5.156000000000003,True
+512,CHEMBL4242522,4.0,nM,2018.0,CCc1ccc(N(C)c2ncnc3occ(C)c23)cc1,8.397940008672037,267.137162164,4,0,3.8615200000000023,True
+513,CHEMBL3947406,4.0,nM,2016.0,COc1ccccc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2o1,8.397940008672037,345.14772684800005,5,1,5.071500000000004,True
+514,CHEMBL545541,4.0,nM,1997.0,COc1cc2ncnc(NCc3ccccc3)c2cc1OC.Cl,8.397940008672037,331.10875449599996,5,1,3.6809000000000025,True
+515,CHEMBL50344,4.0,nM,1996.0,CNc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.397940008672037,328.03235851600004,4,2,4.177600000000002,True
+516,CHEMBL295961,4.0,nM,1996.0,CNc1ccc2cncnc2c1,8.397940008672037,159.079647288,3,1,1.6714999999999998,True
+517,CHEMBL3647421,4.0,nM,2014.0,CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/[C@@H]1CCCN1C,8.397940008672037,469.16808094000004,6,2,5.153500000000005,True
+518,CHEMBL4172718,4.0,nM,2018.0,COc1cc2ncnc(N3CCc4ccccc43)c2cc1NC(=O)/C=C/CN1CCC(CO)CC1,8.397940008672037,473.242689852,7,2,3.531600000000002,True
+519,CHEMBL92812,4.0,nM,1997.0,CNc1ccc2c(Nc3cccc(Br)c3)ncnc2c1,8.397940008672037,328.03235851600004,4,2,4.177600000000002,True
+520,CHEMBL3959632,4.0,nM,2016.0,C=CC(=O)Nc1cccc(-n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cc(C)ccc32)c1,8.397940008672037,464.146010508,4,2,5.7295200000000035,True
+521,CHEMBL3953221,4.0,nM,2016.0,C=CC(=O)N[C@H]1CCC[C@@H](n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cc(C)ccc32)C1,8.397940008672037,470.1929607,4,2,5.4017200000000045,True
+522,CHEMBL3961961,4.0,nM,2016.0,COc1ccc(-c2cc3c(N[C@H](CCO)c4ccccc4)ncnc3o2)cc1,8.397940008672037,375.1582915320001,6,2,4.434000000000002,True
+523,CHEMBL3633774,4.0,nM,2015.0,NC(=O)Nc1ccc2ncnc(Nc3ccc(Oc4cccc(C(F)(F)F)c4)c(Cl)c3)c2c1,8.397940008672037,473.08663706000004,5,3,6.328500000000003,True
+524,CHEMBL3678952,4.0,nM,2015.0,COc1cccc(Nc2nc3cnc(Nc4ccc(N5CCN(C)CC5)cc4)nc3n2C(C)C)c1,8.397940008672037,472.26990764400006,9,2,4.654800000000004,True
+525,CHEMBL209343,4.0,nM,2006.0,CNc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,8.397940008672037,284.082874096,4,2,4.068500000000002,True
+526,CHEMBL3674151,4.0,nM,2015.0,CC(C)n1c(Nc2ccc(F)c(Cl)c2)nc2cnc(Nc3ccc(C(=O)NN4CCN(C)CC4)cc3F)nc21,8.397940008672037,555.207340636,9,3,4.718200000000005,True
+527,CHEMBL3671487,4.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCNC(C)=O,8.397940008672037,501.08117985200005,6,3,4.3045000000000035,True
+528,CHEMBL3671497,4.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(N)=O,8.397940008672037,488.06077875600005,6,4,3.446600000000001,True
+529,CHEMBL3676357,4.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Cl)cc3F)ncnc2cc1OCCNCC(C)=O,8.397940008672037,491.09272308,7,3,4.501200000000003,True
+530,CHEMBL3671502,4.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCN,8.397940008672037,445.0549651040001,6,3,3.737000000000002,True
+531,CHEMBL3678948,4.0,nM,2015.0,C#Cc1cccc(Nc2nc3cnc(Nc4ccc(N5CCN(C)CC5)cc4)nc3n2C(C)C)c1,8.397940008672037,466.25934296,8,2,4.627500000000004,True
+532,CHEMBL3678949,4.0,nM,2015.0,CC(C)n1c(Nc2ccc(F)c(Cl)c2)nc2cnc(Nc3ccc(N4CCN(C)CC4)cc3)nc21,8.397940008672037,494.2109487960001,8,2,5.438700000000005,True
+533,CHEMBL3915508,4.1,nM,2016.0,N#Cc1ccc(Nc2nncc3ccccc23)cc1,8.387216143280265,246.09054632,4,1,3.2450800000000015,True
+534,CHEMBL4166609,4.1,nM,2018.0,C=CC(=O)Nc1cc(Nc2nccc(Nc3ccccc3-n3cccn3)n2)c(OC)cc1N(C)CCN(C)C,8.387216143280265,527.2757212960001,10,3,4.280400000000003,True
+535,CHEMBL2048905,4.1,nM,2012.0,OCCn1ccc2ncnc(Nc3ccc(Oc4cccc5sncc45)c(Cl)c3)c21,8.387216143280265,437.071323432,8,2,5.222600000000003,True
+536,CHEMBL4175045,4.1,nM,2018.0,C=CC(=O)Nc1cc(Nc2nccc(Nc3ccccc3-c3ccn(C)n3)n2)c(OC)cc1N(C)CCN(C)C,8.387216143280265,541.2913713600001,10,3,4.495200000000004,True
+537,CHEMBL3958624,4.1,nM,2012.0,C=CC(=O)N1CC[C@@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@@H]1C(N)=O,8.387216143280265,517.1328383040001,7,2,3.723300000000002,True
+538,CHEMBL428741,4.1,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OCc4cccc(F)c4)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,8.387216143280265,545.207447216,9,2,3.7722000000000016,True
+539,CHEMBL172652,4.1,nM,1996.0,Brc1cccc(Nc2ncnc3cc4[nH]nnc4cc23)c1,8.387216143280265,340.00720638800004,5,2,3.4072000000000005,True
+540,CHEMBL3787344,4.18,nM,2016.0,Cc1cc(C(=O)Nc2nc3cccc(Cl)c3n2[C@@H]2CCCCN(C(=O)/C=C/CN(C)C)C2)ccn1,8.378823718224965,494.21970191200006,6,1,4.316820000000003,True
+541,CHEMBL4227210,4.2,nM,2018.0,C=CC(=O)Nc1cc(Nc2ncc3ncn(-c4ccc(C(C)C)cc4)c3n2)c(OC)cc1N(C)CCN(C)C,8.3767507096021,528.296122392,9,2,4.813400000000003,True
+542,CHEMBL4067871,4.2,nM,2017.0,OC[C@H](Nc1cnc(-c2cc(Cl)ccc2O)c(-c2ccc3cnccc3c2)c1)c1ccccc1,8.3767507096021,467.140054624,5,3,6.468300000000006,True
+543,CHEMBL380669,4.2,nM,2006.0,CC(C)N(CC#CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1)C(C)C,8.3767507096021,453.17316632,5,2,5.226600000000004,True
+544,CHEMBL399373,4.2,nM,2007.0,CCOc1cc2ncnc(C#C[C@@](C)(Cc3ccccc3)N3CCC(C(=O)O)CC3)c2cc1OCC,8.3767507096021,487.24710653599993,6,1,4.576700000000003,True
+545,CHEMBL3622678,4.2,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OCC)c(NC(=O)/C=C/CNC4CC4)cc23)c1,8.3767507096021,427.20082504000004,6,3,4.000100000000002,True
+546,CHEMBL3932286,4.2,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4cccc(Cl)c4)ncnc3cc2OC)CC1,8.3767507096021,438.14586827600004,6,1,4.591200000000004,True
+547,CHEMBL4082515,4.2,nM,2017.0,C=CC(=O)Nc1cccc(-n2c(=O)cc(C)c3cnc(Nc4cnn(CCN(C)C)c4)nc32)c1,8.3767507096021,458.2178720720001,9,2,2.71532,True
+548,CHEMBL50519,4.3,nM,1996.0,COc1ccc2ncnc(Nc3cccc(Br)c3)c2n1,8.366531544420411,330.011623072,5,1,3.539500000000002,True
+549,CHEMBL3906533,4.4,nM,2016.0,CCOC(=O)c1ccc(Nc2nncc3ccccc23)cc1,8.356547323513812,293.11642672,5,1,3.5501000000000014,True
+550,CHEMBL225928,4.4,nM,2007.0,CN(CCCl)CCN/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,8.356547323513812,417.123549032,6,2,4.785700000000004,True
+551,CHEMBL3805774,4.4,nM,2016.0,CCOc1cc2ncnc(Nc3cccc(OC)c3)c2c2c1OCCO2,8.356547323513812,353.13755608799994,7,1,3.5519000000000016,True
+552,CHEMBL3972168,4.4,nM,2012.0,C=CC(=O)N1CC[C@@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@@H]1C(=O)OC,8.356547323513812,532.1325039559999,8,1,4.411000000000003,True
+553,CHEMBL2029430,4.41,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4OCC)nc32)c1,8.355561410532161,542.2753869480001,8,2,4.198700000000003,True
+554,CHEMBL590559,4.45,nM,2010.0,C=C=CCCCCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O,8.351639989019068,413.13063281200004,5,2,6.151800000000004,True
+555,CHEMBL4129138,4.5,nM,2018.0,CN1CCN(c2ccc(Nc3cc4c(N[C@@H]5CCCN(C)C5)nc(Nc5ccccc5)nc4cn3)nc2)CC1,8.346787486224656,524.3124411520001,10,3,4.164900000000003,True
+556,CHEMBL67057,4.5,nM,2002.0,Cc1cc(C(=O)N2CCOCC2)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc4c(ccn4Cc4ccccc4)c3)c21,8.346787486224656,559.2331877880001,7,3,4.824820000000003,True
+557,CHEMBL3818289,4.54,nM,2016.0,O=C1N[C@H](C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3cc2OCCCN2CCOCC2)CO1,8.342944147142896,544.1637238320001,9,3,3.313900000000001,True
+558,CHEMBL598164,4.6,nM,2010.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(OCCCCCC(=O)NO)cc23)c1,8.337242168318426,420.17975524799994,7,3,3.807900000000002,True
+559,CHEMBL3900264,4.6,nM,2016.0,Clc1ccc(/C=C/C(=N/Nc2nncc3ccccc23)c2ccccc2)cc1,8.337242168318426,384.114174224,4,1,5.812800000000004,True
+560,CHEMBL433520,4.6,nM,1998.0,CCN(CC)CC(O)CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.337242168318426,444.12732152000007,7,3,3.645500000000001,True
+561,CHEMBL4127897,4.6,nM,2018.0,C=CC(=O)N1CC[C@@H](Nc2nc(Nc3ccccc3)nc3cnc(Nc4ccc(N5CCN(C)CC5)cn4)cc23)C1,8.337242168318426,550.2917057080001,10,3,3.8576000000000024,True
+562,CHEMBL3956112,4.6,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3cccc(O)c3)cc12)c1ccccc1,8.337242168318426,331.132076784,5,2,4.768500000000003,True
+563,CHEMBL3219133,4.68,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)C(Cc3ccccc3)N(C)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.329754146925875,646.3016016960001,9,2,4.466700000000004,True
+564,CHEMBL1914667,4.7,nM,2011.0,COc1ccc(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3[nH]2)cc1,8.327902142064282,344.16371126,4,2,4.806600000000004,True
+565,CHEMBL93302,4.7,nM,1996.0,Oc1ccc2c(Nc3cccc(Br)c3)ncnc2c1,8.327902142064282,315.00072404,4,2,3.841500000000001,True
+566,CHEMBL4062877,4.7,nM,2017.0,Cc1n[nH]c2ccc(-c3cc(N[C@@H](CO)c4ccccc4)cnc3-c3cc(F)ccc3O)cc12,8.327902142064282,454.180504196,5,4,5.590520000000005,True
+567,CHEMBL4125764,4.7,nM,2018.0,C=CC(=O)N[C@@H]1CCN(c2nc(Nc3ccccc3)nc3cnc(Nc4ccc(N5CCN(C)CC5)cn4)cc23)C1,8.327902142064282,550.2917057080001,10,3,3.5397000000000025,True
+568,CHEMBL308645,4.7,nM,2002.0,Cc1cc(CCC(=O)O)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc(F)c(Cl)c3)c21,8.327902142064282,441.1003953040001,5,4,4.1591200000000015,True
+569,CHEMBL129579,4.8,nM,1997.0,OCC(O)C(O)C(O)C(O)CNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.318758762624412,479.0804309040001,10,7,0.37869999999999987,True
+570,CHEMBL36967,4.8,nM,1997.0,Brc1cccc(Nc2ncnc3cc4[nH]cc(CN5CCOCC5)c4cc23)c1,8.318758762624412,437.08512236,5,2,4.4494000000000025,True
+571,CHEMBL4102886,4.87,nM,2017.0,C#Cc1cccc(Nc2ncnc3cc(OCCCN4C[C@H](O)[C@@H](O)[C@H](O)[C@H]4CO)c(OC)cc23)c1,8.312471038785366,494.2165346799999,10,5,0.8913999999999997,True
+572,CHEMBL4089279,4.9,nM,2017.0,C=CC(=O)NCc1cccc(Nc2cc(-c3[nH]c(SC)nc3-c3ccc(F)cc3)ccn2)c1,8.309803919971486,459.152909544,5,3,5.545500000000004,True
+573,CHEMBL3355887,4.9,nM,2015.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCn1c([N+](=O)[O-])cnc1C,8.309803919971486,472.106208956,9,1,4.6666200000000035,True
+574,CHEMBL4104515,4.9,nM,2017.0,COc1ccc2c(c1)CCCN2c1nc(C)nc2c(Cc3ccccc3)cn(C)c12.Cl,8.309803919971486,434.18733916400004,5,0,5.3822200000000056,True
+575,CHEMBL4103912,4.9,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccc(F)cc34)n2)c(OC)cc1N(C)CCN(C)C,8.309803919971486,517.2601514840001,8,2,4.648900000000004,True
+576,CHEMBL340484,4.9,nM,1997.0,CN1CCN(CCCNc2cc3ncnc(Nc4cccc(Br)c4)c3cn2)CC1,8.309803919971486,455.143305932,7,2,3.580300000000001,True
+577,CHEMBL2032377,4.99,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N(C)C)cc4OC)nc32)c1,8.30189945437661,473.21753772400007,7,2,4.1228000000000025,True
+578,CHEMBL3759280,5.0,nM,2016.0,COc1cc(C=O)ccc1-c1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.301029995663981,413.0401035560001,6,1,5.715500000000002,True
+579,CHEMBL4079501,5.0,nM,2017.0,C=CC(=O)Nc1cc(Nc2n[nH]c3cc(-c4ccncc4)ccc23)c(OC)cc1N(C)CCN(C)C,8.301029995663981,485.25392323200003,7,3,4.499400000000003,True
+580,CHEMBL299893,5.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCC(O)CN(CCO)CCO,8.301029995663981,480.1575758319999,9,4,2.2008000000000005,True
+581,CHEMBL77782,5.0,nM,2004.0,CN(C)CCc1ccc(-c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,8.301029995663981,413.167416736,5,2,5.687300000000004,True
+582,CHEMBL80809,5.0,nM,2004.0,CC(=O)NCCNCc1ccc(-c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,8.301029995663981,456.173230388,6,4,4.808900000000003,True
+583,CHEMBL310827,5.0,nM,2004.0,Cc1c[nH]c2ccc(Nc3ncnc4cc(-c5ccccc5)sc34)cc12,8.301029995663981,356.109567512,4,2,5.891620000000003,True
+584,CHEMBL197640,5.0,nM,2005.0,CN1CCC(Oc2cccc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c23)CC1,8.301029995663981,492.172831972,6,1,6.217900000000005,True
+585,CHEMBL3671499,5.0,nM,2014.0,C=CC(=O)NCCOc1cc2ncnc(Nc3ccc(Br)cc3F)c2cc1NC(=O)C=C,8.301029995663981,499.065529788,6,3,4.0805000000000025,True
+586,CHEMBL3758939,5.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3cccc(C(N)=O)c3)cc12)c1ccccc1,8.301029995663981,374.120132196,5,2,4.630300000000003,True
+587,CHEMBL332882,5.0,nM,1997.0,Nc1cccc(-c2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)c1,8.301029995663981,336.089022096,5,3,3.999100000000001,True
+588,CHEMBL3741424,5.0,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OCCOC(=O)c4ccccc4OC(C)=O)c(OCCOC)cc23)c1,8.301029995663981,541.1849002039999,10,1,4.541000000000004,True
+589,CHEMBL399371,5.0,nM,2007.0,CCOc1cc2ncnc(/C=C/CCc3ccccc3)c2cc1OCC,8.301029995663981,348.18377800799993,4,0,5.073200000000004,True
+590,CHEMBL3758868,5.0,nM,2016.0,COc1ccc(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3s2)c(OC)c1,8.301029995663981,391.13544791199996,6,1,5.548600000000004,True
+591,CHEMBL56266,5.0,nM,2001.0,CNCC(O)COc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,8.301029995663981,406.1207964,7,3,3.1336000000000013,True
+592,CHEMBL3759929,5.0,nM,2016.0,COc1ccc(CO)cc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,8.301029995663981,391.13544791200013,6,2,5.032300000000004,True
+593,CHEMBL312818,5.0,nM,2004.0,c1ccc(CCCN(c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)n2ccnc2)cc1,8.301029995663981,465.17356473600006,7,2,6.0152000000000045,True
+594,CHEMBL3676341,5.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Cl)cc3F)ncnc2cc1OCCNC(C)=O,8.301029995663981,477.077073016,6,3,4.458700000000003,True
+595,CHEMBL4216679,5.0,nM,2017.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cn(C)nc3OC)c3ncn(C(C)C)c3n2)C[C@H]1F,8.301029995663981,443.21934929200006,10,2,1.721799999999999,True
+596,CHEMBL56802,5.0,nM,2001.0,COc1cc2ncnc(Nc3cccc(C)c3)c2cc1OC,8.301029995663981,295.132076784,5,1,3.6990200000000026,True
+597,CHEMBL332612,5.0,nM,1997.0,Nc1ccc(Nc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,8.301029995663981,351.09992112799995,6,4,4.075700000000001,True
+598,CHEMBL402294,5.0,nM,2008.0,CCO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,8.301029995663981,405.17133648000004,8,2,3.709900000000002,True
+599,CHEMBL3416625,5.0,nM,2015.0,COc1ccccc1-c1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.301029995663981,385.04518893600005,5,1,5.903000000000002,True
+600,CHEMBL3357655,5.0,nM,2014.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1NC(=O)/C(F)=C\CN(C)C,8.301029995663981,473.086265232,6,2,4.498000000000003,True
+601,CHEMBL2087356,5.0,nM,2012.0,Brc1cccc(Nc2ncnc3cc4c(cc23)OCCOCOCOCCO4)c1,8.301029995663981,461.05863283999986,8,1,3.871900000000002,True
+602,CHEMBL3759022,5.0,nM,2016.0,COc1cc(CO)ccc1-c1cc2c(NCc3ccccc3)ncnc2s1,8.301029995663981,377.11979784800013,6,2,4.471300000000002,True
+603,CHEMBL4168254,5.0,nM,2018.0,CN(C)C/C=C/C(=O)Nc1cc2c(N3CCc4ccccc43)ncnc2cc1O[C@@H]1CCOC1,8.301029995663981,459.227039788,7,1,3.548000000000002,True
+604,CHEMBL2087355,5.0,nM,2012.0,Brc1cccc(Nc2ncnc3cc4c(cc23)OCCOCCOCCO4)c1,8.301029995663981,445.0637182199999,7,1,3.9403000000000024,True
+605,CHEMBL3758802,5.0,nM,2016.0,C#Cc1cccc(Nc2ncnc3sc(-c4ccc(CO)cc4OC)cc23)c1,8.301029995663981,387.10414778399996,6,2,4.584100000000003,True
+606,CHEMBL258282,5.0,nM,2008.0,CN1CCN(CCOc2n[nH]c3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c23)CC1,8.301029995663981,494.194549784,9,2,3.350100000000001,True
+607,CHEMBL3114687,5.0,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(C(=O)/C=C/CN(CC)CC)CCO4)c1,8.301029995663981,441.216475104,6,1,3.978100000000003,True
+608,CHEMBL2178351,5.0,nM,2015.0,CC(C)n1c(Nc2ccccc2)nc2cnc(Nc3ccc(N4CCN(C)CC4)cc3)nc21,8.301029995663981,442.25934296,8,2,4.646200000000003,True
+609,CHEMBL248392,5.0,nM,2007.0,COc1cc2c(N[C@@H]3C[C@H]3c3ccccc3)c(C#N)cnc2cc1OCCCN1CCOCC1,8.301029995663981,458.23179081999996,7,1,4.184180000000003,True
+610,CHEMBL3114686,5.0,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(C(=O)/C=C/CN2CCCCC2C)CCO4)c1,8.301029995663981,467.232125168,6,1,4.510700000000004,True
+611,CHEMBL3671495,5.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(F)F,8.301029995663981,523.046686164,6,3,4.159600000000002,True
+612,CHEMBL3114701,5.0,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(C(=O)/C=C/CN2CCC(C)CC2)CCO4)c1,8.301029995663981,467.232125168,6,1,4.368200000000004,True
+613,CHEMBL3962343,5.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(NC(C)C)cc3OC)ncc2Cl)c1,8.301029995663981,452.17275172,7,4,5.570600000000003,True
+614,CHEMBL3542268,5.06,nM,2017.0,OCc1ccc(-c2ccc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3c2)o1,8.2958494831602,475.10989736799996,6,2,6.497200000000003,True
+615,CHEMBL3814816,5.06,nM,2016.0,S=C(NCCN1CCOCC1)Nc1ccc2ncnc(Nc3ccc(Cl)cc3)c2c1,8.2958494831602,442.13425803600006,6,3,3.6454000000000013,True
+616,CHEMBL289162,5.1,nM,1997.0,O=C(O)Cn1ccc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,8.292429823902062,396.0221877560001,5,2,4.175200000000002,True
+617,CHEMBL4290568,5.2,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2ncc(C)c(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,8.2839966563652,525.28522336,8,2,4.973320000000004,True
+618,CHEMBL2437471,5.29,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)c(C)nc3cnc(Nc4ccc(OC)cc4)nc32)c1,8.276544327964814,428.1596885,8,2,3.3608200000000013,True
+619,CHEMBL3622671,5.3,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(O[C@H]4CCOC4)c(NC(=O)/C=C/CN4CCCCC4)cc23)c1,8.275724130399214,497.242689852,7,2,4.503000000000004,True
+620,CHEMBL3933539,5.3,nM,2016.0,COc1ccc(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3o2)cc1,8.275724130399214,345.147726848,5,1,5.071500000000004,True
+621,CHEMBL4068839,5.3,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc(OCc4ccccn4)c(Cl)c3)c3c(N)ncnc32)C1,8.275724130399214,489.16800068800006,8,1,4.052400000000002,True
+622,CHEMBL4104658,5.3,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn4c5c(cccc35)CCC4)n2)c(OC)cc1N(C)CCN(C)C,8.275724130399214,525.28522336,8,2,4.919000000000003,True
+623,CHEMBL1243255,5.35,nM,2010.0,CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CNC,8.271646217978772,453.13678081200004,6,3,4.755380000000003,True
+624,CHEMBL3897723,5.4,nM,2016.0,COc1ccc(/C=C/C(=N/Nc2nncc3ccccc23)c2ccc(Cl)cc2)cc1,8.267606240177031,414.12473890800004,5,1,5.821400000000004,True
+625,CHEMBL126384,5.4,nM,1997.0,Brc1cccc(Nc2ncnc3cc(NCCCCN4CCOCC4)ncc23)c1,8.267606240177031,456.12732152000007,7,2,4.055200000000002,True
+626,CHEMBL338215,5.4,nM,1997.0,Cc1cccc(Nc2ncnc3cc(NCCCCN(C)C)ncc23)c1,8.267606240177031,350.221894832,6,2,3.8305200000000026,True
+627,CHEMBL3699622,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCS(=O)(=O)CC4)cc3OC)ncc2C(F)(F)F)c1,8.259637310505756,562.16100894,9,3,4.350500000000003,True
+628,CHEMBL1643971,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCOCC4)cc3OC)ncc2Cl)c1,8.259637310505756,481.15168192799996,8,2,4.635600000000003,True
+629,CHEMBL3699602,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(S(N)(=O)=O)CC4)cc3OC)ncc2C(F)(F)F)c1,8.259637310505756,593.166822592,9,3,3.4899000000000013,True
+630,CHEMBL3699603,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(C(=O)NC)CC4)cc3OC)ncc2C(F)(F)F)c1,8.259637310505756,570.231471448,8,4,4.577100000000003,True
+631,CHEMBL3699588,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C(C)=O)CC4)cc3OC)ncc2C(F)(F)F)c1,8.259637310505756,556.2045880039999,8,2,4.832900000000004,True
+632,CHEMBL3622655,5.5,nM,2015.0,CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C)C1CC1,8.259637310505756,469.16808094000004,6,2,5.153500000000005,True
+633,CHEMBL3699584,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(C(=O)CO)CC4)cc3OC)ncc2C(F)(F)F)c1,8.259637310505756,571.2154870359999,9,4,3.7566000000000024,True
+634,CHEMBL3699586,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(C(C)=O)CC4)cc3OC)ncc2Cl)c1,8.259637310505756,521.194215436,8,3,4.418800000000004,True
+635,CHEMBL3699611,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCCOCC4)cc3OC)ncc2Cl)c1,8.259637310505756,495.16733199199996,8,2,5.025700000000004,True
+636,CHEMBL3699587,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C(C)=O)CC4)cc3OC)ncc2Cl)c1,8.259637310505756,522.178231024,8,2,4.467500000000004,True
+637,CHEMBL3699615,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(S(C)(=O)=O)CC4)cc3OC)ncc2Cl)c1,8.259637310505756,557.1612010559999,9,3,3.8319000000000027,True
+638,CHEMBL3699583,5.5,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C(=O)CO)CC4)cc3OC)ncc2Cl)c1,8.259637310505756,538.173145644,9,3,3.4399000000000015,True
+639,CHEMBL3818563,5.52,nM,2016.0,CCOc1cc2ncnc(N[C@@H](C)c3ccccc3)c2cc1NC(=O)[C@@H]1COC(=O)N1,8.2580609222708,421.175004216,7,3,3.2485,True
+640,CHEMBL1928291,5.54,nM,2012.0,O=C(c1cc2ccccc2[nH]1)c1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.25649023527157,422.040437904,5,2,5.939700000000002,True
+641,CHEMBL4076854,5.6,nM,2017.0,C=CC(=O)Nc1ccc(OC)c(Nc2cc(-c3cnc(SC)[nH]3)ccn2)c1,8.2518119729938,381.1259458480001,6,3,4.070300000000001,True
+642,CHEMBL3903713,5.6,nM,2016.0,C(=C/c1ccccc1)\C(=N\Nc1nncc2ccccc12)c1ccccc1,8.2518119729938,350.153146576,4,1,5.159400000000003,True
+643,CHEMBL341522,5.6,nM,1997.0,Cc1cccc(Nc2ncnc3cc(NCCCN4CCN(C)CC4)ncc23)c1,8.2518119729938,391.24844392800003,7,2,3.1262200000000018,True
+644,CHEMBL1873475,5.6,nM,2011.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1,8.2518119729938,440.19607400800004,7,1,4.2173000000000025,True
+645,CHEMBL3622676,5.6,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(O[C@H]4CCOC4)c(NC(=O)/C=C/CNC4CC4)cc23)c1,8.2518119729938,469.211389724,7,3,3.7691000000000017,True
+646,CHEMBL248393,5.7,nM,2007.0,COc1cc2c(N[C@@H]3C[C@H]3c3ccccc3)c(C#N)cnc2cc1OCCCN1CCN(C)CC1,8.244125144327509,471.26342529600004,7,1,4.099380000000004,True
+647,CHEMBL3219347,5.78,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)C(Cc3ccc(F)cc3)N(C)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.238072161579469,664.2921798840001,9,2,4.605800000000004,True
+648,CHEMBL53203,5.8,nM,1999.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(Oc4ccccc4)cc3)c2c1,8.236572006437061,382.142975816,5,2,5.290200000000003,True
+649,CHEMBL3622629,5.8,nM,2015.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,8.236572006437061,428.10514633599996,6,2,4.458100000000003,True
+650,CHEMBL69071,5.9,nM,2002.0,Cc1cc(C(=O)N2CC(C)NC(C)C2)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc(F)c(Cl)c3)c21,8.229147988357855,509.1742289400001,6,4,3.9643200000000016,True
+651,CHEMBL1928312,5.93,nM,2012.0,COc1ccc2[nH]c(C(=O)c3cc4c(Nc5ccc(F)c(Cl)c5)ncnc4s3)cc2c1,8.226945306635738,452.051002588,6,2,5.948300000000002,True
+652,CHEMBL471058,6.0,nM,2009.0,CCc1nccn1Cc1ccc(Nc2nc3ncnc(Nc4ccc(F)c(Cl)c4)c3s2)cc1,8.221848749616356,479.109520508,8,2,6.173200000000004,True
+653,CHEMBL3963723,6.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4[nH]ccc4c3)ncnc2cc1OC,8.221848749616356,361.15387484800004,5,3,4.211800000000002,True
+654,CHEMBL329856,6.0,nM,2001.0,CN(C)CC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.221848749616356,423.069472296,5,2,3.639400000000001,True
+655,CHEMBL4087538,6.0,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4c(F)cccc34)n2)c(OC)cc1N(C)CCN(C)C,8.221848749616356,517.2601514840001,8,2,4.648900000000004,True
+656,CHEMBL56502,6.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCC(O)CN,8.221848749616356,392.10514633599996,7,3,2.8729000000000005,True
+657,CHEMBL3759900,6.0,nM,2016.0,COc1cc(C=O)ccc1-c1cc2c(NCc3ccccc3)ncnc2s1,8.221848749616356,375.10414778400013,6,1,4.791500000000003,True
+658,CHEMBL3671484,6.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C(=O)CN(C)C)CC1,8.221848749616356,584.1546791400001,7,2,4.5785000000000045,True
+659,CHEMBL7917,6.0,nM,1999.0,COc1cc2ncnc(Nc3cccc(Cl)c3)c2cc1OC,8.221848749616356,315.07745436799996,5,1,4.044000000000002,True
+660,CHEMBL118130,6.0,nM,1997.0,Oc1ccc(-c2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,8.221848749616356,337.073037684,5,3,4.122500000000002,True
+661,CHEMBL3898447,6.0,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4cccc(Cl)c4F)ncnc3cc2OC)CC1,8.221848749616356,456.136446464,6,1,4.730300000000004,True
+662,CHEMBL3914159,6.0,nM,2012.0,C=CC(=O)N1CC(Oc2cc3c(Nc4ccc(Cl)c(Cl)c4F)ncnc3cc2OC)C1,8.221848749616356,462.06617398400005,6,1,4.603500000000004,True
+663,CHEMBL3954587,6.0,nM,2012.0,C=CC(=O)N1CC(Oc2cc3c(Nc4cccc(Cl)c4F)ncnc3cc2OC)C1,8.221848749616356,428.105146336,6,1,3.9501000000000026,True
+664,CHEMBL3926558,6.0,nM,2012.0,C=CC(=O)N1CC(Oc2cc3c(N[C@H](C)c4ccccc4)ncnc3cc2OC)C1,8.221848749616356,404.184840628,6,1,3.587100000000002,True
+665,CHEMBL206955,6.0,nM,2006.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1CN1CCC[C@@H]1C(N)=O,8.221848749616356,429.13678081200004,6,2,3.624200000000002,True
+666,CHEMBL306315,6.0,nM,1996.0,Clc1cccc(Nc2ncnc3[nH]c4ccccc4c23)c1,8.221848749616356,294.067224032,3,2,4.5081000000000016,True
+667,CHEMBL3622648,6.0,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC4CCOCC4)c(NC(=O)/C=C/CN(C)C)cc23)c1,8.221848749616356,471.227039788,7,2,3.9688000000000025,True
+668,CHEMBL3759780,6.0,nM,2016.0,COc1cc(F)ccc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,8.221848749616356,379.1154614160001,5,1,5.679100000000004,True
+669,CHEMBL1645474,6.0,nM,2011.0,NC1CCN(Cc2ccn3ncnc(Nc4cccc(Br)c4)c23)CC1,8.221848749616356,400.101106772,6,2,3.1585,True
+670,CHEMBL3979610,6.0,nM,2016.0,Fc1ccc(Nc2nncc3ccccc23)cc1,8.221848749616356,239.08587554,3,1,3.512500000000001,True
+671,CHEMBL1173655,6.0,nM,2009.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,8.221848749616356,485.16299556,7,2,4.389900000000002,True
+672,CHEMBL2105719,6.0,nM,2012.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CCCCC1.O,8.221848749616356,487.178645624,6,2,4.3304000000000045,True
+673,CHEMBL461795,6.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1CN1CC[C@@H](C(N)=O)C1,8.221848749616356,429.13678081200004,6,2,3.481700000000002,True
+674,CHEMBL207815,6.0,nM,2006.0,COCCN1CC(C(N)=O)(N(C)Cc2cc3c(Nc4cccc(Cl)c4F)ncnc3cc2OC)C1,8.221848749616356,502.189544656,8,2,2.7924000000000007,True
+675,CHEMBL3758471,6.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3cccc(C=O)c3)cc12)c1ccccc1,8.221848749616356,359.109233164,5,1,5.343900000000003,True
+676,CHEMBL3622673,6.1,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OCC)c(NC(=O)/C=C/CN4CCCCC4)cc23)c1,8.214670164989233,455.23212516800004,6,2,4.734000000000004,True
+677,CHEMBL4063301,6.13,nM,2017.0,O=C(Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1)C1CCCCC1,8.212539525481585,380.140388972,4,2,5.545600000000003,True
+678,CHEMBL1229592,6.18,nM,2012.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3OC)ncc2Cl)c1,8.209011524911183,494.18331640400004,8,2,4.550800000000003,True
+679,CHEMBL3937949,6.2,nM,2016.0,O=C(O)c1ccc(Nc2nncc3ccccc23)cc1,8.207608310501746,265.085126592,4,2,3.071600000000001,True
+680,CHEMBL3219348,6.26,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)CN(Cc3ccccc3)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.20342566678957,632.285951632,9,2,4.425800000000003,True
+681,CHEMBL590878,6.27,nM,2016.0,Oc1cc(O)c2cc(O)c(-c3cc(O)c(O)c(O)c3)[o+]c2c1.[Cl-],8.202732459169281,338.019330372,6,6,-0.38149999999999984,True
+682,CHEMBL3966129,6.3,nM,2016.0,Clc1ccc(C(/C=C/c2ccccc2)=N\Nc2nncc3ccccc23)cc1,8.200659450546418,384.114174224,4,1,5.812800000000005,True
+683,CHEMBL4282688,6.3,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2ncc(OC)c(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,8.200659450546418,541.2801379800001,9,2,4.673500000000003,True
+684,CHEMBL4250210,6.4,nM,2018.0,CNc1ccc(N(C)c2ncnc3occ(C)c23)cc1,8.193820026016112,268.132411132,5,1,3.3408200000000017,True
+685,CHEMBL4079658,6.4,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CC[N+](C)(C)[O-],8.193820026016112,515.264487916,8,2,4.522400000000003,True
+686,CHEMBL3622679,6.4,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(O[C@H]4CCOC4)c(NC(=O)/C=C/CNC(C)C)cc23)c1,8.193820026016112,471.227039788,7,3,4.015100000000002,True
+687,CHEMBL162719,6.4,nM,1998.0,CN1CCN(c2cc3c(Nc4cccc(Br)c4)ncnc3cn2)CC1,8.193820026016112,398.0854567080001,6,1,3.282700000000002,True
+688,CHEMBL329867,6.4,nM,1997.0,COc1cc2ncnc(Nc3cncc4ccccc34)c2cc1OC,8.193820026016112,332.127325752,6,1,3.938800000000003,True
+689,CHEMBL4101719,6.47,nM,2017.0,OCCCc1nc(-c2ccc(F)cc2)c(-c2ccnc3[nH]c(-c4ccccc4)cc23)[nH]1,8.1890957193313,412.16993951200004,3,3,5.351000000000004,True
+690,CHEMBL3983586,6.5,nM,2016.0,Cc1ccc(C(/C=C/c2ccc(F)cc2)=N\Nc2nncc3ccccc23)cc1,8.187086643357143,382.159374828,4,1,5.606920000000004,True
+691,CHEMBL63469,6.5,nM,1996.0,Nc1cc2c(Nc3cccc(Br)c3)ncnc2cc1Cl,8.187086643357143,347.9777361,4,2,4.371500000000001,True
+692,CHEMBL3622666,6.5,nM,2015.0,O=C(/C=C/CNC1CC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,8.187086643357143,497.16299556,7,3,4.580300000000003,True
+693,CHEMBL4129209,6.5,nM,2018.0,C=CC(=O)N[C@@H]1CCCN(c2nc(Nc3ccccc3)nc3cnc(Nc4ccc(N5CCN(C)CC5)cn4)cc23)C1,8.187086643357143,564.307355772,10,3,3.929800000000003,True
+694,CHEMBL69629,6.5,nM,2002.0,Cc1cc(C(=O)NCCN2CCOCC2)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc(F)c(Cl)c3)c21,8.187086643357143,525.1691435600001,7,4,3.203920000000001,True
+695,CHEMBL284326,6.6,nM,2000.0,C=CC(=O)Nc1nc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCN(C)CC1,8.180456064458129,499.1898790040001,8,2,3.7017000000000015,True
+696,CHEMBL3979366,6.6,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(Nc4ccc(F)c(Cl)c4F)ncnc3cc2OC)C[C@H]1C(=O)NCCN(C)C,8.180456064458129,588.206337592,8,2,3.9158000000000026,True
+697,CHEMBL1914668,6.6,nM,2011.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(F)cc3)cc12)c1ccccc1,8.180456064458129,332.143724764,3,2,4.937100000000004,True
+698,CHEMBL3804868,6.7,nM,2016.0,CCOc1cc2ncnc(Nc3ccc(C)c(Cl)c3)c2c2c1OCCO2,8.173925197299173,371.10366911599994,6,1,4.505120000000003,True
+699,CHEMBL2148050,6.7,nM,2012.0,CS(=O)(=O)CC(=O)NCCn1ccc2ncnc(Nc3ccc(Oc4cccc(Cl)c4)c(Cl)c3)c21,8.173925197299173,533.069130512,8,2,4.434800000000004,True
+700,CHEMBL3950630,6.7,nM,2016.0,Cc1cc(C)nc(NS(=O)(=O)c2ccc(Nc3nncc4ccccc34)cc2)n1,8.173925197299173,406.121194816,7,2,3.5810400000000016,True
+701,CHEMBL4102577,6.8,nM,2017.0,CCC(=O)Nc1cccc(Nc2cc(-c3[nH]c(SC)nc3-c3ccc(F)cc3)ccn2)c1,8.167491087293763,447.152909544,5,3,6.0918000000000045,True
+702,CHEMBL3963403,6.9,nM,2016.0,Fc1ccc(/C=C/C(=N/Nc2nncc3ccccc23)c2ccccc2)cc1,8.161150909262744,368.143724764,4,1,5.298500000000003,True
+703,CHEMBL2437460,6.95,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(N5CCOCC5)cc4)nc32)c1,8.158015195409886,469.18623759600007,9,2,2.8804000000000007,True
+704,CHEMBL2029426,6.95,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccccc4)nc32)c1,8.158015195409886,400.16477388000004,5,2,4.048200000000002,True
+705,CHEMBL3219132,6.99,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)CN(c3ccccc3)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.155522824254321,618.270301568,9,2,4.430200000000004,True
+706,CHEMBL57759,7.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN(C)C,8.154901959985743,390.12588178,6,1,4.114900000000003,True
+707,CHEMBL255170,7.0,nM,2008.0,Cc1ccc(Oc2ccc(Nc3ncnc4[nH]nc(OCCN5CCC(O)CC5)c34)cc2Cl)cn1,8.154901959985743,495.178565372,9,3,4.081120000000001,True
+708,CHEMBL1172843,7.0,nM,2010.0,C=CC(=O)Nc1cccc(-c2c(-c3ccccc3)oc3ncnc(N[C@H](CO)c4ccccc4)c23)c1,8.154901959985743,476.184840628,6,3,5.826800000000005,True
+709,CHEMBL3758762,7.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3ccc(C(N)=O)cc3)cc12)c1ccccc1,8.154901959985743,374.120132196,5,2,4.630300000000003,True
+710,CHEMBL3671570,7.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN1CCCCC1,8.154901959985743,570.139029076,7,3,4.380400000000003,True
+711,CHEMBL2087357,7.0,nM,2012.0,Brc1cccc(Nc2ncnc3cc4c(cc23)OCCSCCO4)c1,8.154901959985743,417.01465985199997,6,1,4.6403000000000025,True
+712,CHEMBL4062178,7.0,nM,2018.0,Cc1cc(Nc2ncc3c(n2)N([C@H]2CCN(C(=O)CO)C2)C(=O)N(c2ccccc2Cl)C3)ccc1N1CCN(C)CC1,8.154901959985743,590.25206466,8,2,3.473620000000002,True
+713,CHEMBL3233020,7.0,nM,2014.0,O=C(/C=C/CN1CC2(COC2)C1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.154901959985743,459.093201748,7,2,4.054300000000002,True
+714,CHEMBL2103842,7.0,nM,2017.0,C[C@@H]1COC(Nc2ccc3ncnc(Nc4ccc(OCc5nccs5)c(Cl)c4)c3c2)=N1,8.154901959985743,466.0978725280001,9,2,5.2489000000000035,True
+715,CHEMBL3968784,7.0,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(Nc4ccc(Cl)c(Cl)c4F)ncnc3cc2OC)C1,8.154901959985743,476.08182404800004,6,1,4.993600000000004,True
+716,CHEMBL53850,7.0,nM,1996.0,CNc1ccc2ncncc2c1,8.154901959985743,159.079647288,3,1,1.6714999999999998,True
+717,CHEMBL2178350,7.0,nM,2015.0,CN1CCN(c2ccc(Nc3ncc4nc(Nc5ccccc5)n(C5CC5)c4n3)cc2)CC1,8.154901959985743,440.243692896,8,2,4.400200000000003,True
+718,CHEMBL3946396,7.0,nM,2016.0,COc1cccc(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3o2)c1,8.154901959985743,345.14772684800005,5,1,5.071500000000004,True
+719,CHEMBL3233787,7.0,nM,2014.0,O=C(/C=C/CN1CCC(F)(F)CC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.154901959985743,481.0950935680001,6,2,5.453200000000003,True
+720,CHEMBL121796,7.0,nM,1997.0,Clc1cccc(Nc2[nH]cnc3nnc(NCc4ccccc4)c2-3)c1,8.154901959985743,350.10467216,5,3,4.313600000000001,True
+721,CHEMBL311109,7.0,nM,2004.0,NC(=O)C1CCN(Cc2ccc(-c3cc4ncnc(Nc5ccc6[nH]ccc6c5)c4s3)cc2)CC1,8.154901959985743,482.188880452,6,3,5.2805000000000035,True
+722,CHEMBL3622670,7.0,nM,2015.0,CC(C)NC/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,8.154901959985743,499.178645624,7,3,4.826300000000003,True
+723,CHEMBL122245,7.0,nM,1997.0,COc1ccc(CNc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,8.154901959985743,380.115236844,6,3,4.370600000000002,True
+724,CHEMBL496174,7.0,nM,2008.0,Fc1cccc(COc2ccc(Nc3ncnc4cc(C#C[C@H]5CCCN5)sc34)cc2Cl)c1,8.154901959985743,478.10303816000004,6,2,5.909900000000003,True
+725,CHEMBL3416628,7.0,nM,2015.0,O=C(Nc1ccc(CN2CCCC2)cc1)c1sc2ncnc3c2c1[nH]c(=O)n3-c1ccc(F)c(Cl)c1,8.154901959985743,522.1041007800001,7,2,4.964100000000004,True
+726,CHEMBL598610,7.0,nM,2010.0,COc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCCCCC(=O)NO,8.154901959985743,462.14701114799993,7,3,5.009200000000003,True
+727,CHEMBL3758758,7.0,nM,2016.0,COC(=O)c1ccc(OC)c(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3s2)c1,8.154901959985743,419.13036253200005,7,1,5.3266000000000036,True
+728,CHEMBL3959248,7.0,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2cc1NC(=O)/C=C/CN(C)C,8.154901959985743,551.264487916,9,2,4.8529000000000035,True
+729,CHEMBL4218154,7.0,nM,2017.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cn(C)nc3CC)c3ncn(C(C)C)c3n2)C[C@H]1F,8.154901959985743,441.24008473600003,9,2,2.2756,True
+730,CHEMBL3674152,7.0,nM,2015.0,COc1cc(C(=O)NN2CCN(C)CC2)ccc1Nc1ncc2nc(Nc3ccccc3)n(C(C)C)c2n1,8.154901959985743,515.2757212960001,10,3,3.795200000000002,True
+731,CHEMBL3883534,7.0,nM,2017.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,8.154901959985743,372.078931588,5,2,4.299000000000002,True
+732,CHEMBL513418,7.0,nM,2009.0,NS(=O)(=O)c1ccc(Nc2nc3ncnc(Nc4cccc(Cl)c4)c3s2)cc1,8.154901959985743,432.022993336,8,3,3.8743000000000016,True
+733,CHEMBL597551,7.1,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCC(=O)NO,8.148741651280925,406.08441089199994,7,3,3.448800000000001,True
+734,CHEMBL340508,7.1,nM,1997.0,NNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.148741651280925,330.02285645200004,6,3,2.8165000000000004,True
+735,CHEMBL3935007,7.1,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4cccc(Br)c4)ncnc3cc2OC)CC1,8.148741651280925,482.0953526960001,6,1,4.700300000000004,True
+736,CHEMBL4237916,7.1,nM,2018.0,CCCN(c1ccc(OC)cc1)c1ncnc2occ(C)c12,8.148741651280925,297.147726848,5,0,4.087920000000003,True
+737,CHEMBL340399,7.2,nM,1997.0,Cc1cccc(Nc2ncnc3cc(NCCc4c[nH]cn4)ncc23)c1,8.142667503568731,345.17019360800003,6,3,3.4545200000000014,True
+738,CHEMBL4079768,7.2,nM,2017.0,C#Cc1cccc(Nc2ncnc3ccc(OCCCOP(N)(=O)N(CCCl)CCCl)cc23)c1,8.142667503568731,521.115031682,6,2,4.986600000000004,True
+739,CHEMBL4239716,7.2,nM,2018.0,CSc1ccc(N(C)c2ncnc3occ(C)c23)cc1,8.142667503568731,285.0935831,5,0,4.021020000000004,True
+740,CHEMBL3612587,7.3,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4cc(C(=O)OCC)ccc4O)c3cc21,8.136677139879545,480.1644991079999,11,2,3.5069000000000017,True
+741,CHEMBL129825,7.4,nM,1997.0,CN(C)CCCCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.130768280269024,414.11675683600004,6,2,4.284600000000003,True
+742,CHEMBL39811,7.5,nM,1997.0,CN(C)CCN(C)Cc1c[nH]c2cc3ncnc(Nc4cccc(Br)c4)c3cc12,8.1249387366083,452.1324069,5,2,4.6106000000000025,True
+743,CHEMBL300217,7.6,nM,1996.0,Nc1ccc2ncnc(Nc3cccc(Br)c3)c2n1,8.119186407719209,315.01195742000004,5,2,3.113100000000001,True
+744,CHEMBL3910915,7.6,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4ccc(Br)c(C)c4)ncnc3cc2OC)CC1,8.119186407719209,496.1110027600001,6,1,5.008720000000004,True
+745,CHEMBL4089951,7.6,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3ccccc3C)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,8.119186407719209,568.32742252,7,1,4.546340000000004,True
+746,CHEMBL136404,7.7,nM,2001.0,C/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.113509274827518,383.0381721680001,5,2,4.045500000000002,True
+747,CHEMBL4072874,7.8,nM,2017.0,C=CC(=O)Nc1cccc(-c2c[nH]c3nccc(-c4[nH]c(-c5ccccc5)nc4-c4ccc(F)cc4)c23)c1,8.10790539730952,499.18083854400004,3,3,7.2176000000000045,True
+748,CHEMBL2048789,7.8,nM,2012.0,O=C1NCc2ccc(Oc3ccc(Nc4ncnc5ccn(CCO)c45)cc3Cl)cc21,8.10790539730952,435.109817116,7,3,3.856300000000002,True
+749,CHEMBL597752,7.8,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCC(=O)NO,8.10790539730952,420.10006095599994,7,3,3.8389000000000015,True
+750,CHEMBL357570,7.9,nM,1999.0,CCNc1cc2sc3c(Nc4cccc(Br)c4)ncnc3c2cc1F.CCO,8.102372908709556,462.05252258,6,3,5.920100000000004,True
+751,CHEMBL3622677,7.9,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(NC(=O)/C=C/CNC4CC4)cc23)c1,8.102372908709556,413.18517497600004,6,3,3.610000000000002,True
+752,CHEMBL3233776,8.0,nM,2014.0,O=C(/C=C/CNCc1ncccn1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.096910013008056,469.08878506400004,8,3,4.301900000000002,True
+753,CHEMBL123189,8.0,nM,1997.0,COc1cccc(CNc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)c1,8.096910013008056,380.115236844,6,3,4.370600000000002,True
+754,CHEMBL122182,8.0,nM,1997.0,Oc1ccc(Nc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,8.096910013008056,352.083936716,6,4,4.199100000000001,True
+755,CHEMBL120979,8.0,nM,1997.0,COc1cccc(Nc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)c1,8.096910013008056,366.09958678,6,3,4.502100000000002,True
+756,CHEMBL3416594,8.0,nM,2015.0,COc1ccccc1-c1cc2c(NC(CO)c3ccccc3)ncnc2s1,8.096910013008056,377.11979784800013,6,2,4.512400000000002,True
+757,CHEMBL3233778,8.0,nM,2014.0,CCN(CC)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.096910013008056,433.1139371920001,6,2,5.063900000000003,True
+758,CHEMBL1914658,8.0,nM,2011.0,Br.C[C@@H](Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12)c1ccccc1F,8.096910013008056,428.064801516,4,3,5.220600000000004,True
+759,CHEMBL1272061,8.0,nM,2010.0,C=CC(=O)N1CCc2c(sc3ncnc(N[C@H](CO)c4ccccc4)c23)C1,8.096910013008056,380.13069687999996,6,2,2.9075000000000015,True
+760,CHEMBL207687,8.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)[C@@H](C)C(N)=O,8.096910013008056,417.13678081200004,6,2,3.480100000000002,True
+761,CHEMBL2087359,8.0,nM,2012.0,Brc1cccc(Nc2ncnc3cc4c(cc23)OCCCSCCCO4)c1,8.096910013008056,445.04595997999996,6,1,5.420500000000003,True
+762,CHEMBL91867,8.0,nM,2001.0,CC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.096910013008056,380.027273136,4,2,4.0977000000000015,True
+763,CHEMBL206783,8.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCCC[C@@H]1C(N)=O,8.096910013008056,443.15243087600004,6,2,4.014300000000003,True
+764,CHEMBL402553,8.0,nM,2008.0,Clc1cc(Nc2ncnc3[nH]nc(OCCN4CCCC4)c23)ccc1OCc1ccccn1,8.096910013008056,465.168000688,8,2,4.198500000000003,True
+765,CHEMBL257430,8.0,nM,2008.0,Clc1cc(Nc2ncnc3[nH]nc(OCCN4CCNCC4)c23)ccc1OCc1ccccn1,8.096910013008056,480.17889972000006,9,3,3.0079000000000002,True
+766,CHEMBL3759356,8.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3cccc(C(=O)O)c3)cc12)c1ccccc1,8.096910013008056,375.104147784,5,2,5.229600000000003,True
+767,CHEMBL3758951,8.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3ccc(F)c(C=O)c3)cc12)c1ccccc1,8.096910013008056,377.09981135199996,5,1,5.483000000000004,True
+768,CHEMBL255871,8.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,8.096910013008056,391.155686416,8,2,3.3198000000000025,True
+769,CHEMBL60826,8.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCC(O)Cn1ccnc1,8.096910013008056,443.116045368,8,2,3.810900000000002,True
+770,CHEMBL461968,8.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1CN(C)[C@@H](C)C(N)=O,8.096910013008056,417.13678081200004,6,2,3.480100000000002,True
+771,CHEMBL293090,8.0,nM,2001.0,CNCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,8.096910013008056,376.110231716,6,2,3.772700000000002,True
+772,CHEMBL4205392,8.0,nM,2017.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cn(C)nc3OC)c3ncn(CC)c3n2)C[C@H]1F,8.096910013008056,429.20369922800006,10,2,1.1607999999999992,True
+773,CHEMBL3676384,8.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)NCC,8.096910013008056,550.053106532,6,4,4.750800000000003,True
+774,CHEMBL3671494,8.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C1CC1,8.096910013008056,513.081179852,6,3,4.3045000000000035,True
+775,CHEMBL3897363,8.0,nM,2016.0,CN1CCN(c2ccc(Nc3ncnc4cc5oc(=O)n(CCOC(=O)CBr)c5cc34)cc2Cl)CC1,8.096910013008056,574.0730930279999,10,1,3.6246000000000027,True
+776,CHEMBL266995,8.0,nM,1999.0,Oc1cc(O)c2c(O)c(-c3cccc(Cl)c3)cnc2c1,8.096910013008056,287.03492086,4,3,3.6720000000000024,True
+777,CHEMBL473427,8.0,nM,2009.0,Fc1cccc(COc2ccc(Nc3ncnc4cc(-c5cccs5)sc34)cc2Cl)c1,8.096910013008056,467.03291,6,1,7.534900000000002,True
+778,CHEMBL56912,8.0,nM,2001.0,COCCNCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,8.096910013008056,420.136446464,7,2,3.7893000000000017,True
+779,CHEMBL497459,8.0,nM,2008.0,CN(C)/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,8.096910013008056,404.187320892,8,2,3.235000000000002,True
+780,CHEMBL3647423,8.0,nM,2016.0,CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/[C@H]1CCCN1C,8.096910013008056,469.16808094000004,6,2,5.153500000000005,True
+781,CHEMBL461967,8.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1CNC(=O)[C@H]1CCCCN1C,8.096910013008056,457.16808094000004,6,2,4.275000000000003,True
+782,CHEMBL3622649,8.1,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(OC4CCN(C)CC4)c(NC(=O)/C=C/CN(C)C)cc23)c1,8.09151498112135,484.25867426400004,7,2,3.884000000000002,True
+783,CHEMBL4075917,8.1,nM,2017.0,Cc1n[nH]c2ccc(-c3cc(N[C@@H](CO)c4ccccc4)cnc3-c3ccc(F)cc3O)cc12,8.09151498112135,454.180504196,5,4,5.590520000000004,True
+784,CHEMBL162053,8.1,nM,1998.0,CN(C)CCN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,8.09151498112135,400.1011067720001,6,1,3.5287000000000015,True
+785,CHEMBL1243284,8.12,nM,2010.0,CNC/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cc1OCCF,8.090443970758825,471.127359,6,3,4.7049800000000035,True
+786,CHEMBL1204261,8.17,nM,2005.0,CCOc1cc2ncnc(Nc3cccc(F)c3)c2cc1OCC.Cl,8.087777943467584,363.114982748,5,1,4.731700000000004,True
+787,CHEMBL598611,8.2,nM,2010.0,C#Cc1cccc(Nc2ncnc3cc(OCCCCCCC(=O)NO)c(OC)cc23)c1,8.086186147616283,434.19540531199993,7,3,4.198000000000002,True
+788,CHEMBL4089892,8.39,nM,2017.0,OCCCCc1nc(-c2ccc(F)cc2)c(-c2ccnc3[nH]c(-c4ccccc4)cc23)[nH]1,8.0762380391713,426.18558957600004,3,3,5.741100000000005,True
+789,CHEMBL4097369,8.4,nM,2017.0,O=C(Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)c1ccco1,8.075720713938116,408.022187756,5,2,4.981200000000003,True
+790,CHEMBL129824,8.4,nM,1997.0,CN(C)CCCCCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.075720713938116,428.13240690000003,6,2,4.674700000000003,True
+791,CHEMBL597200,8.43,nM,2010.0,O=C(COc1ccc(F)cc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.074172425375258,466.04406607199996,5,2,5.292500000000002,True
+792,CHEMBL460736,8.6,nM,2009.0,CN(N)C/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)ccnc2cn1,8.065501548756432,426.08037132800007,6,3,3.4361000000000015,True
+793,CHEMBL4171543,8.7,nM,2017.0,C=CC(=O)Nc1ccc(-c2ccc(NC(=O)Nc3cccc(Cl)c3)cc2)cn1,8.060480747381384,392.104003464,3,3,5.170500000000002,True
+794,CHEMBL93464,8.7,nM,2001.0,C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.060480747381384,382.0429232,4,2,4.650500000000003,True
+795,CHEMBL3612595,8.7,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4cccc(O)c4)c3cc21,8.060480747381384,408.14336973999997,9,2,3.3302000000000023,True
+796,CHEMBL39355,8.8,nM,1997.0,Brc1cccc(Nc2ncnc3cc4c(cnn4CCCN4CCOCC4)cc23)c1,8.05551732784983,466.11167145600007,7,1,4.207900000000002,True
+797,CHEMBL2048798,8.8,nM,2012.0,OCCn1ccc2ncnc(Nc3ccc(Oc4cccc5sccc45)c(Cl)c3)c21,8.05551732784983,436.076074464,7,2,5.827600000000003,True
+798,CHEMBL136058,8.8,nM,2001.0,O=C(/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1)NCCCN1CCOCC1,8.05551732784983,539.1280497920002,8,3,2.8641000000000005,True
+799,CHEMBL126893,8.8,nM,1997.0,CN(C)CCCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.05551732784983,400.10110677200004,6,2,3.8945000000000016,True
+800,CHEMBL2029431,8.81,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC(C)C)nc32)c1,8.055024091587953,556.2910370120001,8,2,4.587200000000005,True
+801,CHEMBL4075530,8.9,nM,2017.0,Oc1ccc(NC(=S)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)cc1,8.050609993355089,465.02589323200004,5,4,5.650400000000002,True
+802,CHEMBL3622654,8.9,nM,2015.0,COCCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C)C1CC1,8.050609993355089,499.17864562400007,7,2,4.780000000000004,True
+803,CHEMBL4103464,8.9,nM,2017.0,O=C(NCc1ccccc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.050609993355089,447.069472296,4,3,5.457600000000003,True
+804,CHEMBL1203935,8.95,nM,2005.0,CCOc1cc2ncnc(Nc3cc(F)cc(C(F)(F)F)c3)c2cc1OCC.Cl,8.048176964684089,431.10236737599996,5,1,5.750500000000003,True
+805,CHEMBL91009,9.0,nM,2001.0,COCC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.045757490560675,410.03783782,5,2,3.7242000000000015,True
+806,CHEMBL81712,9.0,nM,2004.0,O=C(c1ccccc1)c1cc2ncnc(Nc3ccc4[nH]ccc4c3)c2s1,8.045757490560675,370.08883206800004,5,2,5.1472000000000016,True
+807,CHEMBL3940909,9.0,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2ccc3ncnc(Nc4ccc(F)c(Cl)c4F)c3c2)C1,8.045757490560675,430.100809904,5,1,4.4707000000000034,True
+808,CHEMBL469355,9.0,nM,2009.0,NS(=O)(=O)c1ccc(Nc2nc3ncnc(Nc4ccc(F)c(Cl)c4)c3s2)cc1,8.045757490560675,450.013571524,8,3,4.013400000000002,True
+809,CHEMBL3758990,9.0,nM,2016.0,COC(=O)c1cccc(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3s2)c1OC,8.045757490560675,419.1303625320001,7,1,5.3266000000000036,True
+810,CHEMBL53940,9.0,nM,1998.0,CNc1cc2c(Nc3ccccc3)ncnc2cn1,8.045757490560675,251.11709541599998,5,2,2.8101000000000003,True
+811,CHEMBL1272324,9.0,nM,2010.0,CCN(CC)C/C=C/C(=O)N1CCc2c(sc3ncnc(N[C@H](CO)c4ccccc4)c23)C1,8.045757490560675,465.219846232,7,2,3.619500000000002,True
+812,CHEMBL77452,9.0,nM,2004.0,OCCCNCc1ccc(-c2cc3nccc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,8.045757490560675,428.16708238800004,5,4,5.660200000000003,True
+813,CHEMBL3622644,9.0,nM,2015.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(OCc4ccccn4)cc3)ncnc2cc1O[C@H]1CCOC1,8.045757490560675,540.248503504,9,2,4.571400000000003,True
+814,CHEMBL3633940,9.0,nM,2015.0,NC(=O)Nc1ccc(C(=O)Nc2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)cc1,8.045757490560675,450.100729652,5,4,4.908800000000002,True
+815,CHEMBL3676360,9.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Cl)cc3F)ncnc2cc1OCCNC(=O)CN(C)C,8.045757490560675,520.119272176,7,3,4.000400000000003,True
+816,CHEMBL3759478,9.0,nM,2016.0,OC[C@@H](Nc1ncnc2sc(-c3ccccc3)cc12)c1ccccc1,8.045757490560675,347.109233164,5,2,4.503800000000004,True
+817,CHEMBL301018,9.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OC,8.045757490560675,333.068032556,5,1,4.183100000000002,True
+818,CHEMBL3676355,9.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Br)cc3F)ncnc2cc1OCCNC(=O)CN(C)C,8.045757490560675,564.068756596,7,3,4.109500000000003,True
+819,CHEMBL569880,9.0,nM,2009.0,C=CC(=O)N1CCC[C@H]1C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3F)ncnc2cc1OCCOC,8.045757490560675,531.148488368,7,2,4.445700000000003,True
+820,CHEMBL214478,9.0,nM,2006.0,COc1cc2ncnc(Nc3cc(Cl)ccc3F)c2cc1OC1CCN(CC(N)=O)CC1,8.045757490560675,459.147345496,7,2,3.503000000000002,True
+821,CHEMBL506414,9.0,nM,2009.0,Fc1cccc(COc2ccc(Nc3ncnc4sc(-c5cccs5)cc34)cc2Cl)c1,8.045757490560675,467.03291,6,1,7.534900000000002,True
+822,CHEMBL4280817,9.0,nM,2017.0,O=C1CSC(N2N=C(c3ccncc3)CC2c2ccc(Br)cc2)=N1,8.045757490560675,399.99934413600005,5,0,3.6246000000000027,True
+823,CHEMBL3671533,9.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CCN(C)C,8.045757490560675,544.1233790120001,7,3,3.846200000000003,True
+824,CHEMBL517130,9.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1CN(C)[C@H](C)C(N)=O,8.045757490560675,417.13678081200004,6,2,3.480100000000002,True
+825,CHEMBL3233784,9.0,nM,2014.0,O=C(/C=C/CN1CCCCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.045757490560675,445.1139371920001,6,2,5.208000000000003,True
+826,CHEMBL208118,9.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)[C@H](C)C(N)=O,8.045757490560675,417.13678081200004,6,2,3.480100000000002,True
+827,CHEMBL257860,9.0,nM,2008.0,OC1CCN(CCCOc2n[nH]c3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c23)CC1,8.045757490560675,509.194215436,9,3,3.949500000000003,True
+828,CHEMBL3416447,9.0,nM,2015.0,COc1ccccc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,8.045757490560675,361.1248832280001,5,1,5.540000000000004,True
+829,CHEMBL385471,9.0,nM,2006.0,COc1cc2ncnc(Nc3cc(Cl)ccc3F)c2cc1OCC1CCN(C)CC1,8.045757490560675,430.157181908,6,1,4.895100000000004,True
+830,CHEMBL1645473,9.0,nM,2011.0,NC1CCN(Cc2ccn3ncnc(Nc4cccc(Cl)c4)c23)CC1,8.045757490560675,356.151622352,6,2,3.0494000000000003,True
+831,CHEMBL3671492,9.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCN(C)C,8.045757490560675,473.0862652320001,6,2,4.339900000000004,True
+832,CHEMBL514566,9.0,nM,2008.0,Nc1ncnc(Nc2ccc3c(cnn3Cc3cccc(F)c3)c2)c1/C=N/N1CCN(CCO)CC1,8.045757490560675,489.24008473600003,10,3,2.2832999999999997,True
+833,CHEMBL425601,9.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)C1(C(N)=O)CN(C(C)C)C1,8.045757490560675,486.19463003600004,7,2,3.554400000000003,True
+834,CHEMBL1914660,9.0,nM,2011.0,Br.C[C@@H](Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12)c1cccc(F)c1,8.045757490560675,428.064801516,4,3,5.220600000000004,True
+835,CHEMBL3085374,9.0,nM,2007.0,COc1cc2ncnc(C#C[C@](C)(O)Cc3ccccc3)c2cc1OC,8.045757490560675,348.14739249999997,5,1,2.9922000000000013,True
+836,CHEMBL207130,9.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)C1(C(N)=O)CCN(C)CC1,8.045757490560675,486.19463003600004,7,2,3.5560000000000027,True
+837,CHEMBL3957801,9.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCOCC1,8.045757490560675,487.178645624,7,2,4.615500000000004,True
+838,CHEMBL3814182,9.05,nM,2016.0,S=C(NCCN1CCOCC1)Nc1ccc2ncnc(Nc3ccc(Cl)c(Cl)c3)c2c1,8.043351420794796,476.09528568400003,6,3,4.298800000000003,True
+839,CHEMBL4092951,9.1,nM,2017.0,CNC(=S)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.040958607678906,387.015328548,4,3,4.052100000000002,True
+840,CHEMBL3219125,9.14,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)CN(C)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,8.039053804266171,556.2546515040001,9,2,2.8554000000000004,True
+841,CHEMBL435993,9.2,nM,1997.0,OCCN(CCO)CCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.036212172654443,446.1065860760001,8,4,2.229399999999999,True
+842,CHEMBL3805039,9.2,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(OCC)c4c(c23)OCCO4)c1,8.036212172654443,347.12699140399997,6,1,3.524600000000002,True
+843,CHEMBL3639542,9.2,nM,2013.0,CC(C)N(C)C/C=C/C(=O)N1CCc2sc3ncnc(Nc4ccc(Cl)c(Cl)c4)c3c2C1,8.036212172654443,489.11568678000003,6,1,5.5228000000000055,True
+844,CHEMBL604914,9.25,nM,2010.0,O=C(COc1ccccc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.033858267260968,448.053487884,5,2,5.153400000000003,True
+845,CHEMBL129509,9.3,nM,1997.0,Cc1cccc(Nc2ncnc3cc(NCCCN4CCOCC4)ncc23)c1,8.031517051446064,378.21680945199995,7,2,3.2110200000000013,True
+846,CHEMBL3971939,9.3,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4cccc(C)c4)ncnc3cc2OC)CC1,8.031517051446064,418.200490692,6,1,4.246220000000004,True
+847,CHEMBL1203939,9.31,nM,2005.0,CCOc1cc2ncnc(Nc3ccccc3F)c2cc1OCC.Cl,8.031050319018657,363.114982748,5,1,4.731700000000004,True
+848,CHEMBL357367,9.4,nM,1999.0,CCO.Nc1ccc2sc3c(Nc4ccccc4)ncnc3c2c1,8.0268721464003,338.12013219600004,6,3,4.168900000000002,True
+849,CHEMBL596736,9.4,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCCC(=O)NO,8.0268721464003,434.11571101999994,7,3,4.229000000000002,True
+850,CHEMBL4075103,9.5,nM,2017.0,NS(=O)(=O)c1ccc(NC(=S)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)cc1,8.022276394711152,528.0037778840001,6,4,4.592200000000002,True
+851,CHEMBL53796,9.6,nM,1996.0,CN(C)c1ccc2ncnc(Nc3cccc(Br)c3)c2n1,8.017728766960431,343.04325754800004,5,1,3.5969000000000015,True
+852,CHEMBL3622667,9.6,nM,2015.0,O=C(/C=C/CNC1CC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC(F)F,8.017728766960431,477.11793718800004,6,3,5.014000000000002,True
+853,CHEMBL3805238,9.7,nM,2016.0,CCOc1cc2ncnc(Nc3cccc([N+](=O)[O-])c3)c2c2c1OCCO2,8.013228265733755,368.1120696119999,8,1,3.451500000000002,True
+854,CHEMBL2148051,9.8,nM,2012.0,CC(C(=O)NCCn1ccc2ncnc(Nc3ccc(Oc4cccc(Cl)c4)c(Cl)c3)c21)S(C)(=O)=O,8.008773924307505,547.0847805759998,8,2,4.823300000000003,True
+855,CHEMBL4099377,9.9,nM,2017.0,C=CC(=O)Nc1cc(Nc2ncnc(-c3cn(C)c4ccccc34)c2F)c(OC)cc1N(C)CCN(C)C,8.004364805402451,517.2601514840001,8,2,4.648900000000004,True
+856,CHEMBL325245,10.0,nM,1995.0,COc1cc2ncnc(NCc3ccccc3)c2cc1OC,8.0,295.132076784,5,1,3.259100000000002,True
+857,CHEMBL479800,10.0,nM,2009.0,Fc1cccc(COc2ccc(Nc3ncnc4cc(-c5ccco5)sc34)cc2Cl)c1,8.0,451.05575362,6,1,7.0664000000000025,True
+858,CHEMBL3655348,10.0,nM,2013.0,CN(C)C/C=C/C(=O)N1CCc2c(sc3ncc(C#N)c(Nc4ccc(F)c(Cl)c4)c23)C1,8.0,469.11393719200004,6,1,4.706580000000003,True
+859,CHEMBL3671493,10.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCCNC(C)=O,8.0,515.096829916,6,3,4.694600000000004,True
+860,CHEMBL181617,10.0,nM,2005.0,ClCCNc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,8.0,376.00903622799996,4,2,4.786600000000003,True
+861,CHEMBL470011,10.0,nM,2009.0,Fc1ccc(Nc2ncnc3nc(Nc4ccc(CN5CCCCC5)cc4)sc23)cc1Cl,8.0,468.12992160399995,7,2,6.351900000000004,True
+862,CHEMBL300791,10.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CCN(C)CC1,8.0,445.16808094000004,7,1,3.8007000000000026,True
+863,CHEMBL1645466,10.0,nM,2011.0,C#Cc1cccc(Nc2ncnn3ccc(CN4CCC(N)CC4)c23)c1,8.0,346.190594704,6,2,2.377300000000001,True
+864,CHEMBL251124,10.0,nM,2007.0,CCOc1cc2ncnc(C#Cc3[nH]ccc3-c3ccccc3)c2cc1OCC,8.0,383.163376912,4,1,4.822100000000003,True
+865,CHEMBL205149,10.0,nM,2006.0,COc1cc(OC2CCNCC2)c2c(Nc3ccc(F)c(Cl)c3)ncnc2c1,8.0,402.12588178000004,6,2,4.305300000000003,True
+866,CHEMBL3965948,10.0,nM,2016.0,O=C(CBr)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(N5CCOCC5)c(Cl)c4)c3cc21,8.0,561.0414585520001,10,1,3.7094000000000023,True
+867,CHEMBL4086878,10.0,nM,2017.0,C=CC(=O)Nc1ccc(OC)c(Nc2cc(-c3[nH]c(SC)nc3C)ccn2)c1,8.0,395.14159591200007,6,3,4.378720000000002,True
+868,CHEMBL207445,10.0,nM,2006.0,COCC[C@@H](C(N)=O)N(C)Cc1cc2c(Nc3cccc(Cl)c3F)ncnc2cc1OC,8.0,461.16299556,7,2,3.4967000000000015,True
+869,CHEMBL52076,10.0,nM,1997.0,Nc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,8.0,315.01195742000004,5,2,3.113100000000001,True
+870,CHEMBL4100655,10.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3cccc(F)c3)c3c(N)ncnc32)C1,8.0,366.1604374480001,6,1,2.5641,True
+871,CHEMBL4099713,10.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccccc3)c3c(N)ncnc32)C1,8.0,348.16985926000007,6,1,2.4250000000000007,True
+872,CHEMBL276154,10.0,nM,2006.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OC1CCN(C)CC1,8.0,416.141531844,6,1,4.6475000000000035,True
+873,CHEMBL419137,10.0,nM,1997.0,COc1cc2ncnc(NC3CC3c3ccccc3)c2cc1OC,8.0,321.147726848,5,1,3.615000000000002,True
+874,CHEMBL382823,10.0,nM,2006.0,COCCN(Cc1cc2c(Nc3cccc(Cl)c3F)ncnc2cc1OC)[C@@H](C)C(N)=O,8.0,461.16299556000007,7,2,3.4967000000000006,True
+875,CHEMBL3233774,10.0,nM,2014.0,O=C(/C=C/CNCC1COC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,8.0,447.093201748,7,3,3.9581000000000017,True
+876,CHEMBL135902,10.0,nM,1997.0,COc1cc2ncnc(Sc3cccc(Cl)c3)c2cc1OC,8.0,332.038626336,5,0,4.451600000000003,True
+877,CHEMBL1645476,10.0,nM,2011.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc(F)c(Cl)c4)c23)CC1,8.0,374.14220054,6,2,3.1885000000000003,True
+878,CHEMBL207235,10.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1C[C@H](OC)C[C@@H]1C(N)=O,8.0,459.147345496,7,2,3.249100000000001,True
+879,CHEMBL311129,10.0,nM,1996.0,Cc1c(-c2ccccc2)[nH]c2ncnc(Nc3cccc(Cl)c3)c12,8.0,334.09852416,3,2,5.330320000000001,True
+880,CHEMBL14699,10.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CCOCC1,8.0,432.13644646399996,7,1,3.885500000000003,True
+881,CHEMBL3622638,10.0,nM,2015.0,COCCOc1cc2ncnc(Nc3ccc(OCc4ccccn4)cc3)c2cc1NC(=O)/C=C/CN(C)C,8.0,528.248503504,9,2,4.428900000000003,True
+882,CHEMBL300491,10.0,nM,1996.0,COc1ccc2cncnc2c1,8.0,160.063662876,3,0,1.6383999999999999,True
+883,CHEMBL208292,10.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCC[C@@H]1C(N)=O,8.0,429.13678081200004,6,2,3.624200000000002,True
+884,CHEMBL469354,10.0,nM,2009.0,NS(=O)(=O)c1ccc(Nc2nc3ncnc(Nc4cccc(Br)c4)c3s2)cc1,8.0,475.9724777560001,8,3,3.9834000000000014,True
+885,CHEMBL93181,10.0,nM,1995.0,COc1ccc2c(Nc3cccc(Br)c3)ncnc2c1,8.0,329.016374104,4,1,4.1445000000000025,True
+886,CHEMBL461792,10.08,nM,2009.0,COC[C@H]1Oc2cc3ncnc(Nc4cccc(Cl)c4)c3cc2O[C@@H]1COC,7.996539467890494,401.11423379999997,7,1,3.828000000000002,True
+887,CHEMBL4250273,10.1,nM,2018.0,COc1ccc(N(c2ncnc3occ(C)c23)C(C)C)cc1,7.995678626217357,297.147726848,5,0,4.086320000000003,True
+888,CHEMBL3219130,10.18,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)C(C(C)CC)N(C)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,7.99225222199926,612.31725176,9,2,4.270100000000004,True
+889,CHEMBL4065288,10.2,nM,2017.0,S=C(Nc1cccnc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.991399828238082,450.02622758,5,3,5.339800000000002,True
+890,CHEMBL4066170,10.2,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccc(F)cc34)n2)c(OC)cc1N(C)CC[N+](C)(C)[O-],7.991399828238082,533.2550661040001,8,2,4.661500000000004,True
+891,CHEMBL4287141,10.5,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4cc(F)ccc34)n2)c(OC)cc1N(C)CCN(C)C,7.978810700930063,529.2601514840001,8,2,4.804000000000004,True
+892,CHEMBL4079553,10.71,nM,2017.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1C[C@H](O)[C@@H](O)[C@H](O)[C@H]1CO,7.970210529168143,522.1681405159999,10,5,1.702599999999999,True
+893,CHEMBL1928315,10.8,nM,2012.0,O=C(c1cc2ccccc2s1)c1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.966576244513051,439.0016098720001,6,1,6.6731000000000025,True
+894,CHEMBL4125840,10.8,nM,2018.0,C=CC(=O)N1CC[C@H](Nc2nc(Nc3ccccc3)nc3cnc(Nc4ccc(N5CCN(C)CC5)cn4)cc23)C1,7.966576244513051,550.2917057080001,10,3,3.8576000000000024,True
+895,CHEMBL3805236,10.9,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(OC)c4c(c23)OCCO4)c1,7.962573502059376,333.11134133999997,6,1,3.134500000000002,True
+896,CHEMBL1683973,11.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1C#CCCCN1CCCC1,7.9586073148417755,478.193567416,5,1,6.127620000000006,True
+897,CHEMBL340862,11.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4cncs4)c3)c2cc1OCC,7.9586073148417755,392.13069687999996,7,1,5.294300000000003,True
+898,CHEMBL3908303,11.0,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccccc3)cc12)c1ccccc1,7.9586073148417755,315.137162164,4,1,5.0629000000000035,True
+899,CHEMBL517907,11.0,nM,2004.0,C#Cc1cccc(Nc2ncnc3ccc(OCCCCNCCS(C)(=O)=O)cc23)c1,7.9586073148417755,438.172561692,7,2,3.1479000000000017,True
+900,CHEMBL134312,11.0,nM,2003.0,CN(C)/N=N/c1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.9586073148417755,370.05415658,5,1,4.696200000000003,True
+901,CHEMBL94061,11.0,nM,2003.0,CN(C)C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.9586073148417755,425.08512236,5,2,4.192200000000002,True
+902,CHEMBL2110732,11.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CCCCC1,7.9586073148417755,469.16808094000004,6,2,5.1551000000000045,True
+903,CHEMBL544867,11.0,nM,1999.0,Cc1cccc(Nc2ncnc3c2sc2ccc([N+](=O)[O-])cc23)c1.Cl,7.9586073148417755,372.044774336,6,1,5.226520000000003,True
+904,CHEMBL208594,11.0,nM,2006.0,CNc1ccc2ncnc(Nc3cccc(C)c3)c2c1,7.9586073148417755,264.137496512,4,2,3.7235200000000015,True
+905,CHEMBL3671489,11.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCNC(=O)NCC,7.9586073148417755,530.107728948,6,4,4.487500000000003,True
+906,CHEMBL345294,11.0,nM,1999.0,Brc1cccc(Nc2ncnc3ccsc23)c1,7.9586073148417755,304.96223035599996,4,1,4.197400000000001,True
+907,CHEMBL125920,11.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4cc[nH]n4)c3)c2cc1OCC,7.9586073148417755,375.169524912,6,2,4.560900000000003,True
+908,CHEMBL511990,11.0,nM,2009.0,OC[C@@H]1CCCN1Cc1ccc(Nc2nc3ncnc(Nc4ccc(F)c(Cl)c4)c3s2)cc1,7.9586073148417755,484.12483622400003,8,3,5.322700000000004,True
+909,CHEMBL90013,11.0,nM,1996.0,CN(C)c1ccc2c(Nc3cccc(Br)c3)ncnc2c1,7.9586073148417755,342.04800858000004,4,1,4.201900000000003,True
+910,CHEMBL52784,11.0,nM,1996.0,CN(C)c1ccc2cncnc2c1,7.9586073148417755,173.095297352,3,0,1.6957999999999998,True
+911,CHEMBL4070454,11.2,nM,2017.0,Oc1ccc(-c2nc(-c3ccccc3)c(-c3ccnc4[nH]c(-c5ccccc5)cc34)[nH]2)cc1,7.950781977329817,428.16371126,3,3,6.659600000000005,True
+912,CHEMBL4091921,11.4,nM,2017.0,S=C(NCc1ccccc1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.943095148663526,419.097144256,4,3,5.5134000000000025,True
+913,CHEMBL4100647,11.42,nM,2017.0,CC1(C)OOC2(CCC(C(=O)Nc3ccc4ncnc(Nc5cccc(Cl)c5)c4c3)CC2)OO1,7.9423338960901715,484.15134758,8,2,5.497900000000004,True
+914,CHEMBL4080008,11.6,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn4c5c(cccc35)CCC4)n2)c(OC)cc1N1CC(CN(C)C)C1,7.935542010773082,537.28522336,8,2,4.919000000000003,True
+915,CHEMBL251314,11.7,nM,2007.0,CCOc1cc2ncnc(C#CC(C)(Cc3ccccc3)N3CCC(C(=O)O)CC3)c2cc1OCC,7.931814138253838,487.24710653599993,6,1,4.576700000000003,True
+916,CHEMBL128759,12.0,nM,1997.0,OCCN(CCO)c1cc2ncnc(Nc3cccc(Br)c3)c2cn1,7.920818753952375,403.064386916,7,3,2.3218999999999994,True
+917,CHEMBL4076363,12.0,nM,2017.0,NCCCSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,7.920818753952375,419.15799492400004,5,3,5.4623000000000035,True
+918,CHEMBL3639752,12.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(F)c(Br)cc3F)ncnc2cc1OCCNC(C)=O,7.920818753952375,505.056107976,6,3,4.053500000000002,True
+919,CHEMBL205798,12.0,nM,2006.0,CC(=O)Nc1cccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1,7.920818753952375,486.12588178,5,2,5.949900000000004,True
+920,CHEMBL3671571,12.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN1CCN(C)CC1,7.920818753952375,585.149928108,8,3,3.1419000000000024,True
+921,CHEMBL3671580,12.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCNC(C)=O,7.920818753952375,443.116045368,6,3,3.8053000000000017,True
+922,CHEMBL513208,12.0,nM,2009.0,CN(C)Cc1ccc(Nc2nc3ncnc(Nc4ccc(F)c(Cl)c4)c3s2)cc1,7.920818753952375,428.098621476,7,2,5.427600000000003,True
+923,CHEMBL2178349,12.0,nM,2015.0,CN1CCN(c2ccc(Nc3ncc4nc(Nc5ccccc5)n(C)c4n3)cc2)CC1,7.920818753952375,414.228042832,8,2,3.6023000000000023,True
+924,CHEMBL328691,12.0,nM,1996.0,COC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.920818753952375,372.022187756,5,2,4.314200000000002,True
+925,CHEMBL1914670,12.0,nM,2011.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(C#N)cc3)cc12)c1ccccc1,7.920818753952375,339.148395544,4,2,4.669680000000003,True
+926,CHEMBL399372,12.0,nM,2007.0,CCOc1cc2ncnc(C#Cc3nccn3-c3ccccc3)c2cc1OCC,7.920818753952375,384.15862588,6,0,4.012700000000003,True
+927,CHEMBL256295,12.0,nM,2008.0,Nc1ncnc(Nc2ccc3c(cnn3Cc3cccc(F)c3)c2)c1/C=N/O,7.920818753952375,377.140036352,8,3,3.1476000000000015,True
+928,CHEMBL256297,12.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc(OCc2cccc(F)c2)c(Cl)c1,7.920818753952375,401.10548068400004,7,2,4.154200000000002,True
+929,CHEMBL328704,12.0,nM,2001.0,CCN(CC)CC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.920818753952375,451.100772424,5,2,4.4196000000000035,True
+930,CHEMBL3958006,12.0,nM,2016.0,O=C(/C=C/CN1CCOCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,7.920818753952375,442.13202978000004,7,2,3.3878000000000004,True
+931,CHEMBL511637,12.0,nM,2009.0,Fc1ccc(Nc2ncnc3nc(Nc4ccc(CN5CCOCC5)cc4)sc23)cc1Cl,7.920818753952375,470.10918616,8,2,5.1982000000000035,True
+932,CHEMBL2408045,12.0,nM,2013.0,CNC(=O)CN1CCC(Oc2cc3c(Nc4cccc(Cl)c4F)ncnc3cc2OC)CC1,7.920818753952375,473.16299556000007,7,2,3.763700000000002,True
+933,CHEMBL3919447,12.0,nM,2012.0,C=CC(=O)N1CC[C@H](Oc2cc3c(N[C@H](C)c4ccccc4)ncnc3cc2OC)C1,7.920818753952375,418.200490692,6,1,3.9772000000000034,True
+934,CHEMBL1271561,12.0,nM,2010.0,C[C@@H](Nc1ncnc2sc3c(c12)CCN(C(=O)/C=C/CN(C)C)C3)c1ccccc1,7.920818753952375,421.19363148400004,6,1,3.866900000000003,True
+935,CHEMBL3655343,12.0,nM,2013.0,CN(C)C/C=C/C(=O)N1Cc2sc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2C1,7.920818753952375,431.09828712800004,6,1,4.187400000000003,True
+936,CHEMBL3114699,12.0,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(C(=O)/C=C/CN2CCOCC2)CCO4)c1,7.920818753952375,455.19573965999996,7,1,2.9685000000000015,True
+937,CHEMBL3989970,12.0,nM,2017.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cn(C)nc3OC)c3ncn(C)c3n2)C[C@H]1F,7.920818753952375,415.18804916400006,10,2,0.6778999999999995,True
+938,CHEMBL497697,12.0,nM,2008.0,CN/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,7.920818753952375,390.171670828,8,3,2.8928000000000003,True
+939,CHEMBL420254,12.0,nM,1996.0,CCNc1ccc2c(Nc3cccc(Br)c3)ncnc2c1,7.920818753952375,342.04800858000004,4,2,4.567700000000002,True
+940,CHEMBL1271562,12.0,nM,2010.0,CC[C@@H](Nc1ncnc2sc3c(c12)CCN(C(=O)/C=C/CN(C)C)C3)c1ccccc1,7.920818753952375,435.20928154800004,6,1,4.257000000000003,True
+941,CHEMBL37543,12.0,nM,1997.0,OCC(O)Cn1ncc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,7.920818753952375,413.04873685200005,7,3,2.8388,True
+942,CHEMBL4074601,12.1,nM,2018.0,CC(=O)N1CC[C@H](N2C(=O)N(c3ccccc3Cl)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,7.917214629683549,574.25715004,7,1,4.501220000000004,True
+943,CHEMBL2437467,12.1,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(C(N)=O)cc4)nc32)c1,7.917214629683549,427.1392874040001,8,3,2.1426999999999996,True
+944,CHEMBL2334002,12.1,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCNCCN,7.917214629683549,405.13678081200004,7,3,3.1016000000000004,True
+945,CHEMBL3680378,12.13,nM,2014.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CCCCCC1,7.916139199133427,483.18373100400004,6,2,5.545200000000005,True
+946,CHEMBL243837,12.2,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OCc4cccc(Cl)c4)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,7.9136401693252525,561.1778966759999,9,2,4.286500000000003,True
+947,CHEMBL553351,12.3,nM,1999.0,Cl.O=[N+]([O-])c1ccc2sc3c(Nc4cccc(Br)c4)ncnc3c2c1,7.910094888560603,435.93963634000005,6,1,5.680600000000002,True
+948,CHEMBL2437466,12.5,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(NC(C)=O)cc4)nc32)c1,7.903089986991943,441.15493746800007,8,3,3.0022,True
+949,CHEMBL4061829,12.5,nM,2017.0,OCCc1nc(-c2ccc(F)cc2)c(-c2ccnc3[nH]c(-c4ccccc4)cc23)[nH]1,7.903089986991943,398.15428944800004,3,3,4.960900000000004,True
+950,CHEMBL555921,12.6,nM,1999.0,COc1cccc2c1sc1c(Nc3cccc(Br)c3)ncnc12.Cl,7.899629454882437,420.9651228160001,5,1,5.781000000000003,True
+951,CHEMBL2437488,12.8,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccccc4)nc32)c1,7.892790030352131,384.13347375200004,7,2,3.043800000000001,True
+952,CHEMBL605976,12.8,nM,2010.0,COc1cc2ncnc(N[C@H](C)c3ccccc3)c2cc1OCCCCCCC(=O)NO,7.892790030352131,438.22670543999993,7,3,4.646200000000003,True
+953,CHEMBL399953,13.0,nM,2007.0,COc1cc2ncnc(C#CC(C)(C)Cc3ccccc3)c2cc1OC,7.886056647693162,346.16812794399993,4,0,4.267400000000004,True
+954,CHEMBL257816,13.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2c(ccn2Cc2cccc(F)c2)c1,7.886056647693162,390.16043744800004,7,2,3.924800000000002,True
+955,CHEMBL3676361,13.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(C)=O,7.886056647693162,521.0265574360001,6,3,4.567800000000003,True
+956,CHEMBL3786098,13.0,nM,2017.0,C=CC(=O)N1C[C@H](COc2nc(Nc3cnn(C)c3)nc3[nH]cc(Cl)c23)[C@@H](OC)C1,7.886056647693162,431.147265244,8,2,2.126599999999999,True
+957,CHEMBL470218,13.0,nM,2009.0,CN(C)CCc1ccc(Nc2nc3ncnc(Nc4ccc(F)c(Cl)c4)c3s2)cc1,7.886056647693162,442.11427154,7,2,5.470100000000003,True
+958,CHEMBL571040,13.0,nM,2009.0,C=CC(=O)N1CCC[C@H]1C(=O)Nc1cc2c(Nc3cccc(Cl)c3F)ncnc2cc1OCCOC,7.886056647693162,513.1579101799999,7,2,4.306600000000002,True
+959,CHEMBL3967219,13.0,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccc(F)cc3)cc12)c1ccccc1,7.886056647693162,333.127740352,4,1,5.2020000000000035,True
+960,CHEMBL3671566,13.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)N1CCN(C)CC1,7.886056647693162,571.1342780440001,7,3,3.7353000000000023,True
+961,CHEMBL3759963,13.0,nM,2016.0,COc1cccc(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3s2)c1OC,7.886056647693162,391.1354479120001,6,1,5.548600000000004,True
+962,CHEMBL3759815,13.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3ccc(CO)cc3F)cc12)c1ccccc1,7.886056647693162,379.11546141599996,5,2,5.162800000000004,True
+963,CHEMBL404405,13.0,nM,2008.0,OC1CCN(CCOc2n[nH]c3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c23)CC1,7.886056647693162,495.178565372,9,3,3.559400000000002,True
+964,CHEMBL1683970,13.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1C#CCCN1CCOCC1,7.886056647693162,480.172831972,6,1,4.973920000000005,True
+965,CHEMBL402339,13.0,nM,2008.0,COc1cc(Nc2ncnc3[nH]nc(OCCN4CCC(O)CC4)c23)ccc1OCc1cccc(F)c1,7.886056647693162,508.22343162799996,9,3,3.6587000000000023,True
+966,CHEMBL3676354,13.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Br)cc3F)ncnc2cc1OCCNCC(C)=O,7.886056647693162,535.0422075,7,3,4.610300000000003,True
+967,CHEMBL51707,13.0,nM,1996.0,Fc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,7.886056647693162,317.991636576,4,1,3.6700000000000017,True
+968,CHEMBL66570,13.0,nM,2002.0,CCN1CCN(C(=O)c2cc(C)c(/C=C3\C(=O)Nc4ncnc(Nc5ccc(F)c(Cl)c5)c43)[nH]2)CC1,7.886056647693162,509.1742289400001,6,3,3.919620000000001,True
+969,CHEMBL3806110,13.1,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2c2c1OCCO2,7.8827287043442364,405.089161924,7,1,3.9623000000000026,True
+970,CHEMBL4288080,13.4,nM,2017.0,C=CC(=O)Nc1ccccc1Nc1nc(Nc2ccc(OCCN3CCOCC3)cc2)ncc1Cl,7.872895201635193,494.18331640400004,8,3,4.452700000000004,True
+971,CHEMBL2425735,13.5,nM,2013.0,O=C(CCCN1CCCCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.8696662315049934,467.132072552,5,2,5.340500000000004,True
+972,CHEMBL2334003,13.6,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCNCCN,7.866461091629782,419.15243087600004,7,3,3.4917000000000007,True
+973,CHEMBL4097141,13.6,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn4c5c(cccc35)CCC4)n2)c(OC)cc1N1CC(N(C)C)C1,7.866461091629782,523.2695732960001,8,2,4.671400000000003,True
+974,CHEMBL2437479,13.8,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(OC)cc4)nc32)c1,7.860120913598763,414.144038436,8,2,3.0524000000000013,True
+975,CHEMBL250318,14.0,nM,2007.0,COc1cc2ncnc(C#CCCc3ccccc3)c2cc1OC,7.853871964321763,318.13682781599994,4,0,3.631300000000002,True
+976,CHEMBL3676382,14.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(OC)c(Cl)cc3OC)ncnc2cc1OCCNC(=O)CN(C)C,7.853871964321763,528.188795708,9,3,3.225100000000001,True
+977,CHEMBL272935,14.0,nM,2008.0,CN1CCN(CCCOc2n[nH]c3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c23)CC1,7.853871964321763,508.210199848,9,2,3.7402000000000024,True
+978,CHEMBL125568,14.0,nM,1997.0,OCC(CO)Nc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,7.853871964321763,389.048736852,7,4,2.2959999999999994,True
+979,CHEMBL136491,14.0,nM,2003.0,CN(C)/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.853871964321763,326.10467216,5,1,4.587100000000003,True
+980,CHEMBL402293,14.0,nM,2008.0,CC(C)O/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,7.853871964321763,419.18698654400004,8,2,4.0984000000000025,True
+981,CHEMBL93783,14.0,nM,2001.0,CN(C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)CCO,7.853871964321763,455.095687044,6,3,3.5547000000000017,True
+982,CHEMBL3676362,14.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNCC(C)=O,7.853871964321763,535.0422075,7,3,4.610300000000003,True
+983,CHEMBL497804,14.0,nM,2008.0,O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3s2)C1,7.853871964321763,494.09795278,7,3,4.880700000000003,True
+984,CHEMBL3676339,14.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(F)c3F)ncnc2cc1OCCNC(C)=O,7.853871964321763,445.136174096,6,3,3.4301000000000013,True
+985,CHEMBL3671573,14.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CCN1CCCCC1,7.853871964321763,584.1546791400001,7,3,4.770500000000005,True
+986,CHEMBL342828,14.0,nM,2001.0,O=C(/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1)NCCCn1ccnc1,7.853871964321763,520.0970840120002,8,3,3.428600000000001,True
+987,CHEMBL3943438,14.0,nM,2016.0,COC[C@@H](Nc1ncnc2oc(-c3ccc(OC)cc3)cc12)c1ccccc1,7.853871964321763,375.158291532,6,1,4.698000000000004,True
+988,CHEMBL1914674,14.0,nM,2011.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(C#N)cc3)cc12)c1ccc(F)cc1,7.853871964321763,357.13897373199995,4,2,4.808780000000002,True
+989,CHEMBL3930506,14.0,nM,2016.0,O=C(/C=C/CN1CCCCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,7.853871964321763,440.15276522400006,6,2,4.541500000000003,True
+990,CHEMBL3671517,14.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)COC,7.853871964321763,517.076094472,7,3,3.5409000000000024,True
+991,CHEMBL255237,14.0,nM,2008.0,COCCO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,7.853871964321763,435.18190116400007,9,2,3.336400000000001,True
+992,CHEMBL138940,14.0,nM,2001.0,O=C(/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1)NCCCN1CCOCC1,7.853871964321763,513.1691435600001,8,3,2.894100000000001,True
+993,CHEMBL513362,14.0,nM,2009.0,Cc1cccc(Nc2ncnc3nc(Nc4ccc(S(N)(=O)=O)cc4)sc23)c1,7.853871964321763,412.07761575199993,8,3,3.529320000000001,True
+994,CHEMBL3758768,14.0,nM,2016.0,COc1cc(CO)ccc1-c1cc2c(Nc3ccccc3)ncnc2s1,7.853871964321763,363.10414778400013,6,2,4.602800000000003,True
+995,CHEMBL2425736,14.1,nM,2013.0,Brc1cccc(Nc2ncnc3ccc(NCCCN4CCCCC4)cc23)c1,7.85078088734462,439.13715793200004,5,2,5.4238000000000035,True
+996,CHEMBL249919,14.1,nM,2007.0,OCC#Cc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,7.85078088734462,327.057467872,4,2,3.5097000000000014,True
+997,CHEMBL4129287,14.2,nM,2018.0,C=CC(=O)N[C@H]1CCCN(c2nc(Nc3ccccc3)nc3cnc(Nc4ccc(N5CCN(C)CC5)cn4)cc23)C1,7.847711655616942,564.307355772,10,3,3.929800000000003,True
+998,CHEMBL2437465,14.5,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(N(CC)CC)cc4)nc32)c1,7.8386319977650265,455.2069730400001,8,2,3.8900000000000023,True
+999,CHEMBL597949,14.8,nM,2010.0,C#CCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,7.829738284605042,357.06803255600005,5,1,4.186500000000002,True
+1000,CHEMBL3752008,14.83,nM,2016.0,O=C(Nc1ccncc1)Nc1cc(-c2cncnc2)cc(C(F)(F)F)c1,7.828858848971617,359.099394664,4,2,4.201400000000001,True
+1001,CHEMBL470012,15.0,nM,2009.0,Fc1ccc(Nc2ncnc3nc(Nc4ccc(CCN5CCOCC5)cc4)sc23)cc1Cl,7.823908740944319,484.124836224,8,2,5.240700000000004,True
+1002,CHEMBL250925,15.0,nM,2007.0,CCOc1cc2ncnc(/C=C/c3ccccc3)c2cc1OCC,7.823908740944319,320.15247787999994,4,0,4.5976000000000035,True
+1003,CHEMBL206029,15.0,nM,2006.0,CS(=O)(=O)CCNC(=O)NCc1cccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)n1,7.823908740944319,608.1408802120002,8,3,4.230300000000002,True
+1004,CHEMBL514938,15.0,nM,2009.0,Fc1cccc(COc2ccc(Nc3ncnc4sc(-c5ccco5)cc34)cc2Cl)c1,7.823908740944319,451.05575361999996,6,1,7.0664000000000025,True
+1005,CHEMBL202425,15.0,nM,2006.0,CCN(CC)CC#CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,7.823908740944319,426.13711516000006,6,2,3.8446000000000016,True
+1006,CHEMBL202424,15.0,nM,2006.0,CCCCC#CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1,7.823908740944319,397.1105660640001,5,2,4.693000000000003,True
+1007,CHEMBL2425086,15.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCC2(COC2)C1,7.823908740944319,472.16774659199996,7,1,4.665700000000004,True
+1008,CHEMBL1947124,15.0,nM,2012.0,CC1(C)CC(C(=O)Nc2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)CC(C)(C)N1[O],7.823908740944319,470.175905972,5,2,5.7191000000000045,True
+1009,CHEMBL250523,15.0,nM,2007.0,COc1cc2ncnc(C#CCOc3ccccc3)c2cc1OC,7.823908740944319,320.11609237199997,5,0,3.0775000000000015,True
+1010,CHEMBL2148044,15.0,nM,2012.0,CS(=O)(=O)CC(=O)NCCn1ccc2ncnc(Nc3ccc(Oc4cccc(C(F)(F)F)c4)c(Cl)c3)c21,7.823908740944319,567.095487492,8,2,4.800200000000004,True
+1011,CHEMBL4206501,15.0,nM,2017.0,C=CC(=O)Nc1cc(Nc2ccnc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,7.823908740944319,499.2695732960001,8,2,4.509800000000003,True
+1012,CHEMBL93051,15.0,nM,1996.0,Brc1cccc(Nc2ncnc3cc4c(cc23)OCO4)c1,7.823908740944319,342.99563865999994,5,1,3.864600000000001,True
+1013,CHEMBL4080424,15.0,nM,2017.0,C=CC(=O)Nc1cc(Nc2n[nH]c3cc(-c4cccnc4)ccc23)c(OC)cc1N(C)CCN(C)C,7.823908740944319,485.25392323200003,7,3,4.499400000000003,True
+1014,CHEMBL599398,15.0,nM,2010.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(OCCCCC(=O)NO)cc23)c1,7.823908740944319,406.16410518399994,7,3,3.4178000000000015,True
+1015,CHEMBL65038,15.0,nM,1996.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1[N+](=O)[O-],7.823908740944319,374.00145231199997,6,1,4.052700000000002,True
+1016,CHEMBL3671478,15.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C(N)=O)CC1,7.823908740944319,542.107728948,6,3,4.5690000000000035,True
+1017,CHEMBL3676353,15.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Br)cc3F)ncnc2cc1OCCNC(C)=O,7.823908740944319,521.0265574360001,6,3,4.567800000000003,True
+1018,CHEMBL3678959,15.0,nM,2015.0,CC(C)n1c(NC2CCCCC2)nc2cnc(Nc3ccc(N4CCN(C)CC4)cc3)nc21,7.823908740944319,448.306293152,8,2,4.647200000000004,True
+1019,CHEMBL2437464,15.3,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(N5CCCC5)cc4)nc32)c1,7.815308569182402,453.1913229760001,8,2,3.644000000000002,True
+1020,CHEMBL4280174,15.3,nM,2017.0,C=CC(=O)Nc1ccccc1Nc1nc(Nc2ccc(CN3CCOCC3)cc2)ncc1Cl,7.815308569182402,464.17275172000006,7,3,4.573900000000003,True
+1021,CHEMBL4066951,15.4,nM,2017.0,Nc1cccc(-c2cc3c(-c4[nH]c(-c5ccccc5)nc4-c4ccc(F)cc4)ccnc3[nH]2)c1,7.812479279163536,445.17027386000007,3,3,6.675300000000004,True
+1022,CHEMBL596755,15.4,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1S(=O)(=O)CCCCCCC(=O)NO,7.812479279163536,510.11399676799994,8,3,4.404100000000002,True
+1023,CHEMBL4250191,15.5,nM,2018.0,COc1ccc(N(C)c2ncnc3occ(C)c23)cc1,7.809668301829707,269.11642672,5,0,3.3077200000000015,True
+1024,CHEMBL4089347,15.69,nM,2017.0,C#Cc1cccc(Nc2ncnc3ccc(-c4ccc(CO)o4)cc23)c1,7.804377056413063,341.11642672,5,2,4.107000000000002,True
+1025,CHEMBL2437463,15.7,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(N5CCCCC5)cc4)nc32)c1,7.804100347590767,467.2069730400001,8,2,4.034100000000002,True
+1026,CHEMBL4098507,15.7,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3ccccc3Cl)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,7.804100347590767,588.2728001040001,7,1,4.891320000000005,True
+1027,CHEMBL4102455,15.8,nM,2017.0,S=C(Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)Nc1ccccc1Cl,7.801342913045577,482.99200626000004,4,3,6.598200000000003,True
+1028,CHEMBL4076434,15.8,nM,2017.0,S=C(Nc1ccccc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.801342913045577,449.030978612,4,3,5.9448000000000025,True
+1029,CHEMBL4082884,16.0,nM,2017.0,C=CC(=O)Nc1ccc(OC)c(Nc2cc(-c3[nH]c(SC)nc3C(C)(C)C)ccn2)c1,7.795880017344076,437.18854610400007,6,3,5.367800000000004,True
+1030,CHEMBL257859,16.0,nM,2008.0,Clc1cc(Nc2ncnc3[nH]nc(OCCCN4CCOCC4)c23)ccc1OCc1ccccn1,7.795880017344076,495.178565372,9,2,3.825000000000002,True
+1031,CHEMBL257861,16.0,nM,2008.0,OCCOc1n[nH]c2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12,7.795880017344076,412.10506608400004,8,3,3.0950000000000006,True
+1032,CHEMBL2425087,16.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CC2(COC2)C1,7.795880017344076,444.13644646399996,7,1,3.885500000000003,True
+1033,CHEMBL3676369,16.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)CO,7.795880017344076,537.0214720560001,7,4,3.5402000000000027,True
+1034,CHEMBL126903,16.0,nM,1997.0,CN(CC(=O)O)c1cc2ncnc(Nc3cccc(Br)c3)c2cn1,7.795880017344076,387.033086788,6,2,3.051700000000001,True
+1035,CHEMBL92086,16.0,nM,2001.0,C=C(C)C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.795880017344076,382.0429232,4,2,4.650500000000003,True
+1036,CHEMBL1203940,16.0,nM,2005.0,CCOc1cc2ncnc(Nc3ccc(F)cc3)c2cc1OCC.Cl,7.795880017344076,363.114982748,5,1,4.731700000000004,True
+1037,CHEMBL3970330,16.0,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2cc1NC(=O)/C=C/CN1CCN(C)CC1,7.795880017344076,606.306687076,10,2,4.538700000000003,True
+1038,CHEMBL1092382,16.0,nM,2010.0,CCC(=O)Nc1ccc2nccc(Nc3cccc(Br)c3)c2c1,7.795880017344076,369.04767423199996,3,2,5.089400000000003,True
+1039,CHEMBL3671526,16.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)/C=C/CN(C)C,7.795880017344076,556.1233790120001,7,3,4.012300000000003,True
+1040,CHEMBL498134,16.0,nM,2008.0,CN1CCN(/N=C/c2c(N)ncnc2Nc2ccc3c(cnn3Cc3cccc(F)c3)c2)CC1,7.795880017344076,459.22952005200005,9,2,2.9208000000000007,True
+1041,CHEMBL257815,16.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc(OCc2ccccc2)c(Cl)c1,7.795880017344076,383.114902496,7,2,4.015100000000002,True
+1042,CHEMBL498133,16.0,nM,2008.0,Nc1ncnc(Nc2ccc3c(cnn3Cc3cccc(F)c3)c2)c1/C=N/N1CCOCC1,7.795880017344076,446.19788557600003,9,2,3.005600000000001,True
+1043,CHEMBL3114689,16.0,nM,2014.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(C(=O)/C=C/CN2CCN(C)CC2)CCO4)c1,7.795880017344076,468.227374136,7,1,2.883700000000002,True
+1044,CHEMBL3233767,16.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.795880017344076,348.02478784,5,2,4.351900000000001,True
+1045,CHEMBL3978740,16.2,nM,2012.0,C=CC(=O)N1CCC(Oc2cc3c(Nc4cccc(C(F)(F)F)c4)ncnc3cc2OC)CC1,7.790484985457369,472.17222525600005,6,1,4.956600000000004,True
+1046,CHEMBL2032379,16.4,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(Nc4ccc(N5CCOCC5)cc4OC)nc32)c1,7.785156151952302,515.228102408,8,2,3.8934000000000033,True
+1047,CHEMBL4164396,16.4,nM,2018.0,C=CC(=O)Nc1cc(Nc2nccc(Nc3ccccc3-c3ccn(C)n3)n2)c(OC)cc1OCCN(C)C,7.785156151952302,528.2597368840001,10,3,4.437800000000003,True
+1048,CHEMBL3806170,16.7,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(OC4CCOC4)c4c(c23)OCCO4)c1,7.777283528852418,389.13755608799994,7,1,3.2936000000000014,True
+1049,CHEMBL609321,16.9,nM,2010.0,C=C=CCOc1cc2c(Nc3cccc(Cl)c3)ncnc2cc1O,7.772113295386326,339.077454368,5,2,4.452300000000003,True
+1050,CHEMBL4098587,17.0,nM,2017.0,CC(C)(C)OC(=O)NCC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,7.769551078621726,445.131695432,6,3,4.629100000000003,True
+1051,CHEMBL4228473,17.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N4CCN(C)CC4)cc3OC)n2)c1,7.769551078621726,502.24408682000006,8,4,3.749100000000002,True
+1052,CHEMBL1203937,17.0,nM,2005.0,CCOc1cc2ncnc(NCc3ccc(F)cc3)c2cc1OCC.Cl,7.769551078621726,377.130632812,5,1,4.6002000000000045,True
+1053,CHEMBL1683955,17.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1C,7.769551078621726,357.104418064,4,1,5.208540000000003,True
+1054,CHEMBL3416446,17.0,nM,2015.0,COc1ccccc1-c1cc2c(NCc3ccccc3)ncnc2s1,7.769551078621726,347.1092331640001,5,1,4.979000000000003,True
+1055,CHEMBL4208829,17.0,nM,2017.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cn(C)nc3OC)c3ncn(C(C)(C)C)c3n2)C[C@H]1F,7.769551078621726,457.23499935600006,10,2,1.8958999999999993,True
+1056,CHEMBL4162882,17.0,nM,2018.0,CC/C=C/C(=O)Nc1cc2c(N3CCc4ccccc43)ncnc2cc1OC,7.769551078621726,374.174275944,5,1,4.237300000000003,True
+1057,CHEMBL338049,17.0,nM,1994.0,CN[C@H]1C[C@@H]2O[C@](C)([C@H]1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)N[C@@H]4O,7.769551078621726,482.195405312,7,3,3.844900000000002,True
+1058,CHEMBL4218431,17.0,nM,2018.0,N#Cc1ccc(O)c(-c2nc(NCc3cnccn3)c3ccccc3n2)c1,7.769551078621726,354.122909068,7,2,3.276180000000001,True
+1059,CHEMBL3948084,17.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(cnn4Cc4ccccc4)c3)ncnc2cc1OC,7.769551078621726,452.19607400800004,7,2,5.128500000000003,True
+1060,CHEMBL255135,17.0,nM,2008.0,CNCCOc1n[nH]c2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12,7.769551078621726,425.13670056,8,3,3.3221000000000016,True
+1061,CHEMBL4292351,17.0,nM,2017.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(CN4CCOCC4)cc3OC)ncc2Cl)c1,7.769551078621726,494.183316404,8,3,4.582500000000003,True
+1062,CHEMBL3671561,17.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CNC(=O)O1,7.769551078621726,501.044794344,7,3,3.886700000000003,True
+1063,CHEMBL1914659,17.0,nM,2011.0,Br.Cc1ccccc1C(C)Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12,7.769551078621726,424.089873392,4,3,5.389920000000004,True
+1064,CHEMBL202421,17.0,nM,2006.0,CCCCN(CC#CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1)CCCC,7.769551078621726,482.19971541600006,6,2,5.405000000000004,True
+1065,CHEMBL205045,17.0,nM,2006.0,Fc1cccc(COc2ccc(Nc3ncncc3C#Cc3ccccn3)cc2Cl)c1,7.769551078621726,430.099667032,5,1,5.386500000000003,True
+1066,CHEMBL4088718,17.2,nM,2017.0,S=C(NCc1ccccc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.764471553092451,463.046628676,4,3,5.622500000000002,True
+1067,CHEMBL2031301,17.4,nM,2012.0,CN(C)CCC(=O)N(C)c1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.7594507517174,427.100772424,5,1,4.050400000000002,True
+1068,CHEMBL4060198,17.6,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3ccccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,7.7544873321858505,572.3023506440001,7,1,4.377020000000004,True
+1069,CHEMBL592713,17.7,nM,2010.0,C#CCCCOc1cc2c(Nc3cccc(Cl)c3)ncnc2cc1OC,7.752026733638194,367.108754496,5,1,4.827600000000003,True
+1070,CHEMBL4072620,17.8,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4c(F)cccc34)n2)c(OC)cc1N(C)CC[N+](C)(C)[O-],7.7495799976911055,533.2550661040001,8,2,4.661500000000004,True
+1071,CHEMBL127223,18.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4cscn4)c3)c2cc1OCC,7.744727494896693,392.13069687999996,7,1,5.294300000000004,True
+1072,CHEMBL4226907,18.0,nM,2018.0,O=C(N/N=C/c1ccc(F)cc1Cl)N1CCc2ncnc(Nc3cccc(Br)c3)c2C1,7.744727494896693,502.03197716400007,5,2,4.877000000000003,True
+1073,CHEMBL3786343,18.0,nM,2018.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3)nc3ccsc23)c1,7.744727494896693,486.183795072,8,2,5.103500000000004,True
+1074,CHEMBL69966,18.0,nM,2002.0,C#Cc1cccc(Nc2ncnc3c2/C(=C/c2[nH]c(C(=O)NCCN4CCOCC4)cc2C)C(=O)N3)c1,7.744727494896693,497.217537724,7,4,2.3927199999999997,True
+1075,CHEMBL3676389,18.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(C)N,7.744727494896693,516.0920788840001,7,4,3.2417000000000007,True
+1076,CHEMBL1683965,18.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1/C=C(\F)C(=O)NCCN1CCOCC1,7.744727494896693,543.184873876,7,2,4.658920000000004,True
+1077,CHEMBL3671581,18.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCNC(C)=O,7.744727494896693,443.116045368,6,3,3.8053000000000017,True
+1078,CHEMBL3416626,18.0,nM,2015.0,C#Cc1cccc(Nc2ncnc3sc(-c4ccccc4OC)cc23)c1,7.744727494896693,357.0935831,5,1,5.091800000000004,True
+1079,CHEMBL207009,18.0,nM,2006.0,O=C(NCCCl)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.744727494896693,419.01484988,4,3,4.496200000000002,True
+1080,CHEMBL403435,18.0,nM,2008.0,Cc1cc(Nc2ncnc3[nH]nc(OCCN4CCC(O)CC4)c23)ccc1OCc1ccccn1,7.744727494896693,475.23318778799995,9,3,3.2144200000000014,True
+1081,CHEMBL291496,18.0,nM,1996.0,Clc1ccc2ncnc(Nc3cccc(Br)c3)c2n1,7.744727494896693,333.962086036,4,1,4.184300000000001,True
+1082,CHEMBL3233788,18.0,nM,2014.0,CSC1CCN(C/C=C/C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3s2)CC1,7.744727494896693,491.101658256,7,2,5.5495000000000045,True
+1083,CHEMBL3676344,18.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(F)c3F)ncnc2cc1OCCNC(=O)CN(C)C,7.744727494896693,548.098307136,7,3,3.595200000000002,True
+1084,CHEMBL385479,18.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OCCCN1CCOCC1,7.744727494896693,446.15209652799996,7,1,4.275600000000003,True
+1085,CHEMBL3752370,18.04,nM,2016.0,O=C(Nc1ccncc1)Nc1cc(-c2cncnc2)ccc1OC(F)(F)F,7.743763466794078,375.09430928399996,5,2,4.081200000000001,True
+1086,CHEMBL3680377,18.08,nM,2014.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CCC(F)CC1,7.742801573860655,487.158659128,6,2,5.103100000000005,True
+1087,CHEMBL2333999,18.1,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCBr,7.742321425130815,424.99419468799994,5,1,4.948200000000003,True
+1088,CHEMBL3806143,18.48,nM,2016.0,Brc1cccc(Nc2ncnc3cc(OCCCN4CCOCC4)c4c(c23)OCCO4)c1,7.733298033115912,500.10591737999994,8,1,4.008200000000002,True
+1089,CHEMBL243629,18.7,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OCc4ccccc4)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,7.7281583934635005,527.216869028,9,2,3.6331000000000024,True
+1090,CHEMBL1928293,18.7,nM,2012.0,C#Cc1cccc(Nc2ncnc3sc(C(=O)c4cc5ccccc5[nH]4)cc23)c1,7.7281583934635005,394.088832068,5,2,5.128500000000003,True
+1091,CHEMBL4109796,18.75,nM,2015.0,C=CC(=O)N1CCC[C@@H]1Cn1nc(-c2ccc(Oc3ccccc3)cc2)c2c(N)ncnc21,7.726998727936263,440.19607400800004,7,1,4.044800000000002,True
+1092,CHEMBL4107818,18.85,nM,2016.0,Cc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)nn2C[C@H]1CCCN1C(=O)/C=C/CN(C)C,7.724688645458188,496.25867426400004,7,0,4.702820000000004,True
+1093,CHEMBL3903870,18.85,nM,2015.0,CN(C)C/C=C/C(=O)N1CCCC1Cn1nc(-c2ccc(Oc3ccccc3)cc2)c2c(N)ncnc21,7.724688645458188,497.2539232320001,8,1,3.976600000000002,True
+1094,CHEMBL4279057,18.9,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N1CCC(N(C)C)C1,7.723538195826756,523.2695732960001,8,2,4.807400000000004,True
+1095,CHEMBL3759980,19.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3ccc(C(=O)O)cc3)cc12)c1ccccc1,7.721246399047171,375.104147784,5,2,5.229600000000003,True
+1096,CHEMBL567197,19.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)O[C@H]1CC[C@@](C)(N)CC1,7.721246399047171,538.2804723280001,9,3,4.767900000000003,True
+1097,CHEMBL335648,19.0,nM,1994.0,CO[C@H]1[C@@H]([N+](C)(C)C)C[C@@H]2O[C@@]1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,7.721246399047171,495.23906727209004,5,1,4.840800000000004,True
+1098,CHEMBL3416591,19.0,nM,2015.0,COc1ccccc1-c1cc2c(NC(C)c3ccccc3)ncnc2s1,7.721246399047171,361.1248832280001,5,1,5.540000000000004,True
+1099,CHEMBL119977,19.0,nM,1997.0,Clc1cccc(Nc2[nH]cnc3nnc(-c4ccccc4)c2-3)c1,7.721246399047171,321.078123064,4,2,4.368500000000001,True
+1100,CHEMBL4208811,19.0,nM,2017.0,C=CC(=O)N[C@H]1CCN(c2nc(Nc3ccc(N4CCN(C)CC4)cc3)c3ncn(C(C)C)c3n2)C1,7.721246399047171,489.2964567400001,9,2,2.783500000000001,True
+1101,CHEMBL248114,19.0,nM,2007.0,Cc1cncc(Cn2ncc3cc(Nc4ncnn5ccc(CN6CCC(N)CC6)c45)ccc32)c1,7.721246399047171,467.2545919280001,9,2,3.497420000000001,True
+1102,CHEMBL3921555,19.0,nM,2016.0,CN1CCN(C/C=C/C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3cn2)CC1,7.721246399047171,455.1636642560001,7,2,3.303000000000001,True
+1103,CHEMBL3671523,19.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)/C=C/C,7.721246399047171,513.081179852,6,3,4.470600000000004,True
+1104,CHEMBL1683968,19.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1/C=C(\F)C(=O)NCCS(C)(=O)=O,7.721246399047171,536.1096603359999,7,2,4.371320000000003,True
+1105,CHEMBL1092250,19.0,nM,2010.0,C#Cc1cccc(Nc2ccnc3cc(OC)c(OC)cc23)c1,7.721246399047171,304.121177752,4,1,3.9769000000000023,True
+1106,CHEMBL3671513,19.0,nM,2014.0,C=CCNC(=O)NCCOc1cc2ncnc(Nc3ccc(Br)cc3F)c2cc1NC(=O)C=C,7.721246399047171,528.0920788840001,6,4,4.263500000000002,True
+1107,CHEMBL3676363,19.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)CN(C)C,7.721246399047171,564.068756596,7,3,4.109500000000003,True
+1108,CHEMBL3676345,19.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(F)c3F)ncnc2cc1OCCNC(=O)CCN(CC)CC,7.721246399047171,590.1452573280001,7,3,4.765500000000004,True
+1109,CHEMBL3982289,19.0,nM,2016.0,O=C(CCl)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(N5CCOCC5)c(Cl)c4)c3cc21,7.721246399047171,517.091974132,10,1,3.553300000000003,True
+1110,CHEMBL4089588,19.3,nM,2017.0,O=C(Nc1ccc(Cl)cc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.714442690992227,467.01484988,4,3,6.433300000000003,True
+1111,CHEMBL4097862,19.5,nM,2017.0,S=C(Nc1ccc(Cl)cc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.709965388637482,482.9920062600001,4,3,6.598200000000002,True
+1112,CHEMBL153739,19.8,nM,1999.0,CN(C)c1ccc2sc3c(Nc4cccc(Br)c4)ncnc3c2c1,7.703334809738469,398.0200795800001,5,1,5.416600000000003,True
+1113,CHEMBL344177,20.0,nM,2001.0,O=C(/C=C/Cl)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.698970004336019,402.9835497520001,5,2,4.2219000000000015,True
+1114,CHEMBL3699621,20.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(C(C)=O)[C@H](C(=O)OC)C4)cc3OC)ncc2C(F)(F)F)c1,7.698970004336019,613.22605172,10,3,4.325800000000003,True
+1115,CHEMBL255865,20.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(C#N)c2)c1,7.698970004336019,398.160357196,9,2,3.052380000000002,True
+1116,CHEMBL542755,20.0,nM,1999.0,COc1cccc2sc3c(Nc4cccc(Br)c4)ncnc3c12.Cl,7.698970004336019,420.9651228160001,5,1,5.781000000000003,True
+1117,CHEMBL3930810,20.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3cccc(OC)c3OC)ncc2C(F)(F)F)c1,7.698970004336019,460.135839748,7,2,5.173000000000003,True
+1118,CHEMBL3233775,20.0,nM,2014.0,O=C(/C=C/CNC1CCOCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.698970004336019,461.108851812,7,3,4.490700000000002,True
+1119,CHEMBL3956465,20.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OC)c(OC)c3OC)ncc2C(F)(F)F)c1,7.698970004336019,489.16238884399996,8,3,5.132900000000004,True
+1120,CHEMBL3699582,20.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCOCC4)cc3OC)ncc2C(F)(F)F)c1,7.698970004336019,514.1940233199999,8,3,4.952300000000003,True
+1121,CHEMBL3699593,20.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(S(C)(=O)=O)CC4)cc3OC)ncc2C(F)(F)F)c1,7.698970004336019,591.1875580359999,9,3,4.197300000000003,True
+1122,CHEMBL3954684,20.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OC)cc3OC)ncc2C(F)(F)F)c1,7.698970004336019,459.15182416,7,3,5.1243000000000025,True
+1123,CHEMBL3759459,20.0,nM,2016.0,COC(=O)c1ccc(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3s2)c(OC)c1,7.698970004336019,419.1303625320001,7,1,5.3266000000000036,True
+1124,CHEMBL196438,20.0,nM,2005.0,CCc1c(C(=O)O)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,7.698970004336019,412.16477388000004,7,2,4.131500000000003,True
+1125,CHEMBL4073960,20.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc(F)c4ccccc34)c3c(N)ncnc32)C1,7.698970004336019,416.1760875120001,6,1,3.7173000000000016,True
+1126,CHEMBL3671511,20.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)NC(C)CC,7.698970004336019,544.1233790120001,6,4,4.876000000000004,True
+1127,CHEMBL3699601,20.0,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(S(C)(=O)=O)CC4)cc3OC)ncc2Cl)c1,7.698970004336019,558.145216644,9,2,3.880600000000003,True
+1128,CHEMBL3921302,20.0,nM,2016.0,CN1CCN(c2ccc(Nc3ncnc4cc5oc(=O)n(CCOC(=O)CCl)c5cc34)cc2Cl)CC1,7.698970004336019,530.1236086079999,10,1,3.4685000000000024,True
+1129,CHEMBL207718,20.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)C1(C(N)=O)CN(C)C1,7.698970004336019,458.16332990800004,7,2,2.775800000000001,True
+1130,CHEMBL3953921,20.0,nM,2016.0,C=CC(=O)N1CCCC(n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cc(C)ccc32)C1,7.698970004336019,456.177310636,4,1,4.965320000000004,True
+1131,CHEMBL135853,20.0,nM,1997.0,COc1cc2ncnc(Oc3cccc(Cl)c3)c2cc1OC,7.698970004336019,316.061469956,5,0,4.0927000000000024,True
+1132,CHEMBL4091966,20.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(I)c3c(N)ncnc32)C1,7.698970004336019,398.0352071000001,6,1,1.3626,True
+1133,CHEMBL3944027,20.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(OC)c(OC)c3OC)ncc2Cl)c1,7.698970004336019,456.120047452,8,2,4.816200000000003,True
+1134,CHEMBL31630,20.0,nM,2000.0,C=CC(=O)N(C)c1nc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCOCC1,7.698970004336019,500.173894592,8,1,3.810800000000002,True
+1135,CHEMBL3699597,20.0,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C(=O)NC)CC4)cc3OC)ncc2C(F)(F)F)c1,7.698970004336019,571.215487036,8,3,4.6258000000000035,True
+1136,CHEMBL1645470,20.0,nM,2011.0,Cc1cccc(Nc2ncnn3ccc(CN4CCC(N)CC4)c23)c1,7.698970004336019,336.206244768,6,2,2.7044200000000007,True
+1137,CHEMBL1203936,20.0,nM,2005.0,COc1cc2ncnc(Nc3cc(F)cc(C(F)(F)F)c3)c2cc1OC.Cl,7.698970004336019,403.07106724799996,5,1,4.970300000000003,True
+1138,CHEMBL3676358,20.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Cl)cc3F)ncnc2cc1OCCNC(=O)COC,7.698970004336019,507.08763769999996,7,3,4.085200000000003,True
+1139,CHEMBL3699590,20.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(C(=O)CO)CC4)cc3OC)ncc2Cl)c1,7.698970004336019,537.189130056,9,4,3.3912000000000013,True
+1140,CHEMBL208286,20.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)[C@@H](CO)C(N)=O,7.698970004336019,433.131695432,7,3,2.4525,True
+1141,CHEMBL460731,20.0,nM,2004.0,CS(=O)(=O)CCNCCCCOc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,7.698970004336019,466.12416752800004,7,2,3.959100000000002,True
+1142,CHEMBL382638,20.0,nM,2006.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1CN1CCC[C@H]1C(N)=O,7.698970004336019,429.13678081200004,6,2,3.624200000000002,True
+1143,CHEMBL93386,20.0,nM,2001.0,O=C(C#CCN1CCOCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.698970004336019,465.08003698000005,6,2,3.410000000000001,True
+1144,CHEMBL3759733,20.0,nM,2016.0,COc1cc(C=O)ccc1-c1cc2c(Nc3ccccc3)ncnc2s1,7.698970004336019,361.08849772000013,6,1,4.923000000000003,True
+1145,CHEMBL4064361,20.0,nM,2017.0,COc1cc(Br)c(/C=C2\CN(C)CC(=C\c3nc(C)c(C)nc3C)/C2=N\O)cc1OC,7.698970004336019,486.1266528240001,7,1,4.424160000000003,True
+1146,CHEMBL3612594,20.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4ccc(O)cc4)c3cc21,7.698970004336019,408.14336973999997,9,2,3.3302000000000023,True
+1147,CHEMBL4078023,20.0,nM,2017.0,Cc1nc(C)c(/C=C2\CN(C)C/C(=C\c3nc(C)c(C)nc3C)C2=NO)nc1C,7.698970004336019,392.232459516,7,1,3.359720000000002,True
+1148,CHEMBL379601,20.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)CC(N)=O,7.698970004336019,403.12113074800004,6,2,3.0916000000000015,True
+1149,CHEMBL3699614,20.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(C(C)=O)CC4)cc3OC)ncc2Br)c1,7.698970004336019,565.143699856,8,3,4.527900000000003,True
+1150,CHEMBL1272222,20.0,nM,2010.0,C=CC(=O)N1CCc2c(sc3ncnc(N[C@H](C)c4ccccc4)c23)C1,7.698970004336019,364.13578226,5,1,3.935100000000002,True
+1151,CHEMBL378370,20.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)C1CCNC1=O,7.698970004336019,429.13678081200004,6,2,3.4948000000000023,True
+1152,CHEMBL3699589,20.0,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C(=O)CO)CC4)cc3OC)ncc2C(F)(F)F)c1,7.698970004336019,572.1995026239999,9,3,3.8053000000000026,True
+1153,CHEMBL3805782,20.5,nM,2016.0,Fc1ccc(Nc2ncnc3cc(OC4CCOC4)c4c(c23)OCCO4)cc1Cl,7.688246138944246,417.08916192399994,7,1,4.104800000000003,True
+1154,CHEMBL3647967,20.6,nM,2015.0,C=CC(=O)N[C@H]1CC[C@@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)CC1,7.6861327796308485,454.21172407200004,7,2,4.653700000000003,True
+1155,CHEMBL4078182,20.6,nM,2017.0,S=C(Nc1cccc(Cl)c1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.6861327796308485,482.9920062600001,4,3,6.598200000000002,True
+1156,CHEMBL4173696,20.7,nM,2018.0,C/C=C/c1ccc(Nc2ncnc3cc(OCCCN4CCOCC4)c(OCCCN4CCOCC4)cc23)cc1,7.684029654543082,547.315854792,9,1,4.608700000000004,True
+1157,CHEMBL287289,21.0,nM,1997.0,CN(C)CCCn1ccc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,7.67778070526608,423.10585780400004,5,1,5.042300000000004,True
+1158,CHEMBL387187,21.0,nM,2007.0,O=C(Nc1cccc(Nc2cc(Nc3cccc(C(F)(F)F)c3)ncn2)c1)C1CC1,7.67778070526608,413.14634485600004,5,3,5.331100000000003,True
+1159,CHEMBL565714,21.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OCCN1CCNCC1,7.67778070526608,539.2757212960001,10,3,3.0131000000000006,True
+1160,CHEMBL4103440,21.0,nM,2017.0,COc1ccc(-c2nnc(-n3c(-c4ccccc4)nc4cc(Cl)ccc4c3=O)s2)cc1,7.67778070526608,446.06042440000004,7,0,5.233200000000003,True
+1161,CHEMBL1272325,21.0,nM,2010.0,O=C(/C=C/CN1CCOCC1)N1CCc2c(sc3ncnc(N[C@H](CO)c4ccccc4)c23)C1,7.67778070526608,479.19911078800004,8,2,2.6099000000000006,True
+1162,CHEMBL3671538,21.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CCCN(C)C,7.67778070526608,558.139029076,7,3,4.2363000000000035,True
+1163,CHEMBL3758761,21.0,nM,2016.0,COc1c(C=O)cccc1-c1cc2c(N[C@H](C)c3ccccc3)ncnc2s1,7.67778070526608,389.11979784800013,6,1,5.352500000000004,True
+1164,CHEMBL3676370,21.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)CCOC,7.67778070526608,565.0527721840001,7,3,4.584400000000003,True
+1165,CHEMBL206003,21.0,nM,2006.0,NCc1cccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)n1,7.67778070526608,459.126216128,6,2,4.845200000000003,True
+1166,CHEMBL203295,21.0,nM,2006.0,COc1cc(OC2CCN(C)CC2)c2c(Nc3ccc(F)c(Cl)c3)ncnc2c1,7.67778070526608,416.14153184400004,6,1,4.6475000000000035,True
+1167,CHEMBL3974571,21.0,nM,2016.0,C=C(C)C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCOCC1,7.67778070526608,499.17864562400007,7,2,4.781600000000004,True
+1168,CHEMBL2048794,21.0,nM,2012.0,O=C1NCc2cccc(Oc3ccc(Nc4ncnc5ccn(CCO)c45)cc3Cl)c21,7.67778070526608,435.109817116,7,3,3.856300000000002,True
+1169,CHEMBL3977326,21.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(ccn4Cc4ccccc4)c3)ncnc2cc1OC,7.67778070526608,451.20082504000004,6,2,5.733500000000005,True
+1170,CHEMBL3805461,21.0,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(OCCOC)c4c(c23)OCCO4)c1,7.67778070526608,377.13755608799994,7,1,3.1511000000000013,True
+1171,CHEMBL434827,21.0,nM,2001.0,CCN(CC)CCCNC(=O)/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.67778070526608,525.1487852360001,7,3,3.8737000000000013,True
+1172,CHEMBL3759257,21.0,nM,2016.0,OCc1ccc(-c2cc3c(Nc4ccccc4)ncnc3s2)cc1,7.67778070526608,333.0935831,5,2,4.5942000000000025,True
+1173,CHEMBL4276744,21.5,nM,2017.0,C=CC(=O)Nc1ccccc1Nc1nc(Nc2ccc(OCCCN3CCOCC3)cc2)ncc1Cl,7.667561540084393,508.19896646800004,8,3,4.842800000000004,True
+1174,CHEMBL4278226,21.7,nM,2017.0,C=CC(=O)Nc1ccccc1Nc1nc(Nc2ccc(NC(=O)CN3CCOCC3)cc2)ncc1Cl,7.66354026615147,507.178565372,8,4,4.012400000000002,True
+1175,CHEMBL3805681,21.95,nM,2016.0,Clc1cccc(Nc2ncnc3cc(OCCCN4CCOCC4)c4c(c23)OCCO4)c1,7.6585654754218595,456.15643295999996,8,1,3.8991000000000025,True
+1176,CHEMBL428777,22.0,nM,2008.0,C[C@@H](Oc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12)C(=O)N(C)C,7.657577319177793,477.156767308,7,1,4.856300000000003,True
+1177,CHEMBL3934461,22.0,nM,2016.0,COc1ccc(-c2cc3c(NC(CC(N)=O)c4ccccc4)ncnc3o2)cc1,7.657577319177793,388.1535405,6,2,3.9270000000000014,True
+1178,CHEMBL3972981,22.0,nM,2016.0,CC[C@@H](Nc1ncnc2oc(-c3ccc(OC)cc3)cc12)c1ccccc1,7.657577319177793,359.163376912,5,1,5.461600000000004,True
+1179,CHEMBL3676340,22.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3c(F)cc(Br)cc3F)ncnc2cc1OCCNC(C)=O,7.657577319177793,505.056107976,6,3,4.053500000000002,True
+1180,CHEMBL4089601,22.0,nM,2017.0,C=CC(=O)NCCCSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,7.657577319177793,473.16855960800007,5,3,5.805800000000005,True
+1181,CHEMBL302552,22.0,nM,2002.0,O=C1Nc2ncnc(Nc3ccc(F)c(Cl)c3)c2/C1=C/c1ccc(C(=O)NCCN2CCOCC2)[nH]1,7.657577319177793,511.153493496,7,4,2.895500000000001,True
+1182,CHEMBL3918330,22.0,nM,2016.0,C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCOCC1,7.657577319177793,499.17864562400007,7,2,4.781600000000004,True
+1183,CHEMBL175101,22.0,nM,1996.0,CN(C)CCn1cnc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,7.657577319177793,410.0854567080001,6,1,4.047200000000002,True
+1184,CHEMBL210444,22.0,nM,2006.0,O=C(NCCCl)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.657577319177793,375.06536546,4,3,4.387100000000002,True
+1185,CHEMBL3219128,22.12,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)C(C)N(C)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,7.6552148773673405,570.2703015680001,9,2,3.243900000000002,True
+1186,CHEMBL4278815,22.4,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cnn4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,7.649751981665838,498.24917220000003,9,2,3.8209000000000017,True
+1187,CHEMBL3806292,22.5,nM,2016.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2c2c1OCCO2,7.647817481888637,361.06294717599997,6,1,3.945700000000002,True
+1188,CHEMBL3980550,22.53,nM,2016.0,CN(C)C/C=C/C(=O)NC1CCC(n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)CC1,7.647238808276169,511.2695732960001,8,2,4.585500000000003,True
+1189,CHEMBL3893004,22.53,nM,2015.0,CN(C)C/C=C/C(=O)N[C@H]1CC[C@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)CC1,7.647238808276169,511.2695732960001,8,2,4.585500000000003,True
+1190,CHEMBL4282523,22.8,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)ccc1N(C)CCN(C)C,7.642065152999545,481.2590086120001,7,2,4.656300000000003,True
+1191,CHEMBL3416595,23.0,nM,2015.0,COC[C@@H](Nc1ncnc2sc(-c3ccccc3OC)cc12)c1ccccc1,7.638272163982407,391.135447912,6,1,5.1665000000000045,True
+1192,CHEMBL4282506,23.0,nM,2018.0,N#CCC(=O)N/N=C1\C(=O)Nc2ccc(S(=O)(=O)N3CCOCC3)cc21,7.638272163982407,377.07938958,7,2,-0.6064199999999997,True
+1193,CHEMBL583403,23.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)=NC=NC2N=C1NC(=O)OC[C@@H]1COCCN1,7.638272163982407,544.2346650080001,10,3,3.235400000000001,True
+1194,CHEMBL3921129,23.0,nM,2016.0,CCOc1cc2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2cc1NC(=O)/C=C/CN1CCN(C)CC1,7.638272163982407,576.296122392,9,2,4.912200000000004,True
+1195,CHEMBL329672,23.0,nM,1999.0,Clc1cccc(Nc2ncnc3ccccc23)c1,7.638272163982407,255.056325,3,1,4.0268000000000015,True
+1196,CHEMBL255656,23.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(Cl)c2)c1,7.638272163982407,407.126135876,8,2,3.834100000000002,True
+1197,CHEMBL3921710,23.0,nM,2016.0,CCCCN1C(=O)CS/C1=N/Nc1nncc2ccccc12,7.638272163982407,315.11538116400004,6,1,2.688200000000001,True
+1198,CHEMBL4207984,23.0,nM,2018.0,N#Cc1ccc(O)c(-c2nc(NCc3cccnc3)c3ccccc3n2)c1,7.638272163982407,353.12766010000007,6,2,3.8811800000000014,True
+1199,CHEMBL3416439,23.0,nM,2015.0,C#Cc1cccc(Nc2ncnc3sc(Br)cc23)c1,7.638272163982407,328.96223035599996,4,1,4.178700000000002,True
+1200,CHEMBL255438,23.0,nM,2008.0,Nc1ncnc(Nc2ccc3c(cnn3Cc3cccc(F)c3)c2)c1/C=N/OCc1ccccc1,7.638272163982407,467.186986544,8,2,4.890200000000004,True
+1201,CHEMBL380078,23.0,nM,2006.0,CNC(=O)NCc1cccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)n1,7.638272163982407,516.147679844,6,3,4.815500000000003,True
+1202,CHEMBL3676378,23.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC(CC)NC(=O)CN(C)C,7.638272163982407,558.139029076,7,3,4.234700000000004,True
+1203,CHEMBL565467,23.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)O[C@H]1CC[C@H](N)CC1,7.638272163982407,524.2648222640001,9,3,4.377800000000002,True
+1204,CHEMBL3671501,23.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(F)(F)F,7.638272163982407,541.037264352,6,3,4.456800000000002,True
+1205,CHEMBL3676376,23.1,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OC[C@H](C)NC(=O)CN(C)C,7.636388020107856,578.08440666,7,3,4.498000000000004,True
+1206,CHEMBL4098591,23.4,nM,2018.0,CCC(=O)N1CC[C@@H](N2C(=O)N(c3ccccc3Cl)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,7.6307841425898575,588.2728001040001,7,1,4.891320000000005,True
+1207,CHEMBL4097627,23.6,nM,2017.0,Oc1cccc(-c2nc(-c3ccc(F)cc3)c(-c3ccnc4[nH]c(-c5ccccc5)cc34)[nH]2)c1,7.627087997029892,446.1542894480001,3,3,6.798700000000005,True
+1208,CHEMBL3805509,23.7,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(OC(C)C)c4c(c23)OCCO4)c1,7.6252516539898965,361.14264146799997,6,1,3.9131000000000027,True
+1209,CHEMBL597950,23.8,nM,2010.0,C=C=CCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O,7.623423042943487,357.06803255600005,5,2,4.591400000000003,True
+1210,CHEMBL4066845,23.99,nM,2017.0,CS(=O)(=O)CCNCc1ccc(-c2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)o1,7.619969752032169,474.0928674,7,2,4.560100000000004,True
+1211,CHEMBL3953210,24.0,nM,2016.0,COc1ccc(-c2cc3c(N[C@H](C)c4cccc(F)c4)ncnc3o2)cc1,7.619788758288393,363.138305036,5,1,5.210600000000004,True
+1212,CHEMBL2425083,24.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CC2(C1)CS(=O)(=O)C2,7.619788758288393,506.11908214799996,8,1,3.6738000000000026,True
+1213,CHEMBL3671520,24.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CS(C)(=O)=O,7.619788758288393,565.0430800920001,8,3,2.9391000000000007,True
+1214,CHEMBL493428,24.0,nM,2004.0,CS(=O)(=O)CCNCCCCOc1ccc2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c2c1,7.619788758288393,562.2162380720001,9,2,4.703700000000003,True
+1215,CHEMBL3925584,24.0,nM,2016.0,COc1ccc(-c2cc3c(N[C@H](C)c4ccccc4F)ncnc3o2)cc1,7.619788758288393,363.138305036,5,1,5.210600000000004,True
+1216,CHEMBL3233777,24.0,nM,2014.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.619788758288393,405.0826370640001,6,2,4.283700000000002,True
+1217,CHEMBL133023,24.0,nM,2003.0,Cc1cccc(Nc2ncnc3ccc(/N=N/N(C)C)cc23)c1,7.619788758288393,306.159294576,5,1,4.2421200000000026,True
+1218,CHEMBL4284413,24.0,nM,2017.0,O=C(Nc1nccs1)C(c1ccccc1)N1Cc2ccccc2C1=O,7.619788758288393,349.08849771999996,4,1,3.478900000000002,True
+1219,CHEMBL3092313,24.0,nM,2013.0,CN(C)CCCNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,7.619788758288393,502.189544656,7,3,4.406800000000002,True
+1220,CHEMBL402149,24.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1cccc(Br)c1,7.619788758288393,321.022522104,6,2,2.5452000000000012,True
+1221,CHEMBL2179119,24.1,nM,2017.0,Oc1ccc(-c2nc(-c3ccc(F)cc3)c(-c3ccnc4[nH]c(-c5ccccc5)cc34)[nH]2)cc1,7.617982957425133,446.15428944800004,3,3,6.798700000000005,True
+1222,CHEMBL3806213,24.1,nM,2016.0,Fc1ccc(Nc2ncnc3cc(OCC4CCCO4)c4c(c23)OCCO4)cc1Cl,7.617982957425133,431.10481198799994,7,1,4.494900000000004,True
+1223,CHEMBL4227281,24.2,nM,2018.0,Cc1ccc(/C=N/NC(=O)N2CCc3ncnc(Nc4cccc(C(F)(F)F)c4)c3C2)cc1,7.616184634019568,454.172893952,5,2,4.649220000000003,True
+1224,CHEMBL4088971,24.4,nM,2017.0,OCCCc1nc(-c2ccc(F)cc2)c(-c2ccnc3[nH]ccc23)[nH]1,7.612610173661269,336.13863938400004,3,3,3.684000000000001,True
+1225,CHEMBL4204983,24.7,nM,2018.0,CN(C)CCN(C)c1nc(Nc2ccc(F)cc2)nc2cnc(Nc3ccc(N4CCC(N(C)C)CC4)cn3)cc12,7.607303046740334,558.3343194680001,10,2,4.574300000000004,True
+1226,CHEMBL4284684,24.8,nM,2017.0,C=CC(=O)Nc1ccccc1Nc1nc(Nc2ccc(OCC(=O)N3CCOCC3)cc2)ncc1Cl,7.605548319173782,508.16258096,8,3,3.979300000000003,True
+1227,CHEMBL3753532,24.81,nM,2016.0,COc1cc(NC(=O)Nc2ccccn2)cc(-c2c[nH]cn2)c1OC,7.60537323572779,339.133139404,5,3,3.1329000000000002,True
+1228,CHEMBL3219129,24.83,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)C(C(C)C)N(C)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,7.605023280445436,598.3016016960001,9,2,3.8800000000000026,True
+1229,CHEMBL241919,24.9,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OCc4cccc(C)c4)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,7.603800652904264,541.232519092,9,2,3.9415200000000024,True
+1230,CHEMBL66409,25.0,nM,1996.0,O=[N+]([O-])c1cc2c(Nc3cccc(Br)c3)ncnc2cc1Cl,7.602059991327962,377.9519152760001,5,1,4.697500000000002,True
+1231,CHEMBL4086078,25.0,nM,2017.0,C=CC(=O)N1CCC(Sc2nc(-c3ccc(F)cc3)c(-c3ccnc(Nc4ccccc4)c3)[nH]2)C1,7.602059991327962,485.16855960800007,5,2,5.900400000000005,True
+1232,CHEMBL470010,25.0,nM,2009.0,COCCN(CCOC)S(=O)(=O)c1ccc(Nc2nc3ncnc(Nc4ccc(F)c(Cl)c4)c3s2)cc1,7.602059991327962,566.097301148,10,2,4.649500000000002,True
+1233,CHEMBL74722,25.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3cccc(Br)c3)c2c1C,7.602059991327962,316.03235851600004,3,2,4.080840000000002,True
+1234,CHEMBL3409484,25.0,nM,2015.0,CS(=O)(=O)CCNCc1ccc(-c2cc3c(Nc4ccc(OCc5ccccc5)cc4)ncnc3cn2)o1,7.602059991327962,529.1783753440001,9,2,4.741600000000004,True
+1235,CHEMBL3671505,25.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCOC,7.602059991327962,460.054630756,6,2,4.424700000000003,True
+1236,CHEMBL383246,25.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)C1(C(N)=O)CCN(C(C)C)CC1,7.602059991327962,514.225930164,7,2,4.334600000000004,True
+1237,CHEMBL3671506,25.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNS(C)(=O)=O,7.602059991327962,523.032515408,7,3,3.3275000000000015,True
+1238,CHEMBL541586,25.0,nM,1997.0,COc1cc2ncnc(Nc3cccc(F)c3)c2cc1OC.Cl,7.602059991327962,335.08368262,5,1,3.9515000000000025,True
+1239,CHEMBL3671574,25.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C1CCCN1C(C)=O,7.602059991327962,584.1182936320001,7,3,3.905400000000003,True
+1240,CHEMBL424093,25.0,nM,2003.0,Brc1cccc(Nc2ncnc3ccc(N/N=N/Cc4ccccc4)cc23)c1,7.602059991327962,432.0698066440001,5,2,6.115200000000003,True
+1241,CHEMBL4111809,25.0,nM,2015.0,CC(=O)Nc1cccc(Nc2nc3cnc(Nc4ccc(C(=O)N[N+]5=CCN(C)CC5)cc4F)nc3n2C(C)C)c1,7.602059991327962,559.26882490409,9,4,3.6654000000000018,True
+1242,CHEMBL2425084,25.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CC(O)C1,7.602059991327962,432.13644646399996,7,2,3.619900000000002,True
+1243,CHEMBL3819120,25.53,nM,2016.0,O=C1N[C@H](C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3cc2OCCN2CCCCC2)CO1,7.5929491851957485,528.168809212,8,3,4.077500000000002,True
+1244,CHEMBL3805218,25.86,nM,2016.0,Fc1ccc(Nc2ncnc3cc(OCCCN4CCOCC4)c4c(c23)OCCO4)cc1Cl,7.587371479455625,474.14701114799993,8,1,4.038200000000003,True
+1245,CHEMBL597948,25.9,nM,2010.0,C#CCOc1cc2c(Nc3cccc(Cl)c3)ncnc2cc1OC,7.586700235918747,339.07745436799996,5,1,4.047400000000002,True
+1246,CHEMBL250924,26.0,nM,2007.0,COc1cc2ncnc(C#Cc3ccccc3-c3ccccc3)c2cc1OC,7.585026652029183,366.13682781599994,4,0,4.7138000000000035,True
+1247,CHEMBL3671554,26.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCNCC(C)=O,7.585026652029183,515.096829916,7,3,4.347000000000003,True
+1248,CHEMBL1914662,26.0,nM,2011.0,Br.Oc1ccc(-c2cc3c(NCc4ccc(F)cc4)ncnc3[nH]2)cc1,7.585026652029183,414.0491514520001,4,3,4.659600000000003,True
+1249,CHEMBL3671507,26.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)NCCC,7.585026652029183,530.107728948,6,4,4.487500000000003,True
+1250,CHEMBL333231,26.0,nM,1997.0,Clc1cccc(CNc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)c1,7.585026652029183,384.065699808,5,3,5.015400000000001,True
+1251,CHEMBL3907533,26.0,nM,2016.0,CCOc1cc2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2cc1NC(=O)/C=C/CN1CCOCC1,7.585026652029183,563.264487916,9,2,4.997000000000003,True
+1252,CHEMBL3671477,26.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C(=O)CS(C)(=O)=O)CC1,7.585026652029183,619.090030284,8,2,4.061500000000004,True
+1253,CHEMBL3416629,26.0,nM,2015.0,C#Cc1cccc(-n2c(=O)[nH]c3c(C(=O)Nc4ccc(CN5CCCC5)cc4)sc4ncnc2c43)c1,7.585026652029183,494.152494944,7,2,4.152900000000003,True
+1254,CHEMBL179451,26.0,nM,2005.0,ClCCNc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.585026652029183,332.059551808,4,2,4.677500000000002,True
+1255,CHEMBL3671481,26.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(F)c3F)ncnc2cc1OCC1CCN(C(C)=O)CC1,7.585026652029183,499.183124288,6,2,4.552500000000003,True
+1256,CHEMBL4288300,26.0,nM,2018.0,COc1cccc(Nc2cc(Nc3cc(OC)ccc3OC)ncn2)c1,7.585026652029183,352.1535405,7,2,3.989600000000002,True
+1257,CHEMBL2425090,26.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CC(O)C1,7.585026652029183,418.12079639999996,7,2,3.229800000000002,True
+1258,CHEMBL3760023,26.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3cccc(S(C)(=O)=O)c3)cc12)c1ccccc1,7.585026652029183,409.091868848,6,1,4.934900000000003,True
+1259,CHEMBL331906,26.0,nM,1997.0,Oc1cccc(-c2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)c1,7.585026652029183,337.073037684,5,3,4.122500000000002,True
+1260,CHEMBL3612563,26.0,nM,2015.0,COCCn1c(=O)oc2cc3ncnc(Nc4ccc(F)c(F)c4)c3cc21,7.585026652029183,372.10339674799997,7,1,3.2059000000000015,True
+1261,CHEMBL233325,26.0,nM,2007.0,O[C@H]1CNCCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)C1,7.585026652029183,486.22918570400003,9,3,2.7760999999999996,True
+1262,CHEMBL3676383,26.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN(CC)CC,7.585026652029183,558.139029076,7,3,4.2363000000000035,True
+1263,CHEMBL456758,26.0,nM,2008.0,COC[C@@H]1CCCN1/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,7.585026652029183,474.22918570400003,9,2,3.784200000000002,True
+1264,CHEMBL3754057,26.56,nM,2016.0,O=C(Nc1ccccn1)Nc1cc(-c2cncnc2)ccc1OC(F)(F)F,7.575771929304019,375.09430928399996,5,2,4.081200000000001,True
+1265,CHEMBL4083904,26.6,nM,2018.0,Cc1cc(Nc2ncc3c(n2)N([C@H]2CCN(C(=O)CN(C)C)C2)C(=O)N(c2ccccc2Cl)C3)ccc1N1CCN(C)CC1,7.575118363368933,617.2993492,8,1,4.042920000000003,True
+1266,CHEMBL4062528,26.9,nM,2017.0,S=C(Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)N1CCOCC1,7.570247719997593,443.041543296,5,2,4.164900000000003,True
+1267,CHEMBL3622653,26.9,nM,2015.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C)C1CC1,7.570247719997593,455.15243087600004,6,2,4.763400000000003,True
+1268,CHEMBL3416596,27.0,nM,2015.0,COc1ccccc1-c1cc2c(N[C@H](C)c3ccc(F)cc3)ncnc2s1,7.568636235841013,379.1154614160001,5,1,5.679100000000004,True
+1269,CHEMBL500591,27.0,nM,2008.0,N#Cc1c(N)ncnc1Nc1ccc(OCc2ccccc2)c(Cl)c1,7.568636235841013,351.088687748,6,2,3.906480000000002,True
+1270,CHEMBL4283061,27.0,nM,2018.0,CCOC(=O)CCCC(=O)Nc1cc(Nc2cccc(Cl)c2)ncn1,7.568636235841013,362.11456814800005,6,2,3.5455000000000014,True
+1271,CHEMBL3040910,27.0,nM,2014.0,c1ccc(-c2cccc(Nc3ncnc4cc5c(cc34)OCCCO5)c2)cc1,7.568636235841013,369.147726848,5,1,5.201700000000003,True
+1272,CHEMBL91484,27.0,nM,1997.0,COc1cc2ncnc(NC3CC3c3ccccc3)c2cc1OCCCN(C)C,7.568636235841013,392.221226136,6,1,3.936900000000003,True
+1273,CHEMBL4282460,27.0,nM,2018.0,O=C(O)CCCC(=O)Nc1cc(Nc2cccc(Cl)c2)ncn1,7.568636235841013,334.08326802000005,5,3,3067,True
+1274,CHEMBL31369,27.0,nM,2000.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(OCCN(C)C)c(Br)c3)c2c1,7.568636235841013,455.09568704400004,6,2,4.200800000000003,True
+1275,CHEMBL470003,27.0,nM,2009.0,Clc1cccc(Nc2ncnc3nc(Nc4ccccc4)sc23)c1,7.568636235841013,353.05019406400004,6,2,5.226900000000001,True
+1276,CHEMBL2419762,27.0,nM,2013.0,Cl.c1ccc(-c2cccc(Nc3ncnc4cc5c(cc34)OCCCO5)c2)cc1,7.568636235841013,405.1244045599999,5,1,5.623500000000003,True
+1277,CHEMBL290096,27.0,nM,1997.0,Brc1cccc(Nc2ncnc3ccccc23)c1,7.568636235841013,299.00580942,3,1,4.135900000000001,True
+1278,CHEMBL3973601,27.0,nM,2016.0,COc1ccc(-c2cc3c(N[C@H](C)c4ccc(F)cc4)ncnc3o2)cc1,7.568636235841013,363.138305036,5,1,5.210600000000004,True
+1279,CHEMBL1914672,27.0,nM,2011.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(F)cc3)cc12)c1ccc(F)cc1,7.568636235841013,350.134302952,3,2,5.076200000000003,True
+1280,CHEMBL301359,27.0,nM,1996.0,c1ccc2ncncc2c1,7.568636235841013,130.053098192,2,0,1.6297999999999997,True
+1281,CHEMBL3092322,27.0,nM,2013.0,O=C(NCCO)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,7.568636235841013,461.12661005200005,7,4,3.447400000000001,True
+1282,CHEMBL139044,27.0,nM,2001.0,C=C/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.568636235841013,395.0381721680001,5,2,4.2116000000000025,True
+1283,CHEMBL163168,27.0,nM,1998.0,O=C(O)CCNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.568636235841013,387.0330867880001,6,3,3.4175000000000013,True
+1284,CHEMBL3805325,27.3,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(OCC4CCCO4)c4c(c23)OCCO4)c1,7.5638373529592435,403.15320615199994,7,1,3.6837000000000026,True
+1285,CHEMBL4070640,27.4,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3ccccc3OC)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,7.562249437179612,584.3223371400001,8,1,4.246520000000004,True
+1286,CHEMBL1683963,28.0,nM,2011.0,C/C(=C\c1c(C)ncnc1Nc1ccc(OCc2cccc(F)c2)c(Cl)c1)C(=O)NCCN1CCOCC1,7.552841968657781,539.209945752,7,2,4.751820000000004,True
+1287,CHEMBL3233783,28.0,nM,2014.0,O=C(/C=C/CN1CCC(F)(F)C1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.552841968657781,467.0794435040001,6,2,5.063100000000003,True
+1288,CHEMBL3676368,28.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)CCCN(C)C,7.552841968657781,592.100056724,7,3,4.889700000000004,True
+1289,CHEMBL411897,28.0,nM,2008.0,COC1CCN(CCOc2n[nH]c3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c23)CC1,7.552841968657781,509.194215436,9,2,4.2135000000000025,True
+1290,CHEMBL93734,28.0,nM,1996.0,CC(=O)Nc1cc2ncnc(Nc3cccc(Br)c3)c2cc1[N+](=O)[O-],7.552841968657781,401.01235134399997,6,2,4.002500000000002,True
+1291,CHEMBL3952877,28.0,nM,2016.0,COC[C@@H](Nc1ncnc2oc(-c3ccccc3)cc12)c1ccccc1,7.552841968657781,345.147726848,5,1,4.689400000000004,True
+1292,CHEMBL3827349,28.2,nM,2016.0,c1cnc2ccc(Nc3ncnc4ccc(-c5cnn(C6CCNCC6)c5)cc34)cc2c1,7.549750891680639,421.20149373600003,7,2,4.709600000000004,True
+1293,CHEMBL3921017,28.22,nM,2015.0,C=CC(=O)N(C)CCn1nc(-c2ccc(Oc3ccccc3)cc2)c2c(N)ncnc21,7.549442990581671,414.18042394400004,7,1,3.512200000000001,True
+1294,CHEMBL4071170,28.3,nM,2017.0,S=C(NCc1ccc(Cl)cc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.548213564475709,497.0076563240001,4,3,6.275900000000003,True
+1295,CHEMBL592215,28.5,nM,2010.0,C=C=CCCCOc1cc2c(Nc3cccc(Cl)c3)ncnc2cc1O,7.54515513999149,367.108754496,5,2,5.232500000000004,True
+1296,CHEMBL4064937,28.7,nM,2018.0,Cc1cc(Nc2ncc3c(n2)N([C@H]2CCN(C(=O)C4CC4)C2)C(=O)N(c2ccccc2Cl)C3)ccc1N1CCN(C)CC1,7.542118103266008,600.272800104,7,1,4.891320000000005,True
+1297,CHEMBL304929,28.8,nM,2007.0,C#Cc1cccc(Nc2ncnc3cc(OC)c(OC)cc23)c1,7.5406075122407685,305.11642672,5,1,3.371900000000002,True
+1298,CHEMBL598798,28.8,nM,2010.0,C#Cc1cc(Nc2ncnc3cc(OC)c(OCCCCCCC(=O)NO)cc23)ccc1F,7.5406075122407685,452.18598349999996,7,3,4.337100000000003,True
+1299,CHEMBL3929584,29.0,nM,2016.0,C=Cc1ccc(-c2cc3c(N[C@H](C)c4ccccc4)ncnc3o2)cc1,7.5376020021010435,341.152812228,4,1,5.705900000000004,True
+1300,CHEMBL332765,29.0,nM,1997.0,CN(C)c1ccc(Nc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,7.5376020021010435,379.131221256,6,3,4.5595000000000026,True
+1301,CHEMBL52418,29.0,nM,1996.0,CC(=O)Nc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,7.5376020021010435,357.022522104,5,2,3.489300000000001,True
+1302,CHEMBL3233793,29.0,nM,2014.0,O=C(/C=C/CN1CCS(=O)(=O)CC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.5376020021010435,495.0601873680001,8,2,3.4525000000000015,True
+1303,CHEMBL2178368,29.0,nM,2015.0,CN1CCN(c2ccc(Nc3ncc4nc(Nc5ccccc5)[nH]c4n3)cc2)CC1,7.5376020021010435,400.21239276800003,7,3,3.5919000000000016,True
+1304,CHEMBL3671555,29.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC(C)NC(=O)NCCC,7.5376020021010435,544.1233790120001,6,4,4.876000000000004,True
+1305,CHEMBL4165267,29.0,nM,2018.0,C/C=C/C(=O)Nc1cc2c(N3CCc4ccccc43)ncnc2cc1O[C@@H]1CCOC1,7.5376020021010435,416.18484062799996,6,1,4.006300000000003,True
+1306,CHEMBL153170,29.0,nM,1999.0,Brc1cccc(Nc2ncnc3ccc4[nH]cnc4c23)c1,7.5376020021010435,339.01195742000004,4,2,4.012200000000001,True
+1307,CHEMBL1914673,29.0,nM,2011.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(Br)cc3)cc12)c1ccc(F)cc1,7.5376020021010435,410.054236832,3,2,5.699600000000003,True
+1308,CHEMBL4206312,29.0,nM,2017.0,C=CC(=O)N1CC[C@@H](Nc2nc(Nc3ccc(N4CCN(C)CC4)cc3)c3ncn(C(C)C)c3n2)C1,7.5376020021010435,489.2964567400001,9,2,3.101400000000001,True
+1309,CHEMBL3671552,29.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OC[C@@H](C)NC(C)=O,7.5376020021010435,501.08117985200005,6,3,4.302900000000004,True
+1310,CHEMBL94191,29.0,nM,1996.0,COc1cc2ncnc(Nc3ccccc3)c2cc1OC,7.5376020021010435,281.11642672,5,1,3.390600000000002,True
+1311,CHEMBL242541,29.0,nM,2012.0,Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,7.5376020021010435,288.05780222,4,2,3.748100000000001,True
+1312,CHEMBL75177,29.0,nM,1996.0,Clc1cccc(Nc2ncnc3[nH]c4c(c23)CCCC4)c1,7.5376020021010435,298.09852416,3,2,4.233700000000002,True
+1313,CHEMBL3671512,29.0,nM,2014.0,C=CNC(=O)NCCOc1cc2ncnc(Nc3ccc(Br)cc3F)c2cc1NC(=O)C=C,7.5376020021010435,514.07642882,6,4,4.221000000000003,True
+1314,CHEMBL305194,29.0,nM,2002.0,Cc1cc(C(=O)O)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc(F)c(Cl)c3)c21,7.5376020021010435,413.069095176,5,4,3.8401200000000006,True
+1315,CHEMBL3805283,29.1,nM,2016.0,CC(C)Oc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2c2c1OCCO2,7.536107011014093,389.09424730399996,6,1,4.724300000000003,True
+1316,CHEMBL4280993,29.9,nM,2018.0,C=C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(C)cc1N(C)CCN(C)C,7.52432881167557,495.2746586760001,7,2,4.964720000000004,True
+1317,CHEMBL111197,30.0,nM,1998.0,COc1cccc(Nc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)c1,7.522878745280337,426.06503111200004,6,1,5.054500000000003,True
+1318,CHEMBL472545,30.0,nM,2008.0,Nc1ncnc(Nc2ccc(OCc3ccccc3)c(Cl)c2)c1-c1nnc(CCN2CCOCC2)o1,7.522878745280337,507.178565372,10,2,3.959500000000003,True
+1319,CHEMBL3234753,30.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1cnc2[nH]ncc2c1,7.522878745280337,551.2256577960001,6,3,4.537120000000003,True
+1320,CHEMBL220037,30.0,nM,2007.0,N#Cc1cnc2ccc(NCc3c[nH]cn3)cc2c1Nc1ccc(F)c(Cl)c1,7.522878745280337,392.095250348,5,3,4.977780000000002,True
+1321,CHEMBL540068,30.0,nM,1997.0,COc1cc2ncnc(Nc3cccc(Cl)c3)c2cc1OC.Cl,7.522878745280337,351.05413208,5,1,4.465800000000002,True
+1322,CHEMBL524457,30.0,nM,2008.0,Nc1ncnc(Nc2ccc3c(cnn3Cc3cccc(F)c3)c2)c1/C=N/N1CCCCC1,7.522878745280337,444.21862102000006,8,2,4.1593000000000035,True
+1323,CHEMBL510845,30.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c3s2)C1)N1CCOCC1,7.522878745280337,597.195836976,10,2,4.522800000000004,True
+1324,CHEMBL583218,30.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OCC1CCNCC1,7.522878745280337,524.2648222640001,9,3,4.107500000000002,True
+1325,CHEMBL205966,30.0,nM,2006.0,Nc1ccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)cc1,7.522878745280337,444.115317096,5,2,5.573700000000003,True
+1326,CHEMBL312482,30.0,nM,2004.0,c1cc(Nc2ccc3[nH]ccc3c2)c2sc(-c3ccc(CN4CCOCC4)cc3)cc2n1,7.522878745280337,440.167082388,5,2,6.020400000000005,True
+1327,CHEMBL1688539,30.0,nM,2015.0,Fc1ccc(Nc2ncnc3ccccc23)cc1Cl,7.522878745280337,273.046903188,3,1,4.1659000000000015,True
+1328,CHEMBL2180204,30.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3cccc(C(F)(F)F)c3)c3c(N)ncnc32)C1,7.522878745280337,416.1572438880001,6,1,3.4438000000000013,True
+1329,CHEMBL207584,30.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCC[C@H]1C(N)=O,7.522878745280337,429.13678081200004,6,2,3.624200000000002,True
+1330,CHEMBL211003,30.0,nM,2006.0,CNC(=O)[C@@H](C)N(C)Cc1cc2c(Nc3cccc(Cl)c3F)ncnc2cc1OC,7.522878745280337,431.15243087600004,6,2,3.740800000000002,True
+1331,CHEMBL3678953,30.0,nM,2015.0,COc1ccc(Nc2nc3cnc(Nc4ccc(N5CCN(C)CC5)cc4)nc3n2C(C)C)cc1,7.522878745280337,472.26990764400006,9,2,4.654800000000004,True
+1332,CHEMBL379905,30.0,nM,2006.0,COC[C@@H](C(N)=O)N(C)Cc1cc2c(Nc3cccc(Cl)c3F)ncnc2cc1OC,7.522878745280337,447.14734549600007,7,2,3.106600000000002,True
+1333,CHEMBL204420,30.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCN(C)CC1C(N)=O,7.522878745280337,458.16332990800004,7,2,2.7758000000000003,True
+1334,CHEMBL3297892,30.0,nM,2014.0,C#Cc1cccc(Nc2nc(C)nc3oc(C)cc23)c1,7.522878745280337,263.105862036,4,1,3.564540000000002,True
+1335,CHEMBL394057,30.0,nM,2007.0,O=C(O)COCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,7.522878745280337,446.15026668800004,8,2,3.611200000000002,True
+1336,CHEMBL4062509,30.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc(F)cc3)c3c(N)ncnc32)C1,7.522878745280337,366.1604374480001,6,1,2.5641,True
+1337,CHEMBL122411,30.0,nM,1997.0,COc1ccc(Nc2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,7.522878745280337,366.09958678,6,3,4.502100000000002,True
+1338,CHEMBL52472,30.0,nM,1996.0,COc1ccc2ncncc2c1,7.522878745280337,160.063662876,3,0,1.6383999999999999,True
+1339,CHEMBL1089203,30.0,nM,2010.0,C#Cc1cccc(Nc2ccnc3cc(OCCOC)c(OCCOC)cc23)c1,7.522878745280337,392.17360724799994,6,1,4.010100000000003,True
+1340,CHEMBL3297894,30.2,nM,2014.0,Cc1nc(Nc2ccc(F)c(Cl)c2)c2cc(C)oc2n1,7.519993057042849,291.0574678720001,4,1,4.375740000000002,True
+1341,CHEMBL1946926,31.0,nM,2012.0,CC1(C)CC(C(=O)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)CC(C)(C)N1[O],7.508638306165728,496.13481220400007,5,2,5.689100000000005,True
+1342,CHEMBL515664,31.0,nM,2008.0,COC[C@H]1CCCN1/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,7.508638306165728,474.22918570400003,9,2,3.784200000000002,True
+1343,CHEMBL3678958,31.0,nM,2015.0,CC(C)n1c(Nc2cccnc2)nc2cnc(Nc3ccc(N4CCN(C)CC4)cc3)nc21,7.508638306165728,443.2545919280001,9,2,4.041200000000003,True
+1344,CHEMBL423224,31.0,nM,1999.0,Brc1cccc(Nc2[nH]cnc3nc4ccccc4c2-3)c1,7.508638306165728,338.01670845200005,3,2,4.568800000000001,True
+1345,CHEMBL132348,31.0,nM,1994.0,CO[C@H]1[C@@H](N(C)CC(=O)O)C[C@@H]2O[C@@]1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,7.508638306165728,524.205969996,7,2,4.1510000000000025,True
+1346,CHEMBL3633941,31.0,nM,2015.0,CCNC(=O)Nc1ccc(C(=O)Nc2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)cc1,7.508638306165728,478.13202978000004,5,4,5.559600000000003,True
+1347,CHEMBL3828092,31.9,nM,2016.0,Fc1ccc(Nc2ncnc3ccc(-c4cnn(C5CCNCC5)c4)cc23)cc1Cl,7.496209316942818,422.14220054,6,2,4.9539000000000035,True
+1348,CHEMBL3671572,32.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN1CCOCC1,7.494850021680094,572.1182936320001,8,3,3.226700000000002,True
+1349,CHEMBL3671577,32.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN1CC=CC1,7.494850021680094,554.107728948,7,3,3.766300000000003,True
+1350,CHEMBL193159,32.0,nM,2005.0,O=C(CCl)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.494850021680094,389.988300784,4,2,4.313200000000002,True
+1351,CHEMBL3671518,32.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CO,7.494850021680094,503.060444408,7,4,2.8868000000000014,True
+1352,CHEMBL381604,32.0,nM,2006.0,Nc1nccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)n1,7.494850021680094,446.105815032,7,2,4.363700000000002,True
+1353,CHEMBL4167162,32.0,nM,2018.0,O=C(CN1CCCC1)Nc1ccc2ncnc(Nc3ccc(Cl)cc3)c2c1,7.494850021680094,381.13563794,5,2,4.061100000000003,True
+1354,CHEMBL1645462,32.0,nM,2009.0,Cc1c(NC(=O)OC[C@@H]2COCCN2)cn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,7.494850021680094,530.219014944,10,3,3.8553200000000016,True
+1355,CHEMBL1645472,32.0,nM,2011.0,NC1CCN(Cc2ccn3ncnc(Nc4cccc(F)c4)c23)CC1,7.494850021680094,340.181172892,6,2,2.5351,True
+1356,CHEMBL4169489,32.0,nM,2018.0,CN1CCN(CC(=O)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)CC1,7.494850021680094,454.111671456,6,2,3.3218000000000014,True
+1357,CHEMBL182254,32.0,nM,2005.0,Fc1cccc(COc2ccc(Nc3ncnc4nn5ccccc5c34)cc2Cl)c1,7.494850021680094,419.094916,6,1,5.3926000000000025,True
+1358,CHEMBL3671524,32.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CCC,7.494850021680094,515.096829916,6,3,4.694600000000004,True
+1359,CHEMBL430031,32.0,nM,2008.0,CC(C)CO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,7.494850021680094,433.20263660800003,8,2,4.346000000000003,True
+1360,CHEMBL248321,32.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc(OCc5cnccn5)c(Cl)c4)c23)CC1,7.494850021680094,464.18398510000003,9,2,3.418400000000001,True
+1361,CHEMBL4094438,32.1,nM,2017.0,C=CC(=O)Nc1cccc(-c2cc3c(-c4[nH]c(-c5ccccc5)nc4-c4ccc(F)cc4)ccnc3[nH]2)c1,7.493494967595128,499.18083854400004,3,3,7.217600000000005,True
+1362,CHEMBL1204360,32.2,nM,2005.0,COc1cc2ncnc(Nc3ccccc3F)c2cc1OC.Cl,7.492144128304169,335.08368262,5,1,3.9515000000000025,True
+1363,CHEMBL3622625,32.2,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc(O[C@H]4CCOC4)c(NC(=O)C=C)cc23)c1,7.492144128304169,400.15354049999996,6,2,3.6469000000000023,True
+1364,CHEMBL589826,32.6,nM,2010.0,C=CCCCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,7.4867823999320615,401.13063281200004,5,1,5.909600000000004,True
+1365,CHEMBL590558,32.7,nM,2010.0,C#CCCCCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,7.485452247339714,413.13063281200004,5,1,5.746900000000004,True
+1366,CHEMBL204467,33.0,nM,2006.0,OCc1ccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)o1,7.481486060122112,449.09424730399996,6,2,5.076800000000002,True
+1367,CHEMBL3085375,33.0,nM,2007.0,COc1cc2ncnc(C#C[C@@](C)(Cc3ccccc3)N3CCC(C(=O)O)CC3)c2cc1OC,7.481486060122112,459.21580640799993,6,1,3.7965000000000027,True
+1368,CHEMBL2048788,33.0,nM,2012.0,CC(C)(C)NC(=O)c1cccc(Oc2ccc(Nc3ncnc4ccn(CCO)c34)cc2Cl)c1,7.481486060122112,479.172417372,7,3,5.141200000000004,True
+1369,CHEMBL256529,33.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc(OCc2cc(F)cc(F)c2)c(Cl)c1,7.481486060122112,419.096058872,7,2,4.293300000000003,True
+1370,CHEMBL4162530,33.0,nM,2018.0,CCC/C=C/C(=O)Nc1cc2c(N3CCCc4ccccc43)ncnc2cc1OC,7.481486060122112,402.205576072,5,1,5.017500000000004,True
+1371,CHEMBL1914671,33.0,nM,2011.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccccc3)cc12)c1ccc(F)cc1,7.481486060122112,332.143724764,3,2,4.937100000000003,True
+1372,CHEMBL567873,33.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OC[C@@H]1COCCN1,7.481486060122112,526.2440868200001,10,3,3.0963000000000003,True
+1373,CHEMBL500072,33.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc5c(cnn5Cc5cc(F)ccc5F)c4)c3s2)C1)N1CCOCC1,7.481486060122112,615.186415164,10,2,4.661900000000004,True
+1374,CHEMBL1241487,33.0,nM,2008.0,Nc1ccc(-c2nn(C3CCCC3)c3ncnc(N)c23)cc1O,7.481486060122112,310.15420919599995,7,3,2.4784,True
+1375,CHEMBL392273,33.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(CN6CCCNCC6)c45)ccc32)c1,7.481486060122112,470.23427108400006,8,2,3.8053000000000017,True
+1376,CHEMBL4069672,33.6,nM,2017.0,COc1ccc2c(c1)CCCN2c1nc(C)nc2c(Cc3ccccc3)c[nH]c12.Cl,7.4736607226101555,420.17168910000004,4,1,5.371820000000005,True
+1377,CHEMBL3219134,33.95,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)C(Cc3ccc(OC)cc3)N(C)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,7.469160221383478,676.3121663800001,10,2,4.475300000000003,True
+1378,CHEMBL1683961,34.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1C#CCCCN1CCOCC1,7.468521082957745,494.188482036,6,1,5.364020000000005,True
+1379,CHEMBL3233791,34.0,nM,2014.0,CC(C)N1CCN(C/C=C/C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3s2)CC1,7.468521082957745,488.15613635200003,7,2,4.748100000000003,True
+1380,CHEMBL2425085,34.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CC(OC)C1,7.468521082957745,446.15209652799996,7,1,4.274000000000004,True
+1381,CHEMBL54805,34.0,nM,1996.0,Brc1cccc(Nc2ncnc3cccnc23)c1,7.468521082957745,300.00105838800005,4,1,3.530900000000001,True
+1382,CHEMBL1923007,34.0,nM,2012.0,OCCn1ccc2ncnc(Nc3ccc(Oc4cccc(C(F)(F)F)c4)c(Cl)c3)c21,7.468521082957745,448.091388092,6,2,5.631700000000003,True
+1383,CHEMBL4088135,34.16,nM,2017.0,C#Cc1cccc(Nc2ncnc3ccc(-c4ccc(CNCCS(C)(=O)=O)o4)cc23)c1,7.466482137983032,446.14126156399993,7,2,3.7489000000000026,True
+1384,CHEMBL4208673,34.8,nM,2018.0,CN1CCN(c2nc(Nc3ccc(F)cc3)nc3cnc(Nc4ccc(N5CCC(N(C)C)CC5)cn4)cc23)CC1,7.458420756053419,556.3186694040002,10,2,4.328300000000003,True
+1385,CHEMBL157084,35.0,nM,2003.0,CS(=O)(=O)CCNc1nc(-c2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)cs1,7.455931955649724,477.04962268400004,8,2,4.7459000000000024,True
+1386,CHEMBL135142,35.0,nM,2001.0,O=C(/C=C/C(F)(F)F)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.455931955649724,436.01465776400005,4,2,5.192900000000002,True
+1387,CHEMBL355982,35.0,nM,1999.0,Brc1cccc(Nc2ncnc3sccc23)c1,7.455931955649724,304.96223035599996,4,1,4.197400000000001,True
+1388,CHEMBL52665,35.0,nM,1996.0,Brc1cccc(Nc2ncnc3ccncc23)c1,7.455931955649724,300.00105838800005,4,1,3.530900000000001,True
+1389,CHEMBL249928,35.0,nM,2007.0,CN(CCOc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12)C(=O)CO,7.455931955649724,493.15168192799996,8,2,3.8303000000000025,True
+1390,CHEMBL391778,35.0,nM,2007.0,NCC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,7.455931955649724,484.24992114800006,8,2,4.1807000000000025,True
+1391,CHEMBL248108,35.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,7.455931955649724,470.23427108400006,8,2,3.9331000000000014,True
+1392,CHEMBL56505,35.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN(CCO)CCO,7.455931955649724,450.14701114799993,8,3,2.8399000000000014,True
+1393,CHEMBL3233790,35.0,nM,2014.0,CCN1CCN(C/C=C/C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3s2)CC1,7.455931955649724,474.14048628800003,7,2,4.359600000000002,True
+1394,CHEMBL3633932,35.0,nM,2015.0,CCNC(=O)Nc1ccc2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2c1,7.455931955649724,465.136780812,5,3,5.886300000000004,True
+1395,CHEMBL3671514,35.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)N1CCOCC1,7.455931955649724,592.063671216,7,3,4.473500000000003,True
+1396,CHEMBL4070404,35.8,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cccc(F)c3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,7.446116973356125,572.3023506440001,7,1,4.377020000000004,True
+1397,CHEMBL3409482,36.0,nM,2015.0,CN(CCO)c1cc2c(Nc3ccc4c(cnn4Cc4ccccc4)c3)ncnc2cn1,7.443697499232713,425.1964083560001,8,2,3.5949000000000018,True
+1398,CHEMBL3416603,36.0,nM,2015.0,OC[C@@H](Nc1ncnc2sc(Br)cc12)c1ccccc1,7.443697499232713,348.988445104,5,2,3.599300000000002,True
+1399,CHEMBL3974626,36.0,nM,2016.0,COc1ccc(N2C(=O)CS/C2=N/Nc2nncc3ccccc23)cc1,7.443697499232713,365.09464572,7,1,3.101300000000001,True
+1400,CHEMBL3671510,36.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)NC(C)C,7.443697499232713,530.107728948,6,4,4.4859000000000036,True
+1401,CHEMBL3934034,36.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(OCc4ccccc4)cc3)ncnc2cc1OC,7.443697499232713,428.184840628,6,2,5.309500000000004,True
+1402,CHEMBL248116,36.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c23)CC1,7.443697499232713,463.188736132,8,2,4.023400000000002,True
+1403,CHEMBL2425093,36.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CC2(CCO2)C1,7.443697499232713,458.15209652799996,7,1,4.4181000000000035,True
+1404,CHEMBL3671563,36.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)N1CCOCC1,7.443697499232713,558.1026435680001,7,3,3.8201000000000027,True
+1405,CHEMBL3671550,36.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OC(C)CNC(C)=O,7.443697499232713,501.08117985200005,6,3,4.302900000000004,True
+1406,CHEMBL2048904,36.0,nM,2012.0,Cn1ncc2c(Oc3ccc(Nc4ncnc5ccn(CCO)c45)cc3Cl)cccc21,7.443697499232713,434.125801528,8,2,4.499600000000004,True
+1407,CHEMBL3671525,36.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)/C=C/CC,7.443697499232713,527.096829916,6,3,4.860700000000004,True
+1408,CHEMBL3806200,36.2,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc(Cl)c([N+](=O)[O-])c3)c2c2c1OCCO2,7.441291429466834,432.08366194399997,9,1,3.7314000000000016,True
+1409,CHEMBL4072769,36.8,nM,2017.0,Cc1cccc(Nc2ncnc3ccc(NC(=S)NCc4ccccc4)cc23)c1,7.434152181326482,399.151766672,4,3,5.168420000000003,True
+1410,CHEMBL225720,37.0,nM,2007.0,CN(C)CCN/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.431798275933005,369.14687132,6,2,4.176700000000003,True
+1411,CHEMBL4294156,37.0,nM,2018.0,COc1cccc(Nc2cc(NC(=O)CCCC(=O)O)ncn2)c1,7.431798275933005,330.13280505600005,6,3,2.4222,True
+1412,CHEMBL1928947,37.0,nM,2012.0,C=CC(=O)Nc1cccc(Oc2cc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)ncn2)c1,7.431798275933005,490.1207964000001,6,2,6.508500000000004,True
+1413,CHEMBL4166069,37.0,nM,2018.0,O=C(CN1CCCCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.431798275933005,439.100772424,5,2,4.560300000000003,True
+1414,CHEMBL3818970,37.81,nM,2016.0,CCOc1cc2ncnc(Nc3ccc(OCC4CC4)c(Cl)c3)c2cc1NC(=O)[C@@H]1COC(=O)N1,7.422393322637465,497.14659654799993,8,3,4.261200000000002,True
+1415,CHEMBL247710,38.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c23)CC1,7.420216403383191,480.18406535199995,7,2,4.767500000000004,True
+1416,CHEMBL3233782,38.0,nM,2014.0,O=C(/C=C/CN1CC(O)C1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.420216403383191,433.077551684,7,3,3.398600000000001,True
+1417,CHEMBL1683972,38.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1C#C/C=N/OCCN1CCOCC1,7.420216403383191,523.178645624,8,1,4.586220000000004,True
+1418,CHEMBL566350,38.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OCCN1CCCCC1,7.420216403383191,538.2804723280001,9,2,4.593800000000003,True
+1419,CHEMBL137534,38.0,nM,2003.0,CN(C)CC/N=N/Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.420216403383191,413.09635574000004,6,2,4.476600000000003,True
+1420,CHEMBL2348414,38.0,nM,2013.0,O=C(NCCO)C1=Cc2c(ncnc2Nc2ccc(Oc3cccc(C(F)(F)F)c3)c(Cl)c2)NCC1,7.420216403383191,519.128501872,7,4,4.992200000000002,True
+1421,CHEMBL3416600,38.0,nM,2015.0,C[C@@H](Nc1ncnc2sc(Br)cc12)c1ccccc1,7.420216403383191,332.99353048399996,4,1,4.626900000000003,True
+1422,CHEMBL440453,38.0,nM,1999.0,COc1cc(O)c2c(O)c(-c3cccc(Cl)c3)cnc2c1,7.420216403383191,301.050570924,4,2,3.9750000000000014,True
+1423,CHEMBL584714,38.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OCC1CCCNC1,7.420216403383191,524.2648222640001,9,3,4.107500000000002,True
+1424,CHEMBL2425737,38.4,nM,2013.0,O=C(CCOc1ccccc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.415668775632469,462.069137948,5,2,5.543500000000003,True
+1425,CHEMBL53375,39.0,nM,1996.0,COc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,7.4089353929735005,330.011623072,5,1,3.539500000000002,True
+1426,CHEMBL137617,39.0,nM,2003.0,C/N=N/Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.4089353929735005,356.038506516,5,2,4.544800000000002,True
+1427,CHEMBL3671519,39.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CSC,7.4089353929735005,533.053250852,7,3,4.257500000000003,True
+1428,CHEMBL4081732,40.0,nM,2017.0,N#CCCSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,7.397940008672037,415.12669479600004,5,2,6.027180000000004,True
+1429,CHEMBL4083642,40.0,nM,2017.0,Cc1nc(C)c(/C=C2\CN(C)C/C(=C\c3nc(C)c(C)nc3C)C2=O)nc1C,7.397940008672037,377.221560484,6,0,3.0986200000000013,True
+1430,CHEMBL3671557,40.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCNCCC=O,7.397940008672037,515.096829916,7,3,4.347000000000003,True
+1431,CHEMBL3676359,40.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Cl)cc3F)ncnc2cc1OCCNC(=O)CS(C)(=O)=O,7.397940008672037,555.05462332,8,3,3.4834000000000023,True
+1432,CHEMBL126137,40.0,nM,1997.0,CN(C)CCN(C)c1cc2ncnc(Nc3cccc(Br)c3)c2cn1,7.397940008672037,400.10110677200004,6,1,3.5287000000000015,True
+1433,CHEMBL346863,40.0,nM,1999.0,Brc1cccc(Nc2ncnc3c2sc2ncsc23)c1.CO,7.397940008672037,393.95576507199996,7,2,4.415600000000002,True
+1434,CHEMBL287832,40.0,nM,1997.0,CN(C)CCn1ncc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,7.397940008672037,410.0854567080001,6,1,4.047200000000002,True
+1435,CHEMBL412367,40.0,nM,2005.0,CCc1c(NC(=O)OCCn2ccnc2)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,7.397940008672037,521.2287711040001,10,2,4.878500000000004,True
+1436,CHEMBL193681,40.0,nM,2005.0,CCc1c(C(=O)NCCCn2ccnc2)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,7.397940008672037,519.2495065480001,9,2,4.449900000000003,True
+1437,CHEMBL202398,40.0,nM,2006.0,CCCCN(CC#CC(=O)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1)CCCC,7.397940008672037,481.204466448,5,2,6.010000000000005,True
+1438,CHEMBL380006,40.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)[C@H](C)C(=O)N(C)C,7.397940008672037,445.16808094000004,6,1,4.083000000000004,True
+1439,CHEMBL204570,40.0,nM,2006.0,OCc1cccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)n1,7.397940008672037,460.110231716,6,2,4.878800000000003,True
+1440,CHEMBL504034,40.0,nM,2009.0,CS(=O)(=O)CCNC(=O)O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3s2)C1,7.397940008672037,643.1126168640001,10,3,4.659200000000004,True
+1441,CHEMBL1645467,40.0,nM,2011.0,NC1CCN(Cc2ccn3ncnc(Nc4ccccc4)c23)CC1,7.397940008672037,322.190594704,6,2,2.395999999999999,True
+1442,CHEMBL461426,40.0,nM,2009.0,NC(=O)O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3s2)C1,7.397940008672037,537.103766432,8,3,4.983700000000003,True
+1443,CHEMBL296377,40.0,nM,1996.0,Clc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.397940008672037,333.9620860360001,4,1,4.184300000000001,True
+1444,CHEMBL3233770,40.0,nM,2014.0,O=C(CCl)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.397940008672037,369.98581548800007,5,2,4.404700000000002,True
+1445,CHEMBL566337,40.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OCCn1ccnc1,7.397940008672037,521.2287711040001,10,2,4.004600000000002,True
+1446,CHEMBL93461,40.0,nM,1996.0,CC(=O)Nc1ccc2c(Nc3cccc(Br)c3)ncnc2c1,7.397940008672037,356.0272731360001,4,2,4.094300000000002,True
+1447,CHEMBL484270,40.0,nM,2013.0,CCN1CCN(Cc2ccc(-c3cc4c(N[C@@H](C)c5ccccc5)ncnc4[nH]3)cc2)CC1,7.397940008672037,440.2688450240001,5,2,4.935500000000003,True
+1448,CHEMBL391181,40.0,nM,2007.0,COc1cn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c2c1CN1CCC(N)CC1,7.397940008672037,500.24483576800003,9,2,3.9417000000000026,True
+1449,CHEMBL3949347,41.0,nM,2016.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc4c(cnn4Cc4ccccc4)c3)ncnc2cn1,7.387216143280264,478.2229574520001,8,2,4.222700000000002,True
+1450,CHEMBL3092324,41.0,nM,2013.0,CS(=O)(=O)CCNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,7.387216143280264,523.109245736,8,3,3.4997000000000016,True
+1451,CHEMBL3676365,41.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)CCO,7.387216143280264,551.03712212,7,4,3.930300000000003,True
+1452,CHEMBL37373,41.0,nM,1997.0,CN(C)CCn1ccc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,7.387216143280264,409.09020774000004,5,1,4.652200000000003,True
+1453,CHEMBL68920,41.0,nM,2002.0,Cc1cc(C)c(/C=C2\C(=O)Nc3ncnc(Nc4ccc(F)c(Cl)c4)c32)[nH]1,7.387216143280264,383.09491600000007,4,3,4.450340000000002,True
+1454,CHEMBL512391,41.0,nM,2008.0,Nc1ncnc(Nc2ccc(OCc3ccccc3)c(Cl)c2)c1C(=O)O,7.387216143280264,370.08326801999993,6,3,3.7330000000000023,True
+1455,CHEMBL3758889,41.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3ccc(S(C)(=O)=O)cc3)cc12)c1ccccc1,7.387216143280264,409.091868848,6,1,4.934900000000003,True
+1456,CHEMBL3912723,42.0,nM,2016.0,O=C1CS/C(=N/Nc2nncc3ccccc23)N1c1ccc(Cl)cc1,7.376750709602098,369.045108684,6,1,3.746100000000002,True
+1457,CHEMBL3671584,42.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3Cl)ncnc2cc1OCCNC(C)=O,7.376750709602098,503.03597924800005,6,3,4.428700000000003,True
+1458,CHEMBL205235,42.0,nM,2006.0,Nc1cccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1,7.376750709602098,444.115317096,5,2,5.573700000000003,True
+1459,CHEMBL205284,42.0,nM,2006.0,Fc1cccc(COc2ccc(Nc3ncncc3C#Cc3cc[nH]n3)cc2Cl)c1,7.376750709602098,419.09491600000007,5,2,4.714600000000002,True
+1460,CHEMBL3040806,42.0,nM,2014.0,c1ccc(-c2cccc(Nc3ncnc4cc5c(cc34)OCCO5)c2)cc1,7.376750709602098,355.132076784,5,1,4.811600000000003,True
+1461,CHEMBL3676352,42.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(OC)c(Cl)cc3Cl)ncnc2cc1OCCNC(C)=O,7.376750709602098,489.09705951200004,7,3,4.328200000000003,True
+1462,CHEMBL3297897,42.2,nM,2014.0,COc1ccc(Nc2nc(C)nc3oc(C)cc23)cc1,7.374687549038327,269.11642672,5,1,3.591840000000002,True
+1463,CHEMBL4228120,42.3,nM,2018.0,O=C(N/N=C/c1cc(F)c(F)cc1Cl)N1CCc2ncnc(Nc3ccc(F)c(Cl)c3)c2C1,7.373659632624958,494.0636491200001,5,2,5.046100000000002,True
+1464,CHEMBL3234742,43.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1cnc(N)nc1,7.366531544420412,527.2256577960001,7,3,3.638020000000002,True
+1465,CHEMBL470391,43.0,nM,2009.0,C#Cc1cccc(Nc2ncnc3nc(Nc4ccc(CN5CCOCC5)cc4)sc23)c1,7.366531544420412,442.157580324,8,2,4.387000000000003,True
+1466,CHEMBL3234746,43.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1cnc(NC(C)C)nc1,7.366531544420412,569.2726079880001,7,3,4.876120000000004,True
+1467,CHEMBL1928310,43.7,nM,2012.0,O=C(c1cc2ccccc2[nH]1)c1cc2c(Nc3ccc(F)cc3)ncnc2s1,7.359518563029578,388.0794102560001,5,2,5.286300000000002,True
+1468,CHEMBL3805333,43.8,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc(F)c([N+](=O)[O-])c3)c2c2c1OCCO2,7.358525889495901,416.1132124839999,9,1,3.217100000000001,True
+1469,CHEMBL138363,44.0,nM,2001.0,C=C(C)C(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.356547323513813,383.0381721680001,5,2,4.045500000000002,True
+1470,CHEMBL578044,44.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OCCC1CCNCC1,7.356547323513813,538.2804723280001,9,3,4.497600000000003,True
+1471,CHEMBL52765,44.0,nM,2003.0,Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.356547323513813,314.01670845200005,4,2,3.7181000000000015,True
+1472,CHEMBL177053,44.0,nM,1996.0,Brc1cccc(Nc2ncnc3cc4ncsc4cc23)c1,7.356547323513813,355.9731293880001,5,1,4.745600000000001,True
+1473,CHEMBL383499,44.0,nM,2006.0,CC(C)N(CC#CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cn1)C(C)C,7.356547323513813,454.16841528800006,6,2,4.621600000000003,True
+1474,CHEMBL54788,44.0,nM,1996.0,Fc1ccc2ncnc(Nc3cccc(Br)c3)c2n1,7.356547323513813,317.991636576,4,1,3.670000000000001,True
+1475,CHEMBL2348416,44.0,nM,2013.0,COC(=O)C1=Cc2c(ncnc2Nc2ccc(Oc3cccc4sccc34)c(Cl)c2)NCC1,7.356547323513813,478.0866391480001,8,2,6.252600000000003,True
+1476,CHEMBL3234747,44.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1cnc(NC2CC2)nc1,7.356547323513813,567.2569579240001,7,3,4.630120000000003,True
+1477,CHEMBL3975699,44.0,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccc(C#N)cc3)cc12)c1ccccc1,7.356547323513813,340.132411132,5,1,4.934580000000003,True
+1478,CHEMBL402113,44.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2ccccc2)c1,7.356547323513813,373.165108228,8,2,3.1807000000000016,True
+1479,CHEMBL3671531,44.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CCN(CC)CC,7.356547323513813,572.1546791400001,7,3,4.626400000000004,True
+1480,CHEMBL3828079,44.1,nM,2016.0,Cn1cc(-c2ccc3ncnc(Nc4ccc5ncccc5c4)c3c2)cn1,7.355561410532161,352.143644512,6,1,4.3221000000000025,True
+1481,CHEMBL3912266,44.5,nM,2015.0,C=CC(=O)N[C@H]1CC[C@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)CC1,7.351639989019067,454.21172407200004,7,2,4.653700000000003,True
+1482,CHEMBL4225191,45.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N4CCC(N(C)C)CC4)cc3OC)n2)c1,7.346787486224656,530.2753869480001,8,4,4.527700000000004,True
+1483,CHEMBL3982619,45.0,nM,2016.0,O=C1CS/C(=N/Nc2nncc3ccccc23)N1c1ccccc1,7.346787486224656,335.08408103600004,6,1,3.0927000000000016,True
+1484,CHEMBL283201,45.0,nM,2000.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(CN(C)C)c(Br)c3)c2c1,7.346787486224656,425.08512236,5,2,4.322000000000003,True
+1485,CHEMBL391321,45.0,nM,2007.0,OCCNCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,7.346787486224656,431.18698654400004,8,3,3.0919000000000008,True
+1486,CHEMBL3671576,45.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN1CCCC1,7.346787486224656,556.1233790120001,7,3,3.990300000000003,True
+1487,CHEMBL1914663,45.0,nM,2011.0,Br.Oc1ccc(-c2cc3c(NCc4ccccc4F)ncnc3[nH]2)cc1,7.346787486224656,414.0491514520001,4,3,4.659600000000003,True
+1488,CHEMBL566559,45.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OCC1CCCCN1,7.346787486224656,524.2648222640001,9,3,4.250000000000002,True
+1489,CHEMBL128432,45.0,nM,1997.0,CN(C)CCNc1cc2ncnc(Nc3cccc(Br)c3)c2cn1,7.346787486224656,386.08545670800004,6,2,3.5044000000000013,True
+1490,CHEMBL3680376,45.34,nM,2014.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CCCC(F)C1,7.3435184842095005,487.158659128,6,2,5.103100000000005,True
+1491,CHEMBL4161396,45.4,nM,2018.0,COc1cc2ncnc(N3CCc4ccccc43)c2cc1NC(=O)/C=C/CN1CCCCC1,7.342944147142896,443.23212516800004,6,1,4.313200000000003,True
+1492,CHEMBL4214588,46.0,nM,2018.0,COC(=O)c1ccc(O)c(-c2nc(NCc3cccnc3)c3ccccc3n2)c1,7.337242168318426,386.137890436,7,2,3.796100000000002,True
+1493,CHEMBL4281426,46.0,nM,2018.0,O=C1Nc2ccc(S(=O)(=O)N3CCOCC3)cc2/C1=N/Nc1ccccc1,7.337242168318426,386.104876056,6,2,1.4757999999999996,True
+1494,CHEMBL1272223,46.0,nM,2010.0,C=CC(=O)N1CCc2c(sc3ncnc(N[C@H](CC)c4ccccc4)c23)C1,7.337242168318426,378.151432324,5,1,4.325200000000003,True
+1495,CHEMBL72393,46.0,nM,1996.0,Brc1cccc(Nc2ncnc3[nH]c4c(c23)CCCC4)c1,7.337242168318426,342.04800858000004,3,2,4.342800000000002,True
+1496,CHEMBL4066569,46.5,nM,2017.0,C=CC(=O)Nc1cc(Nc2cc(-c3cn(C)c4ccccc34)nc(C)n2)c(OC)cc1N(C)CCN(C)C,7.3325470471100465,513.28522336,8,2,4.818220000000004,True
+1497,CHEMBL247914,47.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5ccccn5)c4)c23)CC1,7.327902142064282,453.2389418640001,9,2,3.189000000000001,True
+1498,CHEMBL255236,47.0,nM,2008.0,COc1ccccc1CO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(F)c2)c1,7.327902142064282,497.19755122800007,9,2,4.898800000000003,True
+1499,CHEMBL347282,47.0,nM,1999.0,Nc1ccc2sc3c(Nc4cccc(C(F)(F)F)c4)ncnc3c2c1,7.327902142064282,360.06565201200004,5,2,5.189100000000002,True
+1500,CHEMBL210660,47.0,nM,2006.0,O=NN(CCCl)C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.327902142064282,448.00501346799996,6,2,4.890000000000002,True
+1501,CHEMBL3893698,47.0,nM,2016.0,CCN1C(=O)CS/C1=N/Nc1nncc2ccccc12,7.327902142064282,287.08408103600004,6,1,1.9079999999999997,True
+1502,CHEMBL2437458,47.1,nM,2013.0,C=CC(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccc(Cl)cc4)nc32)c1,7.326979092871103,418.09450140000007,7,2,3.6972000000000014,True
+1503,CHEMBL4072383,47.1,nM,2017.0,COc1ccc2c(c1)CCCN2c1nc(N)nc2c(Cc3ccccc3)c[nH]c12,7.326979092871103,385.19026035600007,5,2,4.223800000000002,True
+1504,CHEMBL243839,47.5,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OCc4cccs4)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,7.323306390375134,533.173289964,10,2,3.694600000000002,True
+1505,CHEMBL1203938,47.7,nM,2005.0,COc1cc2ncnc(NCc3ccc(F)cc3)c2cc1OC.Cl,7.3214816209598865,349.099332684,5,1,3.8200000000000025,True
+1506,CHEMBL3758946,48.0,nM,2016.0,OCc1ccc(-c2cc3c(NCc4ccccc4)ncnc3s2)cc1,7.3187587626244115,347.109233164,5,2,4.4627000000000026,True
+1507,CHEMBL4290750,48.0,nM,2018.0,CCOC(=O)c1ccc(Nc2cc(NC(=O)CCCC(=O)O)ncn2)cc1,7.3187587626244115,372.14336974,7,3,2.5903,True
+1508,CHEMBL2425094,48.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CC2(CSC2)C1,7.3187587626244115,474.129252908,7,1,4.992200000000005,True
+1509,CHEMBL402316,48.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2[nH]c(Cc3cccc(F)c3)nc2c1,7.3187587626244115,391.155686416,7,3,3.3889000000000022,True
+1510,CHEMBL540590,48.0,nM,1999.0,Cl.O=[N+]([O-])c1ccc2c(c1)sc1c(Nc3cccc(Br)c3)ncnc12,7.3187587626244115,435.93963634000005,6,1,5.680600000000002,True
+1511,CHEMBL247709,48.0,nM,2007.0,Fc1cccc(COc2ccc(Nc3ncnn4ccc(CN5CCCNCC5)c34)cc2Cl)c1,7.3187587626244115,480.18406535200006,7,2,4.639700000000002,True
+1512,CHEMBL247104,48.0,nM,2007.0,OCCNC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,7.3187587626244115,514.260485832,9,3,3.556300000000002,True
+1513,CHEMBL3647970,48.8,nM,2015.0,CN(C)C/C=C/C(=O)N1CCC[C@@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1,7.311580177997289,497.2539232320001,8,1,4.1491000000000025,True
+1514,CHEMBL3752074,48.81,nM,2016.0,COc1cc(NC(=O)Nc2ccccn2)cc(-c2cccnc2)c1OC,7.311491192343477,350.13789043599996,5,2,3.804800000000002,True
+1515,CHEMBL525725,49.0,nM,2008.0,COc1ccc(/N=C/c2c(N)ncnc2Nc2ccc3c(cnn3Cc3cccc(F)c3)c2)cc1,7.309803919971486,467.18698654400004,8,2,5.098700000000004,True
+1516,CHEMBL4207951,49.0,nM,2017.0,C=CC(=O)N1C[C@@H]2CN(c3nc(Nc4cnn(C)c4)c4ncn(C(C)C)c4n3)C[C@@H]2C1,7.309803919971486,421.23385648400006,9,1,1.9648999999999992,True
+1517,CHEMBL3218346,49.0,nM,2012.0,C=CC(=O)Nc1cccc(Nc2cc(Nc3cccc(Br)c3)ncn2)c1,7.309803919971486,409.053822232,5,3,4.850800000000002,True
+1518,CHEMBL3671582,49.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Cl)cc3Cl)ncnc2cc1OCCNC(C)=O,7.309803919971486,459.086494828,6,3,4.319600000000003,True
+1519,CHEMBL4225255,49.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N(C)CCN(C)C)cc3OC)n2)c1,7.309803919971486,504.25973688400006,8,4,3.9951000000000025,True
+1520,CHEMBL57990,49.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN(C)C,7.309803919971486,404.141531844,6,1,4.5050000000000034,True
+1521,CHEMBL246687,50.0,nM,2007.0,N[C@H]1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)C1,7.301029995663981,456.21862102000006,8,2,3.543000000000001,True
+1522,CHEMBL372112,50.0,nM,2005.0,CCOC(=O)c1cn2ncnc(Nc3ccc4[nH]ncc4c3)c2c1CC,7.301029995663981,350.149123816,7,2,3.088300000000001,True
+1523,CHEMBL542484,50.0,nM,1997.0,COc1cc2ncnc(Nc3ccccc3)c2cc1OC.Cl,7.301029995663981,317.09310443199996,5,1,3.8124000000000025,True
+1524,CHEMBL181742,50.0,nM,2005.0,Clc1cc(Nc2ncnc3nn4ccccc4c23)ccc1OCc1ccccc1,7.301029995663981,401.104337812,6,1,5.2535000000000025,True
+1525,CHEMBL383760,50.0,nM,2006.0,CNC(=O)[C@H]1CCCN1Cc1cc2c(Nc3cccc(Cl)c3F)ncnc2cc1OC,7.301029995663981,443.15243087600004,6,2,3.884900000000002,True
+1526,CHEMBL207674,50.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCOCC1C(N)=O,7.301029995663981,445.131695432,7,2,2.8606000000000007,True
+1527,CHEMBL207037,50.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CC(C(N)=O)C1,7.301029995663981,415.12113074800004,6,2,3.0916000000000015,True
+1528,CHEMBL380889,50.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(C)[C@@H](CN(C)C)C(N)=O,7.301029995663981,460.17897997200004,7,2,3.0218000000000007,True
+1529,CHEMBL3966111,50.0,nM,2016.0,C=CC(=O)NCCCn1c(NC(=O)c2cccc(C(F)(F)F)c2)nc2cc(C)ccc21,7.301029995663981,430.161660572,4,2,4.308120000000003,True
+1530,CHEMBL1645471,50.0,nM,2011.0,Cc1ccc(Nc2ncnn3ccc(CN4CCC(N)CC4)c23)cc1,7.301029995663981,336.206244768,6,2,2.7044200000000007,True
+1531,CHEMBL393264,50.0,nM,2007.0,CC1(N)CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,7.301029995663981,484.24992114800006,8,2,4.323200000000003,True
+1532,CHEMBL555321,50.0,nM,1997.0,Cl.Clc1cccc(Nc2ncnc3ccccc23)c1,7.301029995663981,291.03300271200004,3,1,4.4486000000000026,True
+1533,CHEMBL504117,50.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c3s2)C1)N1CCOCC1,7.301029995663981,590.150302024,10,2,4.613100000000004,True
+1534,CHEMBL3914599,50.0,nM,2009.0,CCCN1CCCOC(COc2cc3ncnc(Nc4ccc(Cl)c(Cl)c4)c3cc2OC)C1,7.301029995663981,490.15384611599995,7,1,5.568500000000006,True
+1535,CHEMBL3944702,50.0,nM,2009.0,COc1cc(Nc2ncnc3cc(OCC4CN(C)CCO4)c(OC)cc23)c(OC)cc1Cl,7.301029995663981,474.16699764399993,9,1,3.762000000000003,True
+1536,CHEMBL501705,50.0,nM,2008.0,CCS(=O)(=O)N[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3s2)C1,7.301029995663981,585.1071375600001,8,3,4.827700000000004,True
+1537,CHEMBL2325101,50.0,nM,2013.0,Clc1ccc(C2=NN(c3ccccc3)C(c3ccc4ccccc4c3)C2)cc1Cl,7.301029995663981,416.084703936,2,0,7.502300000000004,True
+1538,CHEMBL251498,50.3,nM,2007.0,Fc1ccc(Nc2ncnc3ccc(C#CCN4CCOCC4)cc23)cc1Cl,7.298432014944072,396.11531709599996,5,1,3.8496000000000032,True
+1539,CHEMBL2031310,50.7,nM,2012.0,C=CC(=O)Nc1cc2c(Nc3ccc(OCc4ccccn4)c(Cl)c3)c(C#N)cnc2cc1OCC,7.294992040666663,499.14111724400004,7,2,6.0006800000000045,True
+1540,CHEMBL422292,51.0,nM,2001.0,CCOC(=O)/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.292429823902062,441.0436514720001,7,2,3.588700000000001,True
+1541,CHEMBL51265,51.0,nM,1996.0,Brc1cccc(Nc2ncnc3cnccc23)c1,7.292429823902062,300.00105838800005,4,1,3.530900000000001,True
+1542,CHEMBL1203934,51.0,nM,2005.0,COc1cc2ncnc(Nc3ccc(F)cc3)c2cc1OC.Cl,7.292429823902062,335.08368262,5,1,3.9515000000000025,True
+1543,CHEMBL3938794,51.0,nM,2016.0,O=C1CS/C(=N/Nc2nncc3ccccc23)N1,7.292429823902062,259.052780908,6,2,1.1756999999999997,True
+1544,CHEMBL384699,51.0,nM,2006.0,COc1cc2ncnc(Nc3cc(Cl)ccc3F)c2cc1OCCCN1CCOCC1,7.292429823902062,446.15209652799996,7,1,4.275600000000003,True
+1545,CHEMBL4203001,51.3,nM,2018.0,CN(CCO)c1nc(Nc2ccccc2)nc2cnc(Nc3ccc(N4CCC(N(C)C)CC4)cn3)cc12,7.2898826348881824,513.29645674,10,3,3.8659000000000026,True
+1546,CHEMBL4204139,51.9,nM,2018.0,CN(CCCO)c1nc(Nc2ccc(F)cc2)nc2cnc(Nc3ccc(N4CCC(N(C)C)CC4)cn3)cc12,7.284832642151543,545.3026849920002,10,3,4.395100000000004,True
+1547,CHEMBL3905411,52.0,nM,2016.0,CCCCNC(=S)NNc1nncc2ccccc12,7.2839966563652,275.120466544,4,3,2.2208999999999994,True
+1548,CHEMBL298637,52.0,nM,1996.0,CNc1ccc2c(Nc3cccc(Br)c3)ncnc2n1,7.2839966563652,329.02760748400004,5,2,3.5726000000000013,True
+1549,CHEMBL1914664,52.0,nM,2011.0,Br.Oc1ccc(-c2cc3c(NCc4cccc(F)c4)ncnc3[nH]2)cc1,7.2839966563652,414.0491514520001,4,3,4.659600000000003,True
+1550,CHEMBL497863,52.0,nM,2008.0,Nc1ncnc(Nc2ccc3c(cnn3Cc3cccc(F)c3)c2)c1/C=N/NCC(F)(F)F,7.2839966563652,458.15905545600003,8,3,3.825300000000002,True
+1551,CHEMBL2425089,52.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CC2(CSC2)C1,7.2839966563652,460.113602844,7,1,4.602100000000004,True
+1552,CHEMBL4212326,52.0,nM,2017.0,C=CC(=O)N[C@H]1CCN(c2nc(Nc3cnn(C)c3)c3ncn(C(C)C)c3n2)C1,7.2839966563652,395.21820642000006,9,2,1.765199999999999,True
+1553,CHEMBL401251,52.8,nM,2007.0,COCCOc1cc2ncc(C#N)c(N[C@@H]3C[C@H]3c3ccccc3)c2cc1OC,7.277366077466188,389.17394159599996,6,1,4.108280000000003,True
+1554,CHEMBL93545,53.0,nM,1996.0,Nc1cc2ncnc(Nc3cccc(Br)c3)c2cc1[N+](=O)[O-],7.275724130399211,359.00178666,6,2,3.6263000000000014,True
+1555,CHEMBL3927914,53.0,nM,2016.0,COc1ccc(NC(=S)NNc2nncc3ccccc23)cc1,7.275724130399211,325.09973110000004,5,3,2.951900000000001,True
+1556,CHEMBL36819,53.0,nM,1997.0,O=C(O)Cn1ncc2cc3c(Nc4cccc(Br)c4)ncnc3cc21,7.275724130399211,397.01743672400005,6,2,3.5702000000000016,True
+1557,CHEMBL4283970,53.0,nM,2018.0,O=C(O)CCCC(=O)Nc1cc(N2CCOCC2)ncn1,7.275724130399211,294.13280505600005,6,2,0.5065999999999997,True
+1558,CHEMBL3416438,53.0,nM,2015.0,Fc1ccc(Nc2ncnc3sc(Br)cc23)cc1Cl,7.275724130399211,356.91383619199996,4,1,4.989900000000001,True
+1559,CHEMBL3775664,53.1,nM,2016.0,O=C1COc2cc3ncnc(Nc4ccc(F)c(Cl)c4)c3cc2N1CCCN1CCOCC1,7.274905478918531,471.14734549600007,7,1,3.6136000000000026,True
+1560,CHEMBL516487,54.0,nM,2008.0,COC(=O)c1c(N)ncnc1Nc1ccc(OCc2ccccc2)c(Cl)c1,7.267606240177032,384.098918084,7,2,3.8214000000000015,True
+1561,CHEMBL449093,54.0,nM,1991.0,O=C(O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1O,7.267606240177032,365.020537312,7,2,2.1055000000000006,True
+1562,CHEMBL328879,55.0,nM,1996.0,COc1ccc2ncnc(Nc3ccccc3)c2c1,7.259637310505756,251.105862036,4,1,3.3820000000000014,True
+1563,CHEMBL4062722,55.0,nM,2017.0,CSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3cc(F)cc([N+](=O)[O-])c3)c2)[nH]1,7.259637310505756,439.09145216,6,2,5.790600000000003,True
+1564,CHEMBL3416623,55.0,nM,2015.0,COc1ccccc1-c1cc2c(N[C@H](C)c3cccs3)ncnc2s1,7.259637310505756,367.08130416400013,6,1,5.601500000000003,True
+1565,CHEMBL2087353,55.0,nM,2012.0,Brc1cccc(Nc2ncnc3cc4c(cc23)OCCOCCO4)c1,7.259637310505756,401.0375034719999,6,1,3.923700000000002,True
+1566,CHEMBL4086559,55.5,nM,2017.0,C=CC(=O)Nc1cc(Nc2ncnc(-c3cn(C)c4ccccc34)c2OC)c(OC)cc1N(C)CCN(C)C,7.2557070168773246,529.28013798,9,2,4.518400000000004,True
+1567,CHEMBL4092966,55.5,nM,2017.0,S=C(Nc1cncc(Cl)c1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.2557070168773246,440.037770808,5,3,5.884100000000003,True
+1568,CHEMBL115745,56.0,nM,1995.0,COc1cc2ncnc(NCc3ccccc3)c2cc1O,7.251811972993798,281.11642672,5,2,2.9561000000000015,True
+1569,CHEMBL3671480,56.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCc1ccncc1,7.251811972993798,493.0549651040001,6,2,5.3735000000000035,True
+1570,CHEMBL3937527,56.0,nM,2016.0,C[C@@H](Nc1ncnc2oc(-c3ccc(Br)cc3)cc12)c1ccccc1,7.251811972993798,393.04767423199996,4,1,5.825400000000004,True
+1571,CHEMBL92985,56.0,nM,1996.0,Fc1cccc(Nc2ncnc3ccccc23)c1,7.251811972993798,239.08587554,3,1,3.512500000000001,True
+1572,CHEMBL2425092,56.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CC2(COC2)C1,7.251811972993798,458.15209652799996,7,1,4.275600000000003,True
+1573,CHEMBL257814,57.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2c(c1)CCN2Cc1cccc(F)c1,7.244125144327507,392.17608751200004,7,2,3.4845000000000024,True
+1574,CHEMBL334801,57.0,nM,2001.0,CN(C)CCCNC(=O)/C=C/C(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.244125144327507,497.11748510800004,7,3,3.0935000000000006,True
+1575,CHEMBL55425,57.0,nM,2001.0,CCN(CC)CCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,7.244125144327507,432.17283197200004,6,1,5.285200000000005,True
+1576,CHEMBL3948267,57.0,nM,2016.0,O=C(/C=C/CN1CCCC1)Nc1cc2c(Nc3ccc4c(cnn4Cc4ccccc4)c3)ncnc2cn1,7.244125144327507,504.2386075160001,8,2,4.756900000000003,True
+1577,CHEMBL90595,57.0,nM,2001.0,O=C(C#CCN1CCCCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.244125144327507,463.100772424,5,2,4.563700000000003,True
+1578,CHEMBL3676379,57.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(COC)N(C)C,7.244125144327507,574.133943696,8,3,3.4711000000000025,True
+1579,CHEMBL3806145,57.8,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(OC4CCOCC4)c4c(c23)OCCO4)c1,7.2380721615794705,403.15320615199994,7,1,3.6837000000000026,True
+1580,CHEMBL544868,58.0,nM,1999.0,Cl.O=[N+]([O-])c1ccc2sc3c(Nc4ccccc4)ncnc3c2c1,7.236572006437062,358.02912427200005,6,1,4.918100000000003,True
+1581,CHEMBL332333,58.0,nM,1997.0,c1ccc(Nc2nc[nH]c3nnc(Nc4ccccc4)c2-3)cc1,7.236572006437062,302.127994448,5,3,3.7917000000000014,True
+1582,CHEMBL3676371,58.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)CN(CC)CC,7.236572006437062,592.100056724,7,3,4.889700000000004,True
+1583,CHEMBL326596,58.0,nM,1995.0,COc1ccc2c(NCc3ccccc3)ncnc2c1,7.236572006437062,265.1215121,4,1,3.2505000000000015,True
+1584,CHEMBL3806222,58.8,nM,2016.0,Fc1ccc(Nc2ncnc3cc(OC4CCOCC4)c4c(c23)OCCO4)cc1Cl,7.230622673923861,431.10481198799994,7,1,4.494900000000004,True
+1585,CHEMBL345109,59.0,nM,2001.0,CN(C)CCCNC(=O)/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.229147988357855,496.12223614000004,6,3,3.698500000000001,True
+1586,CHEMBL371888,59.0,nM,2005.0,COc1cc2ncnc(Nc3ccc(OCc4ccccn4)c(C)c3)c2cc1OC,7.229147988357855,402.16919056399996,7,1,4.673020000000003,True
+1587,CHEMBL3941626,59.0,nM,2014.0,CCOc1cc2[nH]cc(C#N)c(=Nc3ccc(OCc4ccccn4)c(Cl)c3)c2cc1NC(=O)/C=C/[C@H]1C[C@H](O)CN1C,7.229147988357855,598.209531152,8,3,4.857780000000005,True
+1588,CHEMBL469997,59.0,nM,2009.0,Fc1ccc(Nc2ncnc3nc(Nc4ccccc4)sc23)cc1Cl,7.229147988357855,371.040772252,6,2,5.366000000000001,True
+1589,CHEMBL3671515,59.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCN(C)C(C)=O,7.229147988357855,501.08117985200005,6,2,4.256600000000003,True
+1590,CHEMBL3671488,59.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCNC(=O)C(F)(F)F,7.229147988357855,555.052914416,6,3,4.846900000000002,True
+1591,CHEMBL93049,59.0,nM,2001.0,COCOCC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.229147988357855,440.048402504,6,2,3.6983000000000015,True
+1592,CHEMBL3759649,59.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3ccc(C=O)cc3F)cc12)c1ccccc1,7.229147988357855,377.09981135199996,5,1,5.483000000000004,True
+1593,CHEMBL2437483,59.1,nM,2013.0,COc1ccc(Nc2ncc3ncc(=O)n(-c4ccc(NC(=O)/C=C/CN(C)C)cc4)c3n2)cc1,7.228412519118745,471.20188766000007,9,2,2.9842000000000013,True
+1594,CHEMBL2325100,60.0,nM,2013.0,Cc1ccc(C2=NN(c3ccccc3)C(c3ccc4ccccc4c3)C2)cc1,7.221848749616356,362.178298704,2,0,6.503920000000005,True
+1595,CHEMBL393848,60.0,nM,2007.0,N[C@@H]1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)C1,7.221848749616356,456.21862102000006,8,2,3.543000000000001,True
+1596,CHEMBL4063890,60.0,nM,2017.0,COc1cc(Br)c(/C=C2\CN(C)C/C(=C\c3nc(C)c(C)nc3C)C2=O)cc1OC,7.221848749616356,471.115753792,6,0,4.163060000000003,True
+1597,CHEMBL370934,60.0,nM,2005.0,CCOC(=O)c1cn2ncnc(Nc3cccc(Br)c3)c2c1CC,7.221848749616356,388.053487884,6,1,3.9745000000000026,True
+1598,CHEMBL4286031,60.0,nM,2018.0,Fc1cc(F)cc(NC(=S)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)c1,7.221848749616356,485.012134988,4,3,6.2230000000000025,True
+1599,CHEMBL2180203,60.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc(C(F)(F)F)cc3)c3c(N)ncnc32)C1,7.221848749616356,416.1572438880001,6,1,3.4438000000000013,True
+1600,CHEMBL3973973,60.0,nM,2016.0,C=CC(=O)N[C@@H]1CCC[C@@H](n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cc(C)ccc32)C1,7.221848749616356,470.1929607,4,2,5.4017200000000045,True
+1601,CHEMBL4082783,60.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(C#CC3CCCC3)c3c(N)ncnc32)C1,7.221848749616356,364.20115938800006,6,1,2.2997000000000005,True
+1602,CHEMBL1821869,60.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc(F)cc3)C2)cc1C,7.221848749616356,461.112874572,4,0,7.5751400000000055,True
+1603,CHEMBL217536,60.0,nM,2006.0,O=C(Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)C1CCSS1,7.221848749616356,445.9870652,6,2,5.228100000000002,True
+1604,CHEMBL4065300,60.1,nM,2017.0,Fc1cc(F)cc(NC(=S)Nc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)c1,7.221125527997262,441.06265056800004,4,3,6.113900000000002,True
+1605,CHEMBL2437482,60.4,nM,2013.0,C=CC(=O)Oc1ccc(-n2c(=O)cnc3cnc(Nc4ccc(OC)cc4)nc32)cc1,7.218963061378869,415.128054024,9,1,3.019300000000001,True
+1606,CHEMBL3647973,60.9,nM,2015.0,C=CC(=O)N1CCC(n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)CC1,7.215382707367125,440.19607400800004,7,1,4.2173000000000025,True
+1607,CHEMBL294395,61.0,nM,2001.0,COCCN(CCOC)CCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,7.214670164989233,478.17831127600004,8,1,4.148100000000002,True
+1608,CHEMBL2347231,61.0,nM,2013.0,NC(=O)Nc1ccc2ncnc(Nc3ccc(Cl)cc3)c2c1,7.214670164989233,313.073037684,4,3,3.517400000000001,True
+1609,CHEMBL246284,61.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(COC[C@@H]6CNCCO6)c45)ccc32)c1,7.214670164989233,487.21320129199995,9,2,3.5150000000000015,True
+1610,CHEMBL3968839,61.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(ccn4Cc4ccccn4)c3)ncnc2cc1OC,7.214670164989233,452.19607400800004,7,2,5.128500000000004,True
+1611,CHEMBL328245,62.0,nM,2001.0,CCCN(CC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)CCC,7.207608310501746,479.132072552,5,2,5.199800000000004,True
+1612,CHEMBL1914655,62.0,nM,2011.0,Br.C[C@@H](Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12)c1ccc(Br)cc1,7.207608310501746,487.98473539599996,4,3,5.844000000000003,True
+1613,CHEMBL442754,62.0,nM,2001.0,COCCN(C)C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.207608310501746,469.11133710800004,6,2,4.208800000000003,True
+1614,CHEMBL4229213,62.5,nM,2018.0,O=C(N/N=C/c1cccs1)N1CCc2ncnc(Nc3ccc(F)c(Cl)c3)c2C1,7.204119982655924,430.077886032,6,2,4.176000000000003,True
+1615,CHEMBL1914669,63.0,nM,2011.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(Br)cc3)cc12)c1ccccc1,7.200659450546419,392.06365864400004,3,2,5.560500000000004,True
+1616,CHEMBL499534,63.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3s2)C1)N1CCNCC1,7.200659450546419,606.1616156559999,9,3,4.930200000000005,True
+1617,CHEMBL204625,63.0,nM,2006.0,Nc1ccccc1C#Cc1cncnc1Nc1ccc(OCc2cccc(F)c2)c(Cl)c1,7.200659450546419,444.11531709599996,5,2,5.573700000000002,True
+1618,CHEMBL473553,63.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(-c4nc5ccccc5s4)c(OC)c3)c2cc1OC,7.200659450546419,444.1256115,8,1,5.675900000000003,True
+1619,CHEMBL391779,63.0,nM,2007.0,CNC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,7.200659450546419,484.24992114800006,8,2,4.193800000000002,True
+1620,CHEMBL596059,63.0,nM,2009.0,COc1cc(-c2nc3ccccc3s2)ccc1Nc1ncnc2cc(OC)c(OC)cc12,7.200659450546419,444.1256115,8,1,5.675900000000004,True
+1621,CHEMBL3774947,63.1,nM,2016.0,O=C1COc2cc3ncnc(Nc4cccc(Cl)c4)c3cc2N1CCCN1CCOCC1,7.199970640755867,453.15676730800004,7,1,3.4745000000000017,True
+1622,CHEMBL2334001,63.4,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCO,7.197910742118268,363.07859723999997,6,2,3.5456000000000025,True
+1623,CHEMBL4080711,63.6,nM,2017.0,Oc1cccc(Nc2ncnc3ccc(NC(=S)NCc4ccccc4)cc23)c1,7.1965428843515875,401.13103122800004,5,4,4.565600000000002,True
+1624,CHEMBL4099008,63.8,nM,2017.0,C=CC(=O)N1CCC(Cn2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)C1,7.195179321278838,517.2801379800001,9,1,2.638420000000001,True
+1625,CHEMBL137364,64.0,nM,2003.0,Brc1cccc(Nc2ncnc3ccc(N/N=N/CCN4CCOCC4)cc23)c1,7.1938200260161125,455.10692042400007,7,2,4.247200000000003,True
+1626,CHEMBL245667,64.0,nM,2007.0,NCCCOCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,7.1938200260161125,445.20263660800003,8,2,3.8754000000000017,True
+1627,CHEMBL7866,64.0,nM,1999.0,COC(=O)Cn1cc(-c2cccc(Cl)c2)c(=O)c2c(O)cc(OC)cc21,7.1938200260161125,373.07170029199995,6,1,3.209100000000002,True
+1628,CHEMBL344486,64.0,nM,2001.0,CCOC(=O)/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.1938200260161125,440.048402504,6,2,4.193700000000002,True
+1629,CHEMBL3896476,64.0,nM,2016.0,S=C(NNc1nncc2ccccc12)Nc1ccc(Cl)cc1,7.1938200260161125,329.050194064,4,3,3.596700000000001,True
+1630,CHEMBL4099445,64.3,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn4c5c(cccc35)CCC4)n2)c(OC)cc1N1CCN(C)CC1,7.191789027075777,523.2695732960001,8,2,4.673000000000003,True
+1631,CHEMBL3924500,65.0,nM,2016.0,S=C(NNc1nncc2ccccc12)Nc1ccccc1,7.187086643357143,295.089166416,4,3,2.9433000000000007,True
+1632,CHEMBL3970738,65.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(NS(=O)(=O)c4ccccc4)cc3)ncnc2cc1OC,7.187086643357143,477.1470752160001,7,3,4.5313000000000025,True
+1633,CHEMBL1683959,65.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1/C=N/OCCCN1CCOCC1,7.187086643357143,513.194295688,8,1,4.972920000000005,True
+1634,CHEMBL3699598,65.0,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(S(C)(=O)=O)CC4)cc3OC)ncc2C(F)(F)F)c1,7.187086643357143,592.171573624,9,2,4.246000000000003,True
+1635,CHEMBL3639984,65.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(N4CCN(C(=O)CO)CC4)cc3OC(F)(F)F)ncc2C(F)(F)F)c1,7.187086643357143,625.1872215999999,9,4,4.646600000000002,True
+1636,CHEMBL3910422,65.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OC)cc3OC)ncc2Br)c1,7.187086643357143,469.07495159999996,7,3,4.868000000000003,True
+1637,CHEMBL3904778,65.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(OC)cc3OC)ncc2Br)c1,7.187086643357143,470.05896718800005,7,2,4.916700000000002,True
+1638,CHEMBL3985134,65.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(OC)c(OC)c3OC)ncc2C(F)(F)F)c1,7.187086643357143,490.146404432,8,2,5.181600000000003,True
+1639,CHEMBL3973862,65.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(OC)c(OC)c3OC)ncc2Br)c1,7.187086643357143,500.06953187199997,8,2,4.925300000000004,True
+1640,CHEMBL3954273,65.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OC)c(OC)c3OC)ncc2Br)c1,7.187086643357143,499.085516284,8,3,4.876600000000003,True
+1641,CHEMBL3676348,65.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Cl)nc3)ncnc2cc1OCCNC(C)=O,7.187086643357143,426.120716148,7,3,3.0612000000000004,True
+1642,CHEMBL3943512,65.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(Oc4ccccc4)cc3)ncnc2cc1OC,7.187086643357143,414.169190564,6,2,5.522800000000005,True
+1643,CHEMBL327838,65.0,nM,2001.0,COCCOCC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.187086643357143,454.064052568,6,2,3.740800000000002,True
+1644,CHEMBL3986363,65.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OC)c(OC)c3OC)ncc2Cl)c1,7.187086643357143,455.13603186399996,8,3,4.767500000000003,True
+1645,CHEMBL93784,65.0,nM,2001.0,COCC1CCCN1CC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.187086643357143,493.11133710800004,6,2,4.188600000000003,True
+1646,CHEMBL1947125,65.0,nM,2012.0,CC1(C)CC(C(=O)Nc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)CC(C)(C)N1[O],7.187086643357143,452.18532778400004,5,2,5.5800000000000045,True
+1647,CHEMBL92356,65.0,nM,2001.0,CCN1CCN(CC#CC(=O)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)CC1,7.187086643357143,492.12732152,6,2,3.715300000000002,True
+1648,CHEMBL591040,65.5,nM,2010.0,C=C=CCCCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O,7.183758700008219,399.11498274800005,5,2,5.761700000000004,True
+1649,CHEMBL320705,66.0,nM,1998.0,COc1ccccc1Nc1ncc2cc(-c3c(Cl)cccc3Cl)c(=O)n(C)c2n1,7.180456064458131,426.06503111200004,6,1,5.054500000000003,True
+1650,CHEMBL205776,66.0,nM,2006.0,CN1CCN(CCCOc2cc(OC3CCOCC3)c3c(Nc4ccc(F)c(Cl)c4)ncnc3c2)CC1,7.180456064458131,529.2255958160001,8,1,4.740000000000004,True
+1651,CHEMBL294034,66.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCn1ccnc1,7.180456064458131,413.10548068400004,7,1,4.450000000000003,True
+1652,CHEMBL3754785,66.59,nM,2016.0,COc1ccc(-c2cc(NC(=O)Nc3ccccn3)cc(OC)c2OC)cn1,7.176590985107455,380.14845511999994,6,2,3.8134000000000015,True
+1653,CHEMBL3961532,67.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)ncnc2cc1OC,7.173925197299173,480.136446464,6,2,6.102000000000004,True
+1654,CHEMBL2064383,67.0,nM,2012.0,Cc1ccc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)cc1,7.173925197299173,419.19573966,8,1,3.312020000000002,True
+1655,CHEMBL1241676,67.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2C1CCCC1,7.173925197299173,329.104337812,6,2,3.5496000000000016,True
+1656,CHEMBL1788321,67.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OC[C@H](O)CN1CCOCC1,7.173925197299173,462.14701114799993,8,2,3.246400000000002,True
+1657,CHEMBL210659,67.0,nM,2006.0,O=NN(CCCl)C(=O)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.173925197299173,404.055529048,6,2,4.780900000000003,True
+1658,CHEMBL3676386,68.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=S)NCC,7.167491087293763,566.030262912,6,4,4.915700000000004,True
+1659,CHEMBL92936,68.0,nM,1996.0,CNc1cc2ncnc(Nc3cccc(Br)c3)c2cc1[N+](=O)[O-],7.167491087293763,373.017436724,6,2,4.085800000000002,True
+1660,CHEMBL473436,68.0,nM,2009.0,Fc1cccc(COc2ccc(Nc3ncnc4cc(-c5ccc[nH]5)sc34)cc2Cl)c1,7.167491087293763,450.07173803200004,5,2,6.8015000000000025,True
+1661,CHEMBL15202,68.0,nM,2004.0,COc1ccc2ncnc(Nc3ccc(OCc4ccccc4)cc3)c2c1,7.167491087293763,357.147726848,5,1,4.961000000000003,True
+1662,CHEMBL1683958,68.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1/C=N/OCCN1CCOCC1,7.167491087293763,499.178645624,8,1,4.582820000000004,True
+1663,CHEMBL3639703,68.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCNC(=O)CS(C)(=O)=O,7.167491087293763,579.058730156,8,3,3.329200000000002,True
+1664,CHEMBL4282879,68.0,nM,2018.0,COc1ccc(OC)c(Nc2cc(NC(=O)CCCC(=O)O)ncn2)c1,7.167491087293763,360.14336974,7,3,2.4307999999999996,True
+1665,CHEMBL3092308,68.0,nM,2013.0,O=C(NCCN1CCCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,7.167491087293763,514.1895446560001,7,3,4.550900000000002,True
+1666,CHEMBL4128726,68.0,nM,2018.0,C=CC(=O)Nc1cccc(-n2c(=O)n(C)c(=O)c3cnc(Nc4ccccc4)nc32)c1,7.167491087293763,414.1440384360001,8,2,2.3475,True
+1667,CHEMBL401443,68.0,nM,2007.0,OC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,7.167491087293763,471.21828667200003,8,2,3.966700000000003,True
+1668,CHEMBL248222,68.0,nM,2007.0,COc1cc2ncc(C#N)c(N[C@@H]3C[C@H]3c3ccccc3)c2cc1OCCCc1cccnc1,7.167491087293763,450.205576072,6,1,5.489680000000005,True
+1669,CHEMBL76432,68.0,nM,2004.0,c1ccc(-c2cc3ncnc(Nc4ccc5[nH]ccc5c4)c3s2)cc1,7.167491087293763,342.093917448,4,2,5.583200000000002,True
+1670,CHEMBL245278,68.0,nM,2007.0,C[C@H](c1cccc(F)c1)n1ncc2cc(Nc3ncnn4ccc(COC[C@@H]5CNCCO5)c34)ccc21,7.167491087293763,501.228851356,9,2,4.076000000000001,True
+1671,CHEMBL3297898,68.2,nM,2014.0,COc1ccc(N(C)c2nc(C)nc3oc(C)cc23)cc1,7.166215625343522,283.132076784,5,0,3.6161400000000024,True
+1672,CHEMBL3671568,69.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C1CCCN1C,7.161150909262744,556.1233790120001,7,3,3.9887000000000024,True
+1673,CHEMBL56027,69.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCNC(C)(CO)CO,7.161150909262744,450.14701114799993,8,4,2.886200000000001,True
+1674,CHEMBL3416633,69.0,nM,2015.0,C[C@H](N)C#Cc1cc2c(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)ncnc2s1,7.161150909262744,452.087388096,6,2,5.505100000000003,True
+1675,CHEMBL3671522,69.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(=C)C,7.161150909262744,513.081179852,6,3,4.470600000000004,True
+1676,CHEMBL3957416,69.0,nM,2016.0,CCOc1cc2ncnc(Nc3ccc(NS(=O)(=O)c4ccccc4)cc3)c2cc1NC(=O)/C=C/CN1CCOCC1,7.161150909262744,588.2154891240001,9,3,4.399800000000003,True
+1677,CHEMBL3671556,69.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC(CC)NC(C)=O,7.161150909262744,515.096829916,6,3,4.693000000000004,True
+1678,CHEMBL197689,70.0,nM,2005.0,CCc1c(C(=O)NC)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,7.154901959985742,425.19640835600006,7,2,3.792900000000002,True
+1679,CHEMBL3671536,70.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CCOC,7.154901959985742,531.091744536,7,3,3.9310000000000027,True
+1680,CHEMBL1173814,70.0,nM,2010.0,COc1ccc(C2CC(c3ccc(C)c(C)c3)=NN2C(N)=S)cc1,7.154901959985742,339.140533292,3,1,3.7067400000000017,True
+1681,CHEMBL255490,70.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc(F)c(Cl)c1,7.154901959985742,295.063615872,6,2,2.5752000000000006,True
+1682,CHEMBL4286263,70.0,nM,2018.0,O=C(O)CCCC(=O)Nc1cc(Nc2cccc(Br)c2)ncn1,7.154901959985742,378.0327524400001,5,3,3.176100000000001,True
+1683,CHEMBL207246,70.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCC1C(N)=O,7.154901959985742,415.12113074800004,6,2,3.2341000000000015,True
+1684,CHEMBL248322,70.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc(OCc5cccc[n+]5[O-])c(Cl)c4)c23)CC1,7.154901959985742,479.18365075199995,8,2,3.261800000000001,True
+1685,CHEMBL1272276,70.0,nM,2010.0,CN(C)C/C=C/C(=O)N1CCc2c(sc3ncnc(N[C@H](CO)c4ccccc4)c23)C1,7.154901959985742,437.188546104,7,2,2.8393000000000006,True
+1686,CHEMBL3894938,70.49,nM,2015.0,C=CC(=O)NCCn1nc(-c2ccc(Oc3ccccc3)cc2)c2c(N)ncnc21,7.151872489432125,400.16477388000004,7,2,3.170000000000001,True
+1687,CHEMBL3297899,70.7,nM,2014.0,CCN(c1ccc(OC)cc1)c1nc(C)nc2oc(C)cc12,7.150580586203102,297.147726848,5,0,4.006240000000004,True
+1688,CHEMBL136674,71.0,nM,2003.0,COCC/N=N/Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.1487416512809245,400.064721264,6,2,4.561400000000003,True
+1689,CHEMBL3416634,71.0,nM,2015.0,C#Cc1cc2c(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)ncnc2s1,7.1487416512809245,409.04518893600005,5,1,5.787700000000003,True
+1690,CHEMBL4170916,71.0,nM,2018.0,O=C(CN1CCCC1)Nc1ccc2ncnc(Nc3ccc(OCc4cccc(F)c4)cc3)c2c1,7.1487416512809245,471.20705329199996,6,2,5.125800000000004,True
+1691,CHEMBL299672,71.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCCC1,7.1487416512809245,430.157181908,6,1,5.039200000000005,True
+1692,CHEMBL225929,71.0,nM,2007.0,ClCCN(CCN/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1)Cc1ccccc1,7.1487416512809245,493.15484915999997,6,2,6.356100000000005,True
+1693,CHEMBL414220,71.0,nM,2001.0,C=CCN(C)CC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.1487416512809245,449.08512236,5,2,4.195600000000002,True
+1694,CHEMBL4097682,71.6,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3ccc(F)cc3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,7.145086977692144,572.3023506440001,7,1,4.377020000000004,True
+1695,CHEMBL3752248,71.71,nM,2016.0,O=C(Nc1nccs1)Nc1cc(-c2cncnc2)ccc1OC(F)(F)F,7.144420277498282,381.05073022,6,2,4.1427000000000005,True
+1696,CHEMBL3754556,71.82,nM,2016.0,O=C(Nc1cc(-c2cncnc2)cc(C(F)(F)F)c1)Nc1nccs1,7.143754599209946,365.0558156,5,2,4.262900000000001,True
+1697,CHEMBL4176787,72.0,nM,2018.0,COc1cc2ncnc(N3CCCc4ccccc43)c2cc1NC(=O)/C=C/CN(C)C,7.142667503568732,417.21647510400004,6,1,3.7790000000000026,True
+1698,CHEMBL554983,72.0,nM,1999.0,Brc1cccc(Nc2[nH]cnc3c4ccccc4nc2-3)c1.Cl,7.142667503568732,373.993386164,3,2,4.990600000000002,True
+1699,CHEMBL596957,72.0,nM,2010.0,COc1cc2ncnc(NCc3ccc(Cl)c(F)c3)c2cc1OCCCCCCC(=O)NO,7.142667503568732,476.16266121199993,7,3,4.877700000000003,True
+1700,CHEMBL245869,73.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(COC6CCNCC6)c45)ccc32)c1,7.136677139879544,471.218286672,8,2,4.278600000000003,True
+1701,CHEMBL91925,73.0,nM,2001.0,CCN(CC)C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.136677139879544,453.116422488,5,2,4.972400000000004,True
+1702,CHEMBL3297900,73.3,nM,2014.0,CCCN(c1ccc(OC)cc1)c1nc(C)nc2oc(C)cc12,7.134896025358873,311.163376912,5,0,4.396340000000004,True
+1703,CHEMBL15346,74.0,nM,2004.0,CS(=O)(=O)CCNCCCCOc1ccc2ncnc(Nc3ccc(OCc4ccccc4)cc3)c2c1,7.130768280269023,520.214426504,8,2,4.745600000000003,True
+1704,CHEMBL316127,74.0,nM,2001.0,O=C(/C=C/CN1CCOCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.130768280269023,467.09568704400004,6,2,3.9628000000000014,True
+1705,CHEMBL31965,74.0,nM,2002.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCOCC1,7.130768280269023,485.16299556,7,2,4.391500000000003,True
+1706,CHEMBL3939429,74.0,nM,2016.0,COc1ccc(-c2cc3c(NCc4ccccc4)ncnc3o2)cc1,7.130768280269023,331.132076784,5,1,4.510500000000003,True
+1707,CHEMBL438440,74.0,nM,2006.0,Fc1cccc(COc2ccc(Nc3ncncc3C#Cc3cccnc3)cc2Cl)c1,7.130768280269023,430.099667032,5,1,5.386500000000003,True
+1708,CHEMBL3931858,74.5,nM,2015.0,CN(C/C=C/C(=O)N1CCCC(n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1)CCO,7.127843727251707,527.264487916,9,2,3.511600000000002,True
+1709,CHEMBL3805299,74.6,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc(C)c([N+](=O)[O-])c3)c2c2c1OCCO2,7.127261172527331,412.1382843599999,9,1,3.386420000000002,True
+1710,CHEMBL4067255,75.0,nM,2017.0,Fc1ccc(-c2nc(SCCN3CCOCC3)[nH]c2-c2ccnc(Nc3ccccc3)c2)cc1,7.1249387366083,475.184209672,6,2,5.445700000000004,True
+1711,CHEMBL3676372,75.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3)ncnc2cc1OCCNC(=O)CN(C)C,7.1249387366083,546.078178408,7,3,3.9704000000000024,True
+1712,CHEMBL1744347,75.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCCN1CCN(C)CC1.Cl,7.1249387366083,495.160408716,7,1,4.612600000000006,True
+1713,CHEMBL461311,76.0,nM,2008.0,Nc1ncnc(Nc2ccc(OCc3ccccc3)c(Cl)c2)c1C=O,7.1191864077192095,354.08835339999996,6,2,3.8473000000000024,True
+1714,CHEMBL1380839,76.0,nM,2016.0,CCN=C(S)NNc1nncc2ccccc12,7.1191864077192095,247.08916641599998,4,3,1.8519999999999996,True
+1715,CHEMBL4092003,76.0,nM,2017.0,CC(=O)CCCSc1nc(-c2ccc(F)cc2)c(-c2ccnc(Nc3ccccc3)c2)[nH]1,7.1191864077192095,446.1576605760001,5,2,6.482700000000005,True
+1716,CHEMBL461114,76.0,nM,2008.0,Nc1ncnc(Nc2ccc(OCc3ccccc3)c(Cl)c2)c1C(=O)Nc1ccccc1,7.1191864077192095,445.13055255999996,6,3,5.287100000000003,True
+1717,CHEMBL205047,76.0,nM,2006.0,OCc1nc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)cs1,7.1191864077192095,466.066652652,7,2,4.940300000000003,True
+1718,CHEMBL3671565,76.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)N1CCN(C(C)=O)CC1,7.1191864077192095,599.1291926640001,7,3,3.652000000000003,True
+1719,CHEMBL3977192,77.0,nM,2016.0,NC(=S)NNc1nncc2ccccc12,7.113509274827518,219.05786628799999,4,3,0.7898999999999994,True
+1720,CHEMBL434828,77.0,nM,2001.0,O=C(/C=C/c1ccccc1)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,7.113509274827518,445.0538222320001,5,2,5.182800000000003,True
+1721,CHEMBL207869,77.0,nM,2006.0,Fc1cccc(COc2ccc(Nc3ncncc3C#Cc3ncccn3)cc2Cl)c1,7.113509274827518,431.09491600000007,6,1,4.781500000000002,True
+1722,CHEMBL3219131,77.19,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)C(c3ccccc3)N(C)C(=O)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)c1,7.1124389590699915,632.2859516320001,9,2,4.596700000000004,True
+1723,CHEMBL3671549,78.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(F)c3)ncnc2cc1OCCNC(=O)CN(C)C,7.107905397309519,530.107728948,7,3,3.456100000000002,True
+1724,CHEMBL2064372,78.0,nM,2012.0,O=c1oc2cc3ncnc(Nc4ccc(F)c(Cl)c4)c3cc2n1CCCN1CCOCC1,7.107905397309519,457.1316954320001,8,1,3.7961000000000027,True
+1725,CHEMBL4213400,78.0,nM,2017.0,CC(C)C(CO)Nc1nc(Nc2ccc(N3CCNCC3)cc2)c2ncn(C(C)C)c2n1,7.107905397309519,438.28555770800006,9,4,2.989200000000001,True
+1726,CHEMBL3218000,78.0,nM,2012.0,C#Cc1cccc(Nc2ncnc3ccc(OCc4ccc(C(=O)Nc5ccccc5N)cc4)cc23)c1,7.107905397309519,485.18517497600004,6,3,5.768200000000003,True
+1727,CHEMBL3753142,78.17,nM,2016.0,O=C(Nc1cc(-c2cccnc2)cc(C(F)(F)F)c1)Nc1nccs1,7.106959888042883,364.0605666320001,4,2,4.8679000000000014,True
+1728,CHEMBL207410,79.0,nM,2006.0,CNC(=O)c1cccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1,7.102372908709557,486.12588178,5,2,5.351100000000004,True
+1729,CHEMBL379093,79.0,nM,2006.0,Fc1cccc(COc2ccc(Nc3ncncc3C#Cc3ccccc3)cc2Cl)c1,7.102372908709557,429.104418064,4,1,5.991500000000004,True
+1730,CHEMBL3921347,79.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4[nH]ncc4c3)ncnc2cc1OC,7.102372908709557,362.149123816,6,3,3.6068000000000016,True
+1731,CHEMBL291514,79.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCCCC1,7.102372908709557,444.172831972,6,1,5.429300000000005,True
+1732,CHEMBL540701,79.0,nM,2004.0,C=CCOc1ccc2ncnc(Nc3ccc(OCc4ccccc4)cc3)c2c1,7.102372908709557,383.163376912,5,1,5.517200000000004,True
+1733,CHEMBL592466,80.0,nM,2010.0,Oc1ccc(CN(Cc2cccc(Cl)c2O)C(=S)Nc2ccccc2)cc1,7.096910013008057,398.08557652800005,3,3,5.150400000000005,True
+1734,CHEMBL3676349,80.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(OC)c(Cl)cc3F)ncnc2cc1OCCNC(C)=O,7.096910013008057,473.12661005200005,7,3,3.813900000000002,True
+1735,CHEMBL95774,80.0,nM,2002.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cc1OCCCN1CCOCC1,7.096910013008057,509.16299556000007,7,2,4.868180000000005,True
+1736,CHEMBL380454,80.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CC[C@H](C(N)=O)C1,7.096910013008057,429.13678081200004,6,2,3.481700000000002,True
+1737,CHEMBL113070,80.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3ccc(CCCC(=O)O)cc3)nc21,7.096910013008057,482.09124586,6,2,5.453200000000004,True
+1738,CHEMBL507821,80.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc5c(cnn5Cc5ccccc5)c4)c3s2)C1)N1CCOCC1,7.096910013008057,579.205258788,10,2,4.383700000000004,True
+1739,CHEMBL3416621,80.0,nM,2015.0,Brc1cc2c(Nc3ccccc3)ncnc2s1,7.096910013008057,304.96223035599996,4,1,4.197400000000002,True
+1740,CHEMBL169390,80.0,nM,2001.0,Nc1ncnc2c1c(-c1cccc(O)c1)cn2C1CCCC1,7.096910013008057,294.148061196,5,2,3.5012000000000016,True
+1741,CHEMBL346846,80.0,nM,1999.0,COc1ccc2c(c1)sc1c(Nc3cccc(Br)c3)ncnc12,7.096910013008057,384.98844510400005,5,1,5.359200000000003,True
+1742,CHEMBL92825,80.0,nM,1995.0,Ic1cccc(Nc2ncnc3ccccc23)c1,7.096910013008057,346.99194531999996,3,1,3.9780000000000015,True
+1743,CHEMBL4224932,80.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N4CCC(N5CCN(C)CC5)CC4)cc3OC)n2)c1,7.096910013008057,585.317586108,9,4,4.213500000000003,True
+1744,CHEMBL589588,80.0,nM,2010.0,COc1ccc(NC(=O)c2ccc(N(CCCl)CCCl)cc2)cc1,7.096910013008057,366.09018324,3,1,4.231500000000003,True
+1745,CHEMBL250524,80.0,nM,2007.0,COc1cc2ncnc(C#CC(C)(C)N(C)c3ccccc3)c2cc1OC,7.096910013008057,361.179026976,5,0,3.9135000000000035,True
+1746,CHEMBL4291935,80.8,nM,2017.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(CN4CCOCC4)cc3)ncc2F)c1,7.092588639225414,448.20230226,7,3,4.059600000000002,True
+1747,CHEMBL427671,81.0,nM,2007.0,Cc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,7.091514981121351,372.149872764,6,1,4.318420000000002,True
+1748,CHEMBL4283823,81.0,nM,2018.0,COc1ccc(Nc2cc(NC(=O)c3ccccc3)ncn2)cc1,7.091514981121351,320.127325752,5,2,3.4811000000000005,True
+1749,CHEMBL500115,81.0,nM,2008.0,CS(=O)(=O)O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3s2)C1,7.091514981121351,572.075503084,9,2,4.864600000000004,True
+1750,CHEMBL4103370,81.0,nM,2017.0,Clc1ccc(-c2nnc(Cc3nc4ccccc4[nH]3)o2)cc1,7.091514981121351,310.062138652,4,1,3.8571000000000017,True
+1751,CHEMBL208144,81.0,nM,2006.0,CN(CCCl)C(=O)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.091514981121351,389.081015524,4,2,4.729300000000003,True
+1752,CHEMBL3092310,82.0,nM,2013.0,O=C(NCCN1CCOCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,7.086186147616282,530.184459276,8,3,3.7873000000000028,True
+1753,CHEMBL1172773,82.0,nM,2010.0,C=CC(=O)Nc1ccc(-c2c(-c3ccccc3)oc3ncnc(N[C@H](CO)c4ccccc4)c23)cc1,7.086186147616282,476.184840628,6,3,5.826800000000005,True
+1754,CHEMBL3936505,82.0,nM,2016.0,CCOc1cc2ncnc(Nc3ccc(NS(=O)(=O)c4ccccc4)cc3)c2cc1NC(=O)/C=C/CN1CCN(C)CC1,7.086186147616282,601.2471236,9,3,4.315000000000003,True
+1755,CHEMBL511839,82.0,nM,2009.0,NS(=O)(=O)c1ccc(Nc2nc3ncnc(Nc4ccccc4)c3s2)cc1,7.086186147616282,398.06196568800004,8,3,3.220900000000001,True
+1756,CHEMBL3298000,82.3,nM,2014.0,COc1ccc(N(C)c2nc(C)nc3oc(C)cc23)cc1.Cl,7.08460016478773,319.10875449599996,5,0,4.037940000000003,True
+1757,CHEMBL3805383,82.5,nM,2016.0,CC(C)Oc1cc2ncnc(Nc3ccc(F)c([N+](=O)[O-])c3)c2c2c1OCCO2,7.0835460514500745,400.11829786399994,8,1,3.9791000000000025,True
+1758,CHEMBL607707,83.0,nM,2002.0,CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C)C,7.080921907623925,467.15243087600004,6,2,5.097580000000004,True
+1759,CHEMBL428046,83.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(COC[C@H]6CNCCO6)c45)ccc32)c1,7.080921907623925,487.21320129199995,9,2,3.5150000000000015,True
+1760,CHEMBL3416605,83.0,nM,2015.0,OCC(Nc1ncnc2sc(Br)cc12)c1ccccc1,7.080921907623925,348.988445104,5,2,3.599300000000002,True
+1761,CHEMBL97162,83.0,nM,2001.0,COc1nccc(-c2c(-c3ccc(F)cc3)ncn2[C@H]2CC[C@H](O)CC2)n1,7.080921907623925,368.164854132,6,1,3.6308000000000016,True
+1762,CHEMBL3889694,83.4,nM,2015.0,CN(C)C/C=C/C(=O)N[C@H]1CC[C@@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)CC1,7.078833949362261,511.2695732960001,8,2,4.585500000000003,True
+1763,CHEMBL3804886,83.88,nM,2016.0,Fc1cccc(Nc2ncnc3cc(OCCCN4CCOCC4)c4c(c23)OCCO4)c1,7.0763415782066925,440.18598349999996,8,1,3.384800000000002,True
+1764,CHEMBL90540,84.0,nM,1997.0,COc1cc2ncnc(NC3CC3c3ccccc3)c2cc1OC(C)=O,7.075720713938117,349.14264146799997,6,1,3.5317000000000016,True
+1765,CHEMBL3978686,84.0,nM,2016.0,O=S(=O)(Nc1ccccn1)c1ccc(Nc2nncc3ccccc23)cc1,7.075720713938117,377.09464572,6,2,3.569200000000002,True
+1766,CHEMBL1241581,84.0,nM,2008.0,COc1cc(-c2nn(C3CCCC3)c3ncnc(N)c23)ccc1N,7.075720713938117,324.16985926,7,2,2.7814000000000005,True
+1767,CHEMBL52015,84.0,nM,1996.0,CN(C)c1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.075720713938117,342.04800858000004,4,1,4.201900000000003,True
+1768,CHEMBL121260,84.0,nM,1997.0,Clc1cccc(Nc2[nH]nc3ncnc(Nc4ccccc4)c23)c1,7.075720713938117,336.089022096,5,3,4.493500000000001,True
+1769,CHEMBL604094,84.2,nM,2010.0,O=C(CCCCCCOc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1)NO,7.074687908500351,432.13644646399996,6,3,5.000600000000004,True
+1770,CHEMBL3297999,84.4,nM,2014.0,COc1ccc(N(c2nc(C)nc3oc(C)cc23)C(C)C)cc1,7.073657553374344,311.163376912,5,0,4.394740000000003,True
+1771,CHEMBL1242664,85.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc3cc[nH]c3c1)nn2C1CCCC1,7.070581074285707,318.159294576,5,2,3.6719000000000017,True
+1772,CHEMBL1198361,85.0,nM,2012.0,Brc1cccc(Nc2ncnc3cc4c(cc23)OCCCO4)c1,7.070581074285707,371.02693878799994,5,1,4.297200000000002,True
+1773,CHEMBL419501,85.0,nM,2001.0,COC[C@H]1CCCN1C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.070581074285707,495.12698717200004,6,2,4.741400000000003,True
+1774,CHEMBL91811,85.0,nM,2001.0,CC(C)N(C)CC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.070581074285707,451.100772424,5,2,4.418000000000004,True
+1775,CHEMBL1171792,85.0,nM,2010.0,Cc1ccc(Br)c2c(C#N)cc(C(=O)C3CC3)n12,7.070581074285707,302.0054750720001,3,0,3.4746000000000024,True
+1776,CHEMBL248115,85.0,nM,2007.0,Cc1cncc(COc2ccc(Nc3ncnn4ccc(CN5CCC(N)CC5)c34)cc2Cl)c1,7.070581074285707,477.20438619600003,8,2,4.331820000000003,True
+1777,CHEMBL205870,85.0,nM,2006.0,C#Cc1cncnc1Nc1ccc(OCc2cccc(F)c2)c(Cl)c1,7.070581074285707,353.073117936,4,1,4.573000000000002,True
+1778,CHEMBL3973028,86.0,nM,2016.0,CCC(=O)Nc1cc2c(N[C@H](C)c3ccccc3)ncnc2cc1OC,7.0655015487564325,350.174275944,5,2,4.160000000000003,True
+1779,CHEMBL4225781,86.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N4CCC(N5CCOCC5)CC4)cc3OC)n2)c1,7.0655015487564325,572.285951632,9,4,4.298300000000003,True
+1780,CHEMBL202621,86.0,nM,2006.0,O=C(C#CCN1CCOCC1)Nc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,7.0655015487564325,439.12113074800004,6,2,3.4400000000000004,True
+1781,CHEMBL429827,86.0,nM,2007.0,Cc1ccn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,7.0655015487564325,354.159294576,6,1,4.179320000000002,True
+1782,CHEMBL3964380,86.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(ccn4Cc4ccco4)c3)ncnc2cc1OC,7.0655015487564325,441.180089596,7,2,5.326500000000004,True
+1783,CHEMBL3908272,86.0,nM,2016.0,O=S(=O)(Nc1ncccn1)c1ccc(Nc2nncc3ccccc23)cc1,7.0655015487564325,378.089894688,7,2,2.964200000000001,True
+1784,CHEMBL3676388,87.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(OC)c(Cl)cc3OC)ncnc2cc1OCCNC(C)=O,7.0604807473813835,485.146596548,8,3,3.6834000000000016,True
+1785,CHEMBL57758,87.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CCCC1,7.0604807473813835,416.141531844,6,1,4.649100000000003,True
+1786,CHEMBL591039,87.1,nM,2010.0,C#CCCCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,7.059981844992339,399.11498274800005,5,1,5.356800000000003,True
+1787,CHEMBL3798501,87.5,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C(C)=O)CC4)cc3OC)ncc2SC)c1,7.057991946977688,534.20492444,9,2,4.536000000000004,True
+1788,CHEMBL3676375,88.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCC(C)NC(=O)CN(C)C,7.055517327849832,578.08440666,7,3,4.498000000000004,True
+1789,CHEMBL1242662,88.0,nM,2008.0,CC(C)n1nc(-c2ccc3cc(O)ccc3c2)c2c(N)ncnc21,7.055517327849832,319.14331016400007,6,2,3.515200000000002,True
+1790,CHEMBL3970399,88.0,nM,2016.0,O=S(=O)(Nc1nccs1)c1ccc(Nc2nncc3ccccc23)cc1,7.055517327849832,383.05106665600005,7,2,3.630700000000002,True
+1791,CHEMBL251700,88.7,nM,2007.0,Fc1ccc(Nc2ncnc3ccc(C#CCN4CCCCC4)cc23)cc1Cl,7.052076380168272,394.13605254,4,1,5.003300000000004,True
+1792,CHEMBL3671539,89.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CCO,7.0506099933550885,517.076094472,7,4,3.2769000000000026,True
+1793,CHEMBL1271507,89.0,nM,2010.0,CN1CCN(C/C=C/C(=O)N2CCc3c(sc4ncnc(N[C@H](CO)c5ccccc5)c34)C2)CC1,7.0506099933550885,492.230745264,8,2,2.5251,True
+1794,CHEMBL3671529,89.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN,7.0506099933550885,502.07642882000005,7,4,2.8532,True
+1795,CHEMBL3774906,89.6,nM,2016.0,O=C1COc2cc3ncnc(Nc4cccc(Br)c4)c3cc2N1CCCN1CCOCC1,7.047691990337873,497.106251728,7,1,3.5836000000000015,True
+1796,CHEMBL592457,90.0,nM,2010.0,O=C1CSC(N/N=C/c2cc(Br)ccc2O)=N1,7.045757490560675,312.952059596,5,2,1.7076,True
+1797,CHEMBL196018,90.0,nM,2005.0,CCOC(=O)c1cn2ncnc(Nc3ccc(F)c(Cl)c3)c2c1CC,7.045757490560675,362.094581652,6,1,4.004500000000003,True
+1798,CHEMBL248044,90.0,nM,2007.0,COc1cc2ncc(C#N)c(N[C@@H]3C[C@H]3c3ccccc3)c2cc1OC,7.045757490560675,345.147726848,5,1,4.091680000000003,True
+1799,CHEMBL116853,90.0,nM,2003.0,COc1cc2ncc(C#N)c(Nc3cccc(Br)c3)c2cc1NC(=O)C#CCN(C)C,7.045757490560675,477.08003698,6,2,4.124680000000002,True
+1800,CHEMBL1945448,90.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(Cl)cc1)c1cncc(Br)c1,7.045757490560675,373.91275289600003,4,1,2.616200000000001,True
+1801,CHEMBL92731,90.0,nM,2001.0,CCCN(C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)CCC,7.045757490560675,481.147722616,5,2,5.752600000000005,True
+1802,CHEMBL327127,90.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3cccc(CO)c3)nc21,7.045757490560675,426.06503111200004,6,2,4.538200000000003,True
+1803,CHEMBL1744349,90.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OC/C=C/CN1CCCC1.Cl,7.045757490560675,478.13385962,6,1,5.627100000000006,True
+1804,CHEMBL3671504,90.0,nM,2014.0,C=CCCOc1cc2ncnc(Nc3ccc(Br)cc3F)c2cc1NC(=O)C=C,7.045757490560675,456.05971613599996,5,2,5.354400000000003,True
+1805,CHEMBL500217,90.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc5c(ccn5Cc5ccccc5)c4)c3s2)C1)N1CCOCC1,7.045757490560675,578.2100098200001,9,2,4.988700000000004,True
+1806,CHEMBL3937373,90.0,nM,2016.0,Cc1cccc2nc(NC(=O)c3cccc(C(F)(F)F)c3)n([C@H]3CC[C@H](O)CC3)c12,7.045757490560675,417.16641160399996,4,2,5.091820000000005,True
+1807,CHEMBL231875,90.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(CN6CCNCC6)c45)ccc32)c1,7.045757490560675,456.21862102000006,8,2,3.4152000000000013,True
+1808,CHEMBL3325477,90.0,nM,2014.0,CCOC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2ccccc2n2nnnc12,7.045757490560675,481.1862375960001,10,1,3.0168000000000017,True
+1809,CHEMBL602728,90.0,nM,2010.0,O=C(Nc1cccc2ccccc12)c1ccc(N(CCCl)CCCl)cc1,7.045757490560675,386.09526862,2,1,5.376100000000004,True
+1810,CHEMBL394333,90.0,nM,2007.0,NCCOCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,7.045757490560675,431.18698654400004,8,2,3.4853000000000005,True
+1811,CHEMBL3297896,90.2,nM,2014.0,Cc1nc(Nc2cccc3[nH]ccc23)c2cc(C)oc2n1,7.044793462458057,278.116761068,4,2,4.064540000000002,True
+1812,CHEMBL3403510,90.3,nM,2015.0,COc1ccc(N(C)c2nc(C)nc3oc(C)cc23)cc1OC,7.044312249686494,313.14264146799997,6,0,3.6247400000000027,True
+1813,CHEMBL3753208,90.57,nM,2016.0,O=C(Nc1ccccn1)Nc1cc(-c2cccnc2)ccc1OC(F)(F)F,7.04301563225724,374.099060316,4,2,4.686200000000001,True
+1814,CHEMBL398154,90.8,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OCc4ccccn4)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,7.041914151478915,528.2121179960001,10,2,3.028100000000001,True
+1815,CHEMBL1272167,91.0,nM,2010.0,C=CS(=O)(=O)N1CCc2c(sc3ncnc(N[C@H](CO)c4ccccc4)c23)C1,7.040958607678906,416.09768249999996,7,2,2.6682000000000006,True
+1816,CHEMBL205765,91.0,nM,2006.0,CC(=O)Nc1cccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)n1,7.040958607678906,487.12113074800004,6,2,5.3449000000000035,True
+1817,CHEMBL3671509,91.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=S)NCC,7.040958607678906,532.0692352640001,6,4,4.262300000000002,True
+1818,CHEMBL4093766,91.8,nM,2017.0,C=CC(=O)N1CC[C@H](n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)C1,7.037157318798758,503.26448791600006,9,1,2.56332,True
+1819,CHEMBL4241638,92.5,nM,2018.0,CCN(c1ccc(OC)cc1)c1ncnc2occ(C)c12,7.033858267260968,283.132076784,5,0,3.6978200000000028,True
+1820,CHEMBL3981621,93.0,nM,2016.0,c1ccc(CNc2ncnc3oc(-c4ccccc4)cc23)cc1,7.031517051446066,301.1215121,4,1,4.501900000000003,True
+1821,CHEMBL460732,93.0,nM,2004.0,CS(=O)(=O)CCNCCCCOc1ccc2ncnc(Nc3ccc(S(=O)(=O)c4ccccc4)cc3)c2c1,7.031517051446066,554.16576206,9,2,3.9994000000000023,True
+1822,CHEMBL3233781,93.0,nM,2014.0,CN(C)CCCN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.031517051446066,476.15613635200003,7,2,4.6056000000000035,True
+1823,CHEMBL293064,93.0,nM,2001.0,CCN(CC)CCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,7.031517051446066,418.15718190800004,6,1,4.895100000000004,True
+1824,CHEMBL2425091,94.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CC(OC)C1,7.0268721464003026,432.13644646399996,7,1,3.8839000000000024,True
+1825,CHEMBL3919183,94.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(cnn4Cc4ccccn4)c3)ncnc2cc1OC,7.0268721464003026,453.1913229760001,8,2,4.523500000000002,True
+1826,CHEMBL3671558,94.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OC1CCN(C(C)=O)C1,7.0268721464003026,513.081179852,6,2,4.399100000000004,True
+1827,CHEMBL306732,94.0,nM,2004.0,CN(C)c1ccc(Nc2ncnc3cc(-c4ccccc4)sc23)cc1,7.0268721464003026,346.125217576,5,1,5.167900000000003,True
+1828,CHEMBL399928,94.5,nM,2007.0,CC(O)C#Cc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,7.0245681914907365,341.073117936,4,2,3.898200000000002,True
+1829,CHEMBL4291900,94.7,nM,2017.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OCCN4CCOCC4)cc3)ncc2Cl)c1,7.023650020996727,494.18331640400004,8,3,4.452700000000004,True
+1830,CHEMBL3752825,94.82,nM,2016.0,Cn1cnc(-c2ccc(OC(F)(F)F)c(NC(=O)Nc3ccncc3)c2)c1,7.023100049017062,377.109959348,5,2,4.024700000000001,True
+1831,CHEMBL328977,95.0,nM,2001.0,O=C(C#CCN1CCSCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.022276394711152,481.05719336000004,6,2,4.126600000000002,True
+1832,CHEMBL1914661,95.0,nM,2011.0,Br.Cc1cccc(C(C)Nc2ncnc3[nH]c(-c4ccc(O)cc4)cc23)c1,7.022276394711152,424.089873392,4,3,5.389920000000004,True
+1833,CHEMBL1744086,95.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OC[C@@H](O)CN1CCOCC1,7.022276394711152,462.14701114799993,8,2,3.246400000000002,True
+1834,CHEMBL7827,95.0,nM,1999.0,O=c1c(-c2cccc(Cl)c2)coc2cc(O)cc(O)c12,7.022276394711152,288.01893644800003,4,2,3.524600000000001,True
+1835,CHEMBL332971,96.0,nM,1997.0,COc1ccc(-c2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,7.017728766960431,351.088687748,5,2,4.425500000000002,True
+1836,CHEMBL3671503,96.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC,7.017728766960431,459.0706151680001,6,3,3.9977000000000027,True
+1837,CHEMBL307209,96.0,nM,1996.0,Clc1cccc(Nc2ncnc3[nH]c(-c4ccccc4)c(-c4ccccc4)c23)c1,7.017728766960431,396.114174224,3,2,6.688900000000004,True
+1838,CHEMBL4288482,96.6,nM,2017.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(CC(=O)N4CCOCC4)cc3)ncc2Cl)c1,7.015022873584505,492.16766634000004,7,3,4.1430000000000025,True
+1839,CHEMBL92961,97.0,nM,2001.0,CC(C)N(CC#CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)C(C)C,7.013228265733755,479.132072552,5,2,5.196600000000004,True
+1840,CHEMBL249927,97.0,nM,2007.0,O=C(CO)N1CCC[C@@H]1COc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12,7.013228265733755,519.1673319920001,8,2,4.362900000000003,True
+1841,CHEMBL3805588,97.18,nM,2016.0,FC(F)(F)c1cccc(Nc2ncnc3cc(OCCCN4CCOCC4)c4c(c23)OCCO4)c1,7.0124231052730135,490.18278993999996,8,1,4.2645000000000035,True
+1842,CHEMBL3753886,97.22,nM,2016.0,O=C(Nc1ccncc1)Nc1cc(-c2cccnc2)ccc1OC(F)(F)F,7.012244383261478,374.099060316,4,2,4.686200000000001,True
+1843,CHEMBL56142,98.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CCCCC1,7.008773924307505,430.157181908,6,1,5.039200000000005,True
+1844,CHEMBL4177348,98.0,nM,2018.0,O=C(CN1CCOCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,7.008773924307505,441.08003698000005,6,2,3.406600000000001,True
+1845,CHEMBL3671541,98.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(=O)OCC,7.008773924307505,545.071009092,8,3,3.457600000000002,True
+1846,CHEMBL2070198,98.0,nM,2012.0,Brc1cccc(Nc2ncnc3ccc(NCc4ccc5c(c4)OCCCO5)cc23)c1,7.008773924307505,476.084788012,6,2,5.909300000000003,True
+1847,CHEMBL4084249,98.0,nM,2017.0,COc1ccc(-c2nnc(Cc3nc4ccccc4[nH]3)o2)cc1,7.008773924307505,306.111675688,5,1,3.212300000000001,True
+1848,CHEMBL3671553,98.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OC[C@H](C)NC(C)=O,7.008773924307505,501.08117985200005,6,3,4.302900000000004,True
+1849,CHEMBL3676381,98.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)OC,7.008773924307505,537.021472056,7,3,4.787700000000003,True
+1850,CHEMBL14932,98.0,nM,2004.0,Oc1ccc2ncnc(Nc3ccc(OCc4ccccc4)cc3)c2c1,7.008773924307505,343.132076784,5,2,4.658000000000003,True
+1851,CHEMBL3671508,98.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=S)NC,7.008773924307505,518.0535852000002,6,4,3.872200000000002,True
+1852,CHEMBL3633928,99.0,nM,2015.0,NC(=O)Nc1ccc2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2c1,7.00436480540245,437.10548068400004,5,3,5.235500000000003,True
+1853,CHEMBL3775112,99.0,nM,2016.0,O=C1COc2cc3ncnc(Nc4cccc(Br)c4)c3cc2N1CCCN1CCCCC1,7.00436480540245,495.12698717200004,6,1,4.737300000000004,True
+1854,CHEMBL596761,99.4,nM,2010.0,COc1cc2ncnc(NCc3ccccc3)c2cc1OCCCCCCC(=O)NO,7.002613615602686,424.21105537599993,7,3,4.085200000000002,True
+1855,CHEMBL2309507,100.0,nM,2008.0,COc1cc2ncnc(N[C@H](C)c3ccc(Cl)cc3)c2cc1OCCCCCCC(=O)NO,7.0,472.18773308799996,7,3,5.299600000000003,True
+1856,CHEMBL3975990,100.0,nM,2008.0,C#Cc1cccc(Nc2ncnc3ccc(OCCCCCCC(=O)NO)cc23)c1,7.0,404.18484062799996,6,3,4.189400000000002,True
+1857,CHEMBL3924787,100.0,nM,2008.0,C[C@@H](Nc1ncnc2ccc(OCCCCCC(=O)NO)cc12)c1ccccc1,7.0,394.20049069199996,6,3,4.247500000000003,True
+1858,CHEMBL3984008,100.0,nM,2008.0,C[C@@H](Nc1ncnc2ccc(OCCCCCCC(=O)NO)cc12)c1ccccc1,7.0,408.21614075599996,6,3,4.6376000000000035,True
+1859,CHEMBL133024,100.0,nM,2003.0,C/N=N/Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,7.0,312.089022096,5,2,4.435700000000002,True
+1860,CHEMBL53404,100.0,nM,1996.0,CC(=O)Nc1cc2ncnc(NCc3ccccc3)c2cn1,7.0,293.12766010000007,5,2,2.5953,True
+1861,CHEMBL2309506,100.0,nM,2008.0,COc1cc2ncnc(N[C@H](C)c3ccc(F)cc3)c2cc1OCCCCCCC(=O)NO,7.0,456.21728362799996,7,3,4.785300000000003,True
+1862,CHEMBL188304,100.0,nM,2004.0,Cc1ccn2ncnc(Nc3ccc(F)c(Cl)c3)c12,7.0,276.05780222,4,1,3.5738200000000013,True
+1863,CHEMBL3914607,100.0,nM,2008.0,COc1cc2ncnc(NCc3ccc(F)c(F)c3)c2cc1OCCCCCCC(=O)NO,7.0,460.19221175199993,7,3,4.363400000000002,True
+1864,CHEMBL3917951,100.0,nM,2008.0,COc1cc2ncnc(NCCc3ccccc3)c2cc1OCCCCCCC(=O)NO,7.0,438.22670543999993,7,3,4.127700000000003,True
+1865,CHEMBL3979482,100.0,nM,2008.0,C#Cc1cccc(Nc2ncnc3ccc(OCCCC(=O)NO)cc23)c1,7.0,362.13789043599996,6,3,3.0191,True
+1866,CHEMBL3906200,100.0,nM,2008.0,COc1cc2ncnc(NCc3cccc(Br)c3)c2cc1OCCCCCCC(=O)NO,7.0,502.12156744399994,7,3,4.847700000000003,True
+1867,CHEMBL3950023,100.0,nM,2008.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(NC(=O)CCNCC(=O)NO)cc3)cc12)c1ccccc1,7.0,473.217537724,7,6,3.2216000000000014,True
+1868,CHEMBL3917105,100.0,nM,2008.0,O=C(CCCCCN1CCN(Cc2ccc(-c3cc4c(NCc5ccccc5)ncnc4[nH]3)cc2)CC1)NO,7.0,527.3008734240001,7,4,4.4204000000000025,True
+1869,CHEMBL3914322,100.0,nM,2008.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(OCCCCCCC(=O)NO)cc3)cc12)c1ccc(F)cc1,7.0,491.23326804,6,4,5.771800000000004,True
+1870,CHEMBL3985004,100.0,nM,2008.0,O=C(CCCCCCOc1ccc(-c2cc3c(NCc4ccccc4)ncnc3[nH]2)cc1)NO,7.0,459.2270397880001,6,4,5.071700000000003,True
+1871,CHEMBL80302,100.0,nM,2004.0,Cc1cc2cc(Nc3ncnc4cc(-c5ccccc5)sc34)ccc2[nH]1,7.0,356.109567512,4,2,5.891620000000002,True
+1872,CHEMBL3912598,100.0,nM,2008.0,C#Cc1cccc(Nc2ncnc3ccc(OCCCCCC(=O)NO)cc23)c1,7.0,390.16919056399996,6,3,3.7993000000000015,True
+1873,CHEMBL2325092,100.0,nM,2013.0,COc1ccc(C2=NN(c3ccccc3)C(c3cccc4ccccc34)C2)cc1,7.0,378.17321332399996,3,0,6.204100000000005,True
+1874,CHEMBL3909214,100.0,nM,2008.0,O=C(CCCOc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1)NO,7.0,390.08949627199996,6,3,3.830300000000002,True
+1875,CHEMBL388978,100.0,nM,1994.0,CN[C@@H]1C[C@H]2O[C@@](C)([C@@H]1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,7.0,466.200490692,6,2,4.354000000000003,True
+1876,CHEMBL542729,100.0,nM,1997.0,COc1ccc2ncnc(Nc3cc(OC)c(OC)c(OC)c3)c2c1.Cl,7.0,377.11423379999997,7,1,3.8296000000000032,True
+1877,CHEMBL1202477,100.0,nM,2002.0,COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCCN1CCN(C)CC1.Cl,7.0,539.1098931360001,7,1,4.721700000000006,True
+1878,CHEMBL2448067,100.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCCN1CCCC1.Cl,7.0,466.13385962,6,1,5.461000000000006,True
+1879,CHEMBL330224,100.0,nM,1996.0,Nc1ccc2c(Nc3ccccc3)ncnc2c1,7.0,236.106196384,4,2,2.9556000000000013,True
+1880,CHEMBL490577,100.0,nM,1992.0,N#C/C(=C/c1ccc(O)c(O)c1)C(=O)NCCCCc1ccccc1,7.0,336.1473925,4,3,3.143880000000001,True
+1881,CHEMBL1907944,100.0,nM,2002.0,COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OC[C@H]1CCCN(C)C1,7.0,474.1066663280001,6,1,5.004200000000005,True
+1882,CHEMBL247309,100.0,nM,2007.0,CN(C)C1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,7.0,498.26557121200005,8,1,4.536000000000003,True
+1883,CHEMBL555201,100.0,nM,1997.0,COc1cc2ncnc(Nc3ccc(O)cc3)c2cc1OC.Cl,7.0,333.088019052,6,2,3.518000000000002,True
+1884,CHEMBL286160,100.0,nM,2002.0,COCCOc1cc2ncnc(Nc3ccc(Cl)cc3F)c2cc1OC,7.0,377.094247304,6,1,4.1997000000000035,True
+1885,CHEMBL1928311,100.0,nM,2012.0,O=C(c1cc2cc(O)ccc2[nH]1)c1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,7.0,438.035352524,6,3,5.645300000000002,True
+1886,CHEMBL2448066,100.0,nM,2002.0,COc1cc2c(Nc3cc(O)c(Cl)cc3F)ncnc2cc1OCC1CCN(C)CC1.Cl,7.0,482.12877424000004,7,2,5.022500000000004,True
+1887,CHEMBL24137,100.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCCN1CCOCC1,7.0,446.15209652799996,7,1,4.275600000000004,True
+1888,CHEMBL1907763,100.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OC[C@@H]1CCCN(C)C1,7.0,430.157181908,6,1,4.895100000000005,True
+1889,CHEMBL57892,100.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCNC(C)(C)C,7.0,418.157181908,6,2,4.941400000000003,True
+1890,CHEMBL56543,100.0,nM,1999.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCc1ccccc1,7.0,294.100442308,4,3,2.32118,True
+1891,CHEMBL3622624,100.1,nM,2015.0,C=CC(=O)Nc1cc2c(Nc3ccc(OCc4ccccn4)cc3)ncnc2cc1O[C@H]1CCOC1,6.999565922520682,483.19065428000005,8,2,4.639600000000002,True
+1892,CHEMBL4277822,100.5,nM,2017.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(CC(=O)N4CCOCC4)cc3)ncc2Cl)c1,6.997833938243492,493.15168192799996,7,2,4.191700000000003,True
+1893,CHEMBL4229266,101.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(C(=O)N(CC)CC)cc3OC)n2)c1,6.995678626217357,503.22810240800004,7,4,4.479300000000003,True
+1894,CHEMBL3671542,102.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(=O)O,6.991399828238082,517.0397089639999,7,4,2.9791000000000007,True
+1895,CHEMBL2179128,102.0,nM,2017.0,Fc1ccc(-c2nc(-c3ccccc3)[nH]c2-c2ccnc3[nH]c(-c4ccccc4)cc23)cc1,6.991399828238082,430.15937482800007,2,2,7.093100000000005,True
+1896,CHEMBL4079183,102.0,nM,2017.0,O=c1c2ccc(Cl)cc2nc(-c2ccccc2)n1-c1nnc(C2CC2)s1,6.991399828238082,380.0498597160001,6,0,4.435000000000002,True
+1897,CHEMBL3403518,102.2,nM,2015.0,Cc1nc(N(C)c2ccc(OC(C)C)cc2)c2cc(C)oc2n1,6.990549104201306,311.16337691200005,5,0,4.394740000000003,True
+1898,CHEMBL3297895,102.3,nM,2014.0,Cc1nc(Nc2ccc(Cl)cc2)c2cc(C)oc2n1,6.99012436628784,273.066889684,4,1,4.236640000000002,True
+1899,CHEMBL3622634,102.3,nM,2015.0,COCCOc1cc2ncnc(Nc3ccc(NC(=O)/C=C/CN(C)C)c(C(F)(F)F)c3)c2cc1NC(=O)/C=C/CN(C)C,6.99012436628784,615.2780872919999,9,3,4.530000000000004,True
+1900,CHEMBL3805177,102.6,nM,2016.0,CC(C)Oc1cc2ncnc(Nc3ccc(Cl)c([N+](=O)[O-])c3)c2c2c1OCCO2,6.988852639224203,416.08874732399994,8,1,4.493400000000003,True
+1901,CHEMBL3753623,102.93,nM,2016.0,COc1ccc(-c2ccc(OC(F)(F)F)c(NC(=O)Nc3ccncc3)c2)cn1,6.987458027224164,404.1096250000001,5,2,4.6948000000000025,True
+1902,CHEMBL3403515,103.2,nM,2015.0,COc1ccc2c(c1)CCN2c1nc(C)nc2oc(C)cc12,6.986320302708808,295.132076784,5,0,3.5424400000000027,True
+1903,CHEMBL256527,104.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2ccc(F)cc2)c1,6.982966660701218,391.155686416,8,2,3.3198000000000025,True
+1904,CHEMBL401713,104.0,nM,2008.0,COc1cc(Nc2ncnc3[nH]nc(OCCN4CCC(O)CC4)c23)ccc1OCc1ccccn1,6.982966660701218,491.228102408,10,3,2.914600000000001,True
+1905,CHEMBL14952,104.0,nM,2004.0,CS(=O)(=O)CCNCCCOc1ccc2ncnc(Nc3ccc(OCc4ccccc4)cc3)c2c1,6.982966660701218,506.19877644,8,2,4.355500000000003,True
+1906,CHEMBL3622626,104.7,nM,2015.0,C=CC(=O)Nc1cc2c(Nc3ccc(Cl)c(C(F)(F)F)c3)ncnc2cc1O[C@H]1CCOC1,6.980053318321158,478.101952776,6,2,5.337800000000003,True
+1907,CHEMBL333082,105.0,nM,1995.0,Nc1cccc2c(Nc3cccc(Br)c3)ncnc12,6.978810700930063,314.01670845200005,4,2,3.7181000000000015,True
+1908,CHEMBL4278997,105.0,nM,2018.0,O=C(O)CCCC(=O)Nc1cc(Nc2ccccc2)ncn1,6.978810700930063,300.122240372,5,3,2.4136000000000006,True
+1909,CHEMBL318736,105.0,nM,1996.0,CCCCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCCCC,6.978810700930063,443.12083917199993,5,1,6.493700000000005,True
+1910,CHEMBL94068,106.0,nM,2001.0,O=C(/C=C/CN1CCCCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.9746941347352305,465.116422488,5,2,5.116500000000004,True
+1911,CHEMBL214631,106.0,nM,2006.0,COc1cc2ncnc(Nc3cc(Cl)ccc3F)c2cc1OC1CCN(C)CC1,6.9746941347352305,416.141531844,6,1,4.6475000000000035,True
+1912,CHEMBL608860,106.0,nM,2010.0,CCCCCCOc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC,6.9746941347352305,403.14628287600004,5,1,6.133600000000005,True
+1913,CHEMBL94066,107.0,nM,2001.0,C=C(CN1CCOCC1)C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.97061622231479,467.09568704400004,6,2,3.9628000000000014,True
+1914,CHEMBL241918,107.3,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OCc4cccc(OC)c4)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,6.969400278034049,557.227433712,10,2,3.641700000000002,True
+1915,CHEMBL3416597,108.0,nM,2015.0,COc1ccccc1-c1cc2c(NCc3ccncc3)ncnc2s1,6.966576244513051,348.10448213200004,6,1,4.374000000000001,True
+1916,CHEMBL1928946,108.0,nM,2012.0,CC(=O)Nc1cccc(Oc2cc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)ncn2)c1,6.966576244513051,478.1207964000001,6,2,6.342400000000004,True
+1917,CHEMBL4284841,108.0,nM,2018.0,COc1ccc(C2=C(C#N)C3=NC4=Nc5ccc(S(=O)(=O)N6CCOCC6)cc5C4=NC3C(O)=C2C#N)cc1,6.966576244513051,540.12158874,10,1,2.6986600000000003,True
+1918,CHEMBL140561,108.0,nM,2001.0,CN(C)CCCOC(=O)/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.966576244513051,497.1062517280001,7,2,4.125500000000002,True
+1919,CHEMBL3416635,109.0,nM,2015.0,Fc1cccc(COc2ccc(Nc3ncnc4sc(C#CC5CCCN5)cc34)cc2Cl)c1,6.962573502059376,478.10303816,6,2,5.909900000000003,True
+1920,CHEMBL495979,109.0,nM,2008.0,Fc1cccc(COc2ccc(Nc3ncnc4cc(C#C[C@@H]5CCCN5)sc34)cc2Cl)c1,6.962573502059376,478.10303816000004,6,2,5.909900000000003,True
+1921,CHEMBL3671516,109.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1SCCNC(C)=O,6.962573502059376,503.0426861680001,6,3,4.627700000000003,True
+1922,CHEMBL3622658,109.4,nM,2015.0,O=C(/C=C/CN1CC[S+]([O-])CC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.960982678002588,559.145631244,8,2,3.8926000000000016,True
+1923,CHEMBL202721,110.0,nM,2017.0,COc1cc2c(Nc3ccc(NC(=O)c4ccccc4)cc3)ncnc2cc1OCCCN1CCOCC1,6.9586073148417755,513.237604472,8,2,4.735400000000003,True
+1924,CHEMBL391521,110.0,nM,2007.0,CN(CCO)Cc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,6.9586073148417755,445.20263660800003,8,2,3.434100000000001,True
+1925,CHEMBL4099254,110.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(C3CC3)c3c(N)ncnc32)C1,6.9586073148417755,312.16985926,6,1,1.6354,True
+1926,CHEMBL74481,110.0,nM,1996.0,Cc1ccc(Nc2ncnc3[nH]c4c(c23)CCCC4)cc1,6.9586073148417755,278.153146576,3,2,3.888720000000002,True
+1927,CHEMBL392664,110.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(CNC6CCNCC6)c45)ccc32)c1,6.9586073148417755,470.23427108400006,8,3,3.851600000000002,True
+1928,CHEMBL2348419,110.0,nM,2013.0,COC(=O)C1=Cc2c(ncnc2Nc2ccc(Oc3cccc(C(F)(F)F)c3)c(Cl)c2)NCC1,6.9586073148417755,490.101952776,7,2,6.056700000000003,True
+1929,CHEMBL185637,110.0,nM,2004.0,Fc1ccc(Nc2ncnn3cccc23)cc1Cl,6.9586073148417755,262.042152156,4,1,3.2654000000000014,True
+1930,CHEMBL2325097,110.0,nM,2013.0,Clc1ccc(C2=NN(c3ccccc3)C(c3ccc4ccccc4c3)C2)cc1,6.9586073148417755,382.123676288,2,0,6.848900000000005,True
+1931,CHEMBL247513,110.0,nM,2007.0,O=C(CO)NC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.9586073148417755,528.2397503880001,9,3,3.0829000000000004,True
+1932,CHEMBL4166412,110.0,nM,2017.0,NS(=O)(=O)c1ccc(-n2c(SCC(=O)Nc3cnc4ccccc4c3)nc3cc4ccccc4cc3c2=O)cc1,6.9586073148417755,567.103496152,8,2,4.465300000000004,True
+1933,CHEMBL578255,111.0,nM,2009.0,CCC1=C2C(Nc3ccc4c(cnn4Cc4ccccc4)c3)=NC=NC2N=C1NC(=O)OCCN1CCOCC1,6.954677021213343,540.2597368840001,10,2,3.440100000000002,True
+1934,CHEMBL2011291,113.0,nM,2012.0,Nc1c(-c2ccc(F)cc2)c(-c2ccncc2)nn1-c1c(Cl)cc(Cl)cc1Cl,6.946921556516581,432.011157644,4,1,6.282800000000002,True
+1935,CHEMBL92709,113.0,nM,1996.0,COc1cc2ncnc(Nc3cc(Br)cc(Br)c3)c2cc1OC,6.946921556516581,436.937450856,5,1,4.915600000000002,True
+1936,CHEMBL3297816,113.2,nM,2014.0,Cc1nc(Nc2ccccc2)c2cc(C)oc2n1,6.946153573147748,239.105862036,4,1,3.5832400000000018,True
+1937,CHEMBL215559,114.0,nM,2006.0,COCCN1CCC(Oc2cc3c(Nc4cc(Cl)ccc4F)ncnc3cc2OC)CC1,6.943095148663526,460.167746592,7,1,4.664100000000003,True
+1938,CHEMBL1683966,114.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1/C=C/C(=O)NCCN1CCOCC1,6.943095148663526,525.194295688,7,2,4.361720000000004,True
+1939,CHEMBL251291,114.2,nM,2007.0,OCCCC#Cc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,6.9423338960901715,355.088768,4,2,4.289900000000003,True
+1940,CHEMBL2437486,115.0,nM,2013.0,CN(C)C/C=C/C(=O)Nc1cccc(-n2c(=O)cnc3cnc(Nc4ccccc4)nc32)c1,6.939302159646387,441.1913229760001,8,2,2.975600000000001,True
+1941,CHEMBL475600,115.0,nM,2009.0,Fc1cccc(COc2ccc(Nc3ncnc4sc(-c5ccc[nH]5)cc34)cc2Cl)c1,6.939302159646387,450.071738032,5,2,6.801500000000003,True
+1942,CHEMBL92902,115.0,nM,2001.0,CN1CCC=C(C(=O)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)C1,6.939302159646387,437.08512236,5,2,4.336300000000002,True
+1943,CHEMBL3622619,115.1,nM,2015.0,C=CC(=O)Nc1cc2c(Nc3ccc(NC(=O)C=C)c(C(F)(F)F)c3)ncnc2cc1OCCOC,6.938924676370207,501.16238884399996,7,3,4.666400000000004,True
+1944,CHEMBL3775536,115.9,nM,2016.0,O=C1COc2cc3ncnc(Nc4cccc(Cl)c4)c3cc2N1CCCN1CCCCC1,6.935916564036404,451.17750275200007,6,1,4.628200000000003,True
+1945,CHEMBL3925158,116.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(OCc4ccccn4)cc3)ncnc2cc1OC,6.935542010773082,429.1800895960001,7,2,4.704500000000002,True
+1946,CHEMBL165228,117.0,nM,1998.0,Cc1nc(Nc2cccc(Br)c2)c2cc(NCCN3CCOCC3)ncc2n1,6.931814138253838,442.11167145600007,7,2,3.583420000000002,True
+1947,CHEMBL3234744,120.0,nM,2014.0,CNc1ncc(C(=O)Nc2cc(C(=O)Nc3ccc(CN4CCN(C)CC4)c(C(F)(F)F)c3)ccc2C)cn1,6.920818753952375,541.2413078600001,7,3,4.097520000000004,True
+1948,CHEMBL376967,120.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN(CCN(C)C)[C@@H](C)C(N)=O,6.920818753952375,474.19463003600004,7,2,3.411900000000002,True
+1949,CHEMBL394495,120.0,nM,2007.0,C[C@H](c1ccccc1)n1ncc2cc(Nc3ncnn4ccc(COC[C@@H]5CNCCO5)c34)ccc21,6.920818753952375,483.238273168,9,2,3.9369000000000023,True
+1950,CHEMBL4065503,120.0,nM,2017.0,Cc1nnc(NC(=S)Nc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)s1,6.920818753952375,427.044063128,7,3,4.9956200000000015,True
+1951,CHEMBL246276,120.0,nM,2007.0,OCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,6.920818753952375,388.144787384,7,2,3.5023000000000017,True
+1952,CHEMBL3263380,120.0,nM,2014.0,Cc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc4ccccc4c3)C2)cc1C,6.920818753952375,399.140533292,4,0,5.237140000000005,True
+1953,CHEMBL3235202,120.0,nM,2014.0,COc1ccc(Oc2nc3ccc(C)cc3cc2/C=N/NC(=O)Cn2c([N+](=O)[O-])cnc2C)cc1,6.920818753952375,474.165167804,9,1,3.9075400000000027,True
+1954,CHEMBL4069586,120.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(C#CCC3CCCC3)c3c(N)ncnc32)C1,6.920818753952375,378.21680945200006,6,1,2.689800000000001,True
+1955,CHEMBL1812572,120.0,nM,2011.0,O=C(/C=C/c1cccc([N+](=O)[O-])c1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.920818753952375,489.0436514720001,6,2,5.696000000000002,True
+1956,CHEMBL92398,120.0,nM,1996.0,COc1ccc2c(Nc3ccccc3)ncnc2c1,6.920818753952375,251.105862036,4,1,3.3820000000000006,True
+1957,CHEMBL2325099,120.0,nM,2013.0,COc1ccc(C2=NN(c3ccccc3)C(c3ccc4ccccc4c3)C2)cc1,6.920818753952375,378.17321332399996,3,0,6.204100000000006,True
+1958,CHEMBL4072986,120.0,nM,2017.0,S=C(Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1)Nc1ncc(Cl)s1,6.920818753952375,445.994191744,6,3,5.945600000000002,True
+1959,CHEMBL2064403,120.0,nM,2012.0,O=c1oc2cc3ncnc(Nc4ccc5[nH]ncc5c4)c3cc2n1CCCN1CCOCC1,6.920818753952375,445.18623759600007,9,2,2.879900000000001,True
+1960,CHEMBL604042,120.0,nM,2010.0,Oc1ccc(CN(Cc2cccc(Br)c2O)C(=S)Nc2ccccc2)cc1,6.920818753952375,442.035060948,3,3,5.2595000000000045,True
+1961,CHEMBL343722,120.0,nM,2001.0,C=C=CC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.920818753952375,380.027273136,4,2,4.415500000000002,True
+1962,CHEMBL196925,120.0,nM,2005.0,CCOC(=O)c1cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2c1CC,6.920818753952375,440.19607400800004,8,1,4.610000000000004,True
+1963,CHEMBL425738,120.0,nM,2005.0,CCOC(=O)c1cc2c(Nc3ccc4c(cnn4Cc4ccccc4)c3)ncnn2c1,6.920818753952375,412.16477388000004,8,1,4.047600000000002,True
+1964,CHEMBL194958,120.0,nM,2005.0,CCc1c(C(N)=O)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,6.920818753952375,411.18075829200006,7,2,3.5322000000000022,True
+1965,CHEMBL55150,120.0,nM,1996.0,CN(C)c1ccc2ncncc2c1,6.920818753952375,173.095297352,3,0,1.6957999999999998,True
+1966,CHEMBL2087352,120.0,nM,2012.0,Brc1cccc(Nc2ncnc3cc4c(cc23)Oc2ccccc2O4)c1,6.920818753952375,405.01128872399994,5,1,6.033900000000002,True
+1967,CHEMBL3753811,121.09,nM,2016.0,O=C(Nc1nccs1)Nc1cc(-c2cccnc2)ccc1OC(F)(F)F,6.916891720805265,380.055481252,5,2,4.747700000000001,True
+1968,CHEMBL3622630,121.1,nM,2015.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1O[C@H]1CCOC1,6.916855856856947,472.054630756,6,2,4.567200000000003,True
+1969,CHEMBL3933895,122.0,nM,2016.0,CCOc1cc2ncnc(Nc3ccc4c(ccn4S(=O)(=O)c4ccccc4)c3)c2cc1NC(=O)/C=C/CN1CCOCC1,6.9136401693252525,612.215489124,10,2,4.790700000000003,True
+1970,CHEMBL3297893,122.1,nM,2014.0,Cc1nc(Nc2ccc(C(F)(F)F)cc2)c2cc(C)oc2n1,6.913284336055117,307.093246664,4,1,4.602040000000002,True
+1971,CHEMBL4082763,123.4,nM,2017.0,C=CC(=O)Nc1cc(Nc2cc(-c3cn(C)c4ccccc34)nc(OC)n2)c(OC)cc1N(C)CCN(C)C,6.908684840302778,529.2801379800001,9,2,4.518400000000003,True
+1972,CHEMBL3233789,124.0,nM,2014.0,CN1CCN(C/C=C/C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3s2)CC1,6.9065783148377635,460.12483622400003,7,2,3.969500000000002,True
+1973,CHEMBL53121,124.0,nM,1996.0,Fc1cc2c(Nc3cccc(Br)c3)ncnc2cn1,6.9065783148377635,317.991636576,4,1,3.670000000000001,True
+1974,CHEMBL4283097,125.0,nM,2018.0,COc1ccc(OC)c(Nc2cc(NCCc3cccs3)ncn2)c1,6.903089986991943,356.1306968800001,7,2,3.953500000000002,True
+1975,CHEMBL76589,125.0,nM,1989.0,N#CC(C#N)=C(N)/C(C#N)=C/c1ccc(O)cc1,6.903089986991943,236.069810876,5,2,1.55914,True
+1976,CHEMBL3671530,125.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(C)N(C)C,6.903089986991943,544.1233790120001,7,3,3.8446000000000025,True
+1977,CHEMBL3671578,125.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1=NCCO1,6.903089986991943,485.04987972400005,7,2,4.207000000000003,True
+1978,CHEMBL598406,125.6,nM,2010.0,COc1cc2ncnc(N[C@@H](C)c3ccc(F)cc3)c2cc1OCCCCCCC(=O)NO,6.901010360598823,456.21728362799996,7,3,4.785300000000003,True
+1979,CHEMBL3676380,126.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(CO)N(C)C,6.899629454882437,560.1182936320001,8,4,2.817000000000001,True
+1980,CHEMBL29641,126.7,nM,2013.0,COc1cc2ncnc(Nc3cccc(SC)c3)c2cc1OC,6.897223385116559,327.10414778399996,6,1,4.112500000000003,True
+1981,CHEMBL2333991,126.7,nM,2013.0,COc1cc2ncnc(Nc3cccc(-c4ccccc4)c3)c2cc1OC,6.897223385116559,357.147726848,5,1,5.057600000000003,True
+1982,CHEMBL249509,126.9,nM,2007.0,C#Cc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,6.896538377905295,297.046903188,3,1,4.1472000000000016,True
+1983,CHEMBL3981041,127.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(ccn4S(=O)(=O)c4ccccc4)c3)ncnc2cc1OC,6.896196279044043,501.14707521599996,8,2,4.922200000000003,True
+1984,CHEMBL3671559,128.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OC1CCCN(C(C)=O)C1,6.892790030352131,527.096829916,6,2,4.789200000000005,True
+1985,CHEMBL4228848,128.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(C(=O)N4CCOCC4)cc3OC)n2)c1,6.892790030352131,517.207366964,8,4,3.4697000000000013,True
+1986,CHEMBL3671521,128.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(C)C,6.892790030352131,515.096829916,6,3,4.550500000000004,True
+1987,CHEMBL92174,128.0,nM,1996.0,COc1cc2ncnc(Nc3ccccc3Br)c2cc1OC,6.892790030352131,359.02693878799994,5,1,4.153100000000003,True
+1988,CHEMBL606403,129.0,nM,2010.0,CC(C)c1nsc(C(=O)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)n1,6.889410289700751,468.0367922640001,7,2,5.363100000000003,True
+1989,CHEMBL120069,130.0,nM,1997.0,Cc1cccc(Nc2[nH]cnc3nnc(Nc4cccc(Cl)c4)c2-3)c1,6.886056647693162,350.10467216,5,3,4.753520000000003,True
+1990,CHEMBL120319,130.0,nM,1997.0,Clc1cccc(Nc2[nH]nc3ncnc(Nc4cccc(Br)c4)c23)c1,6.886056647693162,413.999534164,5,3,5.256000000000001,True
+1991,CHEMBL3234745,130.0,nM,2014.0,CCNc1ncc(C(=O)Nc2cc(C(=O)Nc3ccc(CN4CCN(C)CC4)c(C(F)(F)F)c3)ccc2C)cn1,6.886056647693162,555.2569579240001,7,3,4.487620000000004,True
+1992,CHEMBL1173815,130.0,nM,2010.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccc(O)cc3)C2)cc1C,6.886056647693162,325.124883228,3,2,3.4037400000000018,True
+1993,CHEMBL3759127,130.0,nM,2016.0,COc1cc2c(Nc3ccc(NC(=O)c4ccccc4)cc3)ncnc2cc1OCCCN1CCN(C)CC1,6.886056647693162,526.2692389480001,8,2,4.650600000000003,True
+1994,CHEMBL3899216,130.0,nM,2016.0,Cc1cc(NS(=O)(=O)c2ccc(Nc3nncc4ccccc34)cc2)no1,6.886056647693162,381.08956034,7,2,3.470620000000001,True
+1995,CHEMBL4077608,130.0,nM,2017.0,FC(F)(F)c1nnc(NC(=S)Nc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)s1,6.886056647693162,481.01579769200004,7,3,5.706000000000001,True
+1996,CHEMBL3612590,130.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4ccc5[nH]ncc5c4)c3cc21,6.886056647693162,432.15460312000005,9,2,3.5009000000000015,True
+1997,CHEMBL246072,130.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(COCC6CCNCC6)c45)ccc32)c1,6.886056647693162,485.233936736,8,2,4.526200000000004,True
+1998,CHEMBL3085381,130.0,nM,2007.0,CCN(CC)[C@@](C)(CCc1ncnc2cc(OC)c(OC)cc12)Cc1ccccc1,6.886056647693162,407.257277296,5,0,4.922800000000005,True
+1999,CHEMBL234577,130.0,nM,2007.0,CN1CCCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.886056647693162,484.24992114800006,8,1,4.147500000000003,True
+2000,CHEMBL398793,130.0,nM,2007.0,CC1CNCCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)C1,6.886056647693162,484.24992114800006,8,2,4.051300000000002,True
+2001,CHEMBL1645475,130.0,nM,2011.0,NC1CCN(Cc2ccn3ncnc(Nc4cc(Cl)cc(Cl)c4)c23)CC1,6.886056647693162,390.11265,6,2,3.7028000000000016,True
+2002,CHEMBL473320,131.0,nM,2008.0,COc1cc2ncnc(-c3c[nH]c4ccc(Br)cc34)c2cc1OC,6.8827287043442364,383.02693878799994,4,1,4.557800000000003,True
+2003,CHEMBL1379917,131.0,nM,2018.0,O=C(Nc1cc(N2CCOCC2)ncn1)c1ccc(F)cc1,6.8827287043442364,302.11790394,5,1,1.7045999999999997,True
+2004,CHEMBL2112370,131.0,nM,2001.0,COC[C@@H]1CCCN1C/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.8827287043442364,495.12698717200004,6,2,4.741400000000003,True
+2005,CHEMBL3753836,131.09,nM,2016.0,COc1cc(NC(=O)Nc2ccncc2)cc(-c2cccnc2)c1OC,6.882430436536173,350.13789043599996,5,2,3.804800000000002,True
+2006,CHEMBL553137,132.0,nM,1999.0,Cl.Cn1c2ccccc2c2ncnc(Nc3cccc(Br)c3)c21,6.8794260687941495,388.00903622799996,4,1,5.049400000000002,True
+2007,CHEMBL3671532,136.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CNC,6.866461091629782,516.0920788840001,7,4,3.113900000000001,True
+2008,CHEMBL3934539,136.0,nM,2016.0,CCC(=O)Nc1cc2c(NCc3ccccc3)ncnc2cc1OC,6.866461091629782,336.15862588,5,2,3.599000000000003,True
+2009,CHEMBL4073912,137.0,nM,2017.0,FC(F)(F)c1csc(NC(=S)Nc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)n1,6.863279432843593,480.0205487240001,6,3,6.311000000000002,True
+2010,CHEMBL2086760,137.0,nM,2012.0,CCN1CCC(Nc2ccc3c(c2)C(=C(c2ccc(Cl)cc2)c2ncc[nH]2)C(=O)N3)CC1,6.863279432843593,447.18258813200003,4,3,4.870500000000004,True
+2011,CHEMBL3775046,137.9,nM,2016.0,O=C1COc2cc3ncnc(Nc4ccc(F)c(Cl)c4)c3cc2N1CCCN1CCCCC1,6.8604357338241515,469.1680809400001,6,1,4.767300000000004,True
+2012,CHEMBL3233780,139.0,nM,2014.0,CCN(CC)CCN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,6.856985199745905,490.17178641600003,7,2,4.995700000000004,True
+2013,CHEMBL119033,139.0,nM,1995.0,COc1cccc2ncnc(Nc3cccc(Br)c3)c12,6.856985199745905,329.01637410399996,4,1,4.1445000000000025,True
+2014,CHEMBL3774926,139.0,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(CCCN2CCOCC2)C(=O)CO4)c1,6.856985199745905,443.19573965999996,7,1,2.8024000000000013,True
+2015,CHEMBL246694,140.0,nM,2007.0,NC(=O)COCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,6.853871964321763,445.16625110000007,8,2,3.0119000000000007,True
+2016,CHEMBL3946259,140.0,nM,2016.0,Cc1ccc2c(c1)nc(NC(=O)c1cccc(C(F)(F)F)c1)n2[C@H]1CC[C@H](O)CC1,6.853871964321763,417.16641160399996,4,2,5.091820000000004,True
+2017,CHEMBL398388,140.0,nM,2007.0,NC(=O)C1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.853871964321763,498.22918570400003,8,2,3.707300000000002,True
+2018,CHEMBL3926223,140.0,nM,2016.0,NS(=O)(=O)c1ccc(Nc2nncc3ccccc23)cc1,6.853871964321763,300.06809662399996,5,2,2.0208,True
+2019,CHEMBL81375,140.0,nM,2004.0,Cc1cc2cc(Nc3ccnc4cc(-c5ccc(CN(C)CCO)cc5)sc34)ccc2[nH]1,6.853871964321763,442.182732452,5,3,5.9207200000000055,True
+2020,CHEMBL2325094,140.0,nM,2013.0,Clc1ccc(C2=NN(c3ccccc3)C(c3cccc4ccccc34)C2)cc1Cl,6.853871964321763,416.084703936,2,0,7.502300000000004,True
+2021,CHEMBL3612592,140.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4ccc(F)c(F)c4)c3cc21,6.853871964321763,428.129611496,8,1,3.9028000000000027,True
+2022,CHEMBL193544,140.0,nM,2005.0,CN1CCC(Oc2cccc3ncnc(Nc4ccc(OCc5ccccn5)c(Cl)c4)c23)CC1,6.853871964321763,475.177502752,7,1,5.473800000000005,True
+2023,CHEMBL251123,140.0,nM,2007.0,CCOc1cc2ncnc(/C=C/CCCc3ccccc3)c2cc1OCC,6.853871964321763,362.19942807199993,4,0,5.463300000000005,True
+2024,CHEMBL2064386,140.0,nM,2012.0,O=c1oc2cc3ncnc(Nc4ccc(OCc5ccccc5)cc4)c3cc2n1CCCN1CCOCC1,6.853871964321763,511.22195440800004,9,1,4.582600000000004,True
+2025,CHEMBL3622669,141.0,nM,2015.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CNC1CC(F)(F)C1,6.85078088734462,491.13358725200004,6,3,5.056500000000003,True
+2026,CHEMBL4166210,142.7,nM,2018.0,C=CC(=O)Nc1cc(Nc2nccc(Nc3ccccc3-n3cccn3)n2)c(OC)cc1N1CCN(C)CC1,6.845576026885352,525.2600712320001,10,3,4.034400000000002,True
+2027,CHEMBL4226965,143.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N4CCN(C)CC4)cc3)n2)c1,6.844663962534938,472.2335221360001,7,4,3.7405000000000026,True
+2028,CHEMBL4079649,144.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cccc(Cl)c3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.84163750790475,588.2728001040001,7,1,4.891320000000005,True
+2029,CHEMBL3297891,145.2,nM,2014.0,Cc1nc(Nc2cccc3ccccc23)c2cc(C)oc2n1,6.838033383635925,289.1215121,4,1,4.736440000000003,True
+2030,CHEMBL345988,147.0,nM,1999.0,Nc1nc(Nc2cccc(Br)c2)c2c(n1)[nH]c1ccccc12,6.832682665251824,353.027607484,4,3,4.199400000000001,True
+2031,CHEMBL2337373,147.0,nM,2013.0,Nc1nc(Nc2ccccc2)c2c(n1)[nH]c1ccccc12,6.832682665251824,275.117095416,4,3,3.4369000000000014,True
+2032,CHEMBL3622647,147.4,nM,2015.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(C#N)c3)ncnc2cc1O[C@H]1CCOC1,6.831502516476967,476.19721688000004,8,2,3.6081800000000017,True
+2033,CHEMBL3930965,148.0,nM,2016.0,COc1cc2ncnc(Nc3ccc(Cc4ccccn4)cc3)c2cc1NC(=O)/C=C/CN1CCCC1,6.8297382846050425,494.24302420000004,7,2,4.958300000000004,True
+2034,CHEMBL4078026,148.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C(C)=O)CC5)c(C)c4)nc32)C1,6.8297382846050425,630.3078299480001,8,1,4.3023200000000035,True
+2035,CHEMBL1271618,149.0,nM,2010.0,CN(C)C/C=C/C(=O)N1CCc2c(sc3ncnc(N[C@H](CO)Cc4ccccc4)c23)C1,6.826813731587727,451.204196168,7,2,2.7093000000000007,True
+2036,CHEMBL3676394,149.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC(NC(=O)CN(C)C)C(C)C,6.826813731587727,572.1546791400001,7,3,4.480700000000004,True
+2037,CHEMBL321193,150.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3cccc(O)c3)nc21,6.823908740944319,412.04938104800004,6,2,4.751500000000003,True
+2038,CHEMBL258694,150.0,nM,2008.0,Cc1nnc(-c2cn3ncnc(Nc4cnc5[nH]ccc5c4)c3c2C(C)C)o1,6.823908740944319,374.16035719599995,8,2,3.8310200000000014,True
+2039,CHEMBL1641990,150.0,nM,2011.0,CN(C)C/C=C/C(=O)Nc1ccc2c(C#N)cnc(Nc3cccc(Br)c3)c2c1,6.823908740944319,449.08512236,5,2,4.668880000000003,True
+2040,CHEMBL57347,150.0,nM,1997.0,CN1CCN(CCCNc2ncc3cc(-c4c(Cl)cccc4Cl)c(NC(=O)NC(C)(C)C)nc3n2)CC1,6.823908740944319,544.223263068,7,3,4.968000000000003,True
+2041,CHEMBL1951415,150.0,nM,2012.0,Nc1nccc(-c2c(-c3ccc(F)cc3)ncn2C2CCCCC2)n1,6.823908740944319,337.17027386,5,1,4.233600000000003,True
+2042,CHEMBL157128,150.0,nM,2003.0,COCC1CCCN1CC#CC(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.823908740944319,517.111337108,6,2,4.665280000000004,True
+2043,CHEMBL186080,150.0,nM,2004.0,Cc1cc2c(Nc3ccc(F)c(Cl)c3)ncnn2c1,6.823908740944319,276.05780222,4,1,3.5738200000000013,True
+2044,CHEMBL391387,150.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc(OCc5cccnc5)c(Cl)c4)c23)CC1,6.823908740944319,463.188736132,8,2,4.023400000000002,True
+2045,CHEMBL2087354,150.0,nM,2012.0,Cc1ccc(S(=O)(=O)N2CCOc3cc4ncnc(Nc5cccc(Br)c5)c4cc3OCC2)cc1,6.823908740944319,554.062338316,7,1,4.906420000000004,True
+2046,CHEMBL190567,150.0,nM,2005.0,COCC(=O)Nc1ccc2ncnc(Nc3cccc(I)c3)c2c1,6.823908740944319,434.02397372,5,2,3.5629000000000017,True
+2047,CHEMBL3416612,150.0,nM,2015.0,C[C@@H](Nc1ncnc2sc(Br)cc12)c1ccc(F)cc1,6.823908740944319,350.984108672,4,1,4.766000000000002,True
+2048,CHEMBL380386,150.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN[C@H](C)C(N)=O,6.823908740944319,403.12113074800004,6,3,3.137900000000001,True
+2049,CHEMBL461113,150.0,nM,2008.0,Nc1ncnc(Nc2ccc(OCc3ccccc3)c(Cl)c2)c1C(=O)OCCN1CCOCC1,6.823908740944319,483.1673319919999,9,2,3.5238000000000023,True
+2050,CHEMBL251497,151.5,nM,2007.0,CC(C)(O)C#Cc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,6.819587367161676,355.088768,4,2,4.288300000000002,True
+2051,CHEMBL447230,152.0,nM,1996.0,COc1cc2ncnc(N(C)c3cccc(Br)c3)c2cc1OC,6.818156412055227,373.04258885199994,5,0,4.177400000000003,True
+2052,CHEMBL3416437,153.0,nM,2015.0,COc1ccccc1-c1cc2c(N[C@H](C)c3ccccn3)ncnc2s1,6.815308569182402,362.12013219600004,6,1,4.935000000000003,True
+2053,CHEMBL4081252,153.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3ccc(OC)cc3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.815308569182402,584.3223371400001,8,1,4.246520000000004,True
+2054,CHEMBL3800597,153.7,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C(=O)CC)CC4)cc3OC)ncc2SC)c1,6.813326132500254,548.220574504,9,2,4.926100000000004,True
+2055,CHEMBL3671551,154.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC(C)NC(C)=O,6.8124792791635365,501.08117985200005,6,3,4.302900000000004,True
+2056,CHEMBL4094086,154.6,nM,2017.0,C=CC(=O)Nc1cc(Nc2nc(OC)cc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,6.810790510417694,529.2801379800001,9,2,4.518400000000003,True
+2057,CHEMBL3671540,156.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)cc3F)ncnc2cc1OCCNC(=O)CN(C)C,6.806875401645538,470.187795068,7,3,2.8327,True
+2058,CHEMBL379047,156.0,nM,2006.0,CN(CCCl)C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.806875401645538,433.030499944,4,2,4.838400000000003,True
+2059,CHEMBL137082,156.0,nM,2001.0,C=CC(=O)N(CCCN1CCOCC1)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,6.806875401645538,496.1222361400001,7,1,3.7722000000000024,True
+2060,CHEMBL3416602,156.0,nM,2015.0,CC(Nc1ncnc2sc(Br)cc12)c1ccccc1,6.806875401645538,332.99353048399996,4,1,4.626900000000003,True
+2061,CHEMBL3921655,156.3,nM,2015.0,CC#CC(=O)N[C@H]1CC[C@@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)CC1,6.806041021980812,466.21172407200004,7,2,4.491000000000003,True
+2062,CHEMBL2424664,158.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CC2(C1)CS(=O)(=O)C2,6.801342913045577,492.10343208399996,8,1,3.2837000000000014,True
+2063,CHEMBL4227552,158.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N4CCN(CCF)CC4)cc3OC)n2)c1,6.801342913045577,534.250315072,8,4,4.088800000000003,True
+2064,CHEMBL540082,158.0,nM,1999.0,Cl.O=[N+]([O-])c1cccc2c1sc1c(Nc3cccc(Br)c3)ncnc12,6.801342913045577,435.93963634000005,6,1,5.680600000000002,True
+2065,CHEMBL1241484,158.0,nM,2008.0,CC(C)n1nc(-c2ccc(Cl)c(O)c2)c2c(N)ncnc21,6.801342913045577,303.088687748,6,2,3.0154000000000005,True
+2066,CHEMBL3671535,158.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)OC,6.801342913045577,503.060444408,7,3,4.134300000000003,True
+2067,CHEMBL96489,159.0,nM,1996.0,CN(C)c1cc2ncnc(Nc3cccc(Br)c3)c2cc1N,6.798602875679549,357.05890761200004,5,2,3.7841000000000014,True
+2068,CHEMBL3806066,159.9,nM,2016.0,COCCOc1cc2ncnc(Nc3cccc(OC)c3)c2c2c1OCCO2,6.796151536253765,383.14812077199997,8,1,3.1784000000000017,True
+2069,CHEMBL121190,160.0,nM,1997.0,Nc1[nH]cnc2nnc(Nc3cccc(Cl)c3)c1-2,6.795880017344076,260.057721968,5,3,2.2837000000000005,True
+2070,CHEMBL1817964,160.0,nM,2011.0,C/C=C(\C)C(O[C@@H]1O[C@H](CO)[C@@H](O)[C@H](O)[C@H]1O)C(C)/C=C(C)/C=C/CC(C)/C=C/c1oc(OC)c(C)c(=O)c1C,6.795880017344076,562.314183052,9,4,3.594540000000002,True
+2071,CHEMBL2325106,160.0,nM,2013.0,COc1ccc(C2=NN(C(N)=S)C(c3cccc4ccccc34)C2)cc1,6.795880017344076,361.124883228,3,1,4.243100000000003,True
+2072,CHEMBL337027,160.0,nM,1994.0,CO[C@H]1[C@@H](N(C)C(=O)CCC(=O)O)C[C@@H]2O[C@@]1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,6.795880017344076,566.21653468,7,2,4.457800000000002,True
+2073,CHEMBL3612596,160.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4ccc(OC(C)C)cc4)c3cc21,6.795880017344076,450.19031993199997,9,1,4.411800000000004,True
+2074,CHEMBL245867,160.0,nM,2007.0,NCCCCOCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,6.795880017344076,459.21828667200003,8,2,4.265500000000003,True
+2075,CHEMBL3403509,162.3,nM,2015.0,COc1ccc(N(C)c2nc(C)nc3oc(C)cc23)c(OC)c1,6.789681480173768,313.142641468,6,0,3.6247400000000027,True
+2076,CHEMBL3774578,162.7,nM,2016.0,Cc1ccc(Nc2ncnc3cc4c(cc23)N(CCCN2CCOCC2)C(=O)CO4)cc1Cl,6.788612447063142,467.1724173719999,7,1,3.7829200000000025,True
+2077,CHEMBL3922922,164.0,nM,2016.0,CCOc1cc2ncnc(Nc3ccc(OCc4ccccn4)cc3)c2cc1NC(=O)/C=C/CN1CCN(C)CC1,6.785156151952302,553.28013798,9,2,4.488200000000003,True
+2078,CHEMBL3092309,165.0,nM,2013.0,O=C(NCCN1CCCCC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.782516055786092,528.20519472,7,3,4.941000000000003,True
+2079,CHEMBL3754301,165.6,nM,2016.0,Cn1cnc(-c2cc(NC(=O)Nc3ccncc3)cc(C(F)(F)F)c2)c1,6.780939667551138,361.115044728,4,2,4.1449000000000025,True
+2080,CHEMBL3218347,166.0,nM,2012.0,CCC(=O)Nc1cccc(Nc2cc(Nc3cccc(Br)c3)ncn2)c1,6.779891911959945,411.069472296,5,3,5.074800000000002,True
+2081,CHEMBL243628,166.7,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OCc4ccc(F)c(F)c4)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,6.778064400171995,563.198025404,9,2,3.9113000000000024,True
+2082,CHEMBL4098409,167.1,nM,2017.0,COc1ccc2c(c1)CCN2c1nc(C)nc2c(Cc3ccccc3)c[nH]c12.Cl,6.777023550106609,406.15603903600004,4,1,4.981720000000005,True
+2083,CHEMBL3622628,167.3,nM,2015.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(C#N)c3)ncnc2cc1O[C@H]1CCOC1,6.776504059037607,419.139367656,7,2,3.6763800000000018,True
+2084,CHEMBL93173,170.0,nM,1997.0,COc1cc2ncnc(NCc3cccc(C)c3)c2cc1OC,6.769551078621726,309.147726848,5,1,3.5675200000000027,True
+2085,CHEMBL73406,170.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3cc(Cl)cc(Cl)c3)c2c1C,6.769551078621726,306.043901744,3,2,4.625140000000002,True
+2086,CHEMBL377772,170.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCC[C@H]1CC(N)=O,6.769551078621726,443.15243087600004,6,2,4.014300000000003,True
+2087,CHEMBL7819,170.0,nM,1999.0,COc1cc(O)c2c(=O)c(-c3cccc(Cl)c3)cn(C)c2c1,6.769551078621726,315.066220988,4,1,3.573100000000002,True
+2088,CHEMBL263528,170.0,nM,2001.0,NC(=O)CN1CCC(n2cc(-c3cccc(O)c3)c3c(N)ncnc32)CC1,6.769551078621726,366.18042394400004,7,3,1.5083,True
+2089,CHEMBL3416622,170.0,nM,2015.0,COc1ccccc1-c1cc2c(NCc3cccs3)ncnc2s1,6.769551078621726,353.0656541,6,1,5.040500000000002,True
+2090,CHEMBL193368,170.0,nM,2005.0,CCc1c(C(=O)OCCCn2ccnc2)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,6.769551078621726,520.2335221360001,10,1,4.876900000000004,True
+2091,CHEMBL4286871,170.0,nM,2018.0,CCNc1cc(Nc2cccc(Cl)c2)ncn1,6.769551078621726,248.08287409599998,4,2,3.3054000000000014,True
+2092,CHEMBL69960,170.0,nM,2002.0,Cc1cc(C(=O)N2CCOCC2)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc(F)c(Cl)c3)c21,6.769551078621726,482.12694440000007,6,3,3.614320000000001,True
+2093,CHEMBL232082,170.0,nM,2007.0,CN1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.769551078621726,470.23427108400006,8,1,3.7574000000000023,True
+2094,CHEMBL1241481,170.0,nM,2008.0,COc1cc(-c2nn(C(C)C)c3ncnc(N)c23)ccc1NC(=O)OC(C)(C)C,6.769551078621726,398.20663869199996,8,2,4.012000000000002,True
+2095,CHEMBL3676393,172.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC(C)NC(=O)CN(C)C,6.764471553092451,544.1233790120001,7,3,3.8446000000000025,True
+2096,CHEMBL3416624,173.0,nM,2015.0,COc1ccccc1-c1cc2c(Nc3ccccc3)ncnc2s1,6.761953896871206,333.0935831,5,1,5.110500000000003,True
+2097,CHEMBL248391,173.0,nM,2007.0,COc1cc2c(N[C@@H]3C[C@H]3c3ccccc3)c(C#N)cnc2cc1OCCCc1cccnc1,6.761953896871206,450.205576072,6,1,5.489680000000005,True
+2098,CHEMBL192737,174.0,nM,2005.0,COCC(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.7594507517174005,386.03783782,5,2,3.7208000000000014,True
+2099,CHEMBL3904205,175.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(c3)CCN4Cc3ccccc3)ncnc2cc1OC,6.7569619513137065,453.21647510400004,6,2,5.293200000000004,True
+2100,CHEMBL3676343,175.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3c(F)cc(Br)cc3F)ncnc2cc1OCCNC(=O)CN(C)C,6.7569619513137065,548.098307136,7,3,3.595200000000002,True
+2101,CHEMBL1242294,176.0,nM,2008.0,CC(C)n1nc(-c2ccc3[nH]ccc3c2)c2c(N)ncnc21,6.7544873321858505,292.143644512,5,2,3.1377000000000006,True
+2102,CHEMBL3608429,178.0,nM,2015.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cnn(C)c3)c3ncn(C(C)C)c3n2)C[C@H]1F,6.7495799976911055,413.20878460800003,9,2,1.7131999999999992,True
+2103,CHEMBL1242852,179.0,nM,2008.0,CC(C)n1nc(-c2ccc3c(ccn3C(=O)OC(C)(C)C)c2)c2c(N)ncnc21,6.747146969020108,392.19607400800004,8,1,4.394300000000002,True
+2104,CHEMBL2347964,179.0,nM,2013.0,CC(=O)Nc1ccc(-c2c(-c3ccccc3)oc3ncnc(N[C@H](CO)c4ccccc4)c23)cc1,6.747146969020108,464.184840628,6,3,5.660700000000004,True
+2105,CHEMBL552859,180.0,nM,1995.0,C=C(CN(C)C)C(=O)c1ccc(OCc2ccccc2)cc1.Cl,6.7447274948966935,331.133906624,3,0,3.9879000000000038,True
+2106,CHEMBL572030,180.0,nM,2009.0,C=COC(=O)N(CCN(C)C)/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.7447274948966935,439.152350624,8,1,5.1692000000000045,True
+2107,CHEMBL455433,180.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(NCc4cccc(Oc5ccccc5)c4)c3s2)C1)N1CCOCC1,6.7447274948966935,555.194025408,9,2,4.646500000000004,True
+2108,CHEMBL3896779,180.0,nM,2016.0,O=C(/C=C/CN1CCCC1)Nc1cc2c(Nc3ccc(Oc4ccccc4)cc3)ncnc2cn1,6.7447274948966935,466.21172407200004,7,2,5.151200000000004,True
+2109,CHEMBL402011,180.0,nM,2008.0,C[C@@H](Oc1cccc2ncnc(Nc3ccc4c(cnn4Cc4ccccn4)c3)c12)C(=O)N(C)C,6.7447274948966935,467.20697304000004,8,1,4.021900000000002,True
+2110,CHEMBL305782,180.0,nM,2002.0,Cc1[nH]c(/C=C2\C(=O)Nc3ncnc(Nc4ccc(F)c(Cl)c4)c32)c(C)c1CCC(=O)O,6.7447274948966935,455.11604536799996,5,4,4.467540000000002,True
+2111,CHEMBL3235201,180.0,nM,2014.0,Cc1ccc(Oc2nc3ccc(C)cc3cc2/C=N/NC(=O)Cn2c([N+](=O)[O-])cnc2C)cc1,6.7447274948966935,458.170253184,8,1,4.207360000000003,True
+2112,CHEMBL1421,180.0,nM,2006.0,Cc1nc(Nc2ncc(C(=O)Nc3c(C)cccc3Cl)s2)cc(N2CCN(CCO)CC2)n1,6.7447274948966935,487.15572175200003,9,3,3.3135400000000015,True
+2113,CHEMBL3608430,181.0,nM,2015.0,C=CC(=O)N1C[C@@H]2CN(c3nc(Nc4ccc(N5CCN(C)CC5)cc4)c4ncn(C(C)C)c4n3)C[C@@H]2C1,6.742321425130816,515.3121068040001,9,1,2.983200000000001,True
+2114,CHEMBL4077973,181.1,nM,2017.0,C=CC(=O)Nc1cc(Nc2cc(-c3cn4c5c(cccc35)CCC4)nc(OC)n2)c(OC)cc1N(C)CCN(C)C,6.742081549685942,555.295788044,9,2,4.9276000000000035,True
+2115,CHEMBL3416608,183.0,nM,2015.0,CC[C@@H](Nc1ncnc2sc(Br)cc12)c1ccccc1,6.73754891026957,347.00918054799996,4,1,5.017000000000003,True
+2116,CHEMBL3414594,183.0,nM,2015.0,COc1ccccc1-c1cc2c(NCc3ccccn3)ncnc2s1,6.73754891026957,348.10448213200004,6,1,4.374000000000002,True
+2117,CHEMBL4229010,183.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N(CC)CC)cc3OC)n2)c1,6.73754891026957,475.23318778800007,7,4,4.843500000000003,True
+2118,CHEMBL3969628,184.0,nM,2016.0,O=C(CBr)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(N5CCCCC5)c(Cl)c4)c3cc21,6.735182176990462,559.0621939960001,9,1,4.863100000000004,True
+2119,CHEMBL3805089,184.5,nM,2016.0,Cc1ccc(Nc2ncnc3cc(OC(C)C)c4c(c23)OCCO4)cc1[N+](=O)[O-],6.7340036295049215,396.1433697399999,8,1,4.148420000000003,True
+2120,CHEMBL4067014,185.6,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-n3cc(C)c4ccccc43)n2)c(OC)cc1N(C)CCN(C)C,6.731422028117157,499.2695732960001,8,2,4.603420000000003,True
+2121,CHEMBL249921,185.8,nM,2007.0,OCCC#Cc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,6.7309542903423765,341.073117936,4,2,3.8998000000000017,True
+2122,CHEMBL3775459,186.9,nM,2016.0,Cc1cccc(Nc2ncnc3cc4c(cc23)N(CCCN2CCOCC2)C(=O)CO4)c1,6.728390698621168,433.21138972399996,7,1,3.129520000000001,True
+2123,CHEMBL204268,187.0,nM,2006.0,COc1cc(OC2CCOC2)c2c(Nc3ccc(F)c(Cl)c3)ncnc2c1,6.7281583934635005,389.0942473040001,6,1,4.342200000000004,True
+2124,CHEMBL513716,187.0,nM,2009.0,NS(=O)(=O)c1ccc(Nc2nc3ncnc(Nc4c(F)cccc4F)c3s2)cc1,6.7281583934635005,434.04312206400004,8,3,3.499100000000001,True
+2125,CHEMBL3752404,189.49,nM,2016.0,O=C(Nc1ccncc1)Nc1cc(-c2cccnc2)cc(C(F)(F)F)c1,6.722413704215237,358.10414569600005,3,2,4.806400000000002,True
+2126,CHEMBL1812573,190.0,nM,2011.0,O=C(/C=C/c1cccc([N+](=O)[O-])c1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.721246399047171,445.09416705200005,6,2,5.586900000000002,True
+2127,CHEMBL1821870,190.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc(Cl)cc3)C2)cc1C,6.721246399047171,477.083324032,4,0,8.089440000000005,True
+2128,CHEMBL247915,190.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccnc5)c4)c23)CC1,6.721246399047171,453.2389418640001,9,2,3.189000000000001,True
+2129,CHEMBL392774,190.0,nM,2007.0,COC1CNCCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)C1,6.721246399047171,500.24483576800003,9,2,3.430200000000001,True
+2130,CHEMBL247711,190.0,nM,2007.0,COc1cn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c2c1CN1CCCNCC1,6.721246399047171,500.24483576800003,9,2,3.813900000000002,True
+2131,CHEMBL2425088,190.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCN1CC2(CCO2)C1,6.721246399047171,444.13644646399996,7,1,4.028000000000003,True
+2132,CHEMBL111038,190.0,nM,2003.0,COc1cc2ncc(C#N)c(Nc3cccc(Br)c3)c2cc1OC,6.721246399047171,383.02693878799994,5,1,4.629780000000003,True
+2133,CHEMBL3612562,190.0,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc4oc(=O)n(CCOC)c4cc23)c1,6.721246399047171,360.12224037199996,7,1,2.9090000000000007,True
+2134,CHEMBL109631,190.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3cccc(C(=O)O)c3)nc21,6.721246399047171,440.044295668,6,2,4.744100000000002,True
+2135,CHEMBL453398,190.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(Oc5ccccn5)c(Cl)c4)c3s2)C1)N1CCOCC1,6.721246399047171,576.13465196,10,2,4.826400000000004,True
+2136,CHEMBL246073,190.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(COC[C@H]6CCCNC6)c45)ccc32)c1,6.721246399047171,485.233936736,8,2,4.526200000000004,True
+2137,CHEMBL153419,191.0,nM,1999.0,c1ccc(CNc2ncnc3c2sc2ccccc23)cc1,6.718966632752272,291.083018416,4,1,4.456600000000003,True
+2138,CHEMBL413987,191.0,nM,2007.0,C[C@@H](CN(C)C(=O)CO)Oc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12,6.718966632752272,507.167331992,8,2,4.2188000000000025,True
+2139,CHEMBL4227490,192.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccccc3OC)n2)c1,6.71669877129645,404.1596885,6,4,3.997300000000001,True
+2140,CHEMBL4087243,192.3,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn4c5c(cccc35)CCC4)n2)c(OC)cc1N(C)CCO,6.71602071576152,498.23793882,8,3,4.349700000000003,True
+2141,CHEMBL136102,193.0,nM,2001.0,CN(C)CCCNC(=O)/C=C/C(=O)N(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,6.714442690992227,511.13313517200004,7,2,3.117800000000001,True
+2142,CHEMBL139307,194.0,nM,2001.0,C=CC(=O)N(CCCN1CCOCC1)c1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.7121982700697735,495.12698717200004,6,1,4.377200000000003,True
+2143,CHEMBL3608434,194.0,nM,2015.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cn(CC)nc3OC)c3ncn(C)c3n2)C[C@H]1F,6.7121982700697735,429.20369922800006,10,2,1.1607999999999992,True
+2144,CHEMBL2112369,194.0,nM,2001.0,COC[C@@H]1CCCN1C/C=C\C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.7121982700697735,495.12698717200004,6,2,4.741400000000003,True
+2145,CHEMBL3622620,195.8,nM,2015.0,C=CC(=O)Nc1cc2c(Nc3ccc(F)c(C#N)c3)ncnc2cc1OCCOC,6.70818731253288,407.139367656,7,2,3.5338800000000017,True
+2146,CHEMBL3671575,196.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C1CCCN1C(=O)CC,6.707743928643524,598.1339436960001,7,3,4.295500000000003,True
+2147,CHEMBL3092311,197.0,nM,2013.0,COCCCNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.705533773838408,489.15791018,7,3,4.491600000000003,True
+2148,CHEMBL3671528,198.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN(C)CC,6.703334809738469,544.1233790120001,7,3,3.846200000000003,True
+2149,CHEMBL3938358,200.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OC)cc3OC)ncc2Cl)c1,6.698970004336019,425.12546718,7,3,4.758900000000002,True
+2150,CHEMBL3947802,200.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(OC)cc3OC)ncc2C(F)(F)F)c1,6.698970004336019,460.135839748,7,2,5.173000000000003,True
+2151,CHEMBL26641,200.0,nM,2002.0,COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCC1CCNCC1,6.698970004336019,474.1066663280001,6,2,5.052100000000005,True
+2152,CHEMBL3913778,200.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(OC)cc3OC)ncc2Cl)c1,6.698970004336019,426.109482768,7,2,4.8076000000000025,True
+2153,CHEMBL196738,200.0,nM,2005.0,CCOC(=O)c1cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2c1C,6.698970004336019,426.18042394400004,8,1,4.3560200000000036,True
+2154,CHEMBL3347487,200.0,nM,2010.0,CC1(C)[C@H]2CC3OB(COc4ccc5ncnc(Nc6cccc(Cl)c6)c5c4)O[C@@]3(C)[C@@H]1C2,6.698970004336019,463.183399804,6,1,5.673100000000005,True
+2155,CHEMBL3928176,200.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccccc3OC)ncc2F)c1,6.698970004336019,380.128468624,6,2,4.284700000000002,True
+2156,CHEMBL3891187,200.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3cccc(OC)c3OC)ncc2C(F)(F)F)c1,6.698970004336019,459.15182416,7,3,5.1243000000000025,True
+2157,CHEMBL3085379,200.0,nM,2007.0,CCN(CC)[C@@](C)(C#Cc1ncnc2cc(OC)c(OC)cc12)Cc1ccncc1,6.698970004336019,404.221226136,6,0,3.7367000000000026,True
+2158,CHEMBL365606,200.0,nM,2005.0,CCOC(=O)c1cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2c1C(C)C,6.698970004336019,454.21172407200004,8,1,5.171000000000005,True
+2159,CHEMBL283088,200.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCN1CCN(C)CC1,6.698970004336019,445.16808094000004,7,1,3.8007000000000035,True
+2160,CHEMBL4087709,200.0,nM,2017.0,COc1cc2cnnc(Nc3ccc(Cl)cc3F)c2cc1OC,6.698970004336019,333.068032556,5,1,4.183100000000002,True
+2161,CHEMBL3954906,200.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccccc3OC)ncc2Br)c1,6.698970004336019,439.06438691600005,6,3,4.859400000000003,True
+2162,CHEMBL371863,200.0,nM,2005.0,CCOC(=O)c1cn2ncnc(NCc3ccccc3)c2c1CC,6.698970004336019,324.15862588,6,1,3.0805000000000016,True
+2163,CHEMBL181275,200.0,nM,2005.0,Fc1ccc(Nc2ncnc3nn4ccccc4c23)cc1Cl,6.698970004336019,313.053051188,5,1,3.813600000000002,True
+2164,CHEMBL3978161,200.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccccc3OC)ncc2C(F)(F)F)c1,6.698970004336019,430.125275064,6,2,5.164400000000002,True
+2165,CHEMBL75208,200.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3cccc(C#N)c3)c2c1C,6.698970004336019,263.117095416,4,2,3.1900200000000014,True
+2166,CHEMBL393787,200.0,nM,2007.0,O[C@@H]1CNCCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)C1,6.698970004336019,486.22918570400003,9,3,2.7760999999999996,True
+2167,CHEMBL137189,200.0,nM,2003.0,C/N=N/Nc1ccc2ncnc(Nc3cccc(C)c3)c2c1,6.698970004336019,292.143644512,5,2,4.090720000000002,True
+2168,CHEMBL394462,200.0,nM,2007.0,Cc1ccn2ncnc(Nc3ccc4c(cnn4Cc4ccccn4)c3)c12,6.698970004336019,355.15454354400003,7,1,3.574320000000002,True
+2169,CHEMBL186001,200.0,nM,2004.0,Cc1ccc(Nc2ncnn3cc(C)c(C)c23)cc1O,6.698970004336019,268.132411132,5,2,3.1037600000000016,True
+2170,CHEMBL343352,200.0,nM,2003.0,Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.698970004336019,270.067224032,4,2,3.609000000000001,True
+2171,CHEMBL337026,200.0,nM,1994.0,CN[C@H]1C[C@@H]2O[C@](C)([C@H]1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4=O,6.698970004336019,480.179755248,7,2,3.994200000000002,True
+2172,CHEMBL432903,200.0,nM,2002.0,CCN(CC)CCNC(=O)c1c(C)[nH]c(/C=C2\C(=O)Nc3ncnc(Nc4ccc(F)c(Cl)c4)c32)c1C,6.698970004336019,525.205529068,6,4,4.5219400000000025,True
+2173,CHEMBL1095761,200.0,nM,2010.0,Nc1nc(Nc2cccc(Br)c2)c2cc(Cc3ccc(Cl)cc3Cl)[nH]c2n1,6.698970004336019,460.98096290800004,4,3,5.943800000000001,True
+2174,CHEMBL3903641,200.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccccc3OC)ncc2C(F)(F)F)c1,6.698970004336019,429.141259476,6,3,5.115700000000002,True
+2175,CHEMBL372293,200.0,nM,2005.0,CCc1c(C(=O)N(C)C)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,6.698970004336019,439.21205842000006,7,1,4.135100000000003,True
+2176,CHEMBL4212450,200.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccccc2NC(=O)CO)n1,6.698970004336019,498.17823102399996,9,3,3.3571000000000004,True
+2177,CHEMBL2325093,200.0,nM,2013.0,Cc1ccc(C2=NN(c3ccccc3)C(c3cccc4ccccc34)C2)cc1,6.698970004336019,362.178298704,2,0,6.503920000000005,True
+2178,CHEMBL246898,200.0,nM,2007.0,CS(=O)(=O)CCNC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.698970004336019,576.2431215160001,10,2,3.6086000000000027,True
+2179,CHEMBL332938,200.0,nM,1995.0,COc1ccc2ncnc(NCc3ccccc3)c2c1,6.698970004336019,265.1215121,4,1,3.2505000000000015,True
+2180,CHEMBL1907764,200.0,nM,2002.0,COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OC[C@@H]1CCCN(C)C1,6.698970004336019,474.1066663280001,6,1,5.004200000000005,True
+2181,CHEMBL322298,200.0,nM,1998.0,CCn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3ccccc3)nc21,6.698970004336019,410.07011649200007,5,1,5.528800000000003,True
+2182,CHEMBL24979,200.0,nM,2002.0,COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCC1CCN(C)CC1,6.698970004336019,488.1223163920001,6,1,5.394300000000006,True
+2183,CHEMBL24828,200.0,nM,2002.0,COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1,6.698970004336019,474.1066663280001,6,1,5.004200000000005,True
+2184,CHEMBL330323,200.0,nM,1997.0,COc1cc2ncnc(Nc3nccc4ccccc34)c2cc1OC,6.698970004336019,332.127325752,6,1,3.938800000000003,True
+2185,CHEMBL3806005,200.3,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc(F)cc3)c2c2c1OCCO2,6.698319050706424,371.1281342759999,7,1,3.3089000000000013,True
+2186,CHEMBL3977504,201.0,nM,2016.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(Oc4ccccc4)cc3)ncnc2cn1,6.696803942579511,440.19607400800004,7,2,4.617000000000002,True
+2187,CHEMBL93537,203.0,nM,2001.0,O=C(/C=C/CN1CCSCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.692503962086787,483.07284342400004,6,2,4.679400000000004,True
+2188,CHEMBL427298,203.0,nM,1996.0,CN(C)CCn1cnc2c(Cl)c3c(Nc4cccc(Br)c4)ncnc3cc21,6.692503962086787,444.046484356,6,1,4.700600000000003,True
+2189,CHEMBL2346678,203.0,nM,2013.0,Nc1cccc(-c2c(-c3ccccc3)oc3ncnc(N[C@H](CO)c4ccccc4)c23)c1,6.692503962086787,422.174275944,6,3,5.284500000000004,True
+2190,CHEMBL3900054,204.0,nM,2012.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OC1CCN(C(=O)CO)CC1,6.690369832574102,460.13136108399993,7,2,3.5366000000000017,True
+2191,CHEMBL210378,204.0,nM,2006.0,CN(C(=O)N(CCCl)N=O)c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.690369832574102,418.071179112,6,1,4.805200000000003,True
+2192,CHEMBL3980622,205.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(Cc4ccccn4)cc3)ncnc2cc1OC,6.688246138944246,413.18517497600004,6,2,4.716300000000002,True
+2193,CHEMBL4289728,205.0,nM,2018.0,N=c1oc2ccccc2cc1C(=O)N/N=C1\C(=O)Nc2ccc(S(=O)(=O)N3CCOCC3)cc21,6.688246138944246,481.10560432799997,8,3,1.0193699999999994,True
+2194,CHEMBL248864,205.8,nM,2007.0,COc1cc2ncnc(Nc3cccc(C#CC(C)(C)O)c3)c2cc1OC,6.6865546295735845,363.15829153199996,6,2,3.5130000000000026,True
+2195,CHEMBL1242476,207.0,nM,2008.0,CC(C)n1nc(-c2ccc3c(N)n[nH]c3c2)c2c(N)ncnc21,6.684029654543082,308.14979251200003,7,3,2.1148999999999996,True
+2196,CHEMBL515401,209.0,nM,2008.0,COc1cc2ncnc(-c3c[nH]c4cc(F)c(Cl)cc34)c2cc1OC,6.679853713888947,357.068032556,4,1,4.587800000000003,True
+2197,CHEMBL4083224,209.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCCN(C)CC5)c(C)c4)nc32)C1,6.679853713888947,616.3285653920001,8,1,4.775720000000004,True
+2198,CHEMBL3088220,210.0,nM,2013.0,Cc1ncc([N+](=O)[O-])n1C/C(=N/NC(=O)c1ccc(O)cc1)c1ccc(Br)cc1,6.6777807052660805,457.038566092,7,2,3.402120000000002,True
+2199,CHEMBL1645477,210.0,nM,2011.0,COc1ccc(Nc2ncnn3ccc(CN4CCC(N)CC4)c23)cc1Cl,6.6777807052660805,386.16218703600003,7,2,3.0580000000000007,True
+2200,CHEMBL395591,210.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(COCC6CNCCOC6)c45)ccc32)c1,6.6777807052660805,501.22885135599995,9,2,3.7626000000000017,True
+2201,CHEMBL69964,210.0,nM,2002.0,Cc1cc(/C=C2\C(=O)Nc3ncnc(Nc4ccc(F)c(Cl)c4)c32)[nH]c1C(=O)N1CCN(C)CC1,6.6777807052660805,495.1585788760001,6,3,3.5295200000000015,True
+2202,CHEMBL104244,210.0,nM,1998.0,CN1CCN(CCCCNc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)CC1,6.6777807052660805,474.170164876,7,1,3.7418000000000013,True
+2203,CHEMBL2325108,210.0,nM,2013.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1cccc2ccccc12,6.6777807052660805,399.03637384,2,1,5.541300000000003,True
+2204,CHEMBL247100,210.0,nM,2007.0,Cc1ccn2ncnc(Nc3ccc4[nH]ncc4c3)c12,6.6777807052660805,264.112344384,5,2,2.6576200000000005,True
+2205,CHEMBL400413,210.0,nM,2007.0,CS(=O)(=O)N1CCCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.6777807052660805,548.2118213880001,9,1,3.4773000000000014,True
+2206,CHEMBL3774396,211.4,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc4c(cc23)N(CCCN2CCCCC2)C(=O)CO4)c1,6.674895017028593,441.216475104,6,1,3.9561000000000037,True
+2207,CHEMBL3676366,213.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OCCNC(=O)COC,6.671620396561263,551.03712212,7,3,4.194300000000003,True
+2208,CHEMBL94123,215.0,nM,2001.0,O=C(/C=C/N1CCOCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.667561540084393,453.08003698000005,6,2,3.920300000000002,True
+2209,CHEMBL2070199,216.0,nM,2012.0,Clc1cccc(Nc2ncnc3ccc(NCc4ccc5c(c4)OCCCO5)cc23)c1,6.665546248849069,432.13530359199996,6,2,5.800200000000003,True
+2210,CHEMBL257872,216.0,nM,2008.0,Cc1ccc(Oc2ccc(Nc3ncnc4[nH]nc(OCCN5CCC(O)CC5)c34)cc2C)cn1,6.665546248849069,475.233187788,9,3,3.7361400000000016,True
+2211,CHEMBL4096988,216.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5C[C@@H]6CN(C)C[C@@H]6C5)c(C)c4)nc32)C1,6.665546248849069,628.3285653920001,8,1,4.631620000000004,True
+2212,CHEMBL2347965,218.0,nM,2013.0,CC(=O)Nc1cccc(-c2c(-c3ccccc3)oc3ncnc(N[C@H](CO)c4ccccc4)c23)c1,6.661543506395395,464.184840628,6,3,5.660700000000005,True
+2213,CHEMBL234772,220.0,nM,2007.0,O=C(O)C1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.657577319177793,499.21320129200006,8,2,4.306600000000003,True
+2214,CHEMBL1242574,220.0,nM,2008.0,CC(C)n1nc(-c2ccc3cc[nH]c3c2)c2c(N)ncnc21,6.657577319177793,292.143644512,5,2,3.1376999999999997,True
+2215,CHEMBL338935,220.0,nM,1994.0,CO[C@H]1[C@@H](N(C)C(=O)CN)C[C@@H]2O[C@@]1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,6.657577319177793,523.221954408,7,2,3.551700000000003,True
+2216,CHEMBL104153,220.0,nM,1998.0,COc1ccc(Nc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)cc1,6.657577319177793,426.06503111200004,6,1,5.054500000000003,True
+2217,CHEMBL4073874,220.0,nM,2017.0,CN(C)C/C=C/C(=O)N1CCC[C@@H](n2nc(-c3ccccc3)c3c(N)ncnc32)C1,6.657577319177793,405.2277084840001,7,1,2.3568000000000007,True
+2218,CHEMBL50647,220.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3ccc(CC(=O)O)cc3)nc21,6.657577319177793,454.059945732,6,2,4.673000000000004,True
+2219,CHEMBL3416627,220.0,nM,2015.0,COc1ccccc1-c1cc2c(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)ncnc2s1,6.657577319177793,491.0870537480001,6,1,7.482000000000004,True
+2220,CHEMBL122068,220.0,nM,1997.0,Nc1nc(N)c2c(Nc3cccc(Cl)c3)[nH]nc2n1,6.657577319177793,275.068621,6,4,1.9142999999999997,True
+2221,CHEMBL3676373,222.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC(C)(C)NC(=O)CN(C)C,6.653647025549362,558.139029076,7,3,4.234700000000004,True
+2222,CHEMBL1172781,223.0,nM,2010.0,OC[C@@H](Nc1ncnc2oc(-c3ccccc3)c(-c3ccccc3)c12)c1ccccc1,6.6516951369518384,407.163376912,5,2,5.702300000000005,True
+2223,CHEMBL4226702,225.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N4CCOCC4)cc3OC)n2)c1,6.647817481888637,489.21245234400004,8,4,3.8339000000000025,True
+2224,CHEMBL203936,225.0,nM,2006.0,COc1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1OC1CCN(C)CC1,6.647817481888637,416.141531844,6,1,4.6475000000000035,True
+2225,CHEMBL3403513,226.4,nM,2015.0,Cc1nc(N(C)c2ccc3c(c2)CCO3)c2cc(C)oc2n1,6.6451235774837665,295.13207678400005,5,0,3.542440000000002,True
+2226,CHEMBL3633933,227.0,nM,2015.0,CCNC(=O)Nc1ccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c2c1,6.6439741428068775,448.141451592,6,3,5.142200000000003,True
+2227,CHEMBL308593,230.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3cccc(Cl)c3)c2c1-c1ccccc1,6.638272163982407,334.09852416,3,2,5.330320000000003,True
+2228,CHEMBL4203110,230.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccccc2N=[N+]=[N-])n1,6.638272163982407,466.16324965600006,8,1,5.368100000000004,True
+2229,CHEMBL80030,230.0,nM,1995.0,C=C(CN(C)C)C(=O)c1ccc(OS(=O)(=O)c2ccc(C(=O)O)cc2)cc1,6.638272163982407,389.093308328,6,1,2.4530000000000003,True
+2230,CHEMBL3663929,230.0,nM,2016.0,C=CC(=O)N1CC[C@@H](Oc2nc(Nc3ccc(N4CCC(N5CCN(C)CC5)CC4)cc3)c(C(N)=O)nc2CC)C1,6.638272163982407,562.3379872040001,9,2,2.2634000000000016,True
+2231,CHEMBL2064380,230.0,nM,2012.0,CCOC(=O)c1ccc(O)c(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)c1,6.638272163982407,493.196133584,11,2,2.8859000000000012,True
+2232,CHEMBL3092304,232.0,nM,2013.0,C#CCNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.6345120151091015,455.116045368,6,3,4.088300000000002,True
+2233,CHEMBL3806172,232.3,nM,2016.0,CCOC(C)Oc1cc2ncnc(Nc3ccc(F)c([N+](=O)[O-])c3)c2c2c1OCCO2,6.633950790199765,430.1288625479999,9,1,3.9532000000000025,True
+2234,CHEMBL399438,234.0,nM,2007.0,N#Cc1cnc2cc(-c3ccc(CN4CCOCC4)cc3)ccc2c1N[C@@H]1C[C@H]1c1ccccc1,6.6307841425898575,460.226311516,5,1,5.573680000000005,True
+2235,CHEMBL1242376,236.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Br)c(O)c1)nn2C1CCCC1,6.627087997029892,373.053822232,6,2,3.6587000000000014,True
+2236,CHEMBL138125,238.0,nM,2003.0,Brc1cccc(Nc2ncnc3ccc(N/N=N/Cc4ccccn4)cc23)c1,6.623423042943487,433.0650556120001,6,2,5.510200000000003,True
+2237,CHEMBL514942,240.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(-c4nc5ccccc5s4)cc3C)c2cc1OC,6.619788758288393,428.13069688,7,1,5.9757200000000035,True
+2238,CHEMBL2325095,240.0,nM,2013.0,c1ccc(C2=NN(c3ccccc3)C(c3ccc4ccccc4c3)C2)cc1,6.619788758288393,348.16264864,2,0,6.1955000000000044,True
+2239,CHEMBL571809,240.0,nM,2009.0,CC(=O)OCN(C)/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.619788758288393,384.110151464,7,1,4.477900000000003,True
+2240,CHEMBL1958215,240.0,nM,2012.0,Cc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(Br)cc3)C2)cc1,6.619788758288393,413.019745232,4,0,4.538020000000003,True
+2241,CHEMBL3912361,240.0,nM,2016.0,O=C(CCl)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(N5CCCCC5)c(Cl)c4)c3cc21,6.619788758288393,515.112709576,9,1,4.707000000000004,True
+2242,CHEMBL455434,240.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(Cc5ccccc5)cc4)c3s2)C1)N1CCOCC1,6.619788758288393,539.199110788,8,2,4.576500000000004,True
+2243,CHEMBL233324,240.0,nM,2007.0,O=C1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CCN1,6.619788758288393,484.2135356400001,8,2,3.331900000000002,True
+2244,CHEMBL3416599,241.0,nM,2015.0,Brc1cc2c(NCc3ccccc3)ncnc2s1,6.617982957425133,318.97788041999996,4,1,4.065900000000001,True
+2245,CHEMBL3775285,245.1,nM,2016.0,O=C1COc2cc3ncnc(Nc4cccc(F)c4)c3cc2N1CCCN1CCOCC1,6.6106566887479215,437.186317848,7,1,2.9602000000000013,True
+2246,CHEMBL3676391,246.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCOCCOC(=O)CC(=O)OCC,6.609064892896622,604.0968894920001,10,2,4.291300000000004,True
+2247,CHEMBL3815115,247.0,nM,2016.0,S=C(NCCCN1CCOCC1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.607303046740334,500.09939252000004,6,3,4.144600000000002,True
+2248,CHEMBL3805775,247.2,nM,2016.0,COCC(C)Oc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2c2c1OCCO2,6.6069515335832225,419.10481198799994,7,1,4.350800000000003,True
+2249,CHEMBL1242285,249.0,nM,2008.0,CC(C)n1nc(-c2cc(O)cc(Br)c2)c2c(N)ncnc21,6.603800652904264,347.0381721680001,6,2,3.1245000000000003,True
+2250,CHEMBL169570,250.0,nM,2001.0,Nc1ncnc2c1c(-c1ccc(O)cc1)cn2C1CCCC1,6.6020599913279625,294.148061196,5,2,3.5012000000000016,True
+2251,CHEMBL79060,250.0,nM,2004.0,Cc1cc2cc(Nc3ccnc4cc(-c5ccc(CNCCN6CCNCC6)cc5)sc34)ccc2[nH]1,6.6020599913279625,496.2409160240001,6,4,5.491420000000004,True
+2252,CHEMBL247101,250.0,nM,2007.0,Cc1ccn2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c12,6.6020599913279625,382.099667032,5,1,5.152820000000003,True
+2253,CHEMBL3736183,250.0,nM,2015.0,CO[C@H]1CCN(c2nccc(Nc3cc4c(cn3)nc(C)n4C(C)C)n2)C[C@H]1F,6.6020599913279625,399.21828667200003,8,1,3.4174200000000017,True
+2254,CHEMBL113023,250.0,nM,1998.0,COc1ccc(Nc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)cc1C,6.6020599913279625,440.08068117600004,6,1,5.3629200000000035,True
+2255,CHEMBL542733,250.0,nM,1997.0,COc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1.Cl,6.6020599913279625,347.103669116,6,1,3.821000000000003,True
+2256,CHEMBL91748,250.0,nM,2001.0,CN(C)/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.6020599913279625,411.069472296,5,2,4.149700000000002,True
+2257,CHEMBL3671544,251.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C(C)CN(C)C,6.6003262785189625,558.139029076,7,3,4.092200000000004,True
+2258,CHEMBL190651,252.0,nM,2005.0,COCC(=O)Nc1ccc2ncnc(Nc3cc(Cl)c(Cl)cc3F)c2c1,6.598599459218455,394.039959236,5,2,4.404200000000002,True
+2259,CHEMBL3671543,256.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)/C=N/OC,6.591760034688151,530.0713434400001,8,3,3.5267000000000017,True
+2260,CHEMBL1082012,257.0,nM,2009.0,Cc1c(C(=O)NCCN2CCN(C)CC2)[nH]c2cnnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c12,6.590066876668706,551.221179132,7,3,4.358620000000003,True
+2261,CHEMBL4067916,257.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cccc(OC(F)F)c3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.590066876668706,620.3034935160001,8,1,4.839320000000004,True
+2262,CHEMBL3416441,257.0,nM,2015.0,Fc1cccc(COc2ccc(Nc3ncnc4sc(Br)cc34)cc2Cl)c1,6.590066876668706,462.955701004,5,1,6.568900000000002,True
+2263,CHEMBL2347972,258.0,nM,2013.0,OC[C@@H](Nc1ncnc2oc(-c3ccccc3)c(-c3ccc4c(c3)OCO4)c12)c1ccccc1,6.58838029403677,451.15320615199994,7,2,5.4310000000000045,True
+2264,CHEMBL3671534,258.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CCN,6.58838029403677,516.0920788840001,7,4,3.2433000000000005,True
+2265,CHEMBL4078920,258.0,nM,2017.0,C=CC(=O)Nc1cccc(-c2c[nH]c3nccc(-c4[nH]c(CCCO)nc4C4CC4)c23)c1,6.58838029403677,427.20082504000004,4,4,4.546800000000003,True
+2266,CHEMBL338155,260.0,nM,1994.0,CN[C@H]1C[C@@H]2O[C@](C)([C@H]1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)[C@H](O)NC4=O,6.585026652029183,482.195405312,7,3,3.844900000000002,True
+2267,CHEMBL3954370,260.0,nM,2016.0,O=C(Nc1nc2ccccc2n1[C@H]1CC[C@H](O)CC1)c1cccc(C(F)(F)F)c1,6.585026652029183,403.15076153999996,4,2,4.783400000000003,True
+2268,CHEMBL3746557,260.0,nM,2016.0,CC(=O)N1N=C(c2ccc(C(F)(F)F)cc2)CC1c1ccc(C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,6.585026652029183,529.1573034639999,8,0,4.673120000000004,True
+2269,CHEMBL301612,260.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3ccccc3)nc21,6.585026652029183,396.05446642800007,5,1,5.045900000000003,True
+2270,CHEMBL1081312,260.0,nM,2008.0,Nc1ncnc2c1c(-c1cnc3[nH]ccc3c1)nn2C1CCCC1,6.585026652029183,319.15454354400003,6,2,3.0669000000000013,True
+2271,CHEMBL3416606,262.0,nM,2015.0,COC[C@@H](Nc1ncnc2sc(Br)cc12)c1ccccc1,6.581698708680255,363.004095168,5,1,4.253400000000003,True
+2272,CHEMBL301549,263.0,nM,1996.0,COc1ccc2c(Nc3cccc(Br)c3)ncnc2n1,6.580044251510242,330.0116230720001,5,1,3.539500000000002,True
+2273,CHEMBL150280,264.0,nM,1999.0,c1ccc(Nc2[nH]cnc3nc4ccccc4c2-3)cc1,6.578396073130167,260.106196384,3,2,3.806300000000001,True
+2274,CHEMBL4228018,266.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(OCCOC)cc3)n2)c1,6.575118363368933,448.185903248,7,4,4.013900000000002,True
+2275,CHEMBL403357,267.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2c(cnn2Cc2cccc(OC)c2)c1,6.573488738635424,403.175672912,9,2,3.189300000000002,True
+2276,CHEMBL596964,268.0,nM,2010.0,COc1cc2ncnc(NCc3ccc(F)cc3)c2cc1OCCCCCCC(=O)NO,6.5718652059712115,442.20163356399996,7,3,4.224300000000002,True
+2277,CHEMBL3917698,268.7,nM,2015.0,CN(C)C/C=C/C(=O)N1CCC(n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)CC1,6.570732333566832,497.2539232320001,8,1,4.1491000000000025,True
+2278,CHEMBL329642,269.0,nM,2001.0,C/C=C\C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.570247719997593,382.0429232,4,2,4.650500000000003,True
+2279,CHEMBL4075015,270.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc(N(C)C)c4ccccc34)c3c(N)ncnc32)C1,6.568636235841013,441.2277084840001,7,1,3.6442000000000014,True
+2280,CHEMBL3347488,270.0,nM,2010.0,OB(O)/C=C/COc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.568636235841013,355.08949942000004,6,3,2.9738000000000007,True
+2281,CHEMBL3234866,270.0,nM,2014.0,COc1ccc(Oc2nc3ccccc3cc2/C=N/NC(=O)Cn2c([N+](=O)[O-])cnc2C)cc1,6.568636235841013,460.14951773999996,9,1,3.599120000000002,True
+2282,CHEMBL118904,270.0,nM,1997.0,O=[N+]([O-])c1cccc(-c2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)c1,6.568636235841013,366.063201272,6,2,4.325100000000002,True
+2283,CHEMBL420885,270.0,nM,1997.0,CC(C)(C)OC(=O)Nc1ccc(-c2[nH]nc3ncnc(Nc4cccc(Cl)c4)c23)cc1,6.568636235841013,436.14145159200007,6,3,5.763900000000003,True
+2284,CHEMBL1242202,270.0,nM,2008.0,COc1ccc(-c2nn(C3CCC(C)C3)c3ncnc(N)c23)cc1O,6.568636235841013,339.169524912,7,2,3.1508000000000016,True
+2285,CHEMBL3133821,270.0,nM,2014.0,Oc1cccc(Nc2ccnc3[nH]c4ccccc4c23)c1,6.568636235841013,275.105862036,3,3,4.165300000000001,True
+2286,CHEMBL3797606,271.6,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3OC)ncc2SC)c1,6.566070234391535,506.21000982000004,9,2,4.6193000000000035,True
+2287,CHEMBL155100,272.0,nM,1999.0,Brc1cccc(Nc2ncnc3c2ccc2[nH]cnc23)c1,6.5654310959658,339.01195742000004,4,2,4.012200000000002,True
+2288,CHEMBL3894102,272.9,nM,2015.0,Nc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)nn2[C@H]1CC[C@@H](NC(=O)/C=C/CN2CCOCC2)CC1,6.563996464330104,553.28013798,9,2,4.356100000000002,True
+2289,CHEMBL4226436,273.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(C4CCN(C)CC4)cc3OC)n2)c1,6.563837352959244,501.24883785200007,7,4,4.806500000000004,True
+2290,CHEMBL3416598,275.0,nM,2015.0,COc1ccccc1-c1cc2c(NCc3cccnc3)ncnc2s1,6.560667306169737,348.10448213200004,6,1,4.374000000000002,True
+2291,CHEMBL3759085,276.0,nM,2016.0,C[C@@H](Nc1ncnc2sc(-c3ccccc3C(N)=O)cc12)c1ccccc1,6.559090917934783,374.120132196,5,2,4.630300000000003,True
+2292,CHEMBL4077228,279.0,nM,2017.0,CCC(=O)Nc1cccc(-c2c[nH]c3nccc(-c4[nH]c(CCCO)nc4-c4ccc(F)cc4)c23)c1,6.554395796726402,483.207053292,4,4,5.699500000000005,True
+2293,CHEMBL3909438,280.0,nM,2016.0,Cc1ccc2nc(NC(=O)c3cccc(C(F)(F)F)c3)n([C@H]3CC[C@H](O)CC3)c2c1,6.552841968657781,417.16641160399996,4,2,5.091820000000005,True
+2294,CHEMBL4213741,280.0,nM,2017.0,C=CC(=O)N1CC[C@H](Nc2nc(Nc3ccc(N4CCN(C)CC4)cc3)c3ncn(C(C)C)c3n2)C1,6.552841968657781,489.2964567400001,9,2,3.101400000000001,True
+2295,CHEMBL460746,280.0,nM,2009.0,O=C(NC(=S)Nc1ccc(O)c(-c2nc3ccccc3s2)c1)c1ccc([N+](=O)[O-])cc1,6.552841968657781,450.045646928,7,3,4.703900000000003,True
+2296,CHEMBL3092315,281.0,nM,2013.0,CN(C)CCN(C)C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.55129368009492,502.189544656,7,2,4.358900000000002,True
+2297,CHEMBL4245874,283.1,nM,2018.0,COc1ccc(Nc2ncnc3occ(C)c23)cc1,6.548060130634898,255.100776656,5,1,3.2834200000000013,True
+2298,CHEMBL243410,283.3,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OC(CF)CF)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,6.547753425479562,515.198025404,9,2,2.740500000000001,True
+2299,CHEMBL3676377,286.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(Cl)c3F)ncnc2cc1OC[C@@H](C)NC(=O)CN(C)C,6.543633966870956,578.08440666,7,3,4.498000000000004,True
+2300,CHEMBL4074248,287.0,nM,2017.0,NCCn1c(-c2ccccc2)nc2cc(Cl)ccc2c1=O,6.542118103266008,299.08253974799993,4,1,2.675600000000001,True
+2301,CHEMBL4293690,288.0,nM,2018.0,COc1ccc(OC)c(Nc2cc(Nc3ccc(N4CCN(C)CC4)cc3)ncn2)c1,6.5406075122407685,420.22737413600004,8,2,3.732800000000002,True
+2302,CHEMBL4107879,289.4,nM,2015.0,CC#CC(=O)N1CCC[C@@H]1Cn1nc(-c2ccc(Oc3ccccc3)cc2)c2c(N)ncnc21,6.538501473216982,452.19607400800004,7,1,3.882100000000002,True
+2303,CHEMBL3734933,290.0,nM,2015.0,CO[C@H]1CCN(c2nccc(Nc3cc4c(cn3)nc(CO)n4C(C)C)n2)C[C@H]1F,6.5376020021010435,415.213201292,9,2,2.6013,True
+2304,CHEMBL3754722,290.46,nM,2016.0,COc1cc(NC(=O)Nc2ccncc2)cc(-c2cncnc2)c1OC,6.536913666975467,351.133139404,6,2,3.1998000000000015,True
+2305,CHEMBL210893,294.0,nM,2006.0,CN(C(=O)N(CCCl)N=O)c1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.531652669587842,462.02066353199996,6,1,4.914300000000003,True
+2306,CHEMBL168661,295.0,nM,2001.0,COc1cccc(-c2cn(C3CCN(CCN(C)CCO)CC3)c3ncnc(N)c23)c1,6.5301779840218375,424.25867426400004,8,2,2.2500999999999998,True
+2307,CHEMBL4069229,297.0,nM,2017.0,C=CC(=O)Nc1cccc(-c2c[nH]c3nccc(-c4[nH]c(CCCO)nc4C(F)(F)F)c23)c1,6.527243550682787,455.15690954,4,4,4.688200000000004,True
+2308,CHEMBL3403512,298.2,nM,2015.0,Cc1nc(N(C)c2ccc3c(c2)OCO3)c2cc(C)oc2n1,6.525492360883025,297.1113413400001,6,0,3.336240000000002,True
+2309,CHEMBL1202473,300.0,nM,2002.0,COc1cc2c(Nc3cc(O)c(C)cc3F)ncnc2cc1OCC1CCN(C)CC1.Cl,6.522878745280337,462.18339665599996,7,2,4.677520000000005,True
+2310,CHEMBL2335376,300.0,nM,2013.0,Nc1nc(Nc2cccc(Br)c2)c2cc(CCc3ccccn3)[nH]c2n1,6.522878745280337,408.0698066440001,5,3,4.226400000000002,True
+2311,CHEMBL424375,300.0,nM,2000.0,COc1cccc(-c2cn(-c3ccc(CNCCO)cc3)c3ncnc(N)c23)c1,6.522878745280337,389.1851749760001,7,3,2.7602,True
+2312,CHEMBL105436,300.0,nM,2000.0,COc1cccc(-c2cn(-c3ccc(CCN(C)CCO)cc3)c3ncnc(N)c23)c1,6.522878745280337,417.2164751040001,7,2,3.1449000000000007,True
+2313,CHEMBL25425,300.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCC1CCN(C)CC1,6.522878745280337,444.172831972,6,1,5.285200000000006,True
+2314,CHEMBL2448065,300.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCC1CCN(C)CC1.Cl,6.522878745280337,466.13385962,6,1,5.316900000000006,True
+2315,CHEMBL485320,300.0,nM,2008.0,Nc1nc(Nc2cccc(Br)c2)c2cc(CCc3ccccc3)[nH]c2n1,6.522878745280337,407.07455767600004,4,3,4.831400000000002,True
+2316,CHEMBL416191,300.0,nM,2002.0,COc1cc2c(Nc3c(F)cc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1,6.522878745280337,492.0972445160001,6,1,5.143300000000004,True
+2317,CHEMBL2448064,300.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCC1CCNCC1.Cl,6.522878745280337,452.118209556,6,2,4.974700000000005,True
+2318,CHEMBL268868,300.0,nM,1994.0,O=C1NC(=O)c2cc(Nc3ccccc3)c(Nc3ccccc3)cc21,6.522878745280337,329.11642672,4,3,4.057400000000001,True
+2319,CHEMBL542891,300.0,nM,1995.0,CCOC(=O)C1CCN(CCC(=O)c2ccc(OCc3ccccc3)cc2)CC1.Cl,6.522878745280337,431.18633611999996,5,0,4.535300000000006,True
+2320,CHEMBL420059,300.0,nM,1997.0,COc1cc2ncnc(NC3CC3c3ccccc3)c2cc1OCCN1CCOCC1,6.522878745280337,420.21614075599996,7,1,3.317400000000002,True
+2321,CHEMBL1928309,300.0,nM,2012.0,O=C(c1cc2ccccc2[nH]1)c1cc2c(Nc3cccc(Cl)c3)ncnc2s1,6.522878745280337,404.049859716,5,2,5.800600000000003,True
+2322,CHEMBL3906330,300.0,nM,2016.0,O=C(CBr)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(F)c(F)c4)c3cc21,6.522878745280337,478.0088234360001,8,1,3.497600000000001,True
+2323,CHEMBL2325096,300.0,nM,2013.0,Fc1ccc(C2=NN(c3ccccc3)C(c3ccc4ccccc4c3)C2)cc1,6.522878745280337,366.153226828,2,0,6.3346000000000044,True
+2324,CHEMBL25579,300.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCN(C)c1ccncc1,6.522878745280337,453.13678081200004,7,1,5.084700000000005,True
+2325,CHEMBL355330,300.0,nM,2001.0,Nc1ncnc2c1c(-c1cccc(O)c1)cn2C1CCC1,6.522878745280337,280.132411132,5,2,3.1111000000000013,True
+2326,CHEMBL4072688,302.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C6COC6)CC5)c(C)c4)nc32)C1,6.519993057042849,644.3234800120001,9,1,4.154620000000004,True
+2327,CHEMBL3982014,303.6,nM,2015.0,Nc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)nn2C1CCN(C(=O)/C=C/CN2CCOCC2)CC1,6.517698232776557,539.264487916,9,1,3.9197000000000024,True
+2328,CHEMBL3092302,304.0,nM,2013.0,O=C(Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1)N1CCC(CCO)CC1,6.517126416391246,529.1892103079999,7,3,4.9599000000000055,True
+2329,CHEMBL3969056,304.0,nM,2016.0,CN(C)C/C=C/C(=O)Nc1cc2c(Nc3ccc(Cc4ccccn4)cc3)ncnc2cn1,6.517126416391246,439.2120584200001,7,2,3.810500000000002,True
+2330,CHEMBL255866,306.0,nM,2008.0,CO/N=C/c1c(N)ncnc1Nc1ccc2[nH]ncc2c1,6.514278573518419,283.118158036,7,3,1659,True
+2331,CHEMBL3403514,306.6,nM,2015.0,Cc1nc(N(C)c2ccc3occc3c2)c2cc(C)oc2n1,6.513427849481643,293.11642672000005,5,0,4.353740000000003,True
+2332,CHEMBL77688,310.0,nM,1991.0,O=C(O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)c(O)c1,6.508638306165728,365.020537312,7,2,2.1055,True
+2333,CHEMBL55794,310.0,nM,2001.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCNC(C)C,6.508638306165728,404.141531844,6,2,4.551300000000003,True
+2334,CHEMBL433305,310.0,nM,1996.0,c1ccc(Nc2ncnc3[nH]c4c(c23)CCCC4)cc1,6.508638306165728,264.137496512,3,2,3.580300000000002,True
+2335,CHEMBL172514,310.0,nM,2001.0,COCCNCCN1CCC(n2cc(-c3cccc(OC)c3)c3c(N)ncnc32)CC1,6.508638306165728,424.25867426400004,8,2,2.5619999999999994,True
+2336,CHEMBL30973,310.0,nM,2003.0,CN(C)C/C=C/C(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.508638306165728,449.08512236,5,2,4.668880000000003,True
+2337,CHEMBL1952210,310.0,nM,2005.0,COc1ccc(N2Cc3cnc(Nc4ccccc4)nc3N([C@@H]3CC[C@@H](O)C3)C2=O)cc1,6.508638306165728,431.19573966,6,2,4.088800000000003,True
+2338,CHEMBL3752916,310.76,nM,2016.0,Cn1cnc(-c2cc(NC(=O)Nc3nccs3)cc(C(F)(F)F)c2)c1,6.507574887223914,367.071465664,5,2,4.206400000000002,True
+2339,CHEMBL3805949,313.6,nM,2016.0,CC(C)Oc1cc2ncnc(Nc3ccc(F)c(C#N)c3)c2c2c1OCCO2,6.503623945987599,380.128468624,7,1,3.942580000000003,True
+2340,CHEMBL3754709,317.12,nM,2016.0,COc1cc(NC(=O)Nc2nccs2)cc(-c2cccnc2)c1OC,6.498776367194818,356.094311372,6,2,3.8663000000000016,True
+2341,CHEMBL1242568,318.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2C1CCCC1,6.497572880015568,313.133888352,6,2,3.035300000000001,True
+2342,CHEMBL102726,320.0,nM,1995.0,c1ccc(CNc2ncnc3ccccc23)cc1,6.494850021680094,235.110947416,3,1,3.241900000000001,True
+2343,CHEMBL205652,320.0,nM,2006.0,Fc1cccc(COc2ccc(Nc3ccncn3)cc2Cl)c1,6.494850021680094,329.073117936,4,1,4.591700000000002,True
+2344,CHEMBL3676356,321.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Cl)cc3F)ncnc2cc1OCCN(C)C,6.493494967595128,463.09780846,6,2,4.884200000000004,True
+2345,CHEMBL50245,324.0,nM,1996.0,CN(C)c1ccc2c(Nc3cccc(Br)c3)ncnc2n1,6.489454989793388,343.04325754800004,5,1,3.5969000000000024,True
+2346,CHEMBL4288262,324.0,nM,2018.0,Clc1ccc(Nc2cc(Nc3cccc(Cl)n3)ncn2)cc1,6.489454989793388,331.03915071200004,5,2,4.665600000000002,True
+2347,CHEMBL1242287,324.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Br)c(O)c1)nn2C1CCC1,6.489454989793388,359.038172168,6,2,3.268600000000001,True
+2348,CHEMBL3671545,325.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CC(C)N(C)C,6.4881166390211265,558.139029076,7,3,4.234700000000004,True
+2349,CHEMBL3902180,326.0,nM,2015.0,Nc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)nn2C1CCCN(C(=O)/C=C/CN2CCOCC2)C1,6.4867823999320615,539.264487916,9,1,3.9197000000000024,True
+2350,CHEMBL403569,327.0,nM,2007.0,O=C(CO)N1CCC[C@H]1COc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12,6.485452247339714,519.1673319920001,8,2,4.362900000000003,True
+2351,CHEMBL324926,330.0,nM,1998.0,COc1cc(Nc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)cc(OC)c1,6.481486060122112,456.075595796,7,1,5.063100000000004,True
+2352,CHEMBL129946,330.0,nM,1994.0,CCN(C)[C@H]1C[C@@H]2O[C@](C)([C@H]1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,6.481486060122112,494.23179082,6,1,5.086300000000004,True
+2353,CHEMBL3940060,330.0,nM,2016.0,O=C(CCl)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(F)c(Cl)c4)c3cc21,6.481486060122112,450.029788476,8,1,3.855800000000002,True
+2354,CHEMBL333038,330.0,nM,1997.0,Clc1cccc(Nc2nc[nH]c3nnc(Nc4cccc(Cl)c4)c2-3)c1,6.481486060122112,370.050049744,5,3,5.0985000000000005,True
+2355,CHEMBL354310,330.0,nM,2001.0,COc1cccc(-c2cn(C3CC(C(=O)NCCO)C3)c3ncnc(N)c23)c1,6.481486060122112,381.18008959600013,7,3,1.7486999999999997,True
+2356,CHEMBL414631,330.0,nM,2003.0,COCOC#CC(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.481486060122112,450.03275244,6,2,4.132480000000003,True
+2357,CHEMBL441279,330.0,nM,2015.0,COCOCC#CC(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.481486060122112,464.048402504,6,2,4.174980000000002,True
+2358,CHEMBL31876,330.2,nM,2004.0,CC#CC(=O)Nc1ccc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2c1,6.481222931073225,378.068366904,4,2,4.604380000000002,True
+2359,CHEMBL249511,331.0,nM,2007.0,Fc1ccc(Nc2ncnc3ccc(C#Cc4ccccc4)cc23)cc1Cl,6.480172006224282,373.07820331600004,3,1,5.565700000000003,True
+2360,CHEMBL3092303,331.0,nM,2013.0,O=C(Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1)N1CCN(CCO)CC1,6.480172006224282,530.184459276,8,3,3.4754000000000023,True
+2361,CHEMBL474524,333.0,nM,2008.0,COc1cc2ncnc(-c3c[nH]c4cc(F)c(Cl)cc34)c2cc1OCCCN1CCOCC1,6.477555766493679,470.15209652799996,6,1,4.680300000000005,True
+2362,CHEMBL137788,335.0,nM,2003.0,C/N=N/Nc1ccc2ncnc(NCc3ccccc3)c2c1,6.4749551929631535,292.143644512,5,2,3.650800000000002,True
+2363,CHEMBL4082764,336.0,nM,2017.0,NCc1cccc(-c2nc(-c3ccc(F)cc3)c(-c3ccnc4[nH]c(-c5ccccc5)cc34)[nH]2)c1,6.473660722610156,459.18592392400006,3,3,6.5518000000000045,True
+2364,CHEMBL4280395,336.0,nM,2018.0,COc1ccc(OC)c(Nc2cc(Nc3ccc(F)cc3)ncn2)c1,6.473660722610156,340.1335540040001,6,2,4.1201000000000025,True
+2365,CHEMBL380972,340.0,nM,2006.0,COc1cc2c(cc1OC)Oc1ncnc(Nc3cccc(Br)c3)c1NC2,6.468521082957745,428.0484025040001,7,2,4.7177000000000024,True
+2366,CHEMBL1173813,340.0,nM,2010.0,Cc1ccc(C2CC(c3ccc(C)c(C)c3)=NN2C(N)=S)cc1,6.468521082957745,323.145618672,2,1,4.006560000000002,True
+2367,CHEMBL188522,340.0,nM,2004.0,Cc1ccc(Nc2ncnn3ccc(C)c23)cc1O,6.468521082957745,254.116761068,5,2,2.7953400000000017,True
+2368,CHEMBL345077,340.0,nM,2001.0,C=C[S+]([O-])c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,6.468521082957745,373.9836940720001,5,1,3.782000000000002,True
+2369,CHEMBL394056,340.0,nM,2007.0,COCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,6.468521082957745,402.16043744800004,7,1,4.156400000000003,True
+2370,CHEMBL3297998,340.1,nM,2014.0,CCCCN(c1ccc(OC)cc1)c1nc(C)nc2oc(C)cc12,6.468393368067278,325.179026976,5,0,4.786440000000004,True
+2371,CHEMBL3972605,343.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(C(O)c4ccccc4)cc3)ncnc2cc1OC,6.464705879957229,428.184840628,6,3,4.812200000000003,True
+2372,CHEMBL289959,346.0,nM,1997.0,c1ccc(Nc2ncnc3ccccc23)cc1,6.460923901207224,221.095297352,3,1,3.373400000000001,True
+2373,CHEMBL4227812,348.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(OC)cc3OC)n2)c1,6.458420756053419,434.170253184,7,4,4.005900000000001,True
+2374,CHEMBL52197,348.0,nM,1995.0,COc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.458420756053419,329.01637410399996,4,1,4.1445000000000025,True
+2375,CHEMBL544833,350.0,nM,1997.0,COc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1OC.Cl,6.455931955649724,377.11423379999997,7,1,3.8296000000000032,True
+2376,CHEMBL169064,350.0,nM,2001.0,COc1cccc(-c2cn(C3CCN(CC(N)=O)CC3)c3ncnc(N)c23)c1,6.455931955649724,380.19607400800004,7,2,1.8112999999999995,True
+2377,CHEMBL2324871,350.0,nM,2013.0,NC(=S)N1N=C(c2ccc(Br)cc2)CC1c1ccc2ccccc2c1,6.455931955649724,409.02483061199996,2,1,4.997000000000003,True
+2378,CHEMBL176705,350.0,nM,2000.0,COc1ccc(-c2cn(-c3ccccc3)c3ncnc(N)c23)cc1,6.455931955649724,316.132411132,5,1,3.678300000000001,True
+2379,CHEMBL265629,350.0,nM,2007.0,O=C1CN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CCN1,6.455931955649724,470.1978855760001,8,2,2.9418000000000006,True
+2380,CHEMBL290389,350.0,nM,2000.0,COc1cc(/C=C(\C#N)C(N)=O)cc(Sc2nc3ccccc3s2)c1O,6.455931955649724,383.039833276,7,2,3.5539800000000024,True
+2381,CHEMBL1830274,350.0,nM,2011.0,Cc1ccc(C(/C=C/c2ccccc2)=N\NC(N)=S)cc1,6.455931955649724,295.114318544,2,2,3.2457200000000004,True
+2382,CHEMBL3805654,351.8,nM,2016.0,CCOC(C)Oc1cc2ncnc(Nc3ccc(F)c(C#N)c3)c2c2c1OCCO2,6.453704164878558,410.13903330799997,8,1,3.916680000000002,True
+2383,CHEMBL2347971,352.0,nM,2013.0,OC[C@@H](Nc1ncnc2oc(-c3ccccc3)c(-c3ccoc3)c12)c1ccccc1,6.4534573365218675,397.14264146799997,6,2,5.295300000000004,True
+2384,CHEMBL3775911,353.7,nM,2016.0,O=C1COc2cc3ncnc(Nc4ccc(Cl)cc4)c3cc2N1CCCN1CCOCC1,6.451364940185249,453.15676730800004,7,1,3.4745000000000017,True
+2385,CHEMBL116308,355.0,nM,1995.0,O=[N+]([O-])c1cccc2ncnc(Nc3cccc(Br)c3)c12,6.449771646944907,343.990887628,5,1,4.044100000000001,True
+2386,CHEMBL3622659,356.6,nM,2015.0,COCCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CC[S+]([O-])CC1,6.447818661160665,547.1456312439999,8,2,3.7501000000000024,True
+2387,CHEMBL245798,360.0,nM,2007.0,COc1cc2c(N[C@@H]3C[C@H]3c3ccccc3)c(C#N)cnc2cc1OC1CCN(C)CC1,6.443697499232713,428.221226136,6,1,4.556080000000004,True
+2388,CHEMBL4066141,360.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3Cl)Cc3cnc(Nc4ccc(N5CCN(C6COC6)CC5)c(C)c4)nc32)C1,6.443697499232713,660.2939294720001,9,1,4.668920000000004,True
+2389,CHEMBL437885,360.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCCC1,6.443697499232713,386.13096716,5,1,4.770300000000004,True
+2390,CHEMBL440873,360.0,nM,1996.0,FC(F)(F)c1cccc(Nc2ncnc3[nH]c4c(c23)CCCC4)c1,6.443697499232713,332.12488114,3,2,4.599100000000002,True
+2391,CHEMBL552860,360.0,nM,1995.0,CN(C)CCC(=O)c1ccc(OCc2ccccc2)c(O)c1.Cl,6.443697499232713,335.128821244,4,1,3.5274000000000023,True
+2392,CHEMBL4101193,360.0,nM,2017.0,CCC(=O)Nc1ccc(OC)c(Nc2cc(-c3cnc(SC)[nH]3)ccn2)c1,6.443697499232713,383.14159591200007,6,3,4.294300000000002,True
+2393,CHEMBL3752129,362.0,nM,2016.0,COc1cc(NC(=O)Nc2nccs2)cc(-c2cn(C)cn2)c1OC,6.441291429466834,359.10521040400005,7,2,3.2048000000000014,True
+2394,CHEMBL4096822,362.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.441291429466834,602.312915328,8,1,4.385620000000004,True
+2395,CHEMBL3805260,363.3,nM,2016.0,CCOC(C)Oc1cc2ncnc(Nc3ccc(C)c([N+](=O)[O-])c3)c2c2c1OCCO2,6.439734602137285,426.1539344239999,9,1,4.122520000000003,True
+2396,CHEMBL3092307,365.0,nM,2013.0,CCN(CC)CCNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.437707135543525,516.20519472,7,3,4.796900000000003,True
+2397,CHEMBL1952211,365.0,nM,2005.0,COc1ccc(N2Cc3cnc(Nc4ccccc4)nc3N([C@H]3CC[C@H](O)C3)C2=O)cc1,6.437707135543525,431.19573966,6,2,4.088800000000003,True
+2398,CHEMBL4087525,365.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cccc(C)c3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.437707135543525,568.32742252,7,1,4.546340000000004,True
+2399,CHEMBL1242656,366.0,nM,2008.0,CC1CCC(n2nc(-c3ccc(F)c(O)c3)c3c(N)ncnc32)C1,6.436518914605589,327.14953841600004,6,2,3.2813000000000008,True
+2400,CHEMBL257411,366.0,nM,2008.0,C[C@@H](Oc1cccc2ncnc(Nc3ccc4c(cnn4Cc4nccs4)c3)c12)C(=O)N1CCOCC1,6.436518914605589,515.1739586599999,10,1,3.854000000000002,True
+2401,CHEMBL3671569,368.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)c1ccc[nH]1,6.434152181326482,538.07642882,6,4,4.536400000000003,True
+2402,CHEMBL56393,370.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)c1ccc(O)c(O)c1,6.431798275933005,297.063722452,6,4,2.2988800000000005,True
+2403,CHEMBL4084726,373.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3Cl)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.428291168191312,618.283364788,8,1,4.899920000000004,True
+2404,CHEMBL2437457,373.5,nM,2013.0,C=CC(=O)Nc1ccc(-n2c(=O)cnc3cnc(Nc4ccc(Cl)cc4)nc32)cc1,6.427709393848582,418.09450140000007,7,2,3.6972000000000014,True
+2405,CHEMBL281467,374.8,nM,2004.0,C=CC(=O)Nc1cnc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.426200417784259,393.022522104,5,2,4.132080000000002,True
+2406,CHEMBL4097770,377.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3ccc(C)cc3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.4236586497942065,568.32742252,7,1,4.546340000000004,True
+2407,CHEMBL253292,380.0,nM,2008.0,CCN(CC)CCOc1ccc(Nc2cc(NC(=O)Nc3c(Cl)cccc3Cl)ncn2)cc1,6.420216403383191,488.14942943200003,6,3,5.891600000000005,True
+2408,CHEMBL247512,380.0,nM,2007.0,CC(=O)NC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.420216403383191,512.244835768,8,2,4.110500000000002,True
+2409,CHEMBL2064376,380.0,nM,2012.0,COc1ccc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)cc1,6.420216403383191,435.19065428,9,1,3.0122000000000018,True
+2410,CHEMBL1242293,380.0,nM,2008.0,CC(C)n1nc(-c2cnc3[nH]ccc3c2)c2c(N)ncnc21,6.420216403383191,293.13889348000004,6,2,2.5327,True
+2411,CHEMBL1950289,380.0,nM,2012.0,O[C@H]1CC[C@H](Nc2ncc3nc(Nc4c(F)cc(F)cc4F)n([C@H]4CCOC4)c3n2)CC1,6.420216403383191,448.18345863600007,8,3,3.6640000000000024,True
+2412,CHEMBL574059,380.0,nM,2000.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3ccc(F)cc3)nc21,6.420216403383191,414.0450446160001,5,1,5.185000000000002,True
+2413,CHEMBL2064373,380.0,nM,2012.0,C#Cc1cccc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)c1,6.420216403383191,429.180089596,8,1,2.9849000000000014,True
+2414,CHEMBL356324,380.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)S(=O)(=O)/C(C#N)=C/c1ccc(O)c(O)c1,6.420216403383191,384.0416071039999,8,4,2.3529600000000013,True
+2415,CHEMBL3944095,383.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(NCc4ccccc4)cc3)ncnc2cc1OC,6.416801226031379,427.20082504000004,6,3,5.342600000000004,True
+2416,CHEMBL4105392,383.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3ccc(Cl)cc3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.416801226031379,588.2728001040001,7,1,4.891320000000005,True
+2417,CHEMBL4110614,383.7,nM,2015.0,Nc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)nn2[C@@H]1CCCN(C(=O)/C=C/CN2CCOCC2)C1,6.416008200801683,539.264487916,9,1,3.9197000000000024,True
+2418,CHEMBL3968716,383.7,nM,2016.0,Nc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)nn2[C@H]1CCCN(C(=O)/C=C/CN2CCOCC2)C1,6.416008200801683,539.264487916,9,1,3.9197000000000024,True
+2419,CHEMBL4069277,385.5,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn4c5c(cccc35)CCC4)n2)c(OC)cc1N(C)CCN(C)C(C)=O,6.4139756176130245,553.2801379800001,8,2,4.835700000000004,True
+2420,CHEMBL3805280,387.8,nM,2016.0,COCCOc1cc2ncnc(Nc3ccc(F)c(C#N)c3)c2c2c1OCCO2,6.411392195257314,396.12338324399997,8,1,3.180580000000001,True
+2421,CHEMBL3942999,388.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(Cc4ccncc4)cc3)ncnc2cc1OC,6.411168274405793,413.18517497600004,6,2,4.716300000000002,True
+2422,CHEMBL1234815,388.0,nM,2008.0,Cn1nc(-c2ccc3ccccc3c2)c2c(N)ncnc21,6.411168274405793,275.117095416,5,1,2.7657,True
+2423,CHEMBL3671548,389.0,nM,2014.0,C=CC(=O)N(C)c1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(C)=O,6.410050398674293,501.08117985200005,6,2,3.9387000000000025,True
+2424,CHEMBL3799864,389.4,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCCN(C(C)=O)CC4)cc3OC)ncc2SC)c1,6.409604052815987,548.220574504,9,2,4.926100000000004,True
+2425,CHEMBL583683,390.0,nM,2009.0,CN(/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1)C(=O)OCCl,6.4089353929735005,404.0555290479999,7,1,5.290200000000003,True
+2426,CHEMBL127367,390.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4nc[nH]n4)c3)c2cc1OCC,6.4089353929735005,376.16477388,7,2,3.9559000000000015,True
+2427,CHEMBL574058,390.0,nM,2000.0,Cc1cc(Nc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)ccc1F,6.4089353929735005,428.06069468000004,5,1,5.493420000000003,True
+2428,CHEMBL1828862,390.0,nM,2011.0,Cc1ncc([N+](=O)[O-])n1CC(=O)NS(=O)(=O)c1ccc(F)cc1,6.4089353929735005,342.04341867200003,7,1,0.7439199999999999,True
+2429,CHEMBL93423,390.0,nM,1997.0,COc1cc2ncnc(NC3CC3c3ccccc3)c2cc1O,6.4089353929735005,307.132076784,5,2,3.3120000000000016,True
+2430,CHEMBL3813876,390.0,nM,2016.0,Fc1ccc(Nc2ncnc3ccc(NC(=S)NCCCN4CCOCC4)cc23)cc1Cl,6.4089353929735005,474.140486288,6,3,4.1746000000000025,True
+2431,CHEMBL1242853,391.0,nM,2008.0,CC(C)(C)OC(=O)n1ccc2cc(-c3nn(C4CCCC4)c4ncnc(N)c34)ccc21,6.407823242604133,418.21172407200004,8,1,4.928500000000004,True
+2432,CHEMBL2437468,395.0,nM,2013.0,C=CC(=O)Nc1ccc(-n2c(=O)cnc3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)cc1,6.4034029043735385,512.2284367560001,10,2,2.8042000000000007,True
+2433,CHEMBL4218447,396.7,nM,2017.0,COc1ccc(-c2c3c4cc(O)c(OC)cc4oc(=O)c3n3ccc4cc(O)c(OC)cc4c23)cc1O,6.4015377995258484,499.12671663199995,9,3,5.161700000000006,True
+2434,CHEMBL247468,397.0,nM,2007.0,c1ccc(-c2c(-c3ccc(OCCN4CCCC4)cc3)oc3ncnc(NCCN4CCNCC4)c23)cc1,6.401209493236885,512.2899743920001,8,2,4.348500000000001,True
+2435,CHEMBL485070,400.0,nM,1992.0,CCOc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccccc2)c1O,6.3979400086720375,354.103813436,5,2,3.4754800000000023,True
+2436,CHEMBL281872,400.0,nM,2002.0,COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCn1ccnn1,6.3979400086720375,458.05021407200013,8,1,3.954100000000003,True
+2437,CHEMBL490768,400.0,nM,1992.0,N#C/C(=C\c1cc(-c2ccccc2)c(O)c(-c2ccccc2)c1)C(N)=O,6.3979400086720375,340.121177752,3,2,4.118480000000003,True
+2438,CHEMBL25610,400.0,nM,2002.0,COc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCN1CCOCC1,6.3979400086720375,432.13644646399996,7,1,3.885500000000004,True
+2439,CHEMBL2316151,400.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccc(O)c(O)c3)C2=O)cc(OC)c1,6.3979400086720375,366.1467238039999,5,2,4.335000000000004,True
+2440,CHEMBL74432,400.0,nM,1991.0,CNC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,6.3979400086720375,362.057257168,6,1,2.0613,True
+2441,CHEMBL2178352,400.0,nM,2012.0,CN1CCN(c2ccc(Nc3ncc4nc(Nc5ccccc5)n(C5CCCC5)c4n3)cc2)CC1,6.3979400086720375,468.274993024,8,2,5.180400000000004,True
+2442,CHEMBL55979,400.0,nM,1991.0,CC(NC(=O)/C(C#N)=C/c1ccc(O)c(O)c1)c1ccccc1,6.3979400086720375,308.116092372,4,3,2.8821800000000017,True
+2443,CHEMBL67535,400.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCCNC(=O)/C(C#N)=C/c1ccc(O)c(O)c1,6.3979400086720375,448.13828435999994,8,6,1.6456599999999992,True
+2444,CHEMBL397122,400.0,nM,2007.0,C[C@@H](c1cccc(F)c1)n1ncc2cc(Nc3ncnn4ccc(COC[C@@H]5CNCCO5)c34)ccc21,6.3979400086720375,501.228851356,9,2,4.076000000000001,True
+2445,CHEMBL522116,400.0,nM,1992.0,CSCc1cc(/C=C2\C(=O)Nc3ccccc32)cc(CSC)c1O,6.3979400086720375,357.08572084800005,4,2,4.6109000000000036,True
+2446,CHEMBL408683,400.0,nM,2001.0,NC(=O)CN1CCC(n2cc(-c3cccc(O)c3)c3c(N)ncnc32)C1,6.3979400086720375,352.16477388000004,7,3,1.1181999999999999,True
+2447,CHEMBL248674,402.1,nM,2007.0,COc1cc2ncnc(Nc3cccc(C#CCCO)c3)c2cc1OC,6.395665926897088,349.14264146799997,6,2,3.124500000000002,True
+2448,CHEMBL3092305,404.0,nM,2013.0,COC(=O)/C=C/CNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.393618634889394,515.137174736,8,3,4.184300000000002,True
+2449,CHEMBL401054,405.0,nM,2007.0,COc1cc2ncc(C#N)c(N[C@@H]3C[C@H]3c3ccccc3)c2cc1OCCN1CCOCC1,6.392544976785331,444.21614075599996,7,1,3.794080000000003,True
+2450,CHEMBL3967962,405.0,nM,2016.0,O=C(/C=C/CN1CCCC1)Nc1cc2c(Nc3ccc(Cc4ccccn4)cc3)ncnc2cn1,6.392544976785331,465.2277084840001,7,2,4.344700000000002,True
+2451,CHEMBL4206585,409.0,nM,2018.0,CCS(=O)(=O)Nc1cc(-c2ccc3ncnc(Nc4cccc(C(=O)OC)c4)c3c2)cnc1OC,6.388276691992657,493.14198983599994,9,2,3.992200000000002,True
+2452,CHEMBL3601223,409.0,nM,2015.0,C=CC(=O)Nc1cccc(CNc2nc(Nc3ccc(N4CCN(C)CC4)cc3OC)ncc2Cl)c1,6.388276691992657,507.21495088,8,3,4.370600000000004,True
+2453,CHEMBL2152253,410.0,nM,2012.0,CNC(=O)c1nc(-c2ccc(Cl)c(S(=O)(=O)Nc3cccc(F)c3C)c2)cnc1N,6.3872161432802645,449.0724663040001,6,3,2.98712,True
+2454,CHEMBL304971,410.0,nM,2002.0,Cc1c(C(=O)N2CCN(C)CC2)c[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc(F)c(Cl)c3)c21,6.3872161432802645,495.1585788760001,6,3,3.5295200000000007,True
+2455,CHEMBL1830280,410.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1cccc2ccccc12)c1ccccc1,6.3872161432802645,331.114318544,2,2,4.090500000000002,True
+2456,CHEMBL2333998,412.8,nM,2013.0,COc1cc2ncnc(Nc3cccc(C#N)c3)c2cc1OC,6.384260311380845,306.111675688,6,1,3.2622800000000014,True
+2457,CHEMBL4063067,413.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cccc(OC)c3Cl)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.3840499483435975,618.283364788,8,1,4.899920000000004,True
+2458,CHEMBL3416620,415.0,nM,2015.0,C[C@@H](Nc1ncnc2sc(Br)cc12)c1cccs1,6.381951903287908,338.94995142,5,1,4.6884000000000015,True
+2459,CHEMBL3806321,416.1,nM,2016.0,Cc1ccc(Nc2ncnc3cc(OC(C)C)c4c(c23)OCCO4)cc1C#N,6.3808022842070535,376.15354049999996,7,1,4.111900000000003,True
+2460,CHEMBL4105503,417.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cccc(OC)c3)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.379863945026242,584.3223371400001,8,1,4.246520000000004,True
+2461,CHEMBL2093928,419.0,nM,1999.0,C[C@H](Nc1[nH]cnc2c3ccccc3nc1-2)c1ccccc1.Cl,6.377785977033705,324.114174224,3,2,4.657600000000003,True
+2462,CHEMBL3671585,419.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Cl)cc3F)ncnc2cc1OCCNC(=O)CN(C)C,6.377785977033705,486.158244528,7,3,3.3470000000000013,True
+2463,CHEMBL72322,420.0,nM,1996.0,Oc1cccc(Nc2ncnc3[nH]c4c(c23)CCCC4)c1,6.376750709602098,280.132411132,4,3,3.2859000000000007,True
+2464,CHEMBL1079742,420.0,nM,2009.0,C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(OCCOC)cc23)c1.Cl,6.376750709602098,429.1455339279999,7,1,3.8269000000000033,True
+2465,CHEMBL3235203,420.0,nM,2014.0,Cc1ccc2nc(Oc3ccc(F)cc3)c(/C=N/NC(=O)Cn3c([N+](=O)[O-])cnc3C)cc2c1,6.376750709602098,462.145181308,8,1,4.038040000000003,True
+2466,CHEMBL352801,420.0,nM,2001.0,COc1cccc(-c2cn(C3CC(CO)C3)c3ncnc(N)c23)c1,6.376750709602098,324.15862588,6,2,2.6324999999999994,True
+2467,CHEMBL4078801,421.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cccc(OC)c3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(C)c4)nc32)C1,6.375717904164333,602.312915328,8,1,4.385620000000004,True
+2468,CHEMBL3962032,421.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(ccn4CC(C)C)c3)ncnc2cc1OC,6.375717904164333,417.21647510400004,6,2,5.341200000000003,True
+2469,CHEMBL4081429,427.7,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn4c5c(cccc35)CCC4)n2)c(OC)cc1N1CCNC(=O)C1,6.368860749743189,523.233187788,8,3,3.857400000000001,True
+2470,CHEMBL3088219,430.0,nM,2013.0,Cc1ncc([N+](=O)[O-])n1C/C(=N/NC(=O)c1ccc(N)cc1)c1ccc(Br)cc1,6.366531544420412,456.0545505040001,7,2,3.2787200000000007,True
+2471,CHEMBL422066,430.0,nM,1997.0,COc1cc2ncnc(NNc3ccc(F)c(Cl)c3)c2cc1OC,6.366531544420412,348.07893158799993,6,2,3.8785000000000025,True
+2472,CHEMBL395883,430.0,nM,2007.0,COc1cn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c2c1COC[C@@H]1CNCCO1,6.366531544420412,517.223765976,10,2,3.523600000000002,True
+2473,CHEMBL2347970,434.0,nM,2013.0,OC[C@@H](Nc1ncnc2oc(-c3ccccc3)c(-c3ccco3)c12)c1ccccc1,6.362510270487489,397.14264146799997,6,2,5.295300000000004,True
+2474,CHEMBL3774471,434.1,nM,2016.0,O=C1COc2cc3ncnc(Nc4ccc(F)cc4)c3cc2N1CCCN1CCOCC1,6.362410214161299,437.186317848,7,1,2.9602000000000013,True
+2475,CHEMBL3929922,435.3,nM,2016.0,CC#CC(=O)N1CCC[C@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1,6.361211332842602,452.19607400800004,7,1,4.054600000000002,True
+2476,CHEMBL4106607,435.3,nM,2015.0,CC#CC(=O)N1CCC[C@@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1,6.361211332842602,452.19607400800004,7,1,4.054600000000002,True
+2477,CHEMBL4073062,436.3,nM,2017.0,C=CC(=O)N1CC[C@@H](n2c(=O)cc(C)c3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)C1,6.36021478701318,503.26448791600006,9,1,2.56332,True
+2478,CHEMBL1242201,437.0,nM,2008.0,COc1ccc(-c2nn(C3CCCC3)c3ncnc(N)c23)cc1O,6.359518563029578,325.153874848,7,2,2.904800000000001,True
+2479,CHEMBL333418,439.0,nM,1995.0,Nc1cccc2ncnc(Nc3cccc(Br)c3)c12,6.357535479757877,314.01670845200005,4,2,3.7181000000000015,True
+2480,CHEMBL3612573,440.0,nM,2015.0,CCOC(=O)c1ccc(O)c(Nc2ncnc3cc4oc(=O)n(CCOC)c4cc23)c1,6.356547323513813,424.13828435999994,10,2,2.8100000000000014,True
+2481,CHEMBL171311,440.0,nM,2001.0,Nc1ncnc2c1c(-c1ccccc1)cn2C(CO)Cc1ccccc1,6.356547323513813,344.16371126,5,2,3.4566000000000017,True
+2482,CHEMBL355322,440.0,nM,2001.0,COc1cccc(-c2cn(C3CCN(CC(N)=O)C3)c3ncnc(N)c23)c1,6.356547323513813,366.18042394400004,7,2,1.4211999999999994,True
+2483,CHEMBL194389,440.0,nM,2005.0,COc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12,6.356547323513813,392.104003464,6,1,5.009400000000003,True
+2484,CHEMBL3301625,442.0,nM,2017.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OCCOC)cc3)ncc2F)c1,6.354577730650908,423.170667784,7,3,4.252600000000002,True
+2485,CHEMBL544865,444.0,nM,1999.0,COc1cc2sc3c(Nc4cccc(Br)c4)ncnc3c2cc1OC.Cl,6.35261702988538,450.97568750000005,6,1,5.789600000000003,True
+2486,CHEMBL3633938,445.0,nM,2015.0,N#CC(C#N)=CNc1ccc2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2c1,6.351639989019067,470.10581503199995,7,2,6.087860000000003,True
+2487,CHEMBL57366,450.0,nM,1997.0,CC(C)(C)NC(=O)Nc1nc2nc(N)ncc2cc1-c1c(Cl)cccc1Cl,6.346787486224656,404.09191455599995,5,3,4.500800000000003,True
+2488,CHEMBL279459,450.0,nM,2002.0,COc1cc2c(Nc3c(F)cc(Br)cc3F)ncnc2cc1OCC1CCNCC1,6.346787486224656,478.0815944520001,6,2,4.8011000000000035,True
+2489,CHEMBL382822,450.0,nM,2006.0,COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1CN1CCC[C@@H]1C(=O)N(C)C,6.346787486224656,457.16808094000004,6,1,4.227100000000004,True
+2490,CHEMBL355191,450.0,nM,2001.0,COc1cccc(-c2cn(C3CCC3)c3ncnc(N)c23)c1,6.346787486224656,294.148061196,5,1,3.4141000000000012,True
+2491,CHEMBL2385990,450.0,nM,2013.0,Cc1ccc(NC(=O)/C=C/CN(C)C)cc1C(=O)Nc1ccc(OCc2cccc(F)c2)c(Cl)c1,6.346787486224656,495.17249762399996,4,2,5.675120000000005,True
+2492,CHEMBL1914656,450.0,nM,2011.0,Br.Cc1ccc([C@@H](C)Nc2ncnc3[nH]c(-c4ccc(O)cc4)cc23)cc1,6.346787486224656,424.089873392,4,3,5.389920000000004,True
+2493,CHEMBL308672,450.0,nM,2002.0,CCN(CC)CCNC(=O)c1cc(C)c(/C=C2\C(=O)Nc3ncnc(Nc4ccc(Cl)cc4F)c32)[nH]1,6.346787486224656,511.1898790040001,6,4,4.213520000000002,True
+2494,CHEMBL422758,450.0,nM,2002.0,COc1cc2c(Nc3c(F)cc(Cl)cc3F)ncnc2cc1OCC1CCN(C)CC1,6.346787486224656,448.14776009600007,6,1,5.034200000000005,True
+2495,CHEMBL2347969,452.0,nM,2013.0,OC[C@@H](Nc1ncnc2oc(-c3ccccc3)c(Br)c12)c1ccccc1,6.3448615651886175,409.042588852,5,2,4.797800000000003,True
+2496,CHEMBL3753444,455.17,nM,2016.0,COc1ccc(-c2cc(NC(=O)Nc3ccncc3)cc(OC)c2OC)cn1,6.341826369776012,380.14845511999994,6,2,3.8134000000000015,True
+2497,CHEMBL3671583,456.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3C(F)(F)F)ncnc2cc1OCCNC(C)=O,6.341035157335565,537.062336228,6,3,4.794100000000003,True
+2498,CHEMBL3775897,456.2,nM,2016.0,Cc1cccc(Nc2ncnc3cc4c(cc23)N(CCCN2CCCCC2)C(=O)CO4)c1,6.340844719059371,431.232125168,6,1,4.283220000000004,True
+2499,CHEMBL101253,457.7,nM,2007.0,Clc1ccc(Nc2nnc(Cc3ccncc3)c3ccccc23)cc1,6.339419087572701,346.09852416,4,1,5.012600000000003,True
+2500,CHEMBL511478,458.0,nM,2008.0,NNC(=O)c1c(N)ncnc1Nc1ccc(OCc2ccccc2)c(Cl)c1,6.339134521996131,384.110151464,7,4,2.6383,True
+2501,CHEMBL4064224,459.0,nM,2017.0,C=CC(=O)Nc1cccc(-c2c[nH]c3nccc(Cl)c23)c1,6.338187314462738,297.066889684,2,2,4.007800000000001,True
+2502,CHEMBL246491,460.0,nM,2007.0,COC(=O)COCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,6.337242168318426,460.16591675200004,9,1,3.699600000000002,True
+2503,CHEMBL3774808,460.0,nM,2016.0,O=C1COc2cc3ncnc(Nc4cccc(F)c4)c3cc2N1CCCN1CCCCC1,6.337242168318426,435.207053292,6,1,4.113900000000003,True
+2504,CHEMBL168382,460.0,nM,2001.0,COc1cccc(-c2cn(C3CCCC3)c3ncnc(N)c23)c1,6.337242168318426,308.16371126,5,1,3.8042000000000016,True
+2505,CHEMBL357097,460.0,nM,1999.0,c1ccc(CNc2[nH]cnc3c4ccccc4nc2-3)cc1,6.337242168318426,274.121846448,3,2,3.674800000000001,True
+2506,CHEMBL538814,460.0,nM,1999.0,Cl.O=[N+]([O-])c1ccc2sc3c(Nc4cccc(C(F)(F)F)c4)ncnc3c2c1,6.337242168318426,426.0165089,6,1,5.936900000000002,True
+2507,CHEMBL3934594,460.0,nM,2016.0,CC(C)S(=O)(=O)c1ccccc1Nc1nc(N/N=C/c2cccc(C(F)(F)F)c2)ncc1Cl,6.337242168318426,497.090008188,7,2,5.520500000000004,True
+2508,CHEMBL3219507,460.0,nM,2010.0,COc1cc2ncnc(Nc3cccc(Cl)c3)c2cc1B(O)O,6.337242168318426,329.073849356,6,3,1.7152000000000003,True
+2509,CHEMBL3908711,460.0,nM,2016.0,O=C(CBr)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(F)c(Cl)c4)c3cc21,6.337242168318426,493.9792728960001,8,1,4.0119000000000025,True
+2510,CHEMBL4074766,462.0,nM,2017.0,C=CC(=O)Nc1cc(Nc2n[nH]c3ccccc23)c(OC)cc1N(C)CCN(C)C,6.335358024443875,408.22737413600004,6,3,3.437400000000002,True
+2511,CHEMBL4225517,462.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N(C)C)cc3)n2)c1,6.335358024443875,417.1913229760001,6,4,4.054700000000002,True
+2512,CHEMBL93295,463.0,nM,1996.0,COc1cc2nc(N)nc(Nc3cccc(Br)c3)c2cc1OC,6.3344190089820485,374.03783782,6,2,3.7353000000000014,True
+2513,CHEMBL3092321,464.0,nM,2013.0,CN1CCN(C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3cc2O[C@H]2CCOC2)CC1,6.3334820194451185,500.17389459199995,7,2,4.112900000000002,True
+2514,CHEMBL3092317,464.0,nM,2013.0,CN(C)CCCN(C)C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.3334820194451185,516.20519472,7,2,4.749000000000002,True
+2515,CHEMBL1817965,470.0,nM,2011.0,C/C=C(\C)[C@H](O)[C@H](C)/C=C(C)/C=C/CC(C)/C=C/c1oc(OC)c(C)c(=O)c1C,6.327902142064282,400.26135963199994,4,1,5.770340000000006,True
+2516,CHEMBL310580,470.0,nM,1995.0,C=C(CN(C)C)C(=O)c1ccc(OS(=O)(=O)c2ccc(C(=O)O)c(O)c2)cc1,6.327902142064282,405.08822294799995,7,2,2.1586,True
+2517,CHEMBL3612561,470.0,nM,2015.0,COCCn1c(=O)oc2cc3ncnc(Nc4ccc(F)c(Cl)c4)c3cc21,6.327902142064282,388.07384620799996,7,1,3.720200000000002,True
+2518,CHEMBL3965075,470.0,nM,2016.0,CCOCc1ccc2c(c1)nc(NC(=O)c1cccc(C(F)(F)F)c1)n2[C@H]1CC[C@H](O)CC1,6.327902142064282,461.192626352,5,2,5.319900000000005,True
+2519,CHEMBL474324,472.0,nM,2008.0,COCCOc1cc2ncnc(-c3c[nH]c4cc(F)c(Cl)cc34)c2cc1OCCOC,6.326058001365912,445.12046205199994,6,1,4.621000000000004,True
+2520,CHEMBL1928945,473.0,nM,2012.0,Nc1cccc(Oc2cc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)ncn2)c1,6.3251388592621876,436.11023171600004,6,2,5.966200000000002,True
+2521,CHEMBL3805584,473.6,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(OC(C)COC)c4c(c23)OCCO4)c1,6.324588306285137,391.15320615199994,7,1,3.539600000000002,True
+2522,CHEMBL3751967,476.66,nM,2016.0,COc1ccc(-c2cc(NC(=O)Nc3nccs3)cc(C(F)(F)F)c2)cn1,6.321791291345775,394.07113131600005,5,2,4.876500000000002,True
+2523,CHEMBL3092323,479.0,nM,2013.0,COCCNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.319664486585437,475.14226011600005,7,3,4.1015000000000015,True
+2524,CHEMBL406845,480.0,nM,2007.0,CC(C)(C)n1nc(-c2ccc(Cl)cc2)c2c(N)ncnc21,6.3187587626244115,301.109423192,5,1,3.483900000000001,True
+2525,CHEMBL111339,480.0,nM,1998.0,Cc1ccc(Nc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)cc1,6.3187587626244115,410.070116492,5,1,5.354320000000003,True
+2526,CHEMBL137027,482.0,nM,2003.0,CN(C)/N=N/c1ccc2ncnc(NCc3ccccc3)c2c1,6.31695296176115,306.159294576,5,1,3.802200000000002,True
+2527,CHEMBL3926657,487.6,nM,2015.0,Nc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)nn2C1CCCN(C(=O)/C=C/c2c[nH]cn2)C1,6.311936303053657,506.2178720720001,8,2,4.467800000000002,True
+2528,CHEMBL168550,490.0,nM,2001.0,COc1cccc(-c2cn(C3CC(CNCCO)C3)c3ncnc(N)c23)c1,6.309803919971486,367.2008250400001,7,3,2.2220999999999993,True
+2529,CHEMBL246489,490.0,nM,2007.0,COCCOCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,6.309803919971486,446.18665219600007,8,1,4.173000000000003,True
+2530,CHEMBL448154,490.0,nM,1998.0,CCn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3ccncc3)nc21,6.309803919971486,411.0653654600001,6,1,4.923800000000003,True
+2531,CHEMBL373025,490.0,nM,2005.0,CCc1c(CO)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,6.309803919971486,398.185509324,7,2,3.925600000000003,True
+2532,CHEMBL2325091,490.0,nM,2013.0,Brc1ccc(C2=NN(c3ccccc3)C(c3cccc4ccccc34)C2)cc1,6.309803919971486,426.073160708,2,0,6.9580000000000055,True
+2533,CHEMBL3219502,490.0,nM,2010.0,COc1cc2ncnc(Nc3cccc(Cl)c3)c2cc1B1OC(C)(C)C(C)(C)O1,6.309803919971486,411.152099676,6,1,4.334600000000004,True
+2534,CHEMBL186580,490.0,nM,2004.0,COc1cc2ncnc(Nc3cc(NC(=O)c4ccccc4)c(F)cc3F)c2cc1OC,6.309803919971486,436.13469687599996,6,2,4.921100000000004,True
+2535,CHEMBL3753157,495.3,nM,2016.0,COc1ccc(-c2ccc(OC(F)(F)F)c(NC(=O)Nc3nccs3)c2)cn1,6.305131672017544,410.0660459360001,6,2,4.756300000000001,True
+2536,CHEMBL4092788,498.0,nM,2017.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn4c5c(cccc35)CCC4)n2)c(OC)cc1N(C)CC(=O)N(C)C,6.302770657240282,539.264487916,8,2,4.445600000000002,True
+2537,CHEMBL172973,500.0,nM,2000.0,COc1cccc(-c2cn(-c3ccccc3)c3ncnc(N)c23)c1,6.301029995663981,316.132411132,5,1,3.678300000000001,True
+2538,CHEMBL144908,500.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCNC(=O)/C(C#N)=C/c1ccc(O)c(O)c1,6.301029995663981,434.12263429599994,8,6,1.2555599999999996,True
+2539,CHEMBL76444,500.0,nM,1996.0,Cc1[nH]c2ncnc(N(C)c3cccc(Cl)c3)c2c1C,6.301029995663981,286.09852416,3,1,3.9960400000000025,True
+2540,CHEMBL543904,500.0,nM,1997.0,COc1cc2ncnc(Nc3cc(OC)c(OC)c(OC)c3)c2cc1OC.Cl,6.301029995663981,407.12479848399994,8,1,3.8382000000000027,True
+2541,CHEMBL4209588,500.0,nM,2018.0,Cc1c(C(=O)NC(CO)Cc2ccccc2)[nH]c2ccc(Cl)cc12,6.301029995663981,342.113505528,2,3,3.4631200000000018,True
+2542,CHEMBL169920,500.0,nM,2001.0,CN(C)C(=O)CN1CCC(n2cc(-c3cccc(O)c3)c3c(N)ncnc32)CC1,6.301029995663981,394.21172407200004,7,2,2.1111999999999993,True
+2543,CHEMBL77803,500.0,nM,1989.0,N#CC(C#N)=C(N)/C(C#N)=C/c1cc(O)c(O)c(Br)c1,6.301029995663981,329.975237564,6,3,2.027240000000001,True
+2544,CHEMBL293584,500.0,nM,1991.0,N#CC(C#N)=C1CCc2cc(O)c(O)cc21,6.301029995663981,212.058577496,4,2,1.8447599999999997,True
+2545,CHEMBL570918,500.0,nM,2009.0,CN(/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1)C(=O)OCCCl,6.301029995663981,418.0711791119999,7,1,5.3327000000000035,True
+2546,CHEMBL428534,500.0,nM,2002.0,COc1cc2c(Nc3ccc(C)cc3F)ncnc2cc1OCC1CCNCC1,6.301029995663981,396.19615426,6,2,4.207920000000003,True
+2547,CHEMBL396079,500.0,nM,2007.0,c1ccc(Cn2ncc3cc(Nc4ncnn5ccc(COC[C@@H]6CNCCO6)c45)ccc32)nc1,6.301029995663981,470.217872072,10,2,2.770900000000001,True
+2548,CHEMBL78700,500.0,nM,2004.0,Cc1cc2cc(Nc3ccnc4cc(-c5ccc(CNCCCO)cc5)sc34)ccc2[nH]1,6.301029995663981,442.182732452,5,4,5.968620000000005,True
+2549,CHEMBL391675,500.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(CN6CCCC6)c45)ccc32)c1,6.301029995663981,441.207721988,7,1,4.605800000000004,True
+2550,CHEMBL169757,500.0,nM,2000.0,Nc1ncnc2c1c(-c1ccccc1)cn2-c1ccccc1,6.301029995663981,286.121846448,4,1,3.6697000000000015,True
+2551,CHEMBL25450,500.0,nM,2002.0,COc1cc2c(Nc3c(F)cc(Cl)cc3F)ncnc2cc1OCC1CCNCC1,6.301029995663981,434.13211003200007,6,2,4.692000000000004,True
+2552,CHEMBL63356,500.0,nM,1994.0,Oc1cc2cc(-c3cccnc3)cnc2cc1O,6.301029995663981,238.07422756,4,2,2.7080000000000006,True
+2553,CHEMBL1254523,500.0,nM,2010.0,COc1ccc(OC)c(Cc2cc3c(N(C)c4cccc(Br)c4)nc(N)nc3n2C)c1,6.301029995663981,481.11133710800016,7,1,4.688900000000003,True
+2554,CHEMBL352954,500.0,nM,2001.0,Nc1ncnc2c1c(-c1ccccc1)cn2C1CCCC1,6.301029995663981,278.153146576,4,1,3.795600000000002,True
+2555,CHEMBL332096,508.0,nM,2003.0,Nc1ccc2ncnc(NCc3ccccc3)c2c1,6.29413628771608,250.12184644799999,4,2,2.8241000000000014,True
+2556,CHEMBL3916644,509.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(Oc4ccc5c(c4)OCO5)cc3)ncnc2cc1OC,6.293282217663242,458.15901980399997,8,2,5.251500000000004,True
+2557,CHEMBL325589,510.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3cccnc3)nc21,6.292429823902062,397.0497153960001,6,1,4.440900000000003,True
+2558,CHEMBL2070045,510.0,nM,2012.0,COc1ccc2cc(-c3nn(C(C)C)c4ncnc(N)c34)ccc2c1.Cl,6.292429823902062,369.13563794,6,1,4.240000000000003,True
+2559,CHEMBL185853,510.0,nM,2004.0,Cc1ccc(Nc2ncnn3cccc23)cc1O,6.292429823902062,240.101111004,5,2,2.486920000000001,True
+2560,CHEMBL2048790,510.0,nM,2012.0,O=C1NCc2cc(Oc3ccc(Nc4ncnc5ccn(CCO)c45)cc3Cl)ccc21,6.292429823902062,435.109817116,7,3,3.856300000000002,True
+2561,CHEMBL4225571,510.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(C4CCN(C)CC4)cc3)n2)c1,6.292429823902062,471.2382731680001,6,4,4.797900000000003,True
+2562,CHEMBL3219508,510.0,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1B(O)O,6.292429823902062,347.06442754399995,6,3,1.8543000000000003,True
+2563,CHEMBL939,515.0,nM,2002.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1,6.2881927709588075,446.15209652799996,7,1,4.275600000000003,True
+2564,CHEMBL4096014,518.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(CC)c4)nc32)C1,6.285670240254768,616.3285653920001,8,1,4.639600000000004,True
+2565,CHEMBL3775148,518.6,nM,2016.0,O=C1COc2cc3ncnc(Nc4ccccc4)c3cc2N1CCCN1CCOCC1,6.285167487566667,419.19573966,7,1,2.8211000000000013,True
+2566,CHEMBL3960911,519.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(c3)CCN4Cc3ccccn3)ncnc2cc1OC,6.284832642151543,454.21172407200004,7,2,4.688200000000003,True
+2567,CHEMBL3219503,520.0,nM,2010.0,COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1B1OC(C)(C)C(C)(C)O1,6.2839966563652006,429.14267786399995,6,1,4.473700000000004,True
+2568,CHEMBL2324873,520.0,nM,2013.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccc4ccccc4c3)C2)cc1,6.2839966563652006,345.129968608,2,1,4.542920000000003,True
+2569,CHEMBL3622652,520.2,nM,2015.0,O=C1CCN(C/C=C/C(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3cc2O[C@H]2CCOC2)CC1,6.283829652140146,539.173560244,8,2,4.4932000000000025,True
+2570,CHEMBL3923650,522.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(NS(=O)(=O)c4ccccc4)nc3)ncnc2cc1OC,6.282329496997738,478.1423241840001,8,3,3.926300000000002,True
+2571,CHEMBL3237931,525.0,nM,2014.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(NC(=O)CCN3CCCC3)c2)n1,6.279840696594043,565.2568156919999,9,2,4.850700000000003,True
+2572,CHEMBL4225565,529.0,nM,2018.0,CN1CCN(c2ccc(Nc3ncc4nc(Sc5ccccc5)n([C@H]5CC[C@H](O)CC5)c4n3)cc2)CC1,6.276544327964814,515.246729676,9,2,4.948900000000004,True
+2573,CHEMBL247916,530.0,nM,2007.0,NC1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5ccncc5)c4)c23)CC1,6.275724130399211,453.2389418640001,9,2,3.189000000000001,True
+2574,CHEMBL293991,530.0,nM,1997.0,NCCCn1ccc2c(-c3ccnc(Nc4cccc(OC(F)(F)C(F)F)c4)n3)cccc21,6.275724130399211,459.168223172,6,2,5.427400000000003,True
+2575,CHEMBL2324870,530.0,nM,2013.0,NC(=S)N1N=C(c2ccc(Cl)cc2)CC1c1ccc2ccccc2c1,6.275724130399211,365.075346192,2,1,4.887900000000003,True
+2576,CHEMBL3951754,531.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(Oc4cccnc4)cc3)ncnc2cc1OC,6.274905478918531,415.164439532,7,2,4.917800000000004,True
+2577,CHEMBL474323,533.0,nM,2008.0,COc1cc2ncnc(-c3c[nH]c4cc(F)c(C)cc34)c2cc1OC,6.273272790973428,337.12265497199996,4,1,4.242820000000003,True
+2578,CHEMBL3085277,538.0,nM,1999.0,C[C@H](Nc1ncnc2c1sc1ccccc12)c1ccccc1,6.269217724333612,305.09866848,4,1,5.017600000000003,True
+2579,CHEMBL1242385,539.0,nM,2008.0,Cn1ccc2cc(-c3nn(C4CCCC4)c4ncnc(N)c34)ccc21,6.268411234813263,332.17494464,6,1,3.6823000000000015,True
+2580,CHEMBL1242755,540.0,nM,2008.0,Nc1ncnc2c1c(-c1cnc3ccccc3c1)nn2C1CCCC1,6.267606240177032,330.159294576,6,1,3.738800000000002,True
+2581,CHEMBL93284,540.0,nM,1996.0,O=[N+]([O-])c1ccc2c(Nc3cccc(I)c3)ncnc2c1,6.267606240177032,391.9770235280001,5,1,3.8862000000000014,True
+2582,CHEMBL3233764,542.0,nM,2014.0,O=C(CN1CCC(CCO)CC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,6.2660007134616125,463.124501876,7,3,4.260300000000003,True
+2583,CHEMBL3092318,543.0,nM,2013.0,O=C(Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1)N1CC(O)C1,6.265200170411153,473.126610052,7,3,3.5420000000000016,True
+2584,CHEMBL3633775,543.0,nM,2015.0,NC(=O)Nc1ccc2ncnc(Nc3ccc(Oc4ccc(Cl)c(Cl)c4)c(Cl)c3)c2c1,6.265200170411153,473.021307728,5,3,6.616500000000002,True
+2585,CHEMBL3092312,544.0,nM,2013.0,COC(CCNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1)OC,6.26440110030182,519.1684748639999,8,3,4.464100000000002,True
+2586,CHEMBL606964,545.0,nM,2006.0,COc1ccc(N2Cc3cnc(Nc4ccc(F)cc4)nc3N([C@@H]3CC[C@@H](O)C3)C2=O)cc1,6.263603497723357,449.186317848,6,2,4.227900000000003,True
+2587,CHEMBL3234736,550.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1cccnc1,6.259637310505756,511.219509796,5,2,4.660820000000004,True
+2588,CHEMBL327023,550.0,nM,2003.0,N#Cc1cnc2ccc(NC(=O)C#CCN3CCSCC3)cc2c1Nc1cccc(Br)c1,6.259637310505756,505.05719336000004,6,2,4.603280000000003,True
+2589,CHEMBL308582,550.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3cccc(F)c3)c2c1C,6.259637310505756,256.112424636,3,2,3.457440000000002,True
+2590,CHEMBL1241578,550.0,nM,2008.0,CC(C)n1nc(-c2ccc(Br)c(O)c2)c2c(N)ncnc21,6.259637310505756,347.0381721680001,6,2,3.124500000000001,True
+2591,CHEMBL2426282,550.0,nM,2013.0,C=CC(=O)Nc1ccc(OC)c(Nc2ncc(Cl)c(-c3c[nH]c4ccccc34)n2)c1,6.259637310505756,419.11490249600007,5,3,5.155000000000003,True
+2592,CHEMBL4225777,556.0,nM,2018.0,CN(C)CCOc1ccc(Nc2ncc3nc(Sc4ccccc4)n(C4CCOCC4)c3n2)cc1,6.254925208417943,490.2150952,9,1,5.013000000000004,True
+2593,CHEMBL591288,560.0,nM,2010.0,Oc1ccc(CN(Cc2cc(Cl)cc(Cl)c2O)C(=S)Nc2ccccc2)cc1,6.251811972993798,432.04660417599996,3,3,5.803800000000004,True
+2594,CHEMBL592480,560.0,nM,2010.0,O=C1CSC(N/N=C/c2cc(Cl)ccc2O)=N1,6.251811972993798,269.002575176,5,2,1.5984999999999998,True
+2595,CHEMBL73710,560.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3ccc(F)cc3)c2c1C,6.251811972993798,256.112424636,3,2,3.457440000000002,True
+2596,CHEMBL3612570,560.0,nM,2015.0,COCCn1c(=O)oc2cc3ncnc(Nc4cccc(C(C)=O)c4)c3cc21,6.251811972993798,378.13280505599994,8,1,3.130300000000002,True
+2597,CHEMBL340660,560.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4csc(N)n4)c3)c2cc1OCC,6.251811972993798,407.141595912,8,2,4.876500000000004,True
+2598,CHEMBL117326,560.0,nM,2003.0,C=C(CN(C)C)C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cc1OCC,6.251811972993798,467.15243087600004,6,2,5.097580000000004,True
+2599,CHEMBL55204,560.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)c1ccc(F)cc1,6.251811972993798,283.0644714,4,2,3.0267800000000014,True
+2600,CHEMBL3676347,568.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(F)c3F)ncnc2cc1OCCNC(=O)CCCN(C)C,6.2456516642889826,576.129607264,7,3,4.375400000000003,True
+2601,CHEMBL307026,570.0,nM,1996.0,Cc1cccc(Nc2ncnc3[nH]c(C)c(C)c23)c1,6.2441251443275085,252.13749651199998,3,2,3.6267600000000018,True
+2602,CHEMBL170724,570.0,nM,2001.0,COc1ccc(-c2cn(C3CCCC3)c3ncnc(N)c23)cc1,6.2441251443275085,308.16371126,5,1,3.8042000000000016,True
+2603,CHEMBL3921664,570.0,nM,2016.0,CC(C)S(=O)(=O)c1ccccc1Nc1nc(N/N=C/c2ccc(F)cc2)ncc1Cl,6.2441251443275085,447.093201748,7,2,4.640800000000003,True
+2604,CHEMBL3219505,570.0,nM,2010.0,CC1(C)OB(c2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)OC1(C)C,6.2441251443275085,399.13211318,5,1,4.465100000000003,True
+2605,CHEMBL246493,570.0,nM,2007.0,Fc1cccc(COc2ccc(Nc3ncnn4ccc(COC[C@@H]5CNCCO5)c34)cc2Cl)c1,6.2441251443275085,497.16299556,8,2,4.349400000000002,True
+2606,CHEMBL2064389,570.0,nM,2012.0,O=c1oc2cc3ncnc(Nc4ccc(F)c(F)c4)c3cc2n1CCCN1CCOCC1,6.2441251443275085,441.161245972,8,1,3.2818000000000014,True
+2607,CHEMBL2070191,570.0,nM,2012.0,Clc1cccc(Nc2ncnc3ccc(NCc4ccc5c(c4)OCO5)cc23)c1,6.2441251443275085,404.10400346399996,6,2,5.367600000000002,True
+2608,CHEMBL1242475,571.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc3[nH]ncc3c1)nn2C1CCCC1,6.243363891754153,319.15454354400003,6,2,3.0669000000000013,True
+2609,CHEMBL328244,574.0,nM,1996.0,Nc1ccc2ncnc(Nc3cccc(C(F)(F)F)c3)c2c1,6.241088107602026,304.093581012,4,2,3.974400000000001,True
+2610,CHEMBL1241491,575.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc3occc3c1)nn2C1CCCC1,6.2403321553103694,319.143310164,6,1,3.9368000000000025,True
+2611,CHEMBL3234737,575.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1ccccn1,6.2403321553103694,511.219509796,5,2,4.660820000000004,True
+2612,CHEMBL1242198,576.0,nM,2008.0,CC(C)n1nc(-c2cc(O)cc(F)c2)c2c(N)ncnc21,6.239577516576787,287.118238288,6,2,2.501099999999999,True
+2613,CHEMBL92824,577.0,nM,1995.0,FC(F)(F)c1cccc(Nc2ncnc3ccccc23)c1,6.238824186844269,289.08268198,3,1,4.392200000000002,True
+2614,CHEMBL300083,578.0,nM,1996.0,Nc1cc2ncnc(NCc3ccccc3)c2cn1,6.238072161579471,251.11709541599998,5,2,2.2191,True
+2615,CHEMBL1242115,579.0,nM,2008.0,CC(C)n1nc(-c2cccc(C(=O)NC3=NCCS3)c2)c2c(N)ncnc21,6.2373214362725635,381.1371792280001,8,2,2489,True
+2616,CHEMBL601040,580.0,nM,2010.0,Cc1ccc(NC(=O)c2ccc(N(CCCl)CCCl)cc2)cc1,6.236572006437062,350.09526861999996,2,1,4.531320000000004,True
+2617,CHEMBL3894726,587.0,nM,2016.0,COc1ccc(/C=N/Nc2ncc(Cl)c(Nc3ccccc3S(=O)(=O)C(C)C)n2)cc1,6.231361898752387,459.11318824399996,8,2,4.510300000000002,True
+2618,CHEMBL333851,588.0,nM,1995.0,COc1cc2c(NCc3ccccc3)ncnc2cc1O,6.230622673923861,281.11642672,5,2,2.9561000000000015,True
+2619,CHEMBL3676390,589.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CC,6.229884705212897,501.08117985200005,6,3,4.3045000000000035,True
+2620,CHEMBL2347968,589.0,nM,2013.0,OC[C@@H](Nc1ncnc2oc(-c3ccccc3)c(Cl)c12)c1ccccc1,6.229884705212897,365.093104432,5,2,4.688700000000003,True
+2621,CHEMBL3628800,590.0,nM,2015.0,Fc1ccc(Oc2ncnc3ccccc23)cc1Cl,6.229147988357855,274.030918776,3,0,4.214600000000002,True
+2622,CHEMBL3219504,590.0,nM,2010.0,CC1(C)OB(c2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)OC1(C)C,6.229147988357855,381.141534992,5,1,4.326000000000003,True
+2623,CHEMBL1830276,590.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccccc1)c1ccc(Cl)cc1,6.229147988357855,315.059696128,2,2,3.590700000000002,True
+2624,CHEMBL281300,590.0,nM,2003.0,C=CC(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.229147988357855,392.0272731360001,4,2,4.737080000000002,True
+2625,CHEMBL2312654,590.0,nM,2013.0,Cc1cc(-c2cnc(Nc3cc(Cl)cc(Cl)c3)nc2NC2CCC(N(C)C)CC2)on1,6.229147988357855,460.15451481200006,7,2,5.775120000000004,True
+2626,CHEMBL3893810,593.0,nM,2016.0,CC(C)S(=O)(=O)c1ccccc1Nc1nc(N/N=C/c2ccc(C(F)(F)F)cc2)ncc1Cl,6.226945306635737,497.090008188,7,2,5.520500000000004,True
+2627,CHEMBL3941175,593.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(NS(=O)(=O)c4ccccc4)c(F)c3)ncnc2cc1OC,6.226945306635737,495.13765340400005,7,3,4.6704000000000025,True
+2628,CHEMBL3774712,594.5,nM,2016.0,Cc1ccc(Nc2ncnc3cc4c(cc23)N(CCCN2CCOCC2)C(=O)CO4)cc1,6.22584814104529,433.21138972399996,7,1,3.129520000000002,True
+2629,CHEMBL4225828,596.0,nM,2018.0,CNC(=O)c1ccc(Sc2cccc(NC(=S)Nc3ccc(Cl)c(C(F)(F)F)c3)c2)nc1,6.224753740259764,496.040615472,4,3,6.073500000000003,True
+2630,CHEMBL166765,600.0,nM,2001.0,Nc1ncnc2c1c(-c1ccc(O)cc1)cn2C1CCC1,6.221848749616356,280.132411132,5,2,3.1111000000000013,True
+2631,CHEMBL555797,600.0,nM,1997.0,COc1cc2ncnc(Nc3ccc4c(c3)CCC4)c2cc1OC.Cl,6.221848749616356,357.12440455999996,5,1,4.3011000000000035,True
+2632,CHEMBL358746,600.0,nM,1996.0,N#C/C(=C\c1cc(O)c(O)c(O)c1)C(=O)NCCCCNC(=O)/C(C#N)=C/c1cc(O)c(O)c(O)c1,6.221848749616356,494.14376366399995,10,8,1.4469599999999991,True
+2633,CHEMBL173478,600.0,nM,2000.0,Nc1ncnc2c1c(-c1ccccc1)cn2-c1cccc(CO)c1,6.221848749616356,316.13241113199996,5,2,3.1620000000000017,True
+2634,CHEMBL3416630,600.0,nM,2015.0,OC[C@@H](Nc1ncnc2sc(-c3ccc(CN4CCNCC4)cc3)cc12)c1ccccc1,6.221848749616356,445.19363148400004,7,3,3.9090000000000025,True
+2635,CHEMBL4065984,600.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(OC)c4)nc32)C1,6.221848749616356,618.3078299480001,9,1,4.085800000000003,True
+2636,CHEMBL3746473,600.0,nM,2016.0,CC(=O)N1N=C(c2ccc([N+](=O)[O-])cc2)CC1c1ccc(C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,6.221848749616356,506.15499704399997,10,0,3.562520000000003,True
+2637,CHEMBL144589,600.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCCCNC(=O)/C(C#N)=C/c1ccc(O)c(O)c1,6.221848749616356,462.15393442399994,8,6,2.03576,True
+2638,CHEMBL442749,600.0,nM,2004.0,c1nc(Nc2ccc3[nH]ccc3c2)c2sccc2n1,6.221848749616356,266.06261732,4,2,3.9162000000000017,True
+2639,CHEMBL538909,600.0,nM,1992.0,N#C/C(=C/c1cc(Cc2ccccc2)c(O)c(Cc2ccccc2)c1)C(N)=O,6.221848749616356,368.15247788,3,2,3.9660800000000034,True
+2640,CHEMBL3416631,600.0,nM,2015.0,OCCN1CCN(Cc2ccc(-c3cc4c(N[C@H](CO)c5ccccc5)ncnc4s3)cc2)CC1,6.221848749616356,489.21984623200007,8,3,3.6137000000000024,True
+2641,CHEMBL3905284,601.0,nM,2016.0,COc1cccc(/C=N/Nc2ncc(Cl)c(Nc3ccccc3S(=O)(=O)C(C)C)n2)c1,6.221125527997262,459.11318824399996,8,2,4.510300000000003,True
+2642,CHEMBL53552,603.0,nM,1996.0,c1ccc(CNc2ncnc3cccnc23)cc1,6.219682687859849,236.106196384,4,1,2.6369000000000007,True
+2643,CHEMBL57323,610.0,nM,1997.0,Cc1cccc(C)c1-c1cc2cnc(N)nc2nc1NC(=O)NC(C)(C)C,6.214670164989233,364.20115938799995,5,3,3.8108400000000016,True
+2644,CHEMBL1233882,610.0,nM,2008.0,CC(C)n1nc(-c2ccc3ncccc3c2)c2c(N)ncnc21,6.214670164989233,304.143644512,6,1,3.2046,True
+2645,CHEMBL194349,610.0,nM,2005.0,CCOC(=O)c1cn2ncnc(Nc3ccc(Oc4ccccc4)cc3)c2c1CC,6.214670164989233,402.16919056399996,7,1,5.004300000000003,True
+2646,CHEMBL3975598,611.0,nM,2017.0,COC(=O)CNC(=O)c1ccc(Nc2ncnc3cc(OCCCN4CCN(C)CC4)c(OC)cc23)cc1,6.213958789757446,522.259068188,10,2,2.3011,True
+2647,CHEMBL598407,614.0,nM,2010.0,COc1cc2ncnc(N[C@@H](C)c3ccc(Cl)cc3)c2cc1OCCCCCCC(=O)NO,6.211831628858832,472.18773308799996,7,3,5.299600000000003,True
+2648,CHEMBL1173718,620.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccc(-c2ccccc2)cc1,6.207608310501746,377.13755608800005,6,0,4.023320000000003,True
+2649,CHEMBL472544,620.0,nM,2008.0,Nc1ncnc(Nc2ccc(OCc3ccccc3)c(Cl)c2)c1C(=O)NNC(=O)CCN1CCOCC1,6.207608310501746,525.189130056,9,4,2.5181000000000004,True
+2650,CHEMBL245868,620.0,nM,2007.0,CN(C)CCCOCc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccc(F)c4)c3)c12,6.207608310501746,473.23393673600003,8,1,4.4783000000000035,True
+2651,CHEMBL4102288,626.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCOCC5)c(C)c4)nc32)C1,6.2034256667895695,589.281280852,8,1,4.470420000000003,True
+2652,CHEMBL3416593,629.0,nM,2015.0,COc1ccccc1-c1cc2c(N[C@@H](CO)c3ccccc3)ncnc2s1,6.201349354554732,377.11979784800013,6,2,4.512400000000002,True
+2653,CHEMBL1821875,630.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc([N+](=O)[O-])cc3)C2)cc1C,6.200659450546419,488.107374592,6,0,7.344240000000005,True
+2654,CHEMBL572028,630.0,nM,2009.0,CC(=O)OCOC(=O)N(C)/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.200659450546419,428.099980704,9,1,4.614500000000003,True
+2655,CHEMBL2070197,630.0,nM,2012.0,Brc1cccc(Nc2ncnc3ccc(NCc4ccc5c(c4)OCO5)cc23)c1,6.200659450546419,448.053487884,6,2,5.476700000000002,True
+2656,CHEMBL2179124,631.0,nM,2017.0,Fc1ccc(-c2nc(-c3ccccc3)[nH]c2-c2ccnc3[nH]ccc23)cc1,6.199970640755867,354.12807470000007,2,2,5.4261000000000035,True
+2657,CHEMBL3092306,635.0,nM,2013.0,CN(C)CCNC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1,6.197226274708023,488.173894592,7,3,4.016700000000002,True
+2658,CHEMBL1242666,638.0,nM,2008.0,CC(C)n1nc(-c2ccc3c(C=O)c[nH]c3c2)c2c(N)ncnc21,6.195179321278838,320.138559132,6,2,2.9501999999999997,True
+2659,CHEMBL3237929,638.0,nM,2014.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(NC(=O)CCN(C)C)c2)n1,6.195179321278838,539.241165628,9,2,4.316500000000002,True
+2660,CHEMBL1683956,640.0,nM,2011.0,CCc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1C,6.1938200260161125,371.120068128,4,1,5.462520000000003,True
+2661,CHEMBL246492,640.0,nM,2007.0,Fc1cccc(Cn2ncc3cc(Nc4ncnn5ccc(COC[C@@H]6COCCN6)c45)ccc32)c1,6.1938200260161125,487.21320129199995,9,2,3.5150000000000015,True
+2662,CHEMBL4226562,641.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2nc(Nc3ccc(N4CCC(N5CCOCC5)CC4)cc3OC)ncc2Cl)c1,6.193141970481182,606.2469792800001,9,4,4.951700000000004,True
+2663,CHEMBL4095253,642.7,nM,2017.0,C=CS(=O)(=O)N1CCC[C@@H]1Cn1cc(-c2ccc3c(c2)OCO3)c2c(N)ncnc21,6.1919917000896,427.1314251520001,8,1,2.3468999999999998,True
+2664,CHEMBL4227278,644.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(N4CCOCC4)cc3)n2)c1,6.191114132640188,459.20188766000007,7,4,3.825300000000002,True
+2665,CHEMBL3218424,650.0,nM,2010.0,OB(O)c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.187086643357143,299.063284672,5,3,1.7065999999999992,True
+2666,CHEMBL3975588,650.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccccc3OC)ncc2Cl)c1,6.187086643357143,396.098918084,6,2,4.799000000000002,True
+2667,CHEMBL323630,650.0,nM,2003.0,CN(C)C/C=C/C(=O)Nc1ccc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2c1,6.187086643357143,423.126216128,5,2,4.6988800000000035,True
+2668,CHEMBL3263373,650.0,nM,2014.0,Cc1ccc(C2=NN(C3=NC(c4ccccc4)CS3)C(c3ccc4ccccc4c3)C2)cc1C,6.187086643357143,461.192568864,4,0,7.451840000000007,True
+2669,CHEMBL4208712,650.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccccc2NC(=O)CCO)n1,6.187086643357143,512.1938810879999,9,3,3.7472000000000016,True
+2670,CHEMBL3903707,650.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccccc3OC)ncc2Cl)c1,6.187086643357143,395.114902496,6,3,4.750300000000003,True
+2671,CHEMBL184750,650.0,nM,2004.0,Cc1cc2c(Nc3ccc(C)c(O)c3)ncnn2c1,6.187086643357143,254.116761068,5,2,2.7953400000000004,True
+2672,CHEMBL3919271,650.0,nM,2016.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3cccc(OC)c3OC)ncc2Cl)c1,6.187086643357143,425.12546718,7,3,4.758900000000002,True
+2673,CHEMBL1934621,650.0,nM,2012.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1C#Cc1ccccc1,6.187086643357143,443.120068128,4,1,6.299920000000005,True
+2674,CHEMBL3894076,650.0,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3cccc(OC)c3OC)ncc2Br)c1,6.187086643357143,470.05896718800005,7,2,4.916700000000003,True
+2675,CHEMBL3671537,652.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC(=O)NCCN(CC)CC,6.1857524042680785,558.139029076,7,3,4.2363000000000035,True
+2676,CHEMBL77342,657.0,nM,2004.0,Cc1cc2cc(Nc3ccnc4cc(-c5ccc(CNCCOCCO)cc5)sc34)ccc2[nH]1,6.18243463044022,472.193297136,6,4,5.595120000000005,True
+2677,CHEMBL2325087,660.0,nM,2013.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc2ccccc2c1,6.180456064458131,399.03637384,2,1,5.541300000000003,True
+2678,CHEMBL1645469,660.0,nM,2011.0,Cc1ccccc1Nc1ncnn2ccc(CN3CCC(N)CC3)c12,6.180456064458131,336.206244768,6,2,2.7044200000000007,True
+2679,CHEMBL91428,660.0,nM,1997.0,COc1cc2ncnc(Nc3cc4ccccc4cn3)c2cc1OC,6.180456064458131,332.127325752,6,1,3.9388000000000023,True
+2680,CHEMBL251315,662.0,nM,2007.0,CCOc1cc2ncnc(C#C[C@](C)(Cc3ccccc3)N3CCC(C(=O)O)CC3)c2cc1OCC,6.179142010560301,487.24710653599993,6,1,4.576700000000003,True
+2681,CHEMBL1242026,663.0,nM,2008.0,Cc1ccc(-c2nn(C(C)C)c3ncnc(N)c23)cc1O,6.178486471595226,283.143310164,6,2,2.6704200000000005,True
+2682,CHEMBL589560,670.0,nM,2010.0,Oc1c(Cl)cccc1CN(Cc1ccc(F)cc1)C(=S)Nc1ccccc1,6.173925197299173,400.081240096,2,2,5.583900000000003,True
+2683,CHEMBL542887,670.0,nM,1995.0,C=C(CN(C)C)C(=O)c1ccc(OCc2ccccc2)c(O)c1.Cl,6.173925197299173,347.128821244,4,1,3.6935000000000033,True
+2684,CHEMBL111434,670.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3cccc(Br)c3)nc21,6.173925197299173,473.9649784960001,5,1,5.8084000000000024,True
+2685,CHEMBL1645465,670.0,nM,2011.0,C#Cc1cccc(Nc2ncnn3ccc(COC[C@@H]4CNCCO4)c23)c1,6.173925197299173,363.16952491200004,7,2,1.9591999999999998,True
+2686,CHEMBL382041,671.0,nM,2006.0,COCCOc1cc(OC2CCOCC2)c2c(Nc3ccc(F)c(Cl)c3)ncnc2c1,6.173277479831008,447.13611211600005,7,1,4.7489000000000035,True
+2687,CHEMBL4213609,675.0,nM,2017.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cn(C)nc3OC)c3nc[nH]c3n2)C[C@H]1F,6.170696227168975,401.17239910000006,9,3,0.6674999999999993,True
+2688,CHEMBL208240,676.0,nM,2006.0,Cc1cccc(Nc2ncnc3ccc(NC(=O)NCCCl)cc23)c1,6.170053304058364,355.119987876,4,3,4.0421200000000015,True
+2689,CHEMBL3234755,680.0,nM,2014.0,CN1CCN(Cc2ccc(NC(=O)c3cccc(NC(=O)c4cnc5[nH]ccc5c4)c3)cc2C(F)(F)F)CC1,6.167491087293763,536.2147587640001,5,3,4.833700000000004,True
+2690,CHEMBL2325090,680.0,nM,2013.0,Clc1ccc(C2=NN(c3ccccc3)C(c3cccc4ccccc34)C2)cc1,6.167491087293763,382.123676288,2,0,6.848900000000005,True
+2691,CHEMBL291701,684.0,nM,1996.0,Fc1ccc2c(Nc3cccc(Br)c3)ncnc2n1,6.1649438982798825,317.9916365760001,4,1,3.6700000000000017,True
+2692,CHEMBL54475,688.0,nM,1996.0,Brc1cccc(Nc2ncnc3ncccc23)c1,6.162411561764488,300.00105838800005,4,1,3.530900000000001,True
+2693,CHEMBL1221700,689.0,nM,2007.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(C(C)(C)C)cc3)c2c1,6.161780778092375,346.179361324,4,2,4.795400000000003,True
+2694,CHEMBL6246,690.0,nM,2012.0,O=c1oc2c(O)c(O)cc3c(=O)oc4c(O)c(O)cc1c4c23,6.161150909262744,302.006267152,8,4,1.3127999999999997,True
+2695,CHEMBL3758585,690.0,nM,2016.0,COc1cc2c(Nc3ccc(NC(=O)c4ccc(C)cc4)cc3)ncnc2cc1OCCCN1CCN(C)CC1,6.161150909262744,540.2848890120001,8,2,4.959020000000005,True
+2696,CHEMBL436511,690.0,nM,2005.0,CN1CCC(Oc2cccc3ncnc(Nc4ccc(OCc5cnccn5)c(Cl)c4)c23)CC1,6.161150909262744,476.17275172000006,8,1,4.868800000000004,True
+2697,CHEMBL245277,690.0,nM,2007.0,C[C@@H](c1ccccc1)n1ncc2cc(Nc3ncnn4ccc(COC[C@@H]5CNCCO5)c34)ccc21,6.161150909262744,483.238273168,9,2,3.9369000000000023,True
+2698,CHEMBL195204,698.0,nM,2005.0,CN1CCC(Oc2cccc3ncnc(Nc4ccc(OCc5cscn5)c(Cl)c4)c23)CC1,6.156144577376839,481.133923688,8,1,5.535300000000005,True
+2699,CHEMBL3671564,698.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)N1CCNCC1,6.156144577376839,557.1186279800002,7,4,3.3931000000000022,True
+2700,CHEMBL3903249,698.3,nM,2015.0,CN(C)C/C=C/C(=O)N1CCC[C@H]1Cn1nc(-c2ccc(Oc3ccccc3)cc2)c2c(N)ncnc21,6.155957957958983,497.2539232320001,8,1,3.976600000000002,True
+2701,CHEMBL2070048,700.0,nM,2012.0,CCOc1ccc2cc(-c3nn(C(C)C)c4ncnc(N)c34)ccc2c1.Cl,6.154901959985742,383.151288004,6,1,4.630100000000003,True
+2702,CHEMBL53898,700.0,nM,1999.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCCc1ccccc1,6.154901959985742,322.131742436,4,3,2.753780000000001,True
+2703,CHEMBL176309,700.0,nM,2000.0,Nc1ncnc2c1c(-c1cccc(Cl)c1)cn2-c1ccccc1,6.154901959985742,320.082874096,4,1,4.323100000000002,True
+2704,CHEMBL144760,700.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCCCCCNC(=O)/C(C#N)=C/c1ccc(O)c(O)c1,6.154901959985742,490.185234552,8,6,2.8159600000000014,True
+2705,CHEMBL521887,700.0,nM,2008.0,Cc1ccc(NC(=O)c2ccc(CN3CCN(C)CC3)cc2)cc1-c1ccc2ccncc2c1,6.154901959985742,450.24196158,4,1,5.209920000000005,True
+2706,CHEMBL367442,700.0,nM,2000.0,Nc1ncnc2c1c(-c1ccccc1)cn2-c1ccc(CO)cc1,6.154901959985742,316.13241113199996,5,2,3.162000000000001,True
+2707,CHEMBL552634,700.0,nM,1995.0,C=C(CN(C)C)C(=O)c1ccc(OS(=O)(=O)c2ccc(C(=O)N(C)C)cc2)cc1.Cl,6.154901959985742,452.11727058,6,0,2.8784000000000023,True
+2708,CHEMBL1830271,700.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccc(OCc2ccccc2)cc1)c1ccccc1,6.154901959985742,387.140533292,3,2,4.516300000000004,True
+2709,CHEMBL144842,700.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCCCCNC(=O)/C(C#N)=C/c1ccc(O)c(O)c1,6.154901959985742,476.16958448799994,8,6,2.425860000000001,True
+2710,CHEMBL7939,700.0,nM,1994.0,O=C1NC(=O)c2cc(Nc3ccc(F)cc3)c(Nc3ccc(F)cc3)cc21,6.154901959985742,365.097583096,4,3,4.335600000000002,True
+2711,CHEMBL67027,700.0,nM,1994.0,COc1ccc(/C=C(\C#N)c2cccnc2)cc1OC,6.154901959985742,266.105527688,4,0,3.162980000000001,True
+2712,CHEMBL242131,704.0,nM,2007.0,CN(C)C/C=C/C(=O)Nc1ccc2ncnc(Nc3ccc(Br)cc3F)c2c1,6.152427340857887,443.07570054800004,5,2,4.331300000000003,True
+2713,CHEMBL231885,710.0,nM,2007.0,CC(=O)N1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.1487416512809245,498.22918570400003,8,1,3.674100000000002,True
+2714,CHEMBL213560,710.0,nM,2006.0,O=C1NC(=O)N(CCc2ccccc2)/C1=C/c1ccc(O)cc1,6.1487416512809245,308.11609237199997,3,2,2.5276000000000005,True
+2715,CHEMBL2325098,710.0,nM,2013.0,Brc1ccc(C2=NN(c3ccccc3)C(c3ccc4ccccc4c3)C2)cc1,6.1487416512809245,426.073160708,2,0,6.9580000000000055,True
+2716,CHEMBL4204566,713.0,nM,2017.0,C=CC(=O)N[C@H]1CN(c2nc(Nc3cnn(C)c3)c3ncn(C(C)C)c3n2)C[C@@H]1F,6.146910470148134,413.20878460800003,9,2,1.7131999999999992,True
+2717,CHEMBL3939300,714.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc4c(ccn4Cc4cccnc4)c3)ncnc2cc1OC,6.146301788223826,452.19607400800004,7,2,5.128500000000003,True
+2718,CHEMBL4093535,715.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)C(C)C5)c(C)c4)nc32)C1,6.145693958198919,616.3285653920001,8,1,4.774120000000004,True
+2719,CHEMBL462162,720.0,nM,2009.0,COc1cc(Nc2ncnc3[nH]ccc23)ccc1-c1nc2ccccc2s1,6.142667503568732,373.09973110000004,6,2,4.986800000000002,True
+2720,CHEMBL1271950,720.0,nM,2010.0,OC[C@@H](Nc1ncnc2sc3c(c12)CCCC3)c1ccccc1,6.142667503568732,325.124883228,5,2,3.715600000000002,True
+2721,CHEMBL126996,720.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4cocn4)c3)c2cc1OCC,6.142667503568732,376.15354049999996,7,1,4.825800000000004,True
+2722,CHEMBL4072392,720.0,nM,2017.0,CC(=O)c1ccccc1-n1c(-c2ccccc2)nc2cc(Cl)ccc2c1=O,6.142667503568732,374.08220539999996,4,0,4.908700000000003,True
+2723,CHEMBL572031,720.0,nM,2009.0,C=COC(=O)N(C)/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.142667503568732,382.0945014,7,1,5.237400000000003,True
+2724,CHEMBL4066684,725.3,nM,2017.0,Cc1cc(=O)n(-c2ccc(F)cc2)nc1C(=O)Nc1ccc(Oc2ccnc3[nH]ccc23)c(F)c1,6.139482322538253,473.129945844,6,2,4.740020000000002,True
+2725,CHEMBL1257912,726.0,nM,2010.0,CC(=O)Nc1ccc2c(c1)C(c1ccccc1Cl)=Nc1c[nH]nc1N2,6.139063379299906,351.0886877480001,4,3,4.247600000000001,True
+2726,CHEMBL166766,730.0,nM,2001.0,Nc1ncnc2c1c(-c1ccccc1)cn2C1CCC1,6.136677139879544,264.137496512,4,1,3.4055000000000017,True
+2727,CHEMBL92006,730.0,nM,1997.0,COc1cc2ncnc(/N=N/c3ccc(F)c(Cl)c3)c2cc1OC,6.136677139879544,346.06328152399993,6,0,4.854900000000002,True
+2728,CHEMBL3797963,730.5,nM,2016.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(S(C)(=O)=O)CC4)cc3OC)ncc2SC)c1,6.136379779729684,570.1719100600001,10,2,3.9491000000000023,True
+2729,CHEMBL153409,732.0,nM,1999.0,Brc1cccc(Nc2ncnc3c2sc2ncccc23)c1,6.135488918941608,355.973129388,5,1,4.745600000000001,True
+2730,CHEMBL1242295,734.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc3[nH]ccc3c1)nn2C1CCCC1,6.134303940083929,318.159294576,5,2,3.6719000000000026,True
+2731,CHEMBL1784637,736.0,nM,2011.0,CNC(=O)c1ncc(C#Cc2cc(C(=O)Nc3ccc(CN4CCN(CCO)CC4)c(C(F)(F)F)c3)ccc2C)n1C,6.133122185662501,582.256623576,7,3,2.868920000000001,True
+2732,CHEMBL2216827,737.0,nM,2017.0,C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(Oc4ccnc(C(=O)NC)c4)cc3)ncc2F)c1,6.132532512140949,499.17681578400004,8,4,4.774300000000002,True
+2733,CHEMBL2152252,739.0,nM,2012.0,CNC(=O)c1nc(-c2ccc(Cl)c(S(=O)(=O)Nc3cccc(F)c3F)c2)cnc1N,6.131355561605173,453.0473944280001,6,3,2.8178,True
+2734,CHEMBL355019,740.0,nM,2001.0,COC(=O)CN1CCC(n2cc(-c3cccc(O)c3)c3c(N)ncnc32)C1,6.130768280269023,367.16443953200013,8,2,1.8058999999999992,True
+2735,CHEMBL149512,740.0,nM,1999.0,Brc1cccc(Nc2ncnc3c2oc2ccccc23)c1,6.130768280269023,339.00072403999997,4,1,4.882100000000002,True
+2736,CHEMBL152984,742.0,nM,1999.0,Cn1c2ccccc2c2c(Nc3cccc(Br)c3)ncnc21,6.1295960947209736,352.03235851600004,4,1,4.627600000000002,True
+2737,CHEMBL3916141,747.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(CCc4ccccc4)cc3)ncnc2cc1OC,6.126679398184601,426.205576072,5,2,5.515700000000004,True
+2738,CHEMBL589589,750.0,nM,2010.0,CC(C)c1ccc(NC(=O)c2ccc(N(CCCl)CCCl)cc2)cc1,6.1249387366083,378.126568748,2,1,5.346300000000005,True
+2739,CHEMBL116547,750.0,nM,1993.0,COc1cc(/C=C(\C#N)C(=O)c2ccc(O)c(O)c2)cc(CSCc2ccccc2)c1O,6.1249387366083,447.114043772,7,3,5.035280000000005,True
+2740,CHEMBL355269,750.0,nM,2001.0,COc1cccc(-c2cn(C3CCN(CC(=O)N(C)C)CC3)c3ncnc(N)c23)c1,6.1249387366083,408.22737413600004,7,1,2.4141999999999992,True
+2741,CHEMBL1242199,751.0,nM,2008.0,Nc1ncnc2c1c(-c1cc(O)cc(F)c1)nn2C1CCCC1,6.124360062995832,313.133888352,6,2,3.035300000000001,True
+2742,CHEMBL4288648,751.0,nM,2018.0,O=C1Nc2ccc(S(=O)(=O)N3CCOCC3)cc2/C1=N/c1ccc(O)cc1,6.124360062995832,387.088891644,6,2,1486,True
+2743,CHEMBL4285894,752.0,nM,2018.0,Cc1oc2ncnc(Nc3cccc(Br)c3)c2c1C(=O)O,6.123782159408357,346.9905532799999,5,2,3.735520000000002,True
+2744,CHEMBL4293134,754.0,nM,2018.0,CCOc1ccc(Nc2cc(NC(=O)c3ccccc3)ncn2)cc1,6.122628654130226,334.14297581600005,5,2,3.871200000000001,True
+2745,CHEMBL117710,756.0,nM,1995.0,Brc1cccc(Oc2ncnc3ccccc23)c1,6.121478204498794,299.989825008,3,0,4.184600000000002,True
+2746,CHEMBL1242572,760.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc3cn[nH]c3c1)nn2C1CCCC1,6.1191864077192095,319.15454354400003,6,2,3.0669000000000013,True
+2747,CHEMBL3904787,763.0,nM,2017.0,COC(=O)CNC(=O)c1ccc(Nc2ncnc3cc(OCCCN4CCOCC4)c(OC)cc23)cc1,6.117475462045118,509.22743371199994,10,2,2.3858999999999995,True
+2748,CHEMBL1242289,768.0,nM,2008.0,CCOc1ccc(-c2nn(C3CCCC3)c3ncnc(N)c23)cc1O,6.114638779968487,339.169524912,7,2,3.2949000000000015,True
+2749,CHEMBL570709,770.0,nM,2009.0,CN(/N=N/c1ccc2ncnc(Nc3cccc(Cl)c3)c2c1)C(=O)Oc1ccc([N+](=O)[O-])cc1,6.113509274827518,477.0952296719999,9,1,6.064500000000003,True
+2750,CHEMBL89940,770.0,nM,1996.0,Nc1ccc2ncnc(Nc3ccccc3)c2c1,6.113509274827518,236.106196384,4,2,2.9556000000000004,True
+2751,CHEMBL2426278,770.0,nM,2013.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3c[nH]c4ccccc34)n2)c(OC)cc1N1CCN(C)CC1,6.113509274827518,517.199300816,7,3,4.906800000000004,True
+2752,CHEMBL3233766,770.0,nM,2014.0,O=C(CN1CCN(CCO)CC1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,6.113509274827518,464.11975084400007,8,3,2.7758000000000003,True
+2753,CHEMBL1242750,775.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2C1CCCCCC1,6.110698297493689,341.16518848,6,2,3.815500000000002,True
+2754,CHEMBL4276965,779.0,nM,2018.0,COc1ccc(OC)c(Nc2cc(Nc3ccc(S(N)(=O)=O)cc3)ncn2)c1,6.108462542327437,401.1157750880001,8,3,2.6284,True
+2755,CHEMBL330668,780.0,nM,1997.0,COc1cc2ncnc(Nc3cnc4ccccc4n3)c2cc1OC,6.107905397309519,333.12257472,7,1,3.333800000000002,True
+2756,CHEMBL407534,780.0,nM,2007.0,O=C(O)/C=C/c1cc(CO)ccc1CO,6.107905397309519,208.073558864,3,3,0.7689999999999999,True
+2757,CHEMBL234580,780.0,nM,2007.0,O=C1CNCCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)C1,6.107905397309519,484.21353564000003,9,2,2.9843,True
+2758,CHEMBL4077349,780.0,nM,2017.0,O=C(Nn1c(-c2ccccc2)nc2ccccc2c1=O)c1ccc(Br)cc1,6.107905397309519,419.026938788,4,1,4.209900000000003,True
+2759,CHEMBL326280,790.0,nM,2003.0,COCC#CC(=O)Nc1cc2c(Nc3cccc(Br)c3)c(C#N)cnc2cc1OC,6.102372908709557,464.0484025040001,6,2,4.209480000000003,True
+2760,CHEMBL2070193,790.0,nM,2012.0,Clc1cccc(Nc2ncnc3ccc(NCc4ccc5c(c4)OCCO5)cc23)c1,6.102372908709557,418.11965352799996,6,2,5.410100000000003,True
+2761,CHEMBL263788,790.0,nM,2003.0,COc1cc2ncc(C#N)c(Nc3cccc(Br)c3)c2cc1NC(=O)/C=C/CN(C)C,6.102372908709557,479.095687044,6,2,4.677480000000003,True
+2762,CHEMBL168285,790.0,nM,2001.0,Nc1ncnc2c1c(-c1ccccc1)cn2C1CCC(O)C1,6.102372908709557,294.14806119599996,5,2,2.766400000000001,True
+2763,CHEMBL2426280,790.0,nM,2013.0,COc1cc(N2CCN(C(C)=O)CC2)ccc1Nc1ncc(Cl)c(-c2c[nH]c3ccccc23)n1,6.102372908709557,476.17275172000006,6,2,4.699000000000003,True
+2764,CHEMBL4287629,792.0,nM,2018.0,O=C(O)CCC(=O)Nc1cc(Nc2ccc(Cl)cc2)ncn1,6.1012748184105075,320.06761795600005,5,3,2.6769000000000007,True
+2765,CHEMBL3676350,796.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(OCc4cccnc4)c(Cl)c3)ncnc2cc1OCCNC(C)=O,6.099086932262331,532.16258096,8,3,4.640200000000003,True
+2766,CHEMBL22978,797.0,nM,2000.0,CN1CCC(O)(c2nc(-c3ccc(F)cc3)c(-c3ccncc3)o2)CC1,6.098541678603888,353.15395509999996,5,1,3.4559000000000024,True
+2767,CHEMBL3233761,799.0,nM,2014.0,CN(C)CCCC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,6.097453220686009,407.0982871280001,6,2,4.5077000000000025,True
+2768,CHEMBL428039,799.3,nM,2007.0,CCOc1cc2ncnc(NC3=CC(=O)C(OC)=CC3=O)c2cc1NC(=O)/C=C/CN(C)C,6.097290187030122,451.1855689,9,2,2.0626999999999995,True
+2769,CHEMBL2385975,800.0,nM,2013.0,CCOc1cc(N)c(C(=O)Nc2ccc(OCc3ccccn3)c(Cl)c2)cc1NC(=O)/C=C/CN(C)C,6.096910013008057,523.1986321200001,7,3,4.603500000000004,True
+2770,CHEMBL3221551,800.0,nM,2011.0,CCCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1.Cl,6.096910013008057,432.15643295999996,7,2,5.161000000000005,True
+2771,CHEMBL3219506,800.0,nM,2010.0,OB(O)c1ccc2ncnc(Nc3ccc(F)c(Cl)c3)c2c1,6.096910013008057,317.05386286,5,3,1.8456999999999992,True
+2772,CHEMBL175409,800.0,nM,2000.0,COc1cccc(-c2cn(-c3ccc(CC(=O)NCCO)cc3)c3ncnc(N)c23)c1,6.096910013008057,417.1800895960001,7,3,2.3293,True
+2773,CHEMBL514016,800.0,nM,2009.0,Clc1ccc2c(Nc3ccc(-c4nc5ccccc5s4)c(Cl)c3)ncnc2c1,6.096910013008057,422.01597274400007,5,1,6.956900000000003,True
+2774,CHEMBL176815,800.0,nM,2000.0,COc1cccc(-c2cn(-c3cccc(CO)c3)c3ncnc(N)c23)c1,6.096910013008057,346.14297581600005,6,2,3.1706000000000003,True
+2775,CHEMBL262276,800.0,nM,2001.0,COC(=O)CN1CCC(n2cc(-c3cccc(O)c3)c3c(N)ncnc32)CC1,6.096910013008057,381.18008959600013,8,2,2.1959999999999997,True
+2776,CHEMBL4214496,800.0,nM,2018.0,O=C(NC(CO)Cc1ccccc1)c1cc2cc(Cl)ccc2[nH]1,6.096910013008057,328.097855464,2,3,3.154700000000001,True
+2777,CHEMBL24026,800.0,nM,2002.0,COc1cc2c(Nc3ccc(C#N)cc3F)ncnc2cc1OC/C=C/CN1CCCC1,6.096910013008057,433.191403228,7,1,4.423580000000003,True
+2778,CHEMBL201307,800.0,nM,2006.0,COc1cc2c(Nc3ncc(CC(=O)Nc4cccc(F)c4)s3)ncnc2cc1OCCCN1CCC(CO)CC1,6.096910013008057,580.2268027560001,10,3,4.632000000000005,True
+2779,CHEMBL122243,800.0,nM,1997.0,Nc1ncnc2c1c(-c1ccccc1)nn2-c1ccccc1,6.096910013008057,287.117095416,5,1,3.064700000000001,True
+2780,CHEMBL78257,800.0,nM,1989.0,N#CC(C#N)=C(N)/C(C#N)=C/c1cc(O)c(O)c(O)c1,6.096910013008057,268.05964011599997,7,4,0.9703399999999998,True
+2781,CHEMBL2385985,800.0,nM,2013.0,CCOc1cc(N)c(C(=O)Nc2ccc(F)c(Cl)c2)cc1NC(=O)c1ccc(CN2CCN(C)CC2)cc1,6.096910013008057,539.2099457520001,6,3,4.712000000000003,True
+2782,CHEMBL490569,800.0,nM,1992.0,N#C/C(=C\c1cc(CSc2ccccc2)c(O)c(OCc2ccccc2)c1)C(N)=O,6.096910013008057,416.1194635,5,2,4.655780000000003,True
+2783,CHEMBL2018749,800.0,nM,2012.0,CCCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1,6.096910013008057,396.17975524799994,7,2,4.739200000000004,True
+2784,CHEMBL324718,810.0,nM,2003.0,C=CC(=O)Nc1cc2c(Nc3cccc(Br)c3)c(C#N)cnc2cc1OC,6.091514981121351,422.03783782000005,5,2,4.745680000000003,True
+2785,CHEMBL247127,810.0,nM,2007.0,c1cncc(Cn2ncc3cc(Nc4ncnn5ccc(COC[C@@H]6CNCCO6)c45)ccc32)c1,6.091514981121351,470.217872072,10,2,2.770900000000001,True
+2786,CHEMBL93635,810.0,nM,1996.0,O=[N+]([O-])c1ccc2c(Nc3cccc(Cl)c3)ncnc2c1,6.091514981121351,300.041403208,5,1,3.9350000000000014,True
+2787,CHEMBL2347967,820.0,nM,2013.0,O=[N+]([O-])c1cccc(-c2c(-c3ccccc3)oc3ncnc(N[C@H](CO)c4ccccc4)c23)c1,6.086186147616282,452.14845512,7,2,5.610500000000005,True
+2788,CHEMBL90541,820.0,nM,1997.0,COc1cc2ncnc(Nc3nnc4ccccc4n3)c2cc1OC,6.086186147616282,334.117823688,8,1,2.7288000000000006,True
+2789,CHEMBL1821873,820.0,nM,2011.0,COc1ccc(C2CC(c3ccc(C)c(C)c3)=NN2c2nc(-c3ccc(Cl)cc3)cs2)cc1,6.086186147616282,473.132861068,5,0,7.444640000000006,True
+2790,CHEMBL328277,820.0,nM,1997.0,COc1cc2ncnc(N3CCc4ccccc43)c2cc1OC,6.086186147616282,307.132076784,5,0,3.3412000000000015,True
+2791,CHEMBL307062,820.0,nM,1996.0,Cc1cccc(Nc2ncnc3[nH]c4c(c23)CCCC4)c1,6.086186147616282,278.153146576,3,2,3.888720000000001,True
+2792,CHEMBL3774609,823.9,nM,2016.0,O=C1COc2cc3ncnc(Nc4ccc(Br)cc4)c3cc2N1CCCN1CCOCC1,6.084125497142308,497.106251728,7,1,3.5836000000000015,True
+2793,CHEMBL3774982,829.2,nM,2016.0,O=C1COc2cc3ncnc(Nc4cccc(C(F)(F)F)c4)c3cc2N1CCCN1CCOCC1,6.081340706578176,487.183124288,7,1,3.8399000000000028,True
+2794,CHEMBL14874,830.0,nM,2004.0,CN(CCCOc1ccc2ncnc(Nc3ccc(OCc4ccccc4)cc3)c2c1)CCS(C)(=O)=O,6.080921907623925,520.2144265039999,8,1,4.697700000000004,True
+2795,CHEMBL1173455,830.0,nM,2010.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccc(F)cc3)C2)cc1C,6.080921907623925,327.120546796,2,1,3.837240000000002,True
+2796,CHEMBL3901943,830.0,nM,2016.0,C=CC(=O)N1CCCCC(n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cc(C)ccc32)C1,6.080921907623925,470.1929607,4,1,5.355420000000004,True
+2797,CHEMBL355891,830.0,nM,2001.0,COC(=O)CN1CCC(n2cc(-c3cccc(OC)c3)c3c(N)ncnc32)C1,6.080921907623925,381.18008959600013,8,1,2.1088999999999993,True
+2798,CHEMBL117697,842.0,nM,1995.0,COc1cccc(Nc2ncnc3ccccc23)c1,6.074687908500351,251.105862036,4,1,3.3820000000000014,True
+2799,CHEMBL2385974,850.0,nM,2013.0,CCOc1cc([N+](=O)[O-])c(C(=O)Nc2ccc(OCc3ccccn3)c(Cl)c2)cc1NC(=O)/C=C/CN(C)C,6.070581074285707,553.1728112960001,8,2,4.9295000000000035,True
+2800,CHEMBL144791,850.0,nM,1996.0,N#C/C(=C\c1cc(O)c(O)c(Br)c1)S(=O)(=O)/C(C#N)=C/c1cc(O)c(O)c(Br)c1,6.070581074285707,539.8626312399999,8,4,3.8779600000000016,True
+2801,CHEMBL95320,850.0,nM,2002.0,C#Cc1cccc(Nc2c(C#N)cnc3cc(OCCOC)c(OCCOC)cc23)c1,6.070581074285707,417.16885621599994,7,1,3.8817800000000027,True
+2802,CHEMBL3347498,850.0,nM,2010.0,OB(O)c1ccc(COc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)cc1,6.070581074285707,405.10514948400004,6,3,3.2856000000000005,True
+2803,CHEMBL1760035,853.0,nM,2011.0,COc1cc(Nc2nccc(Nc3cnc4ccccc4c3)n2)cc(OC)c1OC,6.069050968832477,403.164439532,8,2,4.5378000000000025,True
+2804,CHEMBL3921446,857.0,nM,2016.0,CN1CCN(C/C=C/C(=O)Nc2cc3c(Nc4ccc(Cc5ccccn5)cc4)ncnc3cn2)CC1,6.0670191780768015,494.2542575800001,8,2,3.4963000000000015,True
+2805,CHEMBL431191,860.0,nM,1996.0,COc1cccc(Nc2ncnc3[nH]c4c(c23)CCCC4)c1,6.0655015487564325,294.148061196,4,2,3.5889000000000015,True
+2806,CHEMBL3671547,866.0,nM,2014.0,CCC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(C)=O,6.062482107982652,489.08117985200005,6,3,4.1384000000000025,True
+2807,CHEMBL1080812,867.0,nM,2009.0,Cc1c(C(=O)NCCN2CCOCC2)[nH]c2cnnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12,6.061980902523789,521.194215436,8,3,3.699320000000001,True
+2808,CHEMBL3917657,870.0,nM,2016.0,CC(C)(C)c1ccc(Nc2ncnc3cc4oc(=O)n(CCOC(=O)CBr)c4cc23)cc1,6.0604807473813835,498.09026731599994,8,1,4.516900000000003,True
+2809,CHEMBL1928708,870.0,nM,2012.0,Oc1ccc(CNc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)cc1,6.0604807473813835,420.0585732640001,5,3,5.4536000000000024,True
+2810,CHEMBL119982,870.0,nM,1997.0,Clc1cccc(Nc2[nH]nc3ncnc(NCc4ccccc4)c23)c1,6.0604807473813835,350.10467216,5,3,4.362000000000001,True
+2811,CHEMBL204330,873.0,nM,2006.0,COc1cc(OC2CCN(C(C)=O)CC2)c2c(Nc3ccc(F)c(Cl)c3)ncnc2c1,6.058985756294431,444.1364464640001,6,1,4.564200000000004,True
+2812,CHEMBL4077064,874.0,nM,2017.0,C=CC(=O)N1CCc2ccc(-n3c(=O)ccc4cnc5ccc(-c6cnn(C)c6)cc5c43)cc21,6.058488567365598,447.16952491200004,6,0,4.0145000000000035,True
+2813,CHEMBL3676342,876.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Cl)cc3Cl)ncnc2cc1OCCNC(C)=O,6.057495893831919,493.047522476,6,3,4.9730000000000025,True
+2814,CHEMBL3809045,880.0,nM,2016.0,S=C=Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.055517327849832,355.973129388,5,1,4.870200000000001,True
+2815,CHEMBL54471,880.0,nM,1991.0,Cc1ccc(C(=O)/C(C#N)=C/c2ccc(O)c(O)c2)cc1,6.055517327849832,279.08954327600003,4,2,3.196100000000002,True
+2816,CHEMBL3735952,880.0,nM,2015.0,COC1CCN(c2nccc(Nc3cc4[nH]cnc4cn3)n2)CC1,6.055517327849832,325.16510822800007,7,2,2.1067,True
+2817,CHEMBL3944572,881.0,nM,2016.0,CCC(=O)Nc1cc2c(Nc3ccc(Oc4cccc(F)c4)cc3)ncnc2cc1OC,6.055024091587953,432.15976875200005,6,2,5.661900000000005,True
+2818,CHEMBL3736508,882.0,nM,2015.0,COC1CCN(c2nccc(Nc3cc4c(cn3)nc(C)n4C(C)C)n2)CC1,6.05453141486818,381.22770848400006,8,1,3.469420000000002,True
+2819,CHEMBL2048793,890.0,nM,2012.0,O=C1NCc2c(Oc3ccc(Nc4ncnc5ccn(CCO)c45)cc3Cl)cccc21,6.0506099933550885,435.109817116,7,3,3.856300000000002,True
+2820,CHEMBL4226151,892.0,nM,2018.0,CN1CCN(c2ccc(Nc3ncc4nc(Sc5ccccc5)n(C5CCOCC5)c4n3)cc2)CC1,6.049635145623879,501.23107961200003,9,1,4.824400000000004,True
+2821,CHEMBL3676346,894.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)c(F)c3F)ncnc2cc1OCCNC(=O)CCN1CCCCC1,6.048662481204082,602.1452573280001,7,3,4.909600000000004,True
+2822,CHEMBL329161,897.0,nM,1995.0,O=[N+]([O-])c1ccc2ncnc(Nc3cccc(Br)c3)c2c1,6.047207556955907,343.990887628,5,1,4.044100000000001,True
+2823,CHEMBL3604920,900.0,nM,2015.0,C=CC(=O)Nc1ccccc1Oc1nc(Nc2cc(C)[nH]n2)cc(N2CCN(C)CC2)n1,6.045757490560675,434.2178720720001,8,3,2.9203200000000002,True
+2824,CHEMBL3098325,900.0,nM,2014.0,COc1cc2nc(Cl)nc(Nc3ccc(C(N)=O)cc3)c2cc1OC,6.045757490560675,358.08326802,6,2,3.142900000000001,True
+2825,CHEMBL3604917,900.0,nM,2015.0,C=CC(=O)Nc1cc(Nc2cc[nH]n2)nc(-c2ccccc2)n1,6.045757490560675,306.122909068,5,3,2.734800000000001,True
+2826,CHEMBL2018757,900.0,nM,2012.0,CCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1C,6.045757490560675,396.17975524799994,7,2,4.657520000000003,True
+2827,CHEMBL3221561,900.0,nM,2011.0,CCOC(=O)Nc1cc(Nc2ncnc3cc(OC)c(OC)cc23)ccc1Cl.Cl,6.045757490560675,438.08616047999993,7,2,5.034200000000004,True
+2828,CHEMBL3221556,900.0,nM,2011.0,CCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1C.Cl,6.045757490560675,432.15643295999996,7,2,5.0793200000000045,True
+2829,CHEMBL3221554,900.0,nM,2011.0,CCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1C.Cl,6.045757490560675,418.14078289599996,7,2,4.689220000000004,True
+2830,CHEMBL490780,900.0,nM,1992.0,CCOc1cc(/C=C2/CCNC2=O)cc(CSc2ccccc2)c1O,6.045757490560675,355.124214532,4,2,3.9865000000000035,True
+2831,CHEMBL2018756,900.0,nM,2012.0,CCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1C,6.045757490560675,382.16410518399994,7,2,4.267420000000003,True
+2832,CHEMBL50,900.0,nM,2009.0,O=c1c(O)c(-c2ccc(O)c(O)c2)oc2cc(O)cc(O)c12,6.045757490560675,302.04265266,7,5,1988,True
+2833,CHEMBL2018760,900.0,nM,2012.0,CCOC(=O)Nc1cc(Nc2ncnc3cc(OC)c(OC)cc23)ccc1Cl,6.045757490560675,402.10948276799996,7,2,4.612400000000004,True
+2834,CHEMBL122397,900.0,nM,1997.0,CCCCCCNC(=O)c1cc(NCc2cc(O)ccc2O)ccc1O,6.045757490560675,358.18925731199994,5,5,3.7256000000000022,True
+2835,CHEMBL2047029,900.0,nM,2012.0,C#Cc1cccc(NC(=O)c2cc(OCCCCCCC(=O)NO)ccc2O)c1,6.045757490560675,396.16852186799997,5,4,3.4605000000000015,True
+2836,CHEMBL4207316,900.0,nM,2018.0,CCc1c(C(=O)NC(CO)Cc2ccccc2)[nH]c2ccc(C(F)(F)F)cc12,6.045757490560675,390.155512572,2,3,4.082500000000002,True
+2837,CHEMBL169200,900.0,nM,2001.0,COc1cccc(-c2cn(C3CCN(CCO)CC3)c3ncnc(N)c23)c1,6.045757490560675,367.2008250400001,7,2,2.3183,True
+2838,CHEMBL426124,900.0,nM,2006.0,COc1ccc2c(c1)CNc1c(Nc3ccc(F)c(Cl)c3)ncnc1O2,6.045757490560675,372.07893158800005,6,2,4.739100000000002,True
+2839,CHEMBL4290375,901.0,nM,2018.0,Cc1oc2ncnc(Nc3cccc(Cl)c3)c2c1C(=O)O,6.045275209020938,303.04106885999994,5,2,3.6264200000000013,True
+2840,CHEMBL4283517,901.0,nM,2018.0,COc1cc(Nc2cc(Nc3ccc(Cl)cc3)ncn2)cc(OC)c1OC,6.045275209020938,386.114568148,7,2,4.643000000000004,True
+2841,CHEMBL1242112,908.0,nM,2008.0,COc1cc(-c2nn(C(C)C)c3ncnc(N)c23)ccc1O,6.041914151478915,299.138224784,7,2,2.3706,True
+2842,CHEMBL3237945,910.0,nM,2014.0,CCOC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1c(C)nn(-c2ccc(C)cc2)c1Cl,6.040958607678906,517.1880674360001,8,1,4.881840000000005,True
+2843,CHEMBL94019,910.0,nM,1997.0,COc1cc2ncnc(NC3CCc4ccccc43)c2cc1OC,6.040958607678906,321.147726848,5,1,3.746400000000002,True
+2844,CHEMBL441083,910.0,nM,1995.0,Cc1cccc(Nc2ncnc3ccccc23)c1,6.040958607678906,235.110947416,3,1,3.681820000000002,True
+2845,CHEMBL104779,910.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(Nc3ccncc3)nc21,6.040958607678906,397.0497153960001,6,1,4.440900000000003,True
+2846,CHEMBL116525,910.0,nM,2003.0,CC#CC(=O)Nc1cc2c(Nc3cccc(Br)c3)c(C#N)cnc2cc1OC,6.040958607678906,434.03783782000005,5,2,4.582980000000004,True
+2847,CHEMBL511623,918.0,nM,2009.0,Fc1ccc(Nc2ncnc3nc(NCCN4CCOCC4)sc23)cc1Cl,6.037157318798758,408.093536096,8,2,3.366500000000002,True
+2848,CHEMBL2070201,920.0,nM,2012.0,Clc1cccc(Nc2ncnc3ccc(NCc4ccc5c(c4)OCCCCO5)cc23)c1,6.036212172654443,446.15095365599996,6,2,6.190300000000003,True
+2849,CHEMBL399735,921.0,nM,2007.0,COc1cc2ncnc(Nc3cccc(C#Cc4ccccc4)c3)c2cc1OC,6.035740369803151,381.147726848,5,1,4.7904000000000035,True
+2850,CHEMBL1241241,922.0,nM,2008.0,CC(C)n1nc(-c2ccc(O)cc2)c2c(N)ncnc21,6.035269078946371,269.1276601,6,2,2362,True
+2851,CHEMBL3676338,924.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cccc(Cl)c3F)ncnc2cc1OCCNC(=O)CN(C)C,6.0343280287798935,486.158244528,7,3,3.3470000000000013,True
+2852,CHEMBL2029427,929.0,nM,2012.0,C=CC(=O)Nc1cccc(N2C(=O)N(C)Cc3cnc(NC)nc32)c1,6.031984286006358,338.14912381600004,5,2,2.3463000000000003,True
+2853,CHEMBL115440,930.0,nM,2003.0,COCCOCC#CC(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.031517051446063,478.064052568,6,2,4.217480000000002,True
+2854,CHEMBL274732,930.0,nM,2001.0,COCCN(C)CCN1CCC(n2cc(-c3cccc(OC)c3)c3c(N)ncnc32)CC1,6.031517051446063,438.27432432800003,8,1,2.9042000000000012,True
+2855,CHEMBL293749,930.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCc1ccccc1,6.031517051446063,308.116092372,4,3,2.3636799999999996,True
+2856,CHEMBL4288761,933.0,nM,2018.0,CCOC(=O)CCC(=O)Nc1cc(Nc2cccc(Br)c2)ncn1,6.0301183562535,392.0484025040001,6,2,3.264500000000001,True
+2857,CHEMBL1241586,937.0,nM,2008.0,CC(C)n1nc(-c2ccc3[nH]c(=O)[nH]c3c2)c2c(N)ncnc21,6.028260409112222,309.13380810000007,6,3,1.8259999999999998,True
+2858,CHEMBL2325104,940.0,nM,2013.0,NC(=S)N1N=C(c2ccc(Cl)cc2)CC1c1cccc2ccccc12,6.0268721464003,365.075346192,2,1,4.887900000000003,True
+2859,CHEMBL432428,940.0,nM,1993.0,N#C/C(=C\c1cc(O)c(O)c(CSCc2ccccc2)c1)C(N)=O,6.0268721464003,340.088163372,5,3,2.9234800000000014,True
+2860,CHEMBL283682,940.0,nM,2003.0,CC#CC(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.0268721464003,404.0272731360001,4,2,4.574380000000002,True
+2861,CHEMBL589831,940.0,nM,2010.0,O=C(Nc1ccc(Br)cc1)c1ccc(N(CCCl)CCCl)cc1,6.0268721464003,413.990130624,2,1,4.985400000000003,True
+2862,CHEMBL342792,940.0,nM,1996.0,COc1cc(/C=C(\C#N)S(=O)(=O)/C(C#N)=C/c2cc(O)c(O)c(OC)c2)cc(O)c1O,6.0268721464003,444.06273647199987,10,4,2.370160000000002,True
+2863,CHEMBL1812571,940.0,nM,2011.0,O=C(/C=C/c1ccccc1[N+](=O)[O-])Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,6.0268721464003,445.09416705200005,6,2,5.586900000000002,True
+2864,CHEMBL590109,940.0,nM,2010.0,NCCn1cc(-c2cc(-c3cc4ccccc4s3)c3[nH]ncc3c2)c2nc(N)ncc21,6.0268721464003,425.1422646080001,7,3,4.397200000000002,True
+2865,CHEMBL54474,940.0,nM,1996.0,Nc1ccc2c(Nc3cccc(Br)c3)ncnc2n1,6.0268721464003,315.01195742000004,5,2,3.113100000000001,True
+2866,CHEMBL4289682,944.0,nM,2018.0,O=C(O)CCCC(=O)Nc1cc(Nc2ccc(Cl)cc2)ncn1,6.025028005701932,334.08326802000005,5,3,3067,True
+2867,CHEMBL196548,950.0,nM,2005.0,CCOCc1cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2c1CC,6.022276394711152,426.216809452,7,1,4.969800000000005,True
+2868,CHEMBL1645464,950.0,nM,2011.0,Cn1ncc2cc(Nc3ncnn4ccc(CN5CCC(N)CC5)c34)ccc21,6.022276394711152,376.21239276800003,8,2,2.2827,True
+2869,CHEMBL438805,950.0,nM,2005.0,CCCc1c(C(=O)OCC)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,6.022276394711152,454.21172407200004,8,1,5.000100000000004,True
+2870,CHEMBL4293326,951.0,nM,2018.0,Cc1oc2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2c1C(=O)O,6.021819483062585,427.07351185999994,6,2,5.344520000000003,True
+2871,CHEMBL1242024,954.0,nM,2008.0,Cc1cc(O)ccc1-c1nn(C(C)C)c2ncnc(N)c12,6.020451625295905,283.143310164,6,2,2.67042,True
+2872,CHEMBL1230790,954.0,nM,2008.0,CC(C)n1nc(-c2cccc(O)c2)c2c(N)ncnc21,6.020451625295905,269.1276601,6,2,2362,True
+2873,CHEMBL1242384,955.0,nM,2008.0,CC(C)n1nc(-c2ccc3c(ccn3C)c2)c2c(N)ncnc21,6.019996628416253,306.159294576,6,1,3.1481000000000003,True
+2874,CHEMBL3676392,956.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCOCCOC(=O)CC(=O)O,6.0195421077239,576.0655893640001,9,3,3.812800000000003,True
+2875,CHEMBL114593,960.0,nM,2003.0,COCC#CC(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,6.017728766960431,434.03783782,5,2,4.200880000000002,True
+2876,CHEMBL4071151,960.0,nM,2017.0,C#Cc1nn([C@@H]2CCCN(C(=O)C=C)C2)c2ncnc(N)c12,6.017728766960431,296.138559132,6,1,0.7393000000000001,True
+2877,CHEMBL592211,960.0,nM,2010.0,O=C(Nc1ccccc1)N(Cc1ccc(O)cc1)Cc1cccc(Cl)c1O,6.017728766960431,382.108420148,3,3,4.985500000000004,True
+2878,CHEMBL2048791,960.0,nM,2012.0,O=C1Cc2cc(Oc3ccc(Nc4ncnc5ccn(CCO)c45)cc3Cl)ccc2N1,6.017728766960431,435.109817116,7,3,4.107500000000002,True
+2879,CHEMBL1241490,964.0,nM,2008.0,CC(C)n1nc(-c2ccc3occc3c2)c2c(N)ncnc21,6.015922966097169,293.1276601,6,1,3.4026000000000005,True
+2880,CHEMBL436137,965.0,nM,2006.0,Cc1cccc(C)c1-c1cc(C)c2nc(Nc3ccc(OCCN4CCCC4)cc3)nnc2c1,6.0154726866562065,453.25286061200006,6,1,5.835260000000005,True
+2881,CHEMBL3092319,967.0,nM,2013.0,O=C(Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1)N1CC(F)C1,6.0145735259169975,475.12227362,6,2,4.519200000000003,True
+2882,CHEMBL602328,970.0,nM,2010.0,O=C1CSC(N/N=C/c2cc(F)ccc2O)=N1,6.013228265733755,253.032125716,5,2,1.0842,True
+2883,CHEMBL1821874,970.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc(O)cc3)C2)cc1C,6.013228265733755,459.11721100399996,5,1,7.141640000000006,True
+2884,CHEMBL4226177,972.0,nM,2018.0,C=CC(=O)Nc1cccc(NC(=O)Nc2ccnc(Nc3ccc(C(=O)N4CCN(C)CC4)cc3OC)n2)c1,6.012333735073725,530.23900144,8,4,3.384900000000002,True
+2885,CHEMBL4278031,974.0,nM,2018.0,COc1cccc(Nc2cc(Nc3cccc(Cl)c3)ncn2)c1,6.011441043121384,326.0934387800001,5,2,4.625800000000003,True
+2886,CHEMBL289787,974.0,nM,1995.0,COc1cccc2c(Nc3cccc(Br)c3)ncnc12,6.011441043121384,329.0163741040001,4,1,4.144500000000002,True
+2887,CHEMBL589561,980.0,nM,2010.0,Oc1c(Br)cccc1CN(Cc1ccc(F)cc1)C(=S)Nc1ccccc1,6.008773924307505,444.0307245160001,2,2,5.693000000000003,True
+2888,CHEMBL4084996,980.0,nM,2017.0,Clc1ccc(-c2nnc(Cc3nc4ccc(Cl)cc4[nH]3)o2)cc1,6.008773924307505,344.0231663,4,1,4.510500000000002,True
+2889,CHEMBL1081849,980.0,nM,2009.0,Cc1c(C(=O)NCCCN2CCN(C)CC2)[nH]c2cnnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c12,6.008773924307505,565.236829196,7,3,4.748720000000004,True
+2890,CHEMBL3671579,987.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)CN1CCC1,6.0056828473303625,542.107728948,7,3,3.6002000000000027,True
+2891,CHEMBL1257911,989.0,nM,2010.0,Nc1ccc2c(c1)C(c1ccccc1Cl)=Nc1c[nH]nc1N2,6.004803708402821,309.07812306400007,4,3,3.8714000000000013,True
+2892,CHEMBL2018752,1000.0,nM,2012.0,CCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1Cl,6.0,402.10948276799996,7,2,4.612400000000004,True
+2893,CHEMBL1242754,1000.0,nM,2008.0,CC(C)n1nc(-c2cnc3ccccc3c2)c2c(N)ncnc21,6.0,304.143644512,6,1,3.2046,True
+2894,CHEMBL230232,1000.0,nM,2009.0,N#Cc1cnc2c(Br)cc(NCc3c[nH]nn3)cc2c1Nc1ccc(F)c(Cl)c1,6.0,471.00101138400004,6,3,5.135280000000001,True
+2895,CHEMBL1917092,1000.0,nM,2011.0,COC(=O)c1ccc2c(c1)S(=O)(=O)N=S2c1ccc(Br)cc1,6.0,398.92346190000006,4,0,3.1579000000000015,True
+2896,CHEMBL490987,1000.0,nM,1992.0,CC(C)NC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,6.0,390.088557296,6,1,2.839900000000001,True
+2897,CHEMBL80164,1000.0,nM,2004.0,Cc1cc2cc(Nc3ccnc4cc(-c5ccc(CNCCO)cc5)sc34)ccc2[nH]1,6.0,428.167082388,5,4,5.578520000000005,True
+2898,CHEMBL231663,1000.0,nM,2007.0,COC(=O)C1CCN(Cc2ccn3ncnc(Nc4ccc5c(cnn5Cc5cccc(F)c5)c4)c23)CC1,6.0,513.2288513560001,9,1,4.395000000000003,True
+2899,CHEMBL62176,1000.0,nM,1994.0,CN1C(=S)C(C(=O)Nc2ccccc2)c2ccccc21,6.0,282.082684068,2,1,3.1861000000000015,True
+2900,CHEMBL44,1000.0,nM,1994.0,O=c1c(-c2ccc(O)cc2)coc2cc(O)cc(O)c12,6.0,270.05282342000004,5,3,2.576800000000001,True
+2901,CHEMBL3221560,1000.0,nM,2011.0,CCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1Cl.Cl,6.0,438.08616047999993,7,2,5.034200000000004,True
+2902,CHEMBL113863,1000.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(NCCCCCC(=O)O)nc21,6.0,434.09124586,6,2,4.359200000000002,True
+2903,CHEMBL3735474,1000.0,nM,2015.0,CO[C@H]1CCN(c2nccc(Nc3cc4c(cn3)nc(CO)n4C(C)C)n2)CC1(F)F,6.0,433.20377948000004,9,2,2.898500000000001,True
+2904,CHEMBL3735958,1000.0,nM,2015.0,Cc1nc2cnc(Nc3ccnc(N4CC[C@H](O)[C@H](F)C4)n3)cc2n1C(C)C,6.0,385.20263660800003,8,2,2.763320000000001,True
+2905,CHEMBL2018753,1000.0,nM,2012.0,CCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1Cl,6.0,416.12513283199996,7,2,5.002500000000004,True
+2906,CHEMBL94275,1000.0,nM,1995.0,O=[N+]([O-])c1ccc2c(Nc3cccc(Br)c3)ncnc2c1,6.0,343.9908876280001,5,1,4.044100000000001,True
+2907,CHEMBL205148,1000.0,nM,2006.0,O=C(O)c1ccc2c(c1)CNc1c(Nc3cccc(Br)c3)ncnc1O2,6.0,412.0171023760001,6,3,4.398700000000002,True
+2908,CHEMBL383614,1000.0,nM,2006.0,Brc1cccc(Nc2ncnc3c2NCc2cc(Br)ccc2O3)c1,6.0,445.937785204,5,2,5.463000000000002,True
+2909,CHEMBL281990,1000.0,nM,2002.0,COc1cc2c(Nc3ccc(C)cc3F)ncnc2cc1OCC1CCN(C)CC1,6.0,410.211804324,6,1,4.550120000000004,True
+2910,CHEMBL205676,1000.0,nM,2006.0,Fc1ccc(Nc2ncnc3c2NCc2cc(Cl)ccc2O3)cc1Cl,6.0,376.029394552,5,2,5.3839000000000015,True
+2911,CHEMBL424853,1000.0,nM,2006.0,Fc1ccc2c(c1)CNc1c(Nc3ccc(F)c(Cl)c3)ncnc1O2,6.0,360.05894509200004,5,2,4.869600000000002,True
+2912,CHEMBL206347,1000.0,nM,2006.0,COc1ccc2c(c1)Oc1ncnc(Nc3ccc(F)c(Cl)c3)c1NC2,6.0,372.078931588,6,2,4.739100000000001,True
+2913,CHEMBL496388,1000.0,nM,2009.0,N#Cc1cnc2c(Cl)cc(NCc3c[nH]nn3)cc2c1Nc1ccc(F)c(Cl)c1,6.0,427.051526964,6,3,5.026180000000001,True
+2914,CHEMBL184682,1000.0,nM,2004.0,COc1cc2ncnc(Nc3ccc(Cl)c(NC(=O)c4cccc(N(C)C)c4)c3)c2cc1OC,6.0,477.156767308,7,2,5.362300000000004,True
+2915,CHEMBL3910297,1000.0,nM,2008.0,C[C@@H](Nc1ncnc2[nH]c(-c3ccc(CNCC(=O)NO)cc3)cc12)c1ccccc1,6.0,416.196074008,6,5,3.3930000000000016,True
+2916,CHEMBL336113,1000.0,nM,2003.0,Cc1cccc(Nc2ncnc3ccc(N)cc23)c1,6.0,250.12184644799999,4,2,3.2640200000000004,True
+2917,CHEMBL504173,1000.0,nM,1992.0,CC(C)c1cc(/C=C(\C#N)C(N)=O)cc(C(C)C)c1O,6.0,272.15247788,3,2,3.031280000000002,True
+2918,CHEMBL3221258,1000.0,nM,2011.0,CCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1Cl.Cl,6.0,452.10181054399993,7,2,5.424300000000004,True
+2919,CHEMBL4101735,1000.0,nM,2017.0,CN(C)C/C=C/C(=O)N1CCC[C@@H](n2nc(-c3cccc(C(F)(F)F)c3)c3c(N)ncnc32)C1,6.0,473.2150931120001,7,1,3.3756000000000013,True
+2920,CHEMBL76958,1000.0,nM,1991.0,O=C(O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,6.0,349.025622692,6,1,2.3999000000000006,True
+2921,CHEMBL3975710,1000.0,nM,2008.0,O=C(/C=C/c1ccc(OCCOc2ccc3ncnc(Nc4ccc(F)c(Cl)c4)c3c2)cc1)NO,6.0,494.11571102,7,3,5.142300000000004,True
+2922,CHEMBL1914666,1008.0,nM,2011.0,Br.CC(Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12)c1cccc2ccccc12,5.996539467890493,460.089873392,4,3,6.234700000000005,True
+2923,CHEMBL2070192,1020.0,nM,2012.0,Brc1cccc(Nc2ncnc3ccc(NCc4ccc5c(c4)OCCO5)cc23)c1,5.991399828238082,462.069137948,6,2,5.519200000000002,True
+2924,CHEMBL3671546,1020.0,nM,2014.0,C=C(C)C(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(C)=O,5.991399828238082,501.08117985200005,6,3,4.304500000000003,True
+2925,CHEMBL1812560,1020.0,nM,2011.0,O=C(/C=C/c1ccccc1[N+](=O)[O-])Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,5.991399828238082,489.0436514720001,6,2,5.696000000000002,True
+2926,CHEMBL247866,1029.0,nM,2007.0,CC(C)Nc1ncnc2oc(-c3ccc(OCCN4CCCC4)cc3)c(-c3ccccc3)c12,5.9875846252375675,442.2368762,6,1,5.8517000000000055,True
+2927,CHEMBL136178,1039.0,nM,2001.0,CC(=O)/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,5.983384452442823,410.03783782,5,2,4.2196000000000025,True
+2928,CHEMBL99024,1040.0,nM,2002.0,COc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1,5.982966660701218,470.15209652799996,7,1,4.752280000000004,True
+2929,CHEMBL3734786,1040.0,nM,2015.0,Cc1nc2cnc(Nc3ccnc(N4CC[C@H](O)C(F)(F)C4)n3)cc2n1C(C)C,5.982966660701218,403.19321479600006,8,2,3.0605200000000012,True
+2930,CHEMBL3233771,1040.0,nM,2014.0,COCCNC/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,5.982966660701218,435.093201748,7,3,3.9581000000000017,True
+2931,CHEMBL2324872,1040.0,nM,2013.0,COc1ccc(C2=NN(C(N)=S)C(c3ccc4ccccc4c3)C2)cc1,5.982966660701218,361.124883228,3,1,4.243100000000003,True
+2932,CHEMBL1241945,1040.0,nM,2008.0,CC(C)n1nc(-c2ccc(O)c(F)c2)c2c(N)ncnc21,5.982966660701218,287.118238288,6,2,2.501099999999999,True
+2933,CHEMBL1821872,1040.0,nM,2011.0,Cc1ccc(C2CC(c3ccc(C)c(C)c3)=NN2c2nc(-c3ccc(Cl)cc3)cs2)cc1,5.982966660701218,457.137946448,4,0,7.744460000000006,True
+2934,CHEMBL4214040,1060.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccc(NC(=O)CO)cc2)n1,5.9746941347352305,498.17823102399996,9,3,3.357100000000001,True
+2935,CHEMBL210502,1061.0,nM,2006.0,Cc1cccc(Nc2ncnc3ccc(NC(=O)N(CCCl)N=O)cc23)c1,5.974284616098659,384.110151464,6,2,4.435920000000003,True
+2936,CHEMBL590714,1070.0,nM,2010.0,O=C(Nc1ccccc1)N(Cc1ccc(O)cc1)Cc1cccc(Br)c1O,5.97061622231479,426.057904568,3,3,5.094600000000004,True
+2937,CHEMBL2325089,1070.0,nM,2013.0,Fc1ccc(C2=NN(c3ccccc3)C(c3cccc4ccccc34)C2)cc1,5.97061622231479,366.153226828,2,0,6.3346000000000044,True
+2938,CHEMBL1958212,1080.0,nM,2012.0,Cc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccccc3)C2)cc1,5.966576244513051,335.109233164,4,0,3.775520000000003,True
+2939,CHEMBL421686,1080.0,nM,1996.0,Cc1[nH]c2ncnc(NCc3ccccc3)c2c1C,5.966576244513051,252.13749651199998,3,2,3.186840000000002,True
+2940,CHEMBL1272006,1090.0,nM,2010.0,OC[C@@H](Nc1ncnc2sc3c(c12)CCC3)c1ccccc1,5.962573502059376,311.109233164,5,2,3.3255000000000017,True
+2941,CHEMBL544074,1100.0,nM,1995.0,C=C(CN1CCCCC1)C(=O)c1ccc(OCc2ccccc2)cc1.Cl,5.9586073148417755,371.165206752,3,0,4.912200000000006,True
+2942,CHEMBL1242386,1100.0,nM,2008.0,CC(C)n1nc(-c2ccc3[nH]ncc3c2)c2c(N)ncnc21,5.9586073148417755,293.13889348000004,6,2,2.5326999999999993,True
+2943,CHEMBL2111784,1100.0,nM,2004.0,C[C@H](Nc1cc(-c2sc(C3CCN(C)CC3)nc2-c2ccc(F)cc2)ccn1)c1ccccc1,5.9586073148417755,472.20969614800003,5,1,6.993500000000007,True
+2944,CHEMBL425402,1100.0,nM,2006.0,Fc1ccc(Nc2ncnc3c2NCc2ccccc2O3)cc1Cl,5.9586073148417755,342.06836690399996,5,2,4.730500000000001,True
+2945,CHEMBL131020,1100.0,nM,1994.0,CO[C@H]1[C@@H](N(C)S(C)(=O)=O)C[C@@H]2O[C@@]1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,5.9586073148417755,544.178040996,7,1,4.0260000000000025,True
+2946,CHEMBL126974,1100.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4cncnc4)c3)c2cc1OCC,5.9586073148417755,387.169524912,7,1,4.627800000000003,True
+2947,CHEMBL429057,1100.0,nM,2000.0,Nc1ncnc2c1c(-c1ccccc1)cn2-c1ccccc1CO,5.9586073148417755,316.13241113199996,5,2,3.1620000000000013,True
+2948,CHEMBL3604912,1100.0,nM,2015.0,C=CC(=O)Nc1cccc(-c2nc(Nc3cc[nH]n3)c3ccccc3n2)c1,5.9586073148417755,356.138559132,5,3,3.888000000000001,True
+2949,CHEMBL194160,1100.0,nM,2005.0,CCc1c(CC(N)=O)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,5.9586073148417755,425.19640835600006,7,2,3.461100000000002,True
+2950,CHEMBL4095071,1100.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4)nc32)C1,5.9586073148417755,588.2972652640001,8,1,4.077200000000003,True
+2951,CHEMBL3085380,1100.0,nM,2007.0,CCN(CC)[C@@](C)(C#Cc1ncnc2cc(OC)c(OC)cc12)CC1CCCCC1,5.9586073148417755,409.27292736,5,0,5.069400000000005,True
+2952,CHEMBL2437461,1100.0,nM,2013.0,C=CC(=O)Nc1ccc(-n2c(=O)cnc3cnc(Nc4ccc(N5CCN(C)CC5)cc4)nc32)cc1,5.9586073148417755,482.2178720720001,9,2,2.7956000000000003,True
+2953,CHEMBL56219,1100.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)Nc1ccccc1Cl,5.9586073148417755,314.04581989200005,4,3,3.2968800000000007,True
+2954,CHEMBL3325473,1100.0,nM,2014.0,COC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2ccccc2n2nnnc12,5.9586073148417755,467.1705875320001,10,1,2.6267000000000005,True
+2955,CHEMBL131426,1100.0,nM,1994.0,CO[C@H]1[C@@H](N(C)CCC#N)C[C@@H]2O[C@@]1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,5.9586073148417755,519.227039788,7,1,4.9800800000000045,True
+2956,CHEMBL1683949,1100.0,nM,2011.0,Cc1cc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)ncn1,5.9586073148417755,343.0887680000001,4,1,4.900120000000003,True
+2957,CHEMBL544067,1100.0,nM,1995.0,C=C(CN1CCOCC1)C(=O)c1ccc(OCc2ccccc2)cc1.Cl,5.9586073148417755,373.144471308,4,0,3.7585000000000037,True
+2958,CHEMBL256362,1100.0,nM,2008.0,Cc1ccc(Oc2ccc(Nc3ncnc4cccc(O[C@H](C)C(=O)N(C)C)c34)cc2C)cn1,5.9586073148417755,457.211389724,7,1,5.033040000000003,True
+2959,CHEMBL4100075,1100.0,nM,2017.0,Cc1nc(C)c(/C=C2\CC(C)C/C(=C\c3nc(C)c(C)nc3C)C2=O)nc1C,5.9586073148417755,376.226311516,5,0,4.5831200000000045,True
+2960,CHEMBL3759830,1110.0,nM,2016.0,COc1ccc(C(=O)Nc2ccc(Nc3ncnc4cc(OCCCN5CCN(C)CC5)c(OC)cc34)cc2)cc1,5.954677021213343,556.2798036319999,9,2,4.659200000000005,True
+2961,CHEMBL2047026,1120.0,nM,2012.0,C#Cc1cccc(NC(=O)c2cc(NC(=O)CCCCCC(=O)NO)c(OC)cc2O)c1,5.950781977329817,439.17433551999994,6,5,3.0288000000000013,True
+2962,CHEMBL169519,1120.0,nM,2001.0,COc1cccc(-c2cn(C3CCNC3)c3ncnc(N)c23)c1,5.950781977329817,309.158960228,6,2,2.2234999999999996,True
+2963,CHEMBL4060821,1120.0,nM,2017.0,O=c1c2ccc(Cl)cc2nc(-c2ccccc2)n1-c1nnc(-c2ccccc2)s1,5.950781977329817,416.0498597160001,6,0,5.224600000000003,True
+2964,CHEMBL255291,1123.0,nM,2008.0,CO/N=C/c1c(N)ncnc1NCc1ccc(F)c(Cl)c1,5.949620243738543,309.079265936,6,2,2.4437000000000006,True
+2965,CHEMBL93754,1124.0,nM,2001.0,O=C(/C=C/Cn1cccn1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,5.949233688766958,448.064721264,6,2,4.527300000000003,True
+2966,CHEMBL92882,1132.0,nM,2001.0,COC/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,5.946153573147748,412.053487884,5,2,4.277000000000003,True
+2967,CHEMBL209818,1139.0,nM,2006.0,Cc1cccc(Nc2ncnc3ccc(N(C)C(=O)N(CCCl)N=O)cc23)c1,5.943476275920899,398.125801528,6,1,4.460220000000003,True
+2968,CHEMBL2070200,1140.0,nM,2012.0,Brc1cccc(Nc2ncnc3ccc(NCc4ccc5c(c4)OCCCCO5)cc23)c1,5.943095148663526,490.100438076,6,2,6.299400000000003,True
+2969,CHEMBL1241580,1150.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2C1CCC1,5.939302159646387,315.088687748,6,2,3.1595000000000013,True
+2970,CHEMBL1958216,1160.0,nM,2012.0,Cc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(C)cc3)C2)cc1,5.935542010773082,349.124883228,4,0,4.083940000000004,True
+2971,CHEMBL1242659,1160.0,nM,2008.0,CCOc1ccc(-c2nn(C3CCCCC3)c3ncnc(N)c23)cc1OC,5.935542010773082,367.20082504000004,7,1,3.988000000000002,True
+2972,CHEMBL2442333,1180.0,nM,2013.0,COc1cc(O)c2c(c1)CCN(c1cccc(C(=O)N3CCCCC3)c1)C2=O,5.928117992693874,380.173607248,4,1,3.229800000000002,True
+2973,CHEMBL4280749,1182.0,nM,2018.0,O=C1Nc2ccc(S(=O)(=O)N3CCOCC3)cc2/C1=N/c1ccc(/N=C2\C(=O)Nc3ccc(S(=O)(=O)N4CCOCC4)cc32)cc1,5.927382523454764,664.141003856,10,2,1.8742,True
+2974,CHEMBL4292110,1188.0,nM,2018.0,CCOC(=O)c1ccc(Nc2cc(Nc3cccc(OC)c3)ncn2)cc1,5.925183559354825,364.1535405000001,7,2,4.149100000000002,True
+2975,CHEMBL1945649,1190.0,nM,2012.0,Cc1ccc(C(=O)NS(=O)(=O)c2ccc(Cl)cc2)c(Cl)n1,5.924453038607469,343.97891854000005,4,1,2.8155200000000002,True
+2976,CHEMBL3233772,1196.0,nM,2014.0,CN(C)CCCNC/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,5.922268820347608,462.14048628800003,7,3,4.2634000000000025,True
+2977,CHEMBL1254443,1200.0,nM,2010.0,Cc1ccccc1Cc1cc2c(N(C)c3cccc(Br)c3)nc(N)nc2n1C,5.920818753952375,435.1058578040001,5,1,4.980120000000004,True
+2978,CHEMBL4241486,1200.0,nM,2018.0,O=C(N/N=C1\CC2(CCCCC2)Oc2c1ccc1ccccc21)C1C2CC3CC(C2)CC1C3,5.920818753952375,442.262028328,3,1,6.217800000000007,True
+2979,CHEMBL3218002,1200.0,nM,2012.0,C#Cc1cccc(Nc2ncnc3ccc(S(=O)(=O)n4ccc(/C=C/C(=O)NO)c4)cc23)c1,5.920818753952375,459.100125024,8,3,2.9118000000000004,True
+2980,CHEMBL80745,1200.0,nM,1989.0,COc1cc(/C=C(\C#N)C(N)=C(C#N)C#N)cc(O)c1O,5.920818753952375,282.07529017999997,7,3,1.27334,True
+2981,CHEMBL3085378,1200.0,nM,2007.0,CCN(CC)[C@@](C)(C#Cc1ncnc2cc(OC)c(OC)cc12)CCc1ccccc1,5.920818753952375,417.241627232,5,0,4.731800000000004,True
+2982,CHEMBL1683950,1200.0,nM,2011.0,Fc1cccc(COc2ccc(Nc3cc(-c4ccccc4)ncn3)cc2Cl)c1,5.920818753952375,405.1044180640001,4,1,6.258700000000004,True
+2983,CHEMBL73301,1200.0,nM,1996.0,COc1cccc(Nc2ncnc3[nH]c(C)c(C)c23)c1,5.920818753952375,268.132411132,4,2,3.3269400000000013,True
+2984,CHEMBL202970,1200.0,nM,2006.0,COc1cc2c(cc1OC)Oc1ncnc(Nc3ccc(F)c(Cl)c3)c1NC2,5.920818753952375,402.089496272,7,2,4.747700000000003,True
+2985,CHEMBL4103761,1200.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(Cl)c4)nc32)C1,5.920818753952375,622.258292912,8,1,4.730600000000004,True
+2986,CHEMBL3612578,1200.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4ccc(Cl)cc4)c3cc21,5.920818753952375,426.109482768,8,1,4.278000000000003,True
+2987,CHEMBL1242573,1200.0,nM,2008.0,CC(C)n1nc(-c2cc(F)c3cn[nH]c3c2)c2c(N)ncnc21,5.920818753952375,311.129471668,6,2,2.6717999999999993,True
+2988,CHEMBL1928944,1204.0,nM,2012.0,O=[N+]([O-])c1cccc(Oc2cc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)ncn2)c1,5.9193735130781935,466.08441089200005,7,1,6.292200000000004,True
+2989,CHEMBL1812431,1210.0,nM,2011.0,O=C(/C=C/c1ccc(Cl)cc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,5.917214629683549,478.019600912,4,2,6.441200000000003,True
+2990,CHEMBL1080990,1210.0,nM,2009.0,CCOC(=O)c1[nH]c(C)c2cnnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c12,5.917214629683549,454.12079639999996,6,2,5.558120000000003,True
+2991,CHEMBL4284911,1229.0,nM,2018.0,COc1cccc(Nc2cc(Nc3ccc(S(N)(=O)=O)cc3)ncn2)c1,5.910448117113546,371.10521040400005,7,3,2.6198000000000006,True
+2992,CHEMBL2442332,1230.0,nM,2013.0,COc1cc2c(c(OC)c1)C(=O)N(c1cccc(C(=O)N3CCCCC3)c1)CC2,5.910094888560603,394.189257312,4,0,3.5328000000000026,True
+2993,CHEMBL590875,1240.0,nM,2010.0,O=C1CSC(N/N=C/c2cc(Br)cc(Br)c2O)=N1,5.9065783148377635,390.8625716640001,5,2,2.470100000000001,True
+2994,CHEMBL502015,1240.0,nM,2008.0,Nc1nc(Nc2cccc(Br)c2)c2cc(Cc3ccc4ccccc4c3)[nH]c2n1,5.9065783148377635,443.07455767600004,4,3,5.790200000000003,True
+2995,CHEMBL56731,1250.0,nM,1999.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)Nc1ccccc1,5.903089986991943,280.084792244,4,3,2.6434800000000003,True
+2996,CHEMBL311111,1250.0,nM,2004.0,Cc1cc2cc(Nc3ccnc4cc(-c5ccc(CN6CCOCC6)cc5)sc34)ccc2[nH]1,5.903089986991943,454.182732452,5,2,6.328820000000005,True
+2997,CHEMBL74778,1250.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3cccc(O)c3)c2c1C,5.903089986991943,254.116761068,4,3,3.0239400000000014,True
+2998,CHEMBL3746711,1260.0,nM,2016.0,CC(=O)N1N=C(c2ccc(I)cc2)CC1c1ccc(C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,5.899629454882437,587.066566804,8,0,4.258920000000003,True
+2999,CHEMBL1958221,1260.0,nM,2012.0,COc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(Br)cc3)C2)cc1,5.899629454882437,429.014659852,5,0,4.2382000000000035,True
+3000,CHEMBL597914,1270.0,nM,2010.0,CCCCCCCCCCCCNC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.896196279044043,479.26717328399997,5,2,6.581500000000007,True
+3001,CHEMBL7339,1270.0,nM,1999.0,COc1cc(O)c2c(=O)c(-c3cccc(Cl)c3)coc2c1,5.896196279044043,302.03458651200003,4,1,3.8276000000000012,True
+3002,CHEMBL1272113,1270.0,nM,2010.0,CC#CC(=O)N1CCc2c(sc3ncnc(N[C@H](CO)c4ccccc4)c23)C1,5.896196279044043,392.13069687999996,6,2,2.7448000000000006,True
+3003,CHEMBL1173783,1270.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccc(OCc2ccccc2)cc1,5.896196279044043,407.148120772,7,0,3.9353200000000026,True
+3004,CHEMBL2070194,1290.0,nM,2012.0,O=C(Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1)c1cccc2c1OCCO2,5.889410289700751,432.09891808399993,6,2,5.050300000000003,True
+3005,CHEMBL1095154,1300.0,nM,2010.0,Cl.NCCc1cn(Cc2ccc(-c3ccccc3)cc2)c2ccc(OCCc3ccc(O)cc3)cc12,5.886056647693162,498.20740591199996,4,2,6.606700000000006,True
+3006,CHEMBL369014,1300.0,nM,2000.0,CCOC(=O)c1ccc(-c2cn(-c3ccccc3)c3ncnc(N)c23)cc1,5.886056647693162,358.14297581600005,6,1,3.846400000000002,True
+3007,CHEMBL56132,1300.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)c1ccccc1,5.886056647693162,265.07389321200003,4,2,2.8876800000000014,True
+3008,CHEMBL444337,1300.0,nM,1994.0,COC(=O)CN(C)[C@H]1C[C@@H]2O[C@](C)([C@H]1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,5.886056647693162,538.2216200600001,8,1,4.239400000000003,True
+3009,CHEMBL4071494,1300.0,nM,2017.0,Oc1ccc(-c2nc(-c3ccco3)c(-c3ccnc4[nH]c(-c5ccccc5)cc34)[nH]2)cc1,5.886056647693162,418.142975816,4,3,6.252600000000004,True
+3010,CHEMBL3218001,1300.0,nM,2012.0,C#Cc1cccc(Nc2ncnc3ccc(S(=O)(=O)n4ccc(/C=C/C(=O)Nc5ccccc5N)c4)cc23)c1,5.886056647693162,534.1474095640001,8,3,4.627300000000003,True
+3011,CHEMBL1641992,1300.0,nM,2011.0,CN1CCN(CCC(=O)Nc2ccc3c(C#N)cnc(Nc4cccc(Br)c4)c3c2)CC1,5.886056647693162,492.12732152,6,2,4.188580000000003,True
+3012,CHEMBL111365,1300.0,nM,1998.0,COc1ccc(Nc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)cn1,5.886056647693162,427.0602800800001,7,1,4.449500000000002,True
+3013,CHEMBL2426279,1300.0,nM,2013.0,C=CC(=O)Nc1cc(Nc2nccc(-c3c[nH]c4ccccc34)n2)c(OC)cc1N1CCN(C)CC1,5.886056647693162,483.2382731680001,7,3,4.253400000000003,True
+3014,CHEMBL4079506,1300.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)c(F)c4)nc32)C1,5.886056647693162,606.2878434520001,8,1,4.216300000000003,True
+3015,CHEMBL518803,1300.0,nM,2009.0,c1ccc2sc(-c3ccc(Nc4ncnc5[nH]ccc45)cc3)nc2c1,5.886056647693162,343.08916641600007,5,2,4.978200000000003,True
+3016,CHEMBL4076515,1300.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N(C)CCN(C)C)c(C)c4)nc32)C1,5.886056647693162,604.3285653920001,8,1,4.631620000000004,True
+3017,CHEMBL78206,1300.0,nM,1991.0,CC(C)(C)NC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,5.886056647693162,404.10420736,6,1,3.230000000000002,True
+3018,CHEMBL3325475,1300.0,nM,2014.0,COC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2cc(OC)ccc2n2nnnc12,5.886056647693162,497.1811522160001,11,1,2.635300000000001,True
+3019,CHEMBL483313,1320.0,nM,2008.0,Nc1nc(Nc2ccc(Cl)cc2F)c2cc(CCc3ccccc3)[nH]c2n1,5.8794260687941495,381.11565144400004,4,3,4.861400000000002,True
+3020,CHEMBL3263366,1320.0,nM,2014.0,Cc1ccc(C2=NN(C3=NC(=O)CS3)C(c3cccc4ccccc34)C2)cc1C,5.8794260687941495,399.140533292,4,0,5.237140000000005,True
+3021,CHEMBL3234743,1330.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1ccc(O)nc1,5.876148359032914,527.214424416,6,3,4.366420000000004,True
+3022,CHEMBL3628792,1330.0,nM,2015.0,Fc1ccc(Nc2ncnc3sc4c(c23)CCCC4)cc1Cl,5.876148359032914,333.050274316,4,1,5.106200000000003,True
+3023,CHEMBL592200,1340.0,nM,2010.0,Oc1c(Cl)cc(Cl)cc1CN(Cc1ccc(F)cc1)C(=S)Nc1ccccc1,5.872895201635193,434.04226774400007,2,2,6.237300000000004,True
+3024,CHEMBL1958022,1350.0,nM,2012.0,O=C1CSC(N2N=C(c3ccccc3)CC2c2ccc(Br)cc2)=N1,5.8696662315049934,399.00409516800005,4,0,4.229600000000003,True
+3025,CHEMBL432738,1360.0,nM,1997.0,CCNC(=O)Nc1nc2nc(N)ncc2cc1-c1c(Cl)cccc1Cl,5.866461091629782,376.060614428,5,3,3.7222000000000017,True
+3026,CHEMBL177688,1360.0,nM,2005.0,OCCCNc1cncc(-c2cncc(Nc3cccc(Cl)c3)n2)c1,5.866461091629782,355.11998787600004,6,3,3.7299000000000015,True
+3027,CHEMBL1173456,1360.0,nM,2010.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccc(Cl)cc3)C2)cc1C,5.866461091629782,343.090996256,2,1,4.351540000000003,True
+3028,CHEMBL437197,1362.6,nM,2007.0,COc1cc2ncnc(Nc3cccc(C#CCCCO)c3)c2cc1OC,5.865631615396621,363.15829153199996,6,2,3.5146000000000024,True
+3029,CHEMBL96627,1367.0,nM,1996.0,COc1ccc2ncnc(Nc3cccc(Br)c3)c2c1OC,5.864231485432178,359.02693878799994,5,1,4.153100000000003,True
+3030,CHEMBL3918367,1370.0,nM,2016.0,Cc1cccc2c1nc(NC(=O)c1cccc(C(F)(F)F)c1)n2[C@H]1CC[C@H](O)CC1,5.863279432843593,417.16641160399996,4,2,5.091820000000004,True
+3031,CHEMBL3416619,1374.0,nM,2015.0,Brc1cc2c(NCc3cccs3)ncnc2s1,5.862013267276469,324.934301356,5,1,4.127400000000001,True
+3032,CHEMBL2442329,1380.0,nM,2013.0,COc1cc(O)c2c(=O)n(-c3cccc(C(=O)N4CCCCC4)c3)ccc2c1,5.860120913598763,378.157957184,5,1,3.331000000000002,True
+3033,CHEMBL205783,1384.0,nM,2006.0,COc1cc(OC2CCOCC2)c2c(Nc3ccc(F)c(Cl)c3)ncnc2c1,5.858863909879261,403.1098973680001,6,1,4.732300000000004,True
+3034,CHEMBL1242029,1400.0,nM,2008.0,COc1cccc(-c2nn(C(C)C)c3ncnc(N)c23)c1,5.853871964321763,283.143310164,6,1,2665,True
+3035,CHEMBL173453,1400.0,nM,2000.0,Nc1ncnc2c1c(-c1ccccc1)cn2-c1ccc(CNCCO)cc1,5.853871964321763,359.174610292,6,3,2.7516,True
+3036,CHEMBL48436,1400.0,nM,1992.0,O=C(NCc1ccccc1)c1cc2ccc(O)c(O)c2cn1,5.853871964321763,294.100442308,4,3,2.5760000000000014,True
+3037,CHEMBL1241768,1400.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2[C@@H]1CCOC1,5.853871964321763,331.08360236799996,7,2,2.3959,True
+3038,CHEMBL2064382,1400.0,nM,2012.0,CCOc1ccc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)cc1,5.853871964321763,449.206304344,9,1,3.402300000000002,True
+3039,CHEMBL50470,1400.0,nM,1998.0,CCN(CC)CCCNc1ncc2cc(-c3c(Cl)cccc3Cl)c(=O)n(C)c2n1,5.853871964321763,433.14361578,6,1,4.446100000000003,True
+3040,CHEMBL1242758,1400.0,nM,2008.0,Nc1ncnc2c1c(-c1cccc3[nH]ccc13)nn2C1CCCC1,5.853871964321763,318.159294576,5,2,3.6719000000000017,True
+3041,CHEMBL418906,1400.0,nM,1991.0,CC(C)(C)OC(=O)NCCNC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,5.853871964321763,491.1362357599999,8,2,2.9562000000000017,True
+3042,CHEMBL49350,1400.0,nM,1992.0,O=C(NCCc1ccccc1)c1cc2ccc(O)c(O)c2cn1,5.853871964321763,308.116092372,4,3,2.618500000000002,True
+3043,CHEMBL1242377,1400.0,nM,2008.0,CC(C)n1nc(-c2ccc(F)c(O)c2)c2c(N)ncnc21,5.853871964321763,287.118238288,6,2,2.501099999999999,True
+3044,CHEMBL4244030,1400.0,nM,2018.0,NCCCCCCC(=S)N/N=C1\CC2(CCCCC2)Oc2c1ccc1ccccc21,5.853871964321763,423.234433676,4,2,5.855500000000006,True
+3045,CHEMBL1240554,1400.0,nM,2008.0,CCOc1ccc(-c2nn(C3CCCC3)c3ncnc(N)c23)cc1OC,5.853871964321763,353.185174976,7,1,3.597900000000002,True
+3046,CHEMBL1241864,1400.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc3[nH]c(=O)ccc3c1)nn2C1CCCC1,5.853871964321763,346.154209196,6,2,3.0321000000000016,True
+3047,CHEMBL4281413,1409.0,nM,2018.0,O=C(Nc1cc(Nc2ccc(Cl)cc2)ncn1)c1ccc(F)cc1,5.851089006890644,342.06836690399996,4,2,4.2650000000000015,True
+3048,CHEMBL65848,1410.0,nM,2002.0,Cc1cc(C(=O)N2CCOCC2)[nH]c1/C=C1\C(=O)Nc2ncnc(Nc3ccc4c(c3)CCC4)c21,5.85078088734462,470.20663869200007,6,3,3.3105200000000012,True
+3049,CHEMBL2047022,1410.0,nM,2012.0,O=C(CCCCCC(=O)Nc1ccc(O)c(C(=O)Nc2ccc(Cl)c(C(F)(F)F)c2)c1)NO,5.85078088734462,487.112183112,5,5,4.711100000000003,True
+3050,CHEMBL2047016,1410.0,nM,2012.0,O=C(CCCCCC(=O)Nc1ccc(O)c(C(=O)Nc2cccc(F)c2)c1)NO,5.85078088734462,403.154349024,5,5,3178,True
+3051,CHEMBL257873,1430.0,nM,2008.0,Cc1ccc(Oc2ccc(Nc3ncnc4[nH]nc(OCCN5CCC(O)CC5)c34)cc2F)cn1,5.844663962534938,479.208115912,9,3,3.5668200000000008,True
+3052,CHEMBL3746642,1450.0,nM,2016.0,CC(=O)N1N=C(c2ccc([N+](=O)[O-])cc2)CC1c1ccc(C(=O)OC(C)Cn2c([N+](=O)[O-])cnc2C)cc1,5.8386319977650265,520.170647108,10,0,3.9510200000000033,True
+3053,CHEMBL553,1450.0,nM,2002.0,C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(OCCOC)cc23)c1,5.8386319977650265,393.16885621599994,7,1,3.405100000000002,True
+3054,CHEMBL592481,1460.0,nM,2010.0,O=C1CSC(N/N=C/c2cc(Cl)cc(Cl)c2O)=N1,5.835647144215562,302.963602824,5,2,2.2519000000000005,True
+3055,CHEMBL54784,1460.0,nM,1996.0,c1ccc(CNc2ncnc3ccncc23)cc1,5.835647144215562,236.106196384,4,1,2.6369000000000007,True
+3056,CHEMBL169065,1470.0,nM,2001.0,COC(=O)CN1CCC(n2cc(-c3cccc(OC)c3)c3c(N)ncnc32)CC1,5.832682665251824,395.19573966000013,8,1,2.4990000000000006,True
+3057,CHEMBL589830,1490.0,nM,2010.0,O=C(Nc1ccc(Cl)cc1)c1ccc(N(CCCl)CCCl)cc1,5.826813731587727,370.040646204,2,1,4.876300000000003,True
+3058,CHEMBL544538,1500.0,nM,1995.0,C=C(CN1CCNCC1)C(=O)c1ccc(OCc2ccccc2)cc1.Cl,5.823908740944319,372.16045572,4,1,3.3315000000000023,True
+3059,CHEMBL544770,1500.0,nM,1995.0,CN(C)CCC(=O)c1ccc(OCc2ccccc2)cc1.Cl,5.823908740944319,319.133906624,3,0,3.8218000000000036,True
+3060,CHEMBL3133904,1500.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3cccc(C)c3F)c2c1,5.823908740944319,322.12298932000004,4,2,3.945420000000002,True
+3061,CHEMBL473556,1500.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(-c4nc5ccccc5s4)cc3)c2cc1OC,5.823908740944319,414.115046816,7,1,5.667300000000004,True
+3062,CHEMBL542893,1500.0,nM,1995.0,Cl.O=C(CCN1CCOCC1)c1ccc(OCc2ccccc2)cc1,5.823908740944319,361.144471308,4,0,3.5924000000000023,True
+3063,CHEMBL4207305,1500.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(NC(=O)CO)c2)n1,5.823908740944319,498.17823102399996,9,3,3.357100000000001,True
+3064,CHEMBL2316142,1500.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccccc3Cl)C2=O)cc(OC)c1,5.823908740944319,368.11792221199994,3,0,5.577200000000005,True
+3065,CHEMBL204965,1500.0,nM,2006.0,Fc1ccc2c(c1)CNc1c(Nc3cccc(Br)c3)ncnc1O2,5.823908740944319,386.017851324,5,2,4.839600000000003,True
+3066,CHEMBL2424796,1500.0,nM,2013.0,Clc1cccc(Nc2ncnc3ccc(NCc4ccc(Br)s4)cc23)c1,5.823908740944319,443.981107228,5,2,6.462900000000001,True
+3067,CHEMBL2385964,1500.0,nM,2013.0,Cc1ncc(C#N)c(Nc2ccc(OCc3ccccn3)c(Cl)c2)c1C#Cc1ccc(CNCCS(C)(=O)=O)o1,5.823908740944319,575.1394029920002,9,2,4.759700000000004,True
+3068,CHEMBL3612599,1500.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4cc(C)cc(C)c4)c3cc21,5.823908740944319,420.179755248,8,1,4.241440000000003,True
+3069,CHEMBL77401,1500.0,nM,1991.0,COC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,5.823908740944319,363.041272756,7,0,2.4883000000000006,True
+3070,CHEMBL4279008,1500.0,nM,2018.0,COc1ccc(-c2nc3sc(-c4ccc(Cl)cc4)cn3n2)cc1,5.823908740944319,341.038960684,5,0,4.786800000000004,True
+3071,CHEMBL1828863,1510.0,nM,2011.0,Cc1ncc([N+](=O)[O-])n1CC(=O)NS(=O)(=O)c1ccc(Cl)cc1,5.82102305270683,358.013868132,7,1,1.2582199999999997,True
+3072,CHEMBL1929305,1510.0,nM,2012.0,Nc1ccccc1-c1nnc(SCc2ccccc2)o1,5.82102305270683,283.077933036,5,1,3.611100000000002,True
+3073,CHEMBL171545,1530.0,nM,2001.0,Nc1ncnc2c1c(-c1cccc(O)c1)cn2C1CCNC1,5.815308569182402,295.143310164,6,3,1.9204999999999997,True
+3074,CHEMBL56319,1530.0,nM,1991.0,CCOC(=O)C(Cc1ccccc1)NC(=O)/C(C#N)=C/c1ccc(O)c(O)c1,5.815308569182402,380.13722174,6,3,2.2953800000000006,True
+3075,CHEMBL59145,1540.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)c1ccccc1Cl,5.8124792791635365,299.03492086,4,2,3.541080000000001,True
+3076,CHEMBL2426287,1550.0,nM,2013.0,COc1ccc(NC(=O)/C=C/CN(C)C)cc1Nc1ncc(Cl)c(-c2c[nH]c3ccccc23)n1,5.809668301829707,476.17275172000006,6,3,5.086800000000003,True
+3077,CHEMBL2047025,1560.0,nM,2012.0,COc1cc(O)c(C(=O)Nc2ccc(F)c(Cl)c2)cc1NC(=O)CCCCCC(=O)NO,5.806875401645538,467.125941356,6,5,3.8400000000000016,True
+3078,CHEMBL1830269,1570.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccc([N+](=O)[O-])cc1)c1ccccc1,5.804100347590767,326.08374668799996,4,2,2.8455000000000013,True
+3079,CHEMBL1241678,1580.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2[C@H]1CCOC1,5.801342913045577,331.08360236799996,7,2,2.3959,True
+3080,CHEMBL4215164,1590.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(NC(=O)CCO)c2)n1,5.798602875679549,512.1938810879999,9,3,3.747200000000001,True
+3081,CHEMBL78685,1600.0,nM,2004.0,c1ccc(-c2cc3ncnc(Nc4ccc5[nH]ncc5c4)c3s2)cc1,5.795880017344076,343.089166416,5,2,4.978200000000001,True
+3082,CHEMBL372692,1600.0,nM,2005.0,CCc1c(CC(=O)O)cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c12,5.795880017344076,426.18042394400004,7,2,4.060400000000002,True
+3083,CHEMBL491677,1600.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(N4Cc5ccccc5C4)cc3)c2cc1OC,5.795880017344076,398.174275944,6,1,4.9108000000000045,True
+3084,CHEMBL4087383,1600.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4OC)nc32)C1,5.795880017344076,618.3078299480001,9,1,4.085800000000003,True
+3085,CHEMBL401930,1600.0,nM,2005.0,Cc1cc(N2CCOCC2)cc2[nH]c(-c3c(NC[C@@H](O)c4cccc(Cl)c4)cc[nH]c3=O)nc12,5.795880017344076,479.172417372,6,4,3.8621200000000018,True
+3086,CHEMBL2316140,1600.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccccc3)C2=O)cc(OC)c1,5.795880017344076,334.15689456399997,3,0,4.923800000000005,True
+3087,CHEMBL114728,1600.0,nM,2003.0,CCOc1cc2ncc(C#N)c(Nc3cccc(Br)c3)c2cc1NC(=O)/C=C/CN(C)C,5.795880017344076,493.111337108,6,2,5.067580000000004,True
+3088,CHEMBL464721,1600.0,nM,1997.0,CCC(C)/C=C/C(=O)C(=O)/C=C/C=C/C=C/C=C/C=C/C=C/[C@@H]1C[C@@H](O)[C@H](C(=O)O)O1,5.795880017344076,426.2042386799999,5,2,3.6671000000000014,True
+3089,CHEMBL417941,1600.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NC1CCCCC1,5.795880017344076,286.131742436,4,3,2.4536800000000003,True
+3090,CHEMBL248220,1610.0,nM,2007.0,COc1cc2ncc(C#N)c(N[C@@H]3C[C@H]3c3ccccc3)c2cc1OCc1ccccc1,5.793174123968151,421.179026976,5,1,5.662080000000005,True
+3091,CHEMBL2152704,1620.0,nM,2012.0,Cc1ccc(O)cc1-n1c(=O)c2c(c3c(N)ncnc31)CCCC2,5.790484985457369,322.142975816,6,2,2.25572,True
+3092,CHEMBL326811,1620.0,nM,2003.0,C/C=C/C(=O)Nc1ccc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,5.790484985457369,406.0429232000001,4,2,5.127180000000003,True
+3093,CHEMBL3098321,1630.0,nM,2014.0,CNS(=O)(=O)c1ccc(Nc2nc(Cl)nc3cc(OC)c(OC)cc23)cc1,5.787812395596043,408.065903704,7,2,2.9521000000000015,True
+3094,CHEMBL1098119,1630.0,nM,2010.0,Cl.NCCc1cn(CCCCCc2ccccc2)c2ccc(OCCc3ccc(O)cc3)cc12,5.787812395596043,478.23870603999995,4,2,6.304400000000006,True
+3095,CHEMBL2070190,1630.0,nM,2012.0,O=C(Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)c1cccc2c1OCCO2,5.787812395596043,476.04840250399997,6,2,5.159400000000003,True
+3096,CHEMBL1928711,1640.0,nM,2012.0,Clc1ccc(CNc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)cc1,5.785156151952302,438.02468629199996,4,2,6.401400000000002,True
+3097,CHEMBL398963,1640.6,nM,2007.0,Fc1ccc(Nc2ncnc3ccc(C#Cc4cccs4)cc23)cc1Cl,5.7849972927850475,379.034624252,4,1,5.627200000000003,True
+3098,CHEMBL399736,1643.6,nM,2007.0,COc1cc2ncnc(Nc3cccc(C#CCO)c3)c2cc1OC,5.7842038674101675,335.12699140399997,6,2,2.734400000000001,True
+3099,CHEMBL457250,1650.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(Sc5ccccn5)cc4)c3s2)C1)N1CCOCC1,5.782516055786092,558.150780692,10,2,4.531900000000004,True
+3100,CHEMBL1958214,1660.0,nM,2012.0,Cc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(Cl)cc3)C2)cc1,5.779891911959945,369.07026081199996,4,0,4.428920000000003,True
+3101,CHEMBL1242109,1670.0,nM,2008.0,CCC(C)n1nc(-c2ccc(C)c(O)c2)c2c(N)ncnc21,5.777283528852418,297.158960228,6,2,3.0605200000000004,True
+3102,CHEMBL499344,1670.0,nM,2008.0,Nc1nc(Nc2cccc(Br)c2)c2cc(Cc3ccccc3)[nH]c2n1,5.777283528852418,393.05890761200004,4,3,4.637000000000002,True
+3103,CHEMBL48614,1680.0,nM,2002.0,CN1CCC(c2c(O)cc(O)c3c2O/C(=C\c2ccccc2Cl)C3=O)CC1,5.774690718274138,385.10808579999997,5,2,4.176600000000002,True
+3104,CHEMBL597492,1688.0,nM,2010.0,COc1cc(C2=C(c3c[nH]c4ccc(I)cc34)C(=O)NC2=O)cc(OC)c1OC,5.772627557710362,504.01821964399994,5,2,3.3655000000000017,True
+3105,CHEMBL208849,1693.0,nM,2006.0,Cc1cccc(Nc2ncnc3ccc(NC(=O)N(C)CCCl)cc23)c1,5.771343041891066,369.13563794,4,2,4.384320000000002,True
+3106,CHEMBL3604935,1700.0,nM,2015.0,Cc1cc(Nc2cc(N3CCN(C)CC3)nc(Oc3ccc(NC(=O)/C=C/CN(C)C)cc3)n2)n[nH]1,5.769551078621726,491.27572129600014,9,3,2.85212,True
+3107,CHEMBL3604937,1700.0,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3n[nH]c4ccccc34)cc(N3CCN(C)CC3)n2)c1,5.769551078621726,470.2178720720001,8,3,3.765100000000002,True
+3108,CHEMBL2064394,1700.0,nM,2012.0,O=c1oc2cc3ncnc(Nc4ccc(OCc5ccccn5)cc4)c3cc2n1CCCN1CCOCC1,5.769551078621726,512.217203376,10,1,3.9776000000000025,True
+3109,CHEMBL56455,1700.0,nM,1991.0,COc1ccc(CCNC(=O)/C(C#N)=C/c2ccc(O)c(O)c2)cc1OC,5.769551078621726,368.13722174,6,3,2.3808800000000003,True
+3110,CHEMBL4208224,1700.0,nM,2018.0,Cc1c2cc(Cl)ccc2n2cc(Cc3ccccc3)[nH]c(=O)c12,5.769551078621726,322.08729078,2,1,4.333420000000003,True
+3111,CHEMBL203132,1700.0,nM,2006.0,Nc1ccc2c(c1)CNc1c(Nc3cccc(Br)c3)ncnc1O2,5.769551078621726,383.038172168,6,3,4.282700000000002,True
+3112,CHEMBL4289274,1700.0,nM,2018.0,COc1cc(-c2nc3sc(-c4ccc(Cl)cc4)cn3n2)cc(OC)c1OC,5.769551078621726,401.06009005199996,7,0,4.804000000000004,True
+3113,CHEMBL443906,1700.0,nM,2009.0,c1cc(Nc2ncnc3[nH]cnc23)cc(-c2nc3ccccc3s2)c1,5.769551078621726,344.08441538399995,6,2,4.3732000000000015,True
+3114,CHEMBL57251,1700.0,nM,1991.0,COc1ccc(NC(=O)/C(C#N)=C/c2ccc(O)c(O)c2)c(OC)c1,5.769551078621726,340.105921612,6,3,2.660680000000001,True
+3115,CHEMBL322066,1704.0,nM,1999.0,COc1cc(Nc2nccc(-c3ccc(N4CCNCC4)nc3)n2)cc(OC)c1OC,5.768530409569318,422.206638692,9,2,2.717600000000001,True
+3116,CHEMBL3092300,1715.0,nM,2013.0,O=C(Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1)N1CCC2(CC1)OCCO2,5.7657358756212105,543.1684748639999,8,2,4.704400000000004,True
+3117,CHEMBL592711,1720.0,nM,2010.0,O=C(Nc1ccc(F)cc1)c1ccc(N(CCCl)CCCl)cc1,5.764471553092451,354.07019674400004,2,1,4.362000000000004,True
+3118,CHEMBL591910,1720.0,nM,2010.0,O=C1CSC(N/N=C/c2ccc(Br)cc2)=N1,5.764471553092451,296.95714497600005,4,1,2002,True
+3119,CHEMBL598305,1720.0,nM,2010.0,CCCCCCCCCCCCOC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.764471553092451,480.25118887199994,6,1,7.008500000000008,True
+3120,CHEMBL1821862,1730.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(F)cc3)C2)cc1C,5.761953896871206,427.151846924,4,0,6.921740000000005,True
+3121,CHEMBL1242111,1770.0,nM,2008.0,Nc1ncnc2c1c(-c1cccc(O)c1F)nn2C1CCCC1,5.752026733638193,313.133888352,6,2,3.035300000000001,True
+3122,CHEMBL3960332,1791.0,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc(O[C@H]4CCOC4)c(NC(=O)/C=C/CN(CC)CC)cc23)c1,5.7469044141509675,485.242689852,7,2,4.358900000000003,True
+3123,CHEMBL3233769,1792.0,nM,2014.0,C=CCOC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,5.746661994673892,378.035352524,6,2,4.961900000000002,True
+3124,CHEMBL2047021,1800.0,nM,2012.0,O=C(CCCCCC(=O)Nc1ccc(O)c(C(=O)Nc2ccc(Cl)c(Cl)c2)c1)NO,5.7447274948966935,453.085826132,5,5,4.345700000000003,True
+3125,CHEMBL76929,1800.0,nM,1991.0,COC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1O,5.7447274948966935,379.036187376,8,1,2.1939000000000006,True
+3126,CHEMBL4216784,1800.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccccc2N)n1,5.7447274948966935,440.17275172,8,2,4.0085000000000015,True
+3127,CHEMBL197525,1800.0,nM,2005.0,COc1ccc(Nc2ncnc3cccc(OC4CCN(C)CC4)c23)cc1Cl,5.7447274948966935,398.150953656,6,1,4.5084000000000035,True
+3128,CHEMBL545006,1800.0,nM,1995.0,Cl.O=C(CCN1CCCCC1)c1ccc(OCc2ccccc2)cc1,5.7447274948966935,359.16520675199996,3,0,4.746100000000005,True
+3129,CHEMBL55379,1800.0,nM,1997.0,FC(F)C(F)(F)Oc1cccc(Nc2nccc(-c3c[nH]c4ccccc34)n2)c1,5.7447274948966935,402.110373948,4,2,5.605200000000003,True
+3130,CHEMBL394463,1800.0,nM,2007.0,Cc1ccn2ncnc(Nc3ccc4c(cnn4Cc4cccnc4)c3)c12,5.7447274948966935,355.15454354400003,7,1,3.574320000000002,True
+3131,CHEMBL4204596,1820.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccccc2N=C=S)n1,5.739928612014924,482.12917265600004,9,1,5.160600000000004,True
+3132,CHEMBL1821864,1840.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(Br)cc3)C2)cc1C,5.735182176990462,487.07178080399996,4,0,7.545140000000005,True
+3133,CHEMBL590526,1860.0,nM,2010.0,O=C(Nc1ccccc1)N(Cc1ccc(O)cc1)Cc1cc(Cl)cc(Cl)c1O,5.730487055782085,416.06944779599996,3,3,5.638900000000004,True
+3134,CHEMBL3416590,1860.0,nM,2015.0,COc1ccccc1-c1cc2c(N[C@@H](C)c3ccccc3)ncnc2s1,5.730487055782085,361.1248832280001,5,1,5.540000000000004,True
+3135,CHEMBL1928886,1870.0,nM,2012.0,Oc1ccc(CNc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)cc1,5.7281583934635005,376.10908884400004,5,3,5.344500000000003,True
+3136,CHEMBL3088221,1890.0,nM,2013.0,Cc1ncc([N+](=O)[O-])n1C/C(=N/NC(=O)c1ccccc1N)c1ccc(Br)cc1,5.723538195826754,456.0545505040001,7,2,3.2787200000000016,True
+3137,CHEMBL4241867,1900.0,nM,2018.0,O=C(N/N=C1\CC2(CCCC2)Oc2ccccc21)Nc1ccc(Cl)cc1,5.721246399047171,369.12440455999996,3,2,4.9611000000000045,True
+3138,CHEMBL306029,1900.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3cccc(C(F)(F)F)c3)c2c1C,5.721246399047171,306.109231076,3,2,4.337140000000002,True
+3139,CHEMBL2316158,1900.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccc(S(C)(=O)=O)cc3)C2=O)cc(OC)c1,5.721246399047171,412.13444486799995,5,0,4.327300000000003,True
+3140,CHEMBL75049,1900.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3ccccc3)c2c1C,5.721246399047171,238.12184644799999,3,2,3.318340000000001,True
+3141,CHEMBL4081727,1900.0,nM,2017.0,COc1cc(Br)c(/C=C2\CC(C)C/C(=C\c3nc(C)c(C)nc3C)C2=O)cc1OC,5.721246399047171,470.120504824,5,0,5.647560000000006,True
+3142,CHEMBL491686,1900.0,nM,2009.0,Cc1cc(Nc2ccnc(Nc3cccc(-c4nc5ccccc5s4)c3)n2)n[nH]1,5.721246399047171,399.1266145440001,7,3,5.272020000000002,True
+3143,CHEMBL424252,1910.0,nM,2003.0,CCN(CC)C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cc1OC,5.718966632752272,481.16808094000004,6,2,5.487680000000005,True
+3144,CHEMBL1821867,1920.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(O)cc3)C2)cc1C,5.71669877129645,425.156183356,5,1,6.488240000000006,True
+3145,CHEMBL3234741,1920.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1cncnc1,5.71669877129645,512.2147587640001,6,2,4.055820000000003,True
+3146,CHEMBL1812374,1929.0,nM,2011.0,Cc1ccc(-c2nc3cc(NC(=O)CCl)ccc3[nH]2)cc1,5.7146677723561154,299.082539748,2,2,3.7156200000000013,True
+3147,CHEMBL589823,1940.0,nM,2010.0,O=C1CSC(N/N=C/c2ccc(Cl)cc2)=N1,5.7121982700697735,253.007660556,4,1,1.8929,True
+3148,CHEMBL326318,1950.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSCc2ccccc2)c1O,5.709965388637482,354.103813436,5,2,3.2264800000000027,True
+3149,CHEMBL3671567,1954.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCCNC(=O)C1CCCN1,5.709075440617247,542.107728948,7,4,3.6465000000000014,True
+3150,CHEMBL592426,1980.0,nM,2010.0,O=C(Nc1ccccc1)N(Cc1ccc(F)cc1)Cc1cccc(Cl)c1O,5.703334809738469,384.10408371599993,2,2,5.419000000000003,True
+3151,CHEMBL2316157,2000.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3cc(OC)cc(OC)c3)C2=O)cc(OC)c1,5.698970004336019,394.1780239319999,5,0,4.941000000000004,True
+3152,CHEMBL8095,2000.0,nM,1994.0,COc1ccc(Nc2cc3c(cc2Nc2ccccc2)C(=O)NC3=O)cc1,5.698970004336019,359.12699140399997,5,3,4.066000000000002,True
+3153,CHEMBL206320,2000.0,nM,2006.0,Fc1ccc2c(c1)CNc1c(Nc3cccc(-c4ccccc4)c3)ncnc1O2,5.698970004336019,384.13863938400004,5,2,5.744100000000004,True
+3154,CHEMBL206280,2000.0,nM,2006.0,Fc1ccc(Nc2ncnc3c2NCc2cc(Br)ccc2O3)cc1Cl,5.698970004336019,419.978878972,5,2,5.493000000000001,True
+3155,CHEMBL490774,2000.0,nM,1992.0,N#C/C(=C/c1ccc(O)c(O)c1)C(=O)NC1CCCCC1,5.698970004336019,286.131742436,4,3,2.4536800000000003,True
+3156,CHEMBL204335,2000.0,nM,2006.0,COc1ccc2c(c1)CNc1c(NCc3ccccc3)ncnc1O2,5.698970004336019,334.142975816,6,2,3.815100000000001,True
+3157,CHEMBL3604936,2000.0,nM,2015.0,Cc1cc(Nc2cc(N3CCN(C)CC3)nc(Oc3ccc(NC(=O)/C=C/C(F)(F)F)cc3)n2)n[nH]1,5.698970004336019,502.2052567000001,8,3,3.852820000000002,True
+3158,CHEMBL93544,2000.0,nM,1996.0,CN(C)c1cc2ncnc(Nc3cccc(Br)c3)c2cc1[N+](=O)[O-],5.698970004336019,387.033086788,6,1,4.110100000000003,True
+3159,CHEMBL464210,2000.0,nM,2009.0,CNC(=O)c1cc(Nc2ccc(-c3nc4ccccc4s3)cc2)ccn1,5.698970004336019,360.104482132,5,2,4.461500000000003,True
+3160,CHEMBL257478,2000.0,nM,2008.0,Cc1ccc(Oc2ccc(Nc3ncnc4cccc(O[C@H](C)C(=O)N(C)CCO)c34)cc2C)cn1,5.698970004336019,487.221954408,8,2,4.395540000000002,True
+3161,CHEMBL121405,2000.0,nM,2004.0,OC1(c2nc(-c3ccc(F)cc3)c(-c3ccnc(NC4CCCCC4)c3)o2)CCNCC1,5.698970004336019,436.227454388,6,3,4.858300000000003,True
+3162,CHEMBL1241770,2010.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2CC1CCNC1,5.696803942579511,344.11523684400004,7,3,2.0439999999999996,True
+3163,CHEMBL1958213,2010.0,nM,2012.0,Cc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(F)cc3)C2)cc1,5.696803942579511,353.09981135199996,4,0,3.914620000000003,True
+3164,CHEMBL1958209,2030.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(Br)cc3)CC2c2ccc(Br)cc2)=N1,5.692503962086787,476.9146072360001,4,0,4.992100000000003,True
+3165,CHEMBL51320,2030.0,nM,1996.0,c1ccc(CNc2ncnc3cnccc23)cc1,5.692503962086787,236.106196384,4,1,2.6369000000000007,True
+3166,CHEMBL441518,2043.6,nM,2004.0,CN(C)C/C=C/C(=O)Nc1cnc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,5.6896041059897735,450.080371328,6,2,4.063880000000002,True
+3167,CHEMBL2325107,2060.0,nM,2013.0,Cc1ccc(C2=NN(C(N)=S)C(c3cccc4ccccc34)C2)cc1,5.6861327796308485,345.129968608,2,1,4.542920000000003,True
+3168,CHEMBL1095957,2070.0,nM,2010.0,Cl.NCCc1c[nH]c2ccc(OCCc3ccc(O)cc3)cc12,5.684029654543082,332.129155592,3,3,3.418000000000002,True
+3169,CHEMBL3416617,2079.0,nM,2015.0,C[C@@H](Nc1ncnc2sc(Br)cc12)c1ccccn1,5.682145510668532,333.988779452,5,1,4.021900000000002,True
+3170,CHEMBL1830261,2080.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1cccc(F)c1)c1ccccc1,5.681936665037237,299.089246668,2,2,3.0764000000000022,True
+3171,CHEMBL1945447,2080.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(Br)cc1)c1cncc(Br)c1,5.681936665037237,417.862237316,4,1,2.7253000000000007,True
+3172,CHEMBL3237944,2090.0,nM,2014.0,CCOC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1c(C)nn(-c2ccccc2)c1Cl,5.679853713888947,503.17241737200004,8,1,4.573420000000004,True
+3173,CHEMBL1990583,2090.0,nM,2012.0,Nc1ncnn2ccc(C(=O)Nc3ccc(NC(=O)Nc4cccc(F)c4)cc3)c12,5.679853713888947,405.134950972,6,4,3.3469000000000015,True
+3174,CHEMBL56542,2100.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)N1CCc2ccccc21,5.6777807052660805,306.100442308,4,2,2.594080000000001,True
+3175,CHEMBL144778,2100.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NC1CCCC[C@@H]1NC(=O)/C(C#N)=C/c1ccc(O)c(O)c1,5.6777807052660805,488.169584488,8,6,2.5667600000000004,True
+3176,CHEMBL194337,2100.0,nM,2005.0,CN1CCC(Oc2cccc3ncnc(Nc4ccc(OCc5ccccn5)cc4)c23)CC1,5.6777807052660805,441.21647510400004,7,1,4.820400000000004,True
+3177,CHEMBL245800,2100.0,nM,2007.0,N#Cc1cnc2ccc(-c3ccc(CN)cc3)cc2c1N[C@@H]1C[C@H]1c1ccccc1,5.6777807052660805,390.184446704,4,2,5.200180000000004,True
+3178,CHEMBL538507,2100.0,nM,1995.0,Cc1ccc(SCC(CN(C)C)C(=O)c2ccc(OCc3ccccc3)cc2)cc1C.Cl,5.6777807052660805,469.184227944,4,0,6.457040000000007,True
+3179,CHEMBL1241681,2100.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc3ncccc3c1)nn2C1CCCC1,5.6777807052660805,330.159294576,6,1,3.738800000000002,True
+3180,CHEMBL3132872,2100.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(Br)cc3F)c2c1,5.6777807052660805,386.017851324,4,2,4.3995000000000015,True
+3181,CHEMBL307599,2100.0,nM,1996.0,Cc1ccc(Nc2ncnc3[nH]c(C)c(C)c23)cc1,5.6777807052660805,252.13749651199998,3,2,3.6267600000000018,True
+3182,CHEMBL168656,2100.0,nM,2001.0,COc1cccc(-c2cn(C3CCN(C(=O)OC(C)(C)C)C3)c3ncnc(N)c23)c1,5.6777807052660805,409.2113897240001,7,1,3.871000000000002,True
+3183,CHEMBL2316143,2100.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccccc3F)C2=O)cc(OC)c1,5.6777807052660805,352.147472752,3,0,5.062900000000004,True
+3184,CHEMBL3358006,2100.0,nM,2014.0,C[C@@H]1CN(c2nc(C(F)(F)F)no2)CCN1c1ncc(OCc2ccc(CS(C)(=O)=O)cc2F)cn1,5.6777807052660805,530.1359370639999,10,0,2.856200000000001,True
+3185,CHEMBL544640,2110.0,nM,1999.0,Cl.c1ccc(Nc2[nH]cnc3c4ccccc4nc2-3)cc1,5.675717544702308,296.082874096,3,2,4.228100000000002,True
+3186,CHEMBL1242848,2120.0,nM,2008.0,CC(C)n1nc(-c2ccc(N)c(O)c2)c2c(N)ncnc21,5.673664139071248,284.138559132,7,3,1.9442,True
+3187,CHEMBL2442324,2120.0,nM,2013.0,COc1cc(OC)c2c(=O)n(-c3cccc(C(=O)N4CCCCC4)c3)ccc2c1,5.673664139071248,392.173607248,5,0,3.634000000000002,True
+3188,CHEMBL605337,2140.0,nM,2010.0,CCCCCCCCCCNC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.669586226650809,451.23587315599997,5,2,5.801300000000007,True
+3189,CHEMBL3134612,2145.0,nM,2014.0,COc1cc(Nc2nccc(-c3ccc(Cl)cc3)n2)cc(OC)c1OC,5.6685727034792555,371.10366911599994,6,1,4.566400000000004,True
+3190,CHEMBL3233794,2159.0,nM,2014.0,O=C(/C=C/CN1CC2(CCOCC2)C1)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,5.665747357665769,487.124501876,7,2,4.834500000000003,True
+3191,CHEMBL1173457,2170.0,nM,2010.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccc(Br)cc3)C2)cc1C,5.66354026615147,387.04048067599996,2,1,4.460640000000003,True
+3192,CHEMBL1830278,2170.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccc(F)cc1)c1ccc(Br)cc1,5.66354026615147,376.999758736,2,2,3.8389000000000015,True
+3193,CHEMBL1828864,2170.0,nM,2011.0,Cc1ncc([N+](=O)[O-])n1CC(=O)NS(=O)(=O)c1ccc(Br)cc1,5.66354026615147,401.963352552,7,1,1.3673199999999996,True
+3194,CHEMBL589822,2180.0,nM,2010.0,O=C1CSC(N/N=C/c2ccc(F)cc2)=N1,5.661543506395395,237.037211096,4,1,1.3786,True
+3195,CHEMBL1242114,2190.0,nM,2008.0,COc1ccc(-c2nn(C(C)C)c3ncnc(N)c23)cc1O,5.6595558851598815,299.138224784,7,2,2.3706,True
+3196,CHEMBL1641995,2200.0,nM,2011.0,N#Cc1cnc(Nc2cccc(Br)c2)c2cc(NC(=O)[C@@H]3CCC(=O)N3)ccc12,5.657577319177793,449.048736852,5,3,3.8296800000000015,True
+3197,CHEMBL3133901,2200.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3c(F)cccc3Br)c2c1,5.657577319177793,386.01785132400005,4,2,4.3995000000000015,True
+3198,CHEMBL3133902,2200.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(Br)cc3C)c2c1,5.657577319177793,382.0429232,4,2,4.568820000000002,True
+3199,CHEMBL360209,2200.0,nM,2004.0,COc1cc2ncnc(Nc3ccc(Cl)c(NC(=O)c4ccccc4)c3)c2cc1OC,5.657577319177793,434.114568148,6,2,5.296300000000003,True
+3200,CHEMBL343887,2200.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCN1CCN(C(=O)/C(C#N)=C/c2ccc(O)c(O)c2)CC1,5.657577319177793,503.18048352,9,5,1.2835599999999996,True
+3201,CHEMBL485321,2200.0,nM,2008.0,COc1ccc(CCc2cc3c(Nc4cccc(Br)c4)nc(N)nc3[nH]2)cc1,5.657577319177793,437.0851223600001,5,3,4.8400000000000025,True
+3202,CHEMBL2316141,2200.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3cccc(Cl)c3)C2=O)cc(OC)c1,5.657577319177793,368.11792221199994,3,0,5.577200000000005,True
+3203,CHEMBL2441565,2200.0,nM,2013.0,CN(C)C/C=C/C(=O)N1CCOc2cc3ncnc(Nc4ccc(F)c(Cl)c4)c3cc21,5.657577319177793,441.13678081200004,6,1,4.009100000000002,True
+3204,CHEMBL168921,2200.0,nM,2001.0,CC(C)(C)OC(=O)N1CCC(n2cc(-c3cccc(O)c3)c3c(N)ncnc32)C1,5.657577319177793,395.19573966000013,7,2,3.5680000000000014,True
+3205,CHEMBL593293,2200.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(-c4nc5ccccc5s4)cc3O)c2cc1OC,5.657577319177793,430.109961436,8,2,5.372900000000003,True
+3206,CHEMBL473351,2200.0,nM,2009.0,COc1cc2ncnc(Nc3ccc(-c4nc5ccccc5s4)c(O)c3)c2cc1OC,5.657577319177793,430.109961436,8,2,5.372900000000003,True
+3207,CHEMBL605413,2200.0,nM,2009.0,CCCC(Cc1coc2nc(N)nc(N)c12)c1ccccc1OC,5.657577319177793,326.174275944,6,2,3.5222000000000016,True
+3208,CHEMBL2047017,2220.0,nM,2012.0,O=C(CCCCCC(=O)Nc1ccc(O)c(C(=O)Nc2ccc(F)c(F)c2)c1)NO,5.653647025549362,421.144927212,5,5,3.3171,True
+3209,CHEMBL2325102,2230.0,nM,2013.0,NC(=S)N1N=C(c2ccccc2)CC1c1cccc2ccccc12,5.6516951369518384,331.114318544,2,1,4.234500000000002,True
+3210,CHEMBL592427,2240.0,nM,2010.0,O=C(Nc1ccccc1)N(Cc1ccc(F)cc1)Cc1cccc(Br)c1O,5.649751981665838,428.05356813599997,2,2,5.528100000000004,True
+3211,CHEMBL2047024,2250.0,nM,2012.0,C#Cc1cccc(NC(=O)c2cc(NC(=O)CCCCCCC(=O)NO)ccc2O)c1,5.647817481888637,423.17942089999997,5,5,3.410300000000001,True
+3212,CHEMBL1958034,2280.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(Cl)cc3)CC2c2ccc(Br)cc2)=N1,5.642065152999545,432.965122816,4,0,4.883000000000004,True
+3213,CHEMBL138691,2282.0,nM,2001.0,C=CC(=O)N(CCN(C)C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1,5.641684359917804,440.09602139200007,6,1,3.6115000000000013,True
+3214,CHEMBL118000,2290.0,nM,2003.0,N#Cc1cnc2ccc(NC(=O)/C=C/CN3CCOCC3)cc2c1Nc1ccc(F)c(Cl)c1,5.6401645176601125,465.13678081200004,6,2,4.469480000000003,True
+3215,CHEMBL1760057,2290.0,nM,2011.0,c1ccc2ncc(Nc3ccnc(Nc4ccc(OCCCN5CCCCC5)cc4)n3)cc2c1,5.6401645176601125,454.24810958000006,7,2,5.766800000000004,True
+3216,CHEMBL3133903,2300.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(Br)c(C)c3)c2c1,5.638272163982407,382.0429232,4,2,4.568820000000002,True
+3217,CHEMBL3612591,2300.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4ccc(OCc5ccccn5)cc4)c3cc21,5.638272163982407,499.1855689,10,1,4.598600000000004,True
+3218,CHEMBL1233881,2300.0,nM,2008.0,COc1ccc(-c2nn(C3CCC3)c3ncnc(N)c23)cc1OC,5.638272163982407,325.153874848,7,1,2.8177000000000003,True
+3219,CHEMBL3787112,2300.0,nM,2016.0,Nc1ncnc2c1c(-c1cccc(O)c1)cn2[C@H]1C[C@@H](CN2CCC2)C1,5.638272163982407,349.19026035600007,6,2,3.0429000000000013,True
+3220,CHEMBL2048792,2300.0,nM,2012.0,O=C1Cc2ccc(Oc3ccc(Nc4ncnc5ccn(CCO)c45)cc3Cl)cc2N1,5.638272163982407,435.109817116,7,3,4.107500000000002,True
+3221,CHEMBL56879,2300.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)c1ccc([N+](=O)[O-])cc1,5.638272163982407,310.05897142,6,2,2.7958800000000013,True
+3222,CHEMBL114490,2320.0,nM,2003.0,COc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN(C)C,5.6345120151091015,453.13678081200004,6,2,4.707480000000004,True
+3223,CHEMBL2047015,2340.0,nM,2012.0,O=C(CCCCCC(=O)Nc1ccc(O)c(C(=O)Nc2ccccc2)c1)NO,5.6307841425898575,385.163770836,5,5,3.038900000000001,True
+3224,CHEMBL3734877,2360.0,nM,2015.0,COC1CCN(c2nccc(Nc3cc4c(cn3)nc(CO)n4C(C)C)n2)CC1,5.627087997029894,397.22262310400004,9,2,2.6533000000000007,True
+3225,CHEMBL1821863,2360.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(Cl)cc3)C2)cc1C,5.627087997029894,443.122296384,4,0,7.4360400000000055,True
+3226,CHEMBL3098317,2370.0,nM,2014.0,COc1cc2nc(Cl)nc(Nc3ccc(S(N)(=O)=O)cc3)c2cc1OC,5.6252516539898965,394.05025363999994,7,2,2.6914000000000007,True
+3227,CHEMBL1958218,2370.0,nM,2012.0,COc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccccc3)C2)cc1,5.6252516539898965,351.104147784,5,0,3.4757000000000025,True
+3228,CHEMBL1830272,2380.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccccc1)c1ccccc1,5.623423042943489,281.09866848,2,2,2.9373000000000014,True
+3229,CHEMBL4208745,2400.0,nM,2018.0,O=c1[nH]c(Cc2ccccc2)cn2c1cc1cc(Cl)ccc12,5.619788758288393,308.07164071600005,2,1,4.025000000000002,True
+3230,CHEMBL4094546,2400.0,nM,2017.0,Cc1nc(C)c(/C=C2\CC(C)C/C(=C\c3nc(C)c(C)nc3C)C2=NO)nc1C,5.619788758288393,391.23721054800006,6,1,4.844220000000004,True
+3231,CHEMBL77030,2400.0,nM,1989.0,N#C/C(=C\c1ccc(O)c(O)c1)C(N)=S,5.619788758288393,220.030648496,4,3,1.2908799999999998,True
+3232,CHEMBL599388,2400.0,nM,2010.0,COc1cc(-c2nc(=O)c3c([nH]2)sc2ccc(C)cc23)ccc1OCC(=O)O,5.619788758288393,396.07799261199995,6,2,3.5852200000000014,True
+3233,CHEMBL130049,2400.0,nM,1994.0,COC(=O)N(C)[C@H]1C[C@@H]2O[C@](C)([C@H]1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,5.619788758288393,524.205969996,7,1,4.832800000000003,True
+3234,CHEMBL260861,2400.0,nM,2008.0,COc1cc(Nc2nn3c(N[C@H](CO)Cc4ccccc4)cc(C4CC4)nc3c2C(N)=O)cc(OC)c1,5.619788758288393,502.23285344,9,4,3.4819000000000013,True
+3235,CHEMBL2424804,2400.0,nM,2013.0,O=C(/C=C/c1ccc(Br)s1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.619788758288393,483.9760218480001,5,2,6.502700000000003,True
+3236,CHEMBL193578,2400.0,nM,2005.0,Clc1cc(Nc2ncnc3cccc(OC4CCOCC4)c23)ccc1OCc1ccccn1,5.619788758288393,462.145868276,7,1,5.558600000000004,True
+3237,CHEMBL1242477,2500.0,nM,2008.0,CC(C)n1nc(-c2ccc3cn[nH]c3c2)c2c(N)ncnc21,5.6020599913279625,293.13889348000004,6,2,2.5326999999999993,True
+3238,CHEMBL1097189,2500.0,nM,2010.0,Cl.NC1CCc2c(c3cc(OCCc4ccc(O)cc4)ccc3n2CCCc2ccccc2)C1,5.6020599913279625,476.223055976,4,2,5.839000000000005,True
+3239,CHEMBL3133905,2500.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(Br)c(OC)c3)c2c1,5.6020599913279625,398.03783782,5,2,4.269000000000002,True
+3240,CHEMBL7914,2500.0,nM,1994.0,Cc1ccc(Nc2cc3c(cc2Nc2ccc(C)cc2)C(=O)NC3=O)cc1,5.6020599913279625,357.147726848,4,3,4.674240000000003,True
+3241,CHEMBL4104427,2500.0,nM,2017.0,Cc1nc(C)c(/C=C2\CN(C(C)C)C/C(=C\c3nc(C)c(C)nc3C)C2=O)nc1C,5.6020599913279625,405.25286061200006,6,0,3.877220000000003,True
+3242,CHEMBL419047,2500.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccc(O)cc2)c1O,5.6020599913279625,356.08307799199997,6,3,2.7909800000000007,True
+3243,CHEMBL267019,2500.0,nM,1994.0,O=C1NC(=O)c2cc(Nc3ccc(O)cc3)c(Nc3ccc(O)cc3)cc21,5.6020599913279625,361.10625596,6,5,3.4686000000000003,True
+3244,CHEMBL309334,2500.0,nM,1989.0,N#CC(C#N)=C(N)/C(C#N)=C/c1ccc(O)c(O)c1,5.6020599913279625,252.064725496,6,3,1.2647399999999998,True
+3245,CHEMBL1095130,2500.0,nM,2010.0,Nc1nc(Nc2ccc(Cl)cc2F)c2cc(Cc3ccc(Cl)cc3Cl)[nH]c2n1,5.6020599913279625,435.02205667600003,4,3,5.9738000000000016,True
+3246,CHEMBL57462,2500.0,nM,1991.0,N#CC(C#N)=C1C(=O)Nc2cc(O)c(O)cc21,5.6020599913279625,227.03309102,5,3,0.8506599999999997,True
+3247,CHEMBL4094527,2500.0,nM,2017.0,C=CC(=O)N1CCC[C@@H](n2ncc3c(N)ncnc32)C1,5.6020599913279625,272.13855913199995,6,1,0.7579999999999997,True
+3248,CHEMBL77397,2500.0,nM,1991.0,COc1cc(/C=C(\C)[N+](=O)[O-])ccc1OS(=O)(=O)c1ccc(C(=O)O)cc1,5.6020599913279625,393.05183744,7,1,2.7986000000000013,True
+3249,CHEMBL76116,2500.0,nM,1996.0,Cc1[nH]c2ncnc(Oc3cccc(Cl)c3)c2c1C,5.6020599913279625,273.066889684,3,1,4.0204400000000025,True
+3250,CHEMBL4074615,2500.0,nM,2018.0,CCC(=O)N1CC[C@H](N2C(=O)N(c3cc(OC)ccc3F)Cc3cnc(Nc4ccc(N5CCN(C)CC5)cc4C)nc32)C1,5.6020599913279625,602.312915328,8,1,4.385620000000004,True
+3251,CHEMBL326100,2500.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSCc2ccccc2Cl)c1O,5.6020599913279625,388.064841084,5,2,3.879880000000003,True
+3252,CHEMBL2325088,2520.0,nM,2013.0,c1ccc(C2=NN(c3ccccc3)C(c3cccc4ccccc34)C2)cc1,5.598599459218455,348.16264864,2,0,6.1955000000000044,True
+3253,CHEMBL3734934,2530.0,nM,2015.0,CC(C)n1c(CO)nc2cnc(Nc3ccnc(N4CC[C@H](O)[C@H](F)C4)n3)cc21,5.596879478824182,401.19755122799995,9,3,1.9471999999999996,True
+3254,CHEMBL247024,2530.0,nM,2007.0,N#Cc1cnc2ccc(-c3ccc(CN4CCOCC4)cc3)cc2c1N[C@@H]1C[C@H]1c1ccccc1,5.596879478824182,460.226311516,5,1,5.573680000000006,True
+3255,CHEMBL169780,2540.0,nM,2001.0,Nc1ncnc2c1c(-c1cccc(O)c1)cn2C1CCN(CCO)CC1,5.5951662833800615,353.185174976,7,3,2.0153,True
+3256,CHEMBL3741655,2550.0,nM,2015.0,Cc1[nH]c(-c2ccccc2)c(-c2ccccc2)c1-c1nnc(C)c2nn(-c3ccc(Cl)cc3)cc12,5.5934598195660445,475.15637338400006,4,1,7.414840000000005,True
+3257,CHEMBL3741069,2560.0,nM,2015.0,Cc1[nH]c(-c2ccccc2)c(-c2ccccc2)c1C(=O)c1cn(-c2ccccc2)nc1-c1ccccc1,5.591760034688151,479.19976242000007,3,1,7.740820000000007,True
+3258,CHEMBL3088222,2580.0,nM,2013.0,Cc1ncc([N+](=O)[O-])n1C/C(=N/NC(=O)c1ccccc1O)c1ccc(Br)cc1,5.58838029403677,457.038566092,7,2,3.402120000000002,True
+3259,CHEMBL403785,2580.0,nM,2007.0,C[C@@H](COc1cccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c12)N(C)C(=O)CO,5.58838029403677,507.16733199199996,8,2,4.218800000000003,True
+3260,CHEMBL248045,2580.0,nM,2007.0,COc1ccc2c(N[C@@H]3C[C@H]3c3ccccc3)c(C#N)cnc2c1,5.58838029403677,315.137162164,4,1,4.0830800000000025,True
+3261,CHEMBL217092,2590.0,nM,2006.0,CN1CCN(CCOc2cc(OC3CCOCC3)c3c(Nc4c(Cl)ccc5c4OCO5)ncnc3c2)CC1,5.586700235918748,541.209196804,10,1,3.9395000000000024,True
+3262,CHEMBL2332119,2600.0,nM,2013.0,NC(=O)C1=C(N)C(=O)C=C(Nc2ccccc2O)C1=O,5.585026652029182,273.074955832,6,4,-0.4620999999999999,True
+3263,CHEMBL130163,2600.0,nM,1994.0,CO[C@H]1[C@@H](N(C)C(C)=O)C[C@@H]2O[C@@]1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,5.585026652029182,508.21105537600005,6,1,4.612900000000003,True
+3264,CHEMBL449949,2600.0,nM,2009.0,O=C(O[C@H]1CN[C@H](C#Cc2cc3ncnc(Nc4ccc(OCc5cccc(F)c5)nc4)c3s2)C1)N1CCOCC1,5.585026652029182,574.1798525639999,10,2,4.098800000000003,True
+3265,CHEMBL1241944,2600.0,nM,2008.0,CC(C)n1nc(-c2ccc(C#N)c(O)c2)c2c(N)ncnc21,5.585026652029182,294.122909068,7,2,2.2336799999999997,True
+3266,CHEMBL475352,2600.0,nM,2009.0,COc1cc(Nc2ncnc3[nH]cnc23)ccc1-c1nc2ccccc2s1,5.585026652029182,374.094980068,7,2,4.381800000000002,True
+3267,CHEMBL1242749,2600.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2[C@@H]1CCOC1,5.585026652029182,315.11315290799996,7,2,1.8815999999999995,True
+3268,CHEMBL4090330,2626.0,nM,2017.0,C=CC(=O)Nc1cc(Nc2n[nH]c3ccccc23)ccc1N(C)CCN(C)C,5.58070527824654,378.21680945200006,5,3,3.4288000000000016,True
+3269,CHEMBL1945648,2640.0,nM,2012.0,Cc1ccc(C(=O)NS(=O)(=O)c2ccc(Br)cc2)c(Cl)n1,5.578396073130167,387.92840296,4,1,2.924620000000001,True
+3270,CHEMBL174634,2650.0,nM,2000.0,Cc1ccccc1-c1cn(-c2ccccc2)c2ncnc(N)c12,5.576754126063192,300.13749651200004,4,1,3.9781200000000014,True
+3271,CHEMBL354033,2670.0,nM,2001.0,Nc1ncnc2c1c(-c1ccc(O)cc1)cn2C1CCNC1,5.573488738635424,295.143310164,6,3,1.9204999999999997,True
+3272,CHEMBL1821865,2670.0,nM,2011.0,Cc1ccc(C2CC(c3ccc(C)c(C)c3)=NN2c2nc(-c3ccccc3)cs2)cc1,5.573488738635424,423.17691880000007,4,0,7.091060000000006,True
+3273,CHEMBL114392,2700.0,nM,2003.0,C=C(CN1CCOCC1)C(=O)Nc1ccc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2c1,5.568636235841012,465.13678081200004,6,2,4.469480000000003,True
+3274,CHEMBL4292715,2700.0,nM,2018.0,Cc1oc2ncnc(Nc3cccc(Cl)c3)c2c1C(=O)NCCO,5.568636235841012,346.08326802,6,3,2.6503200000000002,True
+3275,CHEMBL65063,2700.0,nM,1997.0,Nc1ncnc2c1cnn2-c1ccccc1,5.568636235841012,211.08579528799999,5,1,1.3977,True
+3276,CHEMBL1080815,2700.0,nM,2009.0,Clc1cccc(Nc2ncnc3ccc(Cl)cc23)c1,5.568636235841012,289.01735264800004,3,1,4.680200000000001,True
+3277,CHEMBL3133908,2700.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3cccc(CC)c3)c2c1,5.568636235841012,318.148061196,4,2,4.0603000000000025,True
+3278,CHEMBL319540,2710.0,nM,1997.0,Cc1c(C)n(-c2ccccc2)c2ncnc(N)c12,5.5670307091255955,238.12184644799999,4,1,2.6195399999999998,True
+3279,CHEMBL1241858,2720.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2CC1CCCNC1,5.5654310959658,358.13088690800004,7,3,2.4341,True
+3280,CHEMBL534948,2730.0,nM,2007.0,Cc1cccc(C)c1Nc1ncc(-c2ccc(OCC3CCCN(C)C3)cc2)n2cncc12.Cl,5.563837352959244,477.22953832400003,6,1,5.899140000000005,True
+3281,CHEMBL2070196,2750.0,nM,2012.0,O=C(Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1)C1COc2ccccc2O1,5.560667306169737,432.09891808399993,6,2,4.805300000000003,True
+3282,CHEMBL4286943,2800.0,nM,2018.0,COc1cc(-c2nc3sc(-c4ccccc4)cn3n2)cc(OC)c1OC,5.552841968657781,367.099062404,7,0,4.150600000000004,True
+3283,CHEMBL418907,2800.0,nM,1991.0,COc1cc(/C=C/[N+](=O)[O-])ccc1OS(=O)(=O)c1ccc(C(=O)O)cc1,5.552841968657781,379.036187376,7,1,2.4085,True
+3284,CHEMBL200976,2800.0,nM,2006.0,COC(=O)c1c(OCCN2CCCCC2)c2ccccc2c2oc3c(c12)C(=O)c1ccccc1C3=O,5.552841968657781,483.16818751999995,7,0,5.012700000000005,True
+3285,CHEMBL1241946,2800.0,nM,2008.0,CC(=O)c1cccc(-c2nn(C(C)C)c3ncnc(N)c23)c1,5.552841968657781,295.143310164,6,1,2859,True
+3286,CHEMBL3263378,2800.0,nM,2014.0,COc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc4ccccc4c3)C2)cc1,5.552841968657781,401.119797848,5,0,4.628900000000004,True
+3287,CHEMBL182397,2800.0,nM,2004.0,COc1cc2ncnc(Nc3cccc(NC(=O)c4ccccc4)c3F)c2cc1OC,5.552841968657781,418.144118688,6,2,4.782000000000004,True
+3288,CHEMBL3905432,2807.0,nM,2015.0,CC#CC(=O)N1CCC[C@H]1Cn1nc(-c2ccc(Oc3ccccc3)cc2)c2c(N)ncnc21,5.551757587365562,452.19607400800004,7,1,3.882100000000002,True
+3289,CHEMBL1812569,2810.0,nM,2011.0,O=C(/C=C/c1cccc2ccccc12)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.55129368009492,450.12473890800004,4,2,6.831900000000004,True
+3290,CHEMBL168266,2820.0,nM,2001.0,Nc1ncnc2c1c(-c1ccccc1)cn2C1CC(O)C1,5.549750891680639,280.132411132,5,2,2.3763000000000005,True
+3291,CHEMBL4213082,2820.0,nM,2017.0,C=CC(=O)Nc1ccc(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3OC)ncc2Cl)cc1,5.549750891680639,494.18331640400004,8,2,4.550800000000004,True
+3292,CHEMBL116857,2880.0,nM,2003.0,COc1cc(NC(=O)/C=C/CN(C)C)cc2c(Nc3cccc(Br)c3)c(C#N)cnc12,5.5406075122407685,479.09568704400004,6,2,4.677480000000004,True
+3293,CHEMBL3740003,2890.0,nM,2015.0,Cc1[nH]c(-c2ccccc2)c(-c2ccccc2)c1-c1ccc(NC(=O)c2ccccc2)c(=O)o1,5.539102157243452,446.1630425639999,3,2,6.529620000000005,True
+3294,CHEMBL4085902,2900.0,nM,2017.0,COc1cc(Br)c(/C=C2\CC(C)CC(=C\c3nc(C)c(C)nc3C)/C2=N/O)cc1OC,5.5376020021010435,485.131403856,6,1,5.9086600000000065,True
+3295,CHEMBL116595,2900.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccccc2)c1O,5.5376020021010435,340.088163372,5,2,3.085380000000002,True
+3296,CHEMBL3604940,2900.0,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3n[nH]c4ccc(Br)cc34)cc(N3CCN(C)CC3)n2)c1,5.5376020021010435,548.1283841400002,8,3,4.527600000000003,True
+3297,CHEMBL1242566,2900.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2C1CCC1,5.5376020021010435,299.118238288,6,2,2.6452,True
+3298,CHEMBL1240566,2900.0,nM,2008.0,Cn1nc(-c2ccc3cc[nH]c3c2)c2c(N)ncnc21,5.5376020021010435,264.112344384,5,2,2.0938,True
+3299,CHEMBL1242567,2900.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2C1CNC1,5.5376020021010435,300.11348725600004,7,3,1.0644999999999996,True
+3300,CHEMBL3983460,2933.0,nM,2017.0,COc1cc2c(Nc3ccc(NC(=O)Nc4ccccc4)cc3)ncnc2cc1OCc1ccccc1,5.532687937019448,491.19573966,6,3,6.605000000000004,True
+3301,CHEMBL1828860,2940.0,nM,2011.0,Cc1ncc([N+](=O)[O-])n1CC(=O)NS(=O)(=O)c1ccccc1,5.531652669587842,324.052840484,7,1,0.6048199999999997,True
+3302,CHEMBL3628791,2980.0,nM,2015.0,Fc1ccc(Nc2ncnc3sccc23)cc1Cl,5.525783735923746,279.003324124,4,1,4.227400000000001,True
+3303,CHEMBL2348194,2991.0,nM,2013.0,C[C@@H](Nc1ncnc2oc(-c3ccccc3)c(-c3ccccc3)c12)c1ccccc1,5.5241835869686815,391.168462292,4,1,6.729900000000005,True
+3304,CHEMBL204715,3000.0,nM,2006.0,COc1ccc2c(c1)Oc1ncnc(Nc3cccc(Br)c3)c1NC2,5.522878745280337,398.03783782000005,6,2,4.709100000000001,True
+3305,CHEMBL543661,3000.0,nM,1997.0,COc1cc(Nc2ncnc3cc(OC)c(OC)cc23)cc(OC)c1.Cl,5.522878745280337,377.11423379999997,7,1,3.8296000000000032,True
+3306,CHEMBL492199,3000.0,nM,1992.0,N#CC(C#N)=C(C#N)c1cc(O)c(O)c(O)c1,5.522878745280337,227.03309102,6,3,1.1277399999999995,True
+3307,CHEMBL2064390,3000.0,nM,2012.0,CC(C)Oc1cccc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)c1,5.522878745280337,463.22195440800004,9,1,3.7908000000000026,True
+3308,CHEMBL483233,3000.0,nM,1992.0,CCOc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccc(O)cc2)c1O,5.522878745280337,370.09872805599997,6,3,3.181080000000001,True
+3309,CHEMBL310798,3000.0,nM,1989.0,N#CC(C#N)=Cc1cc(O)c(O)c(O)c1,5.522878745280337,202.037842052,5,3,1.2339599999999997,True
+3310,CHEMBL13485,3000.0,nM,2007.0,CCN(CC)CCNC(=O)c1c(C)[nH]c(/C=C2\C(=O)Nc3ccc(Cl)cc32)c1C,5.522878745280337,414.182253784,3,3,3.8492400000000018,True
+3311,CHEMBL2325109,3010.0,nM,2013.0,NC(=S)N1N=C(c2ccccc2)CC1c1ccc2ccccc2c1,5.521433504406157,331.114318544,2,1,4.234500000000003,True
+3312,CHEMBL1242290,3020.0,nM,2008.0,COc1ccc(-c2nn(C(C)C)c3ncnc(N)c23)cc1OC,5.519993057042849,313.153874848,7,1,2.6736000000000004,True
+3313,CHEMBL1958023,3030.0,nM,2012.0,Cc1ccc(C2CC(c3ccccc3)=NN2C2=NC(=O)CS2)cc1,5.518557371497695,335.109233164,4,0,3.775520000000003,True
+3314,CHEMBL3633939,3050.0,nM,2015.0,N#CC(C#N)=CNc1ccc2ncnc(Nc3ccc(OCc4ccccn4)c(Cl)c3)c2c1,5.515700160653214,453.110485812,8,2,5.343760000000002,True
+3315,CHEMBL1272168,3057.0,nM,2010.0,C=CC(=O)N1CCc2c(sc3ncnc(N[C@@H](CO)c4ccccc4)c23)C1,5.514704561273911,380.13069687999996,6,2,2.9075000000000015,True
+3316,CHEMBL2442327,3060.0,nM,2013.0,C#Cc1cccc(-n2ccc3cc(OC)cc(O)c3c2=O)c1,5.514278573518419,291.08954327600003,4,1,2.6862000000000013,True
+3317,CHEMBL1173454,3060.0,nM,2010.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccc([N+](=O)[O-])cc3)C2)cc1C,5.514278573518419,354.11504681599996,4,1,3.606340000000002,True
+3318,CHEMBL564829,3069.0,nM,2009.0,CNC(=O)c1nn(C)c2c1C(C)(C)Cc1cnc(Nc3ccc(N4CCN(C)CC4)cc3)nc1-2,5.513003111568176,460.26990764400006,8,2,2.5658000000000003,True
+3319,CHEMBL1821866,3080.0,nM,2011.0,COc1ccc(C2CC(c3ccc(C)c(C)c3)=NN2c2nc(-c3ccccc3)cs2)cc1,5.511449283499554,439.17183342,5,0,6.7912400000000055,True
+3320,CHEMBL4203804,3080.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccc(NC(C)=O)cc2)n1,5.511449283499554,482.183316404,8,2,4.384700000000002,True
+3321,CHEMBL4075241,3100.0,nM,2017.0,COc1cc(Cl)c(/C=C2\CN(C(C)C)C/C(=C\c3nc(C)c(C)nc3C)C2=O)cc1OC,5.508638306165726,455.1975695,6,0,4.832560000000004,True
+3322,CHEMBL3604922,3100.0,nM,2015.0,C=CC(=O)Nc1ccc(Oc2nc(Nc3cc(C)[nH]n3)cc(N3CCN(C)CC3)n2)cc1,5.508638306165726,434.2178720720001,8,3,2.920320000000001,True
+3323,CHEMBL296582,3100.0,nM,1992.0,O=C(NCc1ccccc1)c1cc2cc(O)c(O)cc2cn1,5.508638306165726,294.100442308,4,3,2.5760000000000014,True
+3324,CHEMBL55994,3100.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)c1cccs1,5.508638306165726,271.030314148,5,2,2.949180000000001,True
+3325,CHEMBL383444,3100.0,nM,2006.0,COc1ccc2c(c1)CNc1c(Nc3cccc(Br)c3)ncnc1O2,5.508638306165726,398.03783782000005,6,2,4.709100000000002,True
+3326,CHEMBL599728,3110.0,nM,2010.0,CCCCCCCCCCOC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.507239610973163,452.21988874399995,6,1,6.228300000000006,True
+3327,CHEMBL1928712,3130.0,nM,2012.0,Brc1ccc(CNc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)cc1,5.504455662453552,481.97417071200005,4,2,6.510500000000003,True
+3328,CHEMBL3235200,3170.0,nM,2014.0,Cc1ccc2nc(Oc3ccccc3)c(/C=N/NC(=O)Cn3c([N+](=O)[O-])cnc3C)cc2c1,5.49894073778225,444.15460312,8,1,3.8989400000000014,True
+3329,CHEMBL519147,3180.0,nM,2008.0,Nc1nc(Nc2ccc(Cl)cc2)c2cc(CCc3ccccc3)[nH]c2n1,5.497572880015569,363.125073256,4,3,4.722300000000002,True
+3330,CHEMBL1958037,3200.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(Br)cc3)CC2c2ccccc2)=N1,5.494850021680094,399.00409516800005,4,0,4.229600000000003,True
+3331,CHEMBL186747,3200.0,nM,2004.0,COc1cc2ncnc(Nc3ccc(C)c(NC(=O)c4ccccc4)c3)c2cc1OC,5.494850021680094,414.16919056399996,6,2,4.9513200000000035,True
+3332,CHEMBL47940,3200.0,nM,2000.0,Nc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)cn2C1CCCC1,5.494850021680094,370.179361324,5,1,5.587900000000003,True
+3333,CHEMBL3133909,3200.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(CC)cc3)c2c1,5.494850021680094,318.148061196,4,2,4.0603000000000025,True
+3334,CHEMBL3740131,3220.0,nM,2015.0,CCOC(=O)c1nn(-c2ccccc2)cc1C(=O)c1c(C)[nH]c(-c2ccccc2)c1-c1ccccc1,5.492144128304169,475.1895916600001,5,1,6.250520000000005,True
+3335,CHEMBL1928707,3220.0,nM,2012.0,Oc1ccccc1CNc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,5.492144128304169,420.0585732640001,5,3,5.4536000000000024,True
+3336,CHEMBL1173651,3240.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccc(Br)cc1,5.489454989793388,379.01676802800006,6,0,3.1188200000000013,True
+3337,CHEMBL3263379,3250.0,nM,2014.0,Cc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc4ccccc4c3)C2)cc1,5.4881166390211265,385.124883228,4,0,4.928720000000004,True
+3338,CHEMBL184311,3250.0,nM,2004.0,Cc1ccc2c(Nc3ccc(F)c(Cl)c3)ncnn12,5.4881166390211265,276.05780222,4,1,3.5738200000000013,True
+3339,CHEMBL592707,3260.0,nM,2010.0,Cc1ccc(/C=N/NC2=NC(=O)CS2)cc1,5.4867823999320615,233.062282972,4,1,1.5479199999999997,True
+3340,CHEMBL1945446,3270.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(F)cc1)c1cncc(Br)c1,5.485452247339714,357.942303436,4,1,2.1018999999999997,True
+3341,CHEMBL3425671,3270.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(NC(C)=O)c2)n1,5.485452247339714,482.183316404,8,2,4.384700000000002,True
+3342,CHEMBL2325110,3280.0,nM,2013.0,NC(=S)N1N=C(c2ccc(F)cc2)CC1c1ccc2ccccc2c1,5.484126156288321,349.104896732,2,1,4.373600000000002,True
+3343,CHEMBL469996,3300.0,nM,2009.0,NS(=O)(=O)c1ccc(Nc2nc3ncnc(Nc4ccc(N5CCOCC5)c(Cl)c4)c3s2)cc1,5.481486060122112,517.07575718,10,3,3.710900000000003,True
+3344,CHEMBL461140,3300.0,nM,2008.0,CN(C)CCOc1ccc(/C=C/c2cc(-c3cc4c(=O)[nH]cnc4[nH]3)ccn2)cc1,5.481486060122112,401.1851749760001,5,2,3.4240000000000013,True
+3345,CHEMBL103860,3300.0,nM,1994.0,O=C(O)c1cc(CCc2cc(O)ccc2O)ccc1O,5.481486060122112,274.084123548,4,4,2.286800000000001,True
+3346,CHEMBL242740,3300.0,nM,2006.0,COc1c(O)cc2occ(-c3ccc(O)cc3)c(=O)c2c1O,5.481486060122112,300.063388104,6,3,2.5854000000000004,True
+3347,CHEMBL1240553,3300.0,nM,2008.0,COc1ccc(-c2nn(C3CCCC3)c3ncnc(N)c23)cc1OC,5.481486060122112,339.169524912,7,1,3.2078000000000007,True
+3348,CHEMBL2047020,3310.0,nM,2012.0,C#Cc1cccc(NC(=O)c2cc(NC(=O)CCCCCC(=O)NO)ccc2O)c1,5.480172006224282,409.16377083599997,5,5,3.020200000000001,True
+3349,CHEMBL1958019,3380.0,nM,2012.0,O=C1CSC(N2N=C(c3ccccc3)CC2c2ccccc2)=N1,5.471083299722345,321.09358310000005,4,0,3.467100000000002,True
+3350,CHEMBL3233765,3399.0,nM,2014.0,CN1CCN(CC(=O)Nc2cc3c(Nc4ccc(F)c(Cl)c4)ncnc3s2)CC1,5.468648835416942,434.10918616000004,7,2,3.4133000000000013,True
+3351,CHEMBL477197,3400.0,nM,2008.0,Oc1cc2c(cc1O)[C@@H]1c3ccc(O)c(O)c3OC[C@]1(O)C2,5.468521082957745,302.079038168,6,5,1.3204999999999993,True
+3352,CHEMBL2424795,3400.0,nM,2013.0,Clc1cccc(Nc2ncnc3ccc(NCc4cccs4)cc23)c1,5.468521082957745,366.07059516,5,2,5.700400000000002,True
+3353,CHEMBL482489,3400.0,nM,2008.0,Nc1nc(Nc2cccc(Br)c2)c2cc(CCc3ccccc3Cl)[nH]c2n1,5.468521082957745,441.03558532400007,4,3,5.484800000000002,True
+3354,CHEMBL203219,3400.0,nM,2006.0,Brc1cccc(Nc2ncnc3c2NCc2ccccc2O3)c1,5.468521082957745,368.027273136,5,2,4.700500000000003,True
+3355,CHEMBL3133894,3400.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(NC3CCCCC3)c2c1,5.468521082957745,296.16371126,4,2,3.4989000000000026,True
+3356,CHEMBL4084214,3400.0,nM,2017.0,CCC(=O)N1CCC[C@@H](n2nc(-c3cccc(F)c3)c3c(N)ncnc32)C1,5.468521082957745,368.1760875120001,6,1,2.7881,True
+3357,CHEMBL378145,3400.0,nM,2006.0,Clc1ccc2c(c1)CNc1c(Nc3cccc(Br)c3)ncnc1O2,5.468521082957745,401.98830078400005,5,2,5.353900000000002,True
+3358,CHEMBL169467,3400.0,nM,2001.0,COc1ccc(CC(CO)n2cc(-c3cccc(O)c3)c3c(N)ncnc32)cc1,5.468521082957745,390.1691905640001,7,3,3.1708000000000007,True
+3359,CHEMBL176702,3400.0,nM,2000.0,Nc1ncnc2c1c(-c1ccccc1)cn2-c1cccc(CNCCO)c1,5.468521082957745,359.174610292,6,3,2.7516,True
+3360,CHEMBL1828861,3430.0,nM,2011.0,Cc1ccc(S(=O)(=O)NC(=O)Cn2c([N+](=O)[O-])cnc2C)cc1,5.464705879957229,338.068490548,7,1,0.9132399999999996,True
+3361,CHEMBL3739586,3450.0,nM,2015.0,Cc1ccc(-n2cc3c(-c4c[nH]c(-c5ccccc5)c4-c4ccccc4)nnc(O)c3n2)cc1,5.4621809049267265,443.17461029200007,5,2,6.158620000000005,True
+3362,CHEMBL1812570,3450.0,nM,2011.0,O=C(/C=C/c1ccc([N+](=O)[O-])cc1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.4621809049267265,445.09416705200005,6,2,5.586900000000002,True
+3363,CHEMBL604785,3460.0,nM,2010.0,Cc1cccc(CN(Cc2ccc(O)cc2)C(=S)Nc2ccccc2)c1O,5.460923901207224,378.14019894399996,3,3,4.805420000000003,True
+3364,CHEMBL480356,3480.0,nM,2009.0,Cc1[nH]c(/C=C2\C(=O)Nc3ccc(C(=O)NNc4ccccc4)cc32)c(C)c1CCC(=O)O,5.458420756053419,444.17975524799994,4,5,3.898340000000003,True
+3365,CHEMBL1958021,3490.0,nM,2012.0,O=C1CSC(N2N=C(c3ccccc3)CC2c2ccc(Cl)cc2)=N1,5.45717457304082,355.054610748,4,0,4.120500000000003,True
+3366,CHEMBL1812564,3490.0,nM,2011.0,O=C(/C=C/c1ccc(Br)cc1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.45717457304082,478.0196009120001,4,2,6.441200000000003,True
+3367,CHEMBL334915,3500.0,nM,1997.0,Cn1c([Se][Se]c2c(C(=O)O)c3ccccc3n2C)c(C(=O)O)c2ccccc21,5.455931955649724,507.94404959199994,4,2,1.3405999999999996,True
+3368,CHEMBL2426281,3500.0,nM,2013.0,C=CC(=O)Nc1cccc(Nc2ncc(Cl)c(-c3c[nH]c4ccccc34)n2)c1,5.455931955649724,389.10433781200004,4,3,5.146400000000003,True
+3369,CHEMBL1504817,3500.0,nM,2012.0,O=C1NN(c2ccc(F)c(Cl)c2)C(=O)/C1=C\c1cccc(OC(=O)c2cccs2)c1,5.455931955649724,442.0190337639999,5,1,4.221200000000002,True
+3370,CHEMBL2385970,3500.0,nM,2013.0,CN(C)C/C=C/C(=O)Nc1ccc(-c2cncc(C#N)c2Nc2ccc(F)c(Cl)c2)cc1,5.455931955649724,449.14186619200007,5,2,5.212680000000004,True
+3371,CHEMBL1272275,3503.0,nM,2010.0,O=C(/C=C/c1ccccc1)N1CCc2c(sc3ncnc(N[C@H](CO)c4ccccc4)c23)C1,5.455559862682307,456.161997008,6,2,4.434900000000003,True
+3372,CHEMBL2442319,3510.0,nM,2013.0,C#Cc1cccc(-n2ccc3cc(OC)cc(OC)c3c2=O)c1,5.454692883534176,305.10519334,4,0,2.989200000000001,True
+3373,CHEMBL3426225,3518.0,nM,2015.0,CCn1nc(C#Cc2cc(C(=O)Nc3ccc(CN4CCN(C)CC4)c(C(F)(F)F)c3)ccc2C)c2c(N)ncnc21,5.453704164878557,576.2572922720001,8,2,4.155120000000003,True
+3374,CHEMBL2047018,3530.0,nM,2012.0,O=C(CCCCCC(=O)Nc1ccc(O)c(C(=O)Nc2ccc(F)c(Cl)c2)c1)NO,5.452225294612178,437.115376672,5,5,3.8314000000000012,True
+3375,CHEMBL1928716,3540.0,nM,2012.0,Oc1ccccc1CNc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.450996737974212,376.10908884400004,5,3,5.344500000000003,True
+3376,CHEMBL1762110,3580.0,nM,2011.0,CC(=O)NC[C@H]1CC[C@H](c2nc(-c3cc4ccccc4[nH]3)c3c(N)nccn32)CC1,5.446116973356125,402.21680945200006,5,3,3.869700000000001,True
+3377,CHEMBL597708,3580.0,nM,2010.0,CCCCCCCCCNC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.446116973356125,437.22022309199997,5,2,5.411200000000006,True
+3378,CHEMBL3604941,3600.0,nM,2015.0,C=CC(=O)Nc1cccc(Oc2nc(Nc3n[nH]c4ccccc34)cc(N3CCN(C(C)=O)CC3)n2)c1,5.443697499232711,498.21278669200007,8,3,3.6818000000000017,True
+3379,CHEMBL2424794,3600.0,nM,2013.0,O=C(/C=C/c1cccnc1Cl)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.443697499232711,435.06536546000007,5,2,5.727100000000003,True
+3380,CHEMBL3740923,3600.0,nM,2015.0,Oc1nnc(-c2c[nH]c(-c3ccccc3)c2-c2ccccc2)c2cn(-c3ccccc3)nc12,5.443697499232711,429.15896022800007,5,2,5.8502000000000045,True
+3381,CHEMBL1812561,3610.0,nM,2011.0,O=C(/C=C/c1ccccc1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.442492798094341,400.10908884400004,4,2,5.678700000000003,True
+3382,CHEMBL1172803,3620.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccc(Cl)cc1,5.441291429466834,335.067283608,6,0,3.0097200000000015,True
+3383,CHEMBL1242751,3660.0,nM,2008.0,COc1cccc(-c2nn(C(C)C)c3ncnc(N)c23)c1OC,5.436518914605589,313.153874848,7,1,2.6736000000000004,True
+3384,CHEMBL3741960,3670.0,nM,2015.0,Cc1c(C(=O)c2coc3ccc(O)cc23)[nH]c(-c2ccccc2)c1-c1ccccc1,5.435333935747911,393.136493468,3,2,6.3399200000000056,True
+3385,CHEMBL2070195,3680.0,nM,2012.0,O=C(Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1)C1COc2ccccc2O1,5.434152181326481,476.04840250399997,6,2,4.914400000000003,True
+3386,CHEMBL2064399,3700.0,nM,2012.0,C[C@H](Nc1ncnc2cc3oc(=O)n(CCCN4CCOCC4)c3cc12)c1ccccc1,5.431798275933005,433.211389724,8,1,3.4331000000000023,True
+3387,CHEMBL206197,3700.0,nM,2006.0,Nc1ccc2c(c1)CNc1c(Nc3ccc(F)c(Cl)c3)ncnc1O2,5.431798275933005,357.079265936,6,3,4.312700000000002,True
+3388,CHEMBL104466,3700.0,nM,2003.0,COc1cc2ncc(N[C@H]3CC[C@H](O)CC3)nc2cc1OC,5.431798275933005,303.158291532,6,2,2.3624,True
+3389,CHEMBL4079125,3700.0,nM,2017.0,Clc1ccc(-c2nnc(Cc3nc4ccccc4[nH]3)o2)c(Cl)c1,5.431798275933005,344.02316629999996,4,1,4.510500000000001,True
+3390,CHEMBL3604915,3700.0,nM,2015.0,CCC(=O)Nc1cccc(-c2nc(Nc3cc[nH]n3)c3ccccc3n2)c1,5.431798275933005,358.154209196,5,3,4.112000000000001,True
+3391,CHEMBL3133896,3710.0,nM,2013.0,C=CC(=O)N1CCc2c(sc3ncnc(Nc4ccc(Br)cc4F)c23)C1,5.430626090384954,432.00557238799996,5,1,4.407200000000002,True
+3392,CHEMBL1242110,3720.0,nM,2008.0,CC(C)n1nc(-c2cccc(O)c2F)c2c(N)ncnc21,5.429457060118103,287.118238288,6,2,2.501099999999999,True
+3393,CHEMBL1830263,3740.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1cccc([N+](=O)[O-])c1)c1ccccc1,5.427128397799518,326.08374668799996,4,2,2.8455000000000013,True
+3394,CHEMBL287022,3762.4,nM,2004.0,CC#CC(=O)Nc1cnc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2c1,5.424535034261977,379.063615872,5,2,3.9993800000000013,True
+3395,CHEMBL332497,3830.0,nM,2003.0,COc1cc2ncc(C#N)c(Nc3cccc(Br)c3)c2cc1NC(=O)/C=C/CN1CCOCC1,5.416801226031377,521.106251728,7,2,4.448080000000003,True
+3396,CHEMBL1821868,3850.0,nM,2011.0,Cc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc([N+](=O)[O-])cc3)C2)cc1C,5.414539270491499,454.14634694399996,6,0,6.690840000000005,True
+3397,CHEMBL1241485,3850.0,nM,2008.0,COc1cc(-c2nn(C(C)C)c3ncnc(N)c23)ccc1N,5.414539270491499,298.154209196,7,2,2.2472,True
+3398,CHEMBL1241483,3860.0,nM,2008.0,COc1cc(-c2nn(C(C)C)c3ncnc(N)c23)ccc1F,5.413412695328245,301.133888352,6,1,2.8041,True
+3399,CHEMBL1173794,3870.0,nM,2010.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccccc3Cl)C2)cc1C,5.412289034981089,343.090996256,2,1,4.351540000000003,True
+3400,CHEMBL1170278,3880.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1cccc2ccccc12,5.411168274405791,351.12190602400005,6,0,3.509520000000003,True
+3401,CHEMBL3416614,3883.0,nM,2015.0,Brc1cc2c(NCc3ccncc3)ncnc2s1,5.410832609453952,319.9731293880001,5,1,3.4609000000000005,True
+3402,CHEMBL3740582,3890.0,nM,2015.0,Cc1[nH]c(-c2ccccc2)c(-c2ccccc2)c1-c1nnc(C)c2nn(-c3ccccc3)cc12,5.410050398674293,441.1953457360001,4,1,6.761440000000006,True
+3403,CHEMBL4213146,3900.0,nM,2018.0,CCc1c2cc(C(F)(F)F)ccc2n2cc(Cc3ccccc3)[nH]c(=O)c12,5.4089353929735005,370.129297824,2,1,4.952800000000004,True
+3404,CHEMBL541307,3900.0,nM,1995.0,CN(C)CC(CNNC(N)=O)C(=O)c1ccc(OCc2ccccc2)cc1.Cl,5.4089353929735005,406.177168404,5,3,2.220800000000002,True
+3405,CHEMBL3221542,3900.0,nM,2011.0,CCCOc1cc2ncnc(Nc3ccc(NC(=O)OCC)c(C)c3)c2cc1OC.Cl,5.4089353929735005,446.17208302399996,7,2,5.469420000000005,True
+3406,CHEMBL2316154,3900.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccc(N(C)C)cc3)C2=O)cc(OC)c1,5.4089353929735005,377.19909372399997,4,0,4.989800000000005,True
+3407,CHEMBL3809489,3900.0,nM,2018.0,Nc1nc(Nc2ccc3c(c2)CC[C@@H](N2CCCC2)CC3)nn1-c1cc2c(nn1)-c1ccccc1CCC2,5.4089353929735005,506.2906430880001,8,2,4.882000000000005,True
+3408,CHEMBL3604927,3900.0,nM,2015.0,Cc1cc(Nc2cc(N3CCN(C)CC3)nc(Oc3cccc([N+](=O)[O-])c3)n2)n[nH]1,5.4089353929735005,410.18148656400007,9,2,2.70402,True
+3409,CHEMBL3234740,3900.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1cnccn1,5.4089353929735005,512.2147587640001,6,2,4.055820000000003,True
+3410,CHEMBL4102284,3900.0,nM,2017.0,Cc1nc(C)c(/C=C2\CN(C(C)C)C/C(=C\c3nc(C)c(C)nc3C)C2=NO)nc1C,5.4089353929735005,420.26375964400006,7,1,4.138320000000003,True
+3411,CHEMBL4062617,3920.0,nM,2017.0,C=CC(=O)NCc1cccc(-c2nc(C3CC3)c(-c3ccnc4[nH]c(-c5ccccc5)cc34)[nH]2)c1,5.406713932979542,459.20591042000007,3,3,5.966600000000005,True
+3412,CHEMBL1365395,3920.0,nM,2015.0,Cc1ccc2c(C)nc(Nc3nc(O)cc(CSc4nnnn4-c4ccccc4)n3)nc2c1,5.406713932979542,457.14332722800015,11,2,3.7538400000000003,True
+3413,CHEMBL3628799,3950.0,nM,2015.0,O=C(Nc1ccc(Nc2ncnc3sc4c(c23)CCCC4)cc1)Nc1cccc(Br)c1,5.4034029043735385,493.05719336000004,5,3,6.720200000000005,True
+3414,CHEMBL3133895,3950.0,nM,2013.0,C=CC(=O)N1CCc2c(sc3ncnc(Nc4cccc(C)c4F)c23)C1,5.4034029043735385,368.110710384,5,1,3.953120000000003,True
+3415,CHEMBL3263359,3960.0,nM,2014.0,Cc1ccc(C2=NN(C3=NC(c4ccccc4)CS3)C(c3cccc4ccccc34)C2)cc1C,5.402304814074488,461.192568864,4,0,7.451840000000007,True
+3416,CHEMBL3221552,4000.0,nM,2011.0,COC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1C.Cl,5.3979400086720375,404.12513283199996,7,2,4.299120000000003,True
+3417,CHEMBL358494,4000.0,nM,1996.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)N1CCN(C(=O)/C(C#N)=C/c2ccc(O)c(O)c2)CC1,5.3979400086720375,460.13828435999994,8,4,1.6939599999999995,True
+3418,CHEMBL483232,4000.0,nM,1992.0,CCOc1cc(/C=C(\C#N)C(N)=O)cc(CSc2cccc(OC)c2)c1O,5.3979400086720375,384.11437811999997,6,2,3.484080000000002,True
+3419,CHEMBL319620,4000.0,nM,1997.0,O=C(O)c1cc(NCc2cc(O)ccc2O)ccc1O,5.3979400086720375,275.07937251600003,5,5,2.1137,True
+3420,CHEMBL2018755,4000.0,nM,2012.0,COC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1C,5.3979400086720375,368.14845511999994,7,2,3.877320000000002,True
+3421,CHEMBL543669,4000.0,nM,1997.0,COc1cc2ncnc(N(C)c3ccccc3)c2cc1OC.Cl,5.3979400086720375,331.10875449599996,5,0,3.8367000000000036,True
+3422,CHEMBL78280,4000.0,nM,1991.0,CNC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C(\C)[N+](=O)[O-])cc2OC)cc1,5.3979400086720375,406.08347191599995,7,1,2.460000000000001,True
+3423,CHEMBL7810,4000.0,nM,1999.0,COc1cc(O)c2c(=O)c(-c3cccc(Cl)c3)cn(CCc3ccccc3)c2c1,5.3979400086720375,405.11317118,4,1,5.278800000000004,True
+3424,CHEMBL2312304,4090.0,nM,2013.0,O=C(NCCCN1CCOC1=O)c1cnc(NCc2cc(Cl)ccc2Cl)nc1NC1CCCC1,5.388276691992658,506.159994116,7,3,4.3221000000000025,True
+3425,CHEMBL448730,4100.0,nM,1999.0,CCN(CC)CCn1c2ccccc2c2c(Nc3cccc(Br)c3)ncnc21,5.3872161432802645,437.1215078680001,5,1,5.432400000000005,True
+3426,CHEMBL117804,4100.0,nM,1995.0,c1ccc(CCNc2ncnc3ccccc23)cc1,5.3872161432802645,249.12659748,3,1,3.2844000000000015,True
+3427,CHEMBL1641989,4100.0,nM,2011.0,CN(C)CCCC(=O)Nc1ccc2c(C#N)cnc(Nc3cccc(Br)c3)c2c1,5.3872161432802645,451.100772424,5,2,4.8928800000000034,True
+3428,CHEMBL2424807,4100.0,nM,2013.0,Clc1cccc(Nc2ncnc3ccc(NCc4cccc(Br)n4)cc23)c1,5.3872161432802645,439.01993526,5,2,5.796400000000002,True
+3429,CHEMBL382186,4100.0,nM,2006.0,CS(=O)(=O)Nc1ccc2c(c1)CNc1c(Nc3cccc(Br)c3)ncnc1O2,5.3872161432802645,461.01572247200005,7,3,4.072000000000002,True
+3430,CHEMBL103552,4100.0,nM,1994.0,O=C(O)c1cc(N(Cc2ccccc2O)Cc2cc(O)ccc2O)ccc1O,5.3872161432802645,381.12123732799995,6,5,3.414000000000002,True
+3431,CHEMBL1172802,4120.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccc(F)cc1,5.3851027839668655,319.096834148,6,0,2.49542,True
+3432,CHEMBL1958039,4120.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(Br)cc3)CC2c2ccc(Cl)cc2)=N1,5.3851027839668655,432.9651228160001,4,0,4.883000000000004,True
+3433,CHEMBL1683971,4130.0,nM,2011.0,Cc1ncnc(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)c1C#CCN1CCOCC1,5.3840499483435975,466.157181908,6,1,4.583820000000004,True
+3434,CHEMBL3746212,4130.0,nM,2016.0,CC(=O)N1N=C(c2ccc(Br)cc2)CC1c1ccc(C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,5.3840499483435975,539.0804309040001,8,0,4.416820000000004,True
+3435,CHEMBL589809,4150.0,nM,2010.0,O=C(Nc1ccccc1)N(Cc1ccc(F)cc1)Cc1cc(Cl)cc(Cl)c1O,5.381951903287908,418.06511136399996,2,2,6.072400000000004,True
+3436,CHEMBL3237940,4150.0,nM,2014.0,Cc1nn(-c2ccc(Cl)cc2)c(Cl)c1C1C(C#N)=C(N)N(c2cccnc2)C2=C1C(=O)CCC2,5.381951903287908,490.10756462000006,7,1,5.187300000000004,True
+3437,CHEMBL3608431,4192.0,nM,2015.0,C=CC(=O)N[C@H]1CCN(c2nc(Nc3ccc(N4CCN(C)CC4)cc3)c3ncn(CCO)c3n2)C1,5.377578726024329,491.2757212960001,10,3,1.1949000000000003,True
+3438,CHEMBL2047019,4200.0,nM,2012.0,O=C(CCCCCC(=O)Nc1ccc(O)c(C(=O)Nc2cccc(C(F)(F)F)c2)c1)NO,5.376750709602098,453.151155464,5,5,4.057700000000001,True
+3439,CHEMBL195218,4200.0,nM,2005.0,CONC(=O)c1cc(Nc2ncnn3cc(NC(=O)OCCCS(C)(=O)=O)c(C(C)C)c23)c(F)cc1F,5.376750709602098,540.160259992,10,3,3.148900000000002,True
+3440,CHEMBL1173688,4210.0,nM,2010.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccccc3Br)C2)cc1C,5.375717904164333,387.04048067599996,2,1,4.460640000000003,True
+3441,CHEMBL4216265,4210.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccccc2NC(C)=O)n1,5.375717904164333,482.183316404,8,2,4.384700000000002,True
+3442,CHEMBL1958217,4240.0,nM,2012.0,COc1ccc(C2CC(c3ccc(C)cc3)=NN2C2=NC(=O)CS2)cc1,5.372634143407269,365.119797848,5,0,3.7841200000000024,True
+3443,CHEMBL1958024,4270.0,nM,2012.0,COc1ccc(C2CC(c3ccccc3)=NN2C2=NC(=O)CS2)cc1,5.369572124974977,351.104147784,5,0,3.4757000000000016,True
+3444,CHEMBL153518,4270.0,nM,1999.0,CCN(CC)CCn1c2ccc(OC)cc2c2c(Nc3cccc(Br)c3)ncnc21,5.369572124974977,467.132072552,6,1,5.441000000000005,True
+3445,CHEMBL3233762,4286.0,nM,2014.0,CN(C)CCN(C)CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,5.36794783329419,436.12483622400003,7,2,3.659300000000001,True
+3446,CHEMBL2312303,4290.0,nM,2013.0,O=C(NCCCN1CCCC1=O)c1cnc(NCc2cc(Cl)ccc2Cl)nc1NC1CCCC1,5.367542707815275,504.18072956000003,6,3,4.492300000000003,True
+3447,CHEMBL3325474,4300.0,nM,2014.0,COC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2cc(C)ccc2n2nnnc12,5.366531544420414,481.1862375960001,10,1,2.9351200000000013,True
+3448,CHEMBL291986,4300.0,nM,1991.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)N1CCN(c2ccccc2)CC1,5.366531544420414,349.142641468,5,2,2.35358,True
+3449,CHEMBL1242847,4300.0,nM,2008.0,COc1ccc(-c2nn(C(C)C)c3ncnc(N)c23)cc1,5.366531544420414,283.143310164,6,1,2665,True
+3450,CHEMBL1944921,4300.0,nM,2012.0,COc1cccc2c1C(=O)c1c(O)ccc(O)c1C2=O,5.366531544420414,270.05282342,5,2,1.8817999999999997,True
+3451,CHEMBL4069070,4300.0,nM,2017.0,COc1ccc(OC)c(Sc2cccc3[nH]c4nc(N)nc(N)c4c23)c1,5.366531544420414,367.11029578400013,7,3,3.4439,True
+3452,CHEMBL3098322,4300.0,nM,2014.0,COc1cc2nc(Cl)nc(Nc3ccc(O)cc3)c2cc1OC,5.366531544420414,331.072368988,6,2,3.749600000000002,True
+3453,CHEMBL499345,4310.0,nM,2008.0,Nc1nc(Nc2cccc(Br)c2)c2cc(Cc3ccccc3Cl)[nH]c2n1,5.3655227298392685,427.01993526000007,4,3,5.290400000000002,True
+3454,CHEMBL1242286,4320.0,nM,2008.0,COCOc1cc(-c2nn(C(C)C)c3ncnc(N)c23)ccc1Br,5.364516253185088,391.06438691600005,7,1,3.401600000000001,True
+3455,CHEMBL3742200,4390.0,nM,2015.0,Oc1nnc(-c2c[nH]c(-c3ccccc3)c2-c2ccccc2)c2cn(-c3ccc(Cl)cc3)nc12,5.357535479757878,463.11998787600004,5,2,6.503600000000005,True
+3456,CHEMBL206848,4400.0,nM,2006.0,O=C(O)c1ccc2c(c1)CNc1c(Nc3ccc(F)c(Cl)c3)ncnc1O2,5.356547323513811,386.058196144,6,3,4.428700000000002,True
+3457,CHEMBL1241674,4400.0,nM,2008.0,CC(C)n1nc(-c2cc3cc(O)ccc3[nH]2)c2c(N)ncnc21,5.356547323513811,308.138559132,6,3,2.8432999999999993,True
+3458,CHEMBL332269,4400.0,nM,1998.0,CCCCNc1ncc2cc(-c3c(Cl)cccc3Cl)c(=O)n(C)c2n1,5.356547323513811,376.085766556,5,1,4.514300000000003,True
+3459,CHEMBL3133897,4400.0,nM,2013.0,C=CC(=O)N1CCc2c(sc3ncnc(Nc4ccc(Br)c(C)c4)c23)C1,5.356547323513811,428.030644264,5,1,4.576520000000003,True
+3460,CHEMBL115519,4400.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2nc3cc(Cl)ccc3s2)c1O,5.356547323513811,431.01651098799994,7,2,4.348480000000002,True
+3461,CHEMBL1928889,4410.0,nM,2012.0,Clc1ccc(CNc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)cc1,5.355561410532161,394.075201872,4,2,6.292300000000003,True
+3462,CHEMBL3739587,4480.0,nM,2015.0,CC(=O)c1nn(-c2ccc(Cl)cc2)cc1C(=O)c1c(C)[nH]c(-c2ccccc2)c1-c1ccccc1,5.348721986001856,479.140054624,4,1,6.929820000000006,True
+3463,CHEMBL106232,4500.0,nM,1998.0,CN1CCN(CCCCCNc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)CC1,5.346787486224656,488.18581494,7,1,4.131900000000003,True
+3464,CHEMBL4094471,4500.0,nM,2017.0,Clc1ccccc1-c1nnc(Cc2nc3ccccc3[nH]2)o1,5.346787486224656,310.062138652,4,1,3.8571000000000017,True
+3465,CHEMBL2385983,4500.0,nM,2013.0,CCOc1cc(N)c(C(=O)Nc2ccc(F)c(Cl)c2)cc1NC(=O)/C=C/CN(C)C,5.346787486224656,434.152096528,5,3,3.768600000000002,True
+3466,CHEMBL2064398,4500.0,nM,2012.0,C[C@@H](Nc1ncnc2cc3oc(=O)n(CCCN4CCOCC4)c3cc12)c1ccccc1,5.346787486224656,433.211389724,8,1,3.4331000000000023,True
+3467,CHEMBL109296,4500.0,nM,1998.0,CCNc1ncc2cc(-c3c(Cl)cccc3Cl)c(=O)n(C)c2n1,5.346787486224656,348.054466428,5,1,3.7341000000000015,True
+3468,CHEMBL489083,4600.0,nM,2008.0,N=C(N)SCCCn1c(=O)c2n3ccc4cccc(c43)c3cc4ccccc4n3c=2c1=O,5.337242168318426,441.125945848,7,2,3.199650000000002,True
+3469,CHEMBL1242757,4600.0,nM,2008.0,CC(C)n1nc(-c2cccc3[nH]ccc23)c2c(N)ncnc21,5.337242168318426,292.143644512,5,2,3.1377000000000006,True
+3470,CHEMBL2316153,4600.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccc(O)cc3)C2=O)cc(OC)c1,5.337242168318426,350.15180918399994,4,1,4.629400000000004,True
+3471,CHEMBL135577,4600.0,nM,1997.0,CCN(CC)CCNC(=O)c1c([Se][Se]c2[nH]c3ccccc3c2C(=O)NCCN(CC)CC)[nH]c2ccccc12,5.337242168318426,676.15431712,4,4,2.066600000000003,True
+3472,CHEMBL418203,4600.0,nM,2002.0,CN1CCC(c2c(O)cc(O)c3c(=O)cc(-c4ccccc4Cl)oc23)[C@@H](O)C1,5.337242168318426,401.10300041999994,6,3,3.3046000000000015,True
+3473,CHEMBL1914657,4608.0,nM,2011.0,Br.CC(Nc1ncnc2[nH]c(-c3ccc(O)cc3)cc12)c1ccc(C(F)(F)F)cc1,5.3364875295848435,478.061607956,4,3,6.100300000000004,True
+3474,CHEMBL3759155,4610.0,nM,2016.0,COc1cc2c(Nc3ccc(NC(=O)c4ccccc4)cc3)ncnc2cc1OCCN1CCCCC1,5.336299074610351,497.24268985200007,7,2,5.499000000000004,True
+3475,CHEMBL3739750,4670.0,nM,2015.0,CC(=O)c1nn(-c2ccccc2)cc1C(=O)c1c(C)[nH]c(-c2ccccc2)c1-c1ccccc1,5.330683119433887,445.179026976,4,1,6.276420000000005,True
+3476,CHEMBL1822063,4680.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc(C)cc3)C2)cc1,5.329754146925875,459.117211004,5,0,7.136220000000006,True
+3477,CHEMBL157807,4700.0,nM,1995.0,Cn1c(SSc2c(C(N)=O)c3ccccc3n2C)c(C(N)=O)c2ccccc21,5.327902142064282,410.087117816,6,2,3.667200000000002,True
+3478,CHEMBL484109,4700.0,nM,2008.0,Nc1nc(Nc2cccc(Br)c2)c2cc(CCc3ccc4ccccc4c3)[nH]c2n1,5.327902142064282,457.09020774000004,4,3,5.984600000000003,True
+3479,CHEMBL4081698,4700.0,nM,2017.0,CCC(=O)N1CCC[C@@H](n2nc(-c3ccccc3)c3c(N)ncnc32)C1,5.327902142064282,350.18550932400007,6,1,2649,True
+3480,CHEMBL263666,4700.0,nM,1997.0,CCN(CC)CCNC(=O)c1c([Se][Se]c2c(C(=O)NCCN(CC)CC)c3ccccc3n2C)n(C)c2ccccc12,5.327902142064282,704.1856172479999,6,2,2.0874000000000037,True
+3481,CHEMBL2333985,4700.0,nM,2013.0,COc1cc2ncnc(Nc3ccc(C(C)(F)F)cc3)c2cc1OC,5.327902142064282,345.128883224,5,1,4.5023000000000035,True
+3482,CHEMBL3902295,4700.0,nM,2016.0,O=C(CCl)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(F)c(F)c4)c3cc21,5.327902142064282,434.059339016,8,1,3.3415000000000017,True
+3483,CHEMBL2424801,4700.0,nM,2013.0,O=C(/C=C/c1cccnc1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.327902142064282,401.104337812,5,2,5.073700000000002,True
+3484,CHEMBL590876,4710.0,nM,2010.0,O=C1CSC(N/N=C/c2ccc(O)cc2)=N1,5.326979092871103,235.041547528,5,2,0.9451,True
+3485,CHEMBL481789,4720.0,nM,2015.0,COc1ccc2c(c1)SCc1cnc(-c3ccccc3)nc1-2,5.3260580013659125,306.08268406800005,4,0,4.424900000000004,True
+3486,CHEMBL1958028,4790.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(F)cc3)CC2c2ccc(Br)cc2)=N1,5.319664486585436,416.9946733560001,4,0,4.368700000000003,True
+3487,CHEMBL2018750,4800.0,nM,2012.0,COc1cc2ncnc(Nc3ccc(NC(=O)OC(C)C)cc3)c2cc1OC,5.318758762624412,382.16410518399994,7,2,4.347500000000003,True
+3488,CHEMBL1242748,4800.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2[C@H]1CCOC1,5.318758762624412,315.11315290799996,7,2,1.8815999999999995,True
+3489,CHEMBL126456,4800.0,nM,2002.0,CCOc1cc2ncnc(Nc3cccc(-c4csc(C)n4)c3)c2cc1OCC,5.318758762624412,406.14634694399996,7,1,5.602720000000004,True
+3490,CHEMBL77100,4800.0,nM,1991.0,CCCCNC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,5.318758762624412,404.10420736,6,1,3.231600000000002,True
+3491,CHEMBL79704,4800.0,nM,1994.0,O=C(O)CCc1c(SSc2[nH]c3ccccc3c2CCC(=O)O)[nH]c2ccccc12,5.318758762624412,440.08644911999994,4,4,5.483000000000003,True
+3492,CHEMBL3327179,4800.0,nM,2014.0,N#CC1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2ccccc2n2nnnc12,5.318758762624412,434.1603571960001,9,1,2.9772800000000013,True
+3493,CHEMBL2316159,4800.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3cc(C(C)(C)C)c(O)c(C(C)(C)C)c3)C2=O)cc(OC)c1,5.318758762624412,462.27700969599994,4,1,7.224400000000008,True
+3494,CHEMBL1241579,4800.0,nM,2008.0,C[C@H](CN)n1nc(-c2ccc(Cl)c(O)c2)c2c(N)ncnc21,5.318758762624412,318.09958678000004,7,3,1.9542,True
+3495,CHEMBL484108,4800.0,nM,2008.0,Nc1nc(Nc2cccc(Br)c2)c2cc(CCc3cccc4ccccc34)[nH]c2n1,5.318758762624412,457.09020774000004,4,3,5.984600000000003,True
+3496,CHEMBL325156,4840.0,nM,2003.0,CCN(CC)C(C)/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cc1OC,5.315154638355588,495.18373100400004,6,2,5.876180000000006,True
+3497,CHEMBL1958020,4860.0,nM,2012.0,O=C1CSC(N2N=C(c3ccccc3)CC2c2ccc(F)cc2)=N1,5.313363730737707,339.084161288,4,0,3.606200000000003,True
+3498,CHEMBL1271619,4884.0,nM,2010.0,CN(C)C/C=C/C(=O)N1CCc2c(sc3ncnc(NCCO)c23)C1,5.3112243447271545,361.157245976,7,2,1.0979999999999996,True
+3499,CHEMBL330882,4900.0,nM,1995.0,COc1cccc2ncnc(NCc3ccccc3)c12,5.309803919971486,265.1215121,4,1,3.2505000000000015,True
+3500,CHEMBL204164,4900.0,nM,2006.0,C=CC(=O)Nc1ccc2c(c1)CNc1c(Nc3ccc(F)c(Cl)c3)ncnc1O2,5.309803919971486,411.08983062000004,6,3,4.855000000000002,True
+3501,CHEMBL1821891,4940.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(Cl)cc3)C2)cc1,5.306273051076354,445.10156093999996,5,0,6.827800000000005,True
+3502,CHEMBL599145,4960.0,nM,2010.0,CCCCCCCCCOC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.304518323509802,438.20423867999995,6,1,5.838200000000006,True
+3503,CHEMBL3233759,4997.0,nM,2014.0,COC(=O)CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,5.301290650557413,394.03026714400005,7,2,3.729000000000002,True
+3504,CHEMBL4103121,5000.0,nM,2017.0,CCC(=O)N1CCC[C@@H](n2nc(-c3ccc(F)cc3)c3c(N)ncnc32)C1,5.301029995663981,368.1760875120001,6,1,2.7881,True
+3505,CHEMBL328295,5000.0,nM,1996.0,O=[N+]([O-])c1ccc2ncnc(Nc3ccccc3)c2c1,5.301029995663981,266.08037556,5,1,3.281600000000001,True
+3506,CHEMBL1241587,5000.0,nM,2008.0,CC(C)n1nc(-c2ccc3c(c2)CCO3)c2c(N)ncnc21,5.301029995663981,295.143310164,6,1,2.5912999999999995,True
+3507,CHEMBL2018762,5000.0,nM,2012.0,CCOC(=O)Nc1cc(Nc2ncnc3cc(OC)c(OC)cc23)ccc1C,5.301029995663981,382.16410518399994,7,2,4.267420000000003,True
+3508,CHEMBL440298,5000.0,nM,1999.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)NCCCCc1ccccc1,5.301029995663981,336.1473925,4,3,3.143880000000001,True
+3509,CHEMBL3221555,5000.0,nM,2011.0,CCOC(=O)Nc1cc(Nc2ncnc3cc(OC)c(OC)cc23)ccc1C.Cl,5.301029995663981,418.14078289599996,7,2,4.689220000000004,True
+3510,CHEMBL2385992,5000.0,nM,2013.0,Cc1ccc(NC(=O)/C=C/CN(C)C)cc1C(=O)Nc1nccc(-c2cccnc2)n1,5.301029995663981,416.19607400800004,6,2,3.1556200000000008,True
+3511,CHEMBL485065,5000.0,nM,1992.0,Cl.NCCNC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,5.301029995663981,427.060483976,7,2,1.8120000000000005,True
+3512,CHEMBL87084,5000.0,nM,1994.0,Oc1cc2cc(-c3ccncc3)cnc2cc1O,5.301029995663981,238.07422756,4,2,2.7080000000000006,True
+3513,CHEMBL4202955,5010.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(NC(=O)/C=C/CN(C)C)c2)n1,5.300162274132753,551.241165628,9,2,4.482600000000002,True
+3514,CHEMBL361322,5010.0,nM,2005.0,c1ccc(Cc2nc3cc(Nc4ncnc5nn6ccccc6c45)ccc3[nH]2)cc1,5.300162274132753,391.15454354400003,6,2,4.488200000000003,True
+3515,CHEMBL3747281,5020.0,nM,2016.0,CC(=O)N1N=C(c2ccc(F)cc2)CC1c1ccc(C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,5.29929628285498,479.160497024,8,0,3.793420000000003,True
+3516,CHEMBL1270795,5048.0,nM,2010.0,CSc1cn2c(-c3cn[nH]c3)cnc2c(Nc2cc(C)ns2)n1,5.296880653763922,343.06738541600004,8,2,3.3498200000000002,True
+3517,CHEMBL1821897,5070.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc(F)cc3)C2)cc1,5.294992040666664,463.09213912800004,5,0,6.966900000000004,True
+3518,CHEMBL599218,5077.0,nM,2010.0,COc1cc2ncnc(N[C@@H](C)c3ccccc3)c2cc1OCCCCCCC(=O)NO,5.294392836595395,438.22670543999993,7,3,4.646200000000003,True
+3519,CHEMBL1242569,5080.0,nM,2008.0,C=CCn1nc(-c2ccc(OCC)c(OC)c2)c2c(N)ncnc21,5.29413628771608,325.15387484800004,7,1,2.6688,True
+3520,CHEMBL2424799,5100.0,nM,2013.0,CSCCCNc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.292429823902063,358.10189528800004,5,2,5.191800000000003,True
+3521,CHEMBL202162,5100.0,nM,2006.0,CCN(CC)CCOc1c(C(=O)OC)c2c3c(oc2c2ccccc12)C(=O)c1ccccc1C3=O,5.292429823902063,471.16818751999995,7,0,4.868600000000004,True
+3522,CHEMBL3612564,5100.0,nM,2015.0,COCCn1c(=O)oc2cc3ncnc(Nc4ccc(OC)cc4)c3cc21,5.292429823902063,366.13280505599994,8,1,2.936300000000001,True
+3523,CHEMBL367625,5100.0,nM,1999.0,CCn1cnc2c(Nc3cccc(Cl)c3)nc(N[C@@H]3CCCC[C@@H]3N)nc21,5.292429823902063,385.17817144800006,7,3,3.9250000000000007,True
+3524,CHEMBL113185,5100.0,nM,1999.0,COc1cc(Nc2nccc(-c3ccc(NCCN)nc3)n2)cc(OC)c1OC,5.292429823902063,396.19098862799996,9,3,2.6786000000000003,True
+3525,CHEMBL55360,5100.0,nM,1991.0,Cc1cccc(C)c1NC(=O)/C(C#N)=C/c1ccc(O)c(O)c1,5.292429823902063,308.11609237199997,4,3,3.260320000000002,True
+3526,CHEMBL3740492,5100.0,nM,2015.0,Cc1c(C(=O)c2coc3c2cc(O)c2ccccc23)[nH]c(-c2ccccc2)c1-c1ccccc1,5.292429823902063,443.152143532,3,2,7.493120000000006,True
+3527,CHEMBL475351,5100.0,nM,2009.0,COc1nc(Nc2ccc(-c3nc4ccccc4s3)c(OC)c2)c2cc[nH]c2n1,5.292429823902063,403.110295784,7,2,4.995400000000003,True
+3528,CHEMBL1830270,5110.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccc(-c2ccccc2)cc1)c1ccccc1,5.291579099865287,357.129968608,2,2,4.604300000000003,True
+3529,CHEMBL1929303,5110.0,nM,2012.0,Fc1ccccc1-c1nnc(SCc2ccccc2)o1,5.291579099865287,286.05761219199997,4,0,4.168000000000003,True
+3530,CHEMBL3235199,5120.0,nM,2014.0,Cc1ncc([N+](=O)[O-])n1CC(=O)N/N=C/c1cc2ccccc2nc1Oc1ccc(Cl)cc1,5.290730039024169,464.099980704,8,1,4.243920000000003,True
+3531,CHEMBL2437478,5129.0,nM,2013.0,C=CC(=O)Nc1ccc(-n2c(=O)cnc3cnc(Nc4ccc(OC)cc4)nc32)cc1,5.289967300934246,414.144038436,8,2,3.0524000000000013,True
+3532,CHEMBL1242660,5140.0,nM,2008.0,COc1cc(-c2nn(C(C)C)c3ncnc(N)c23)cc(OC)c1OC,5.289036881004725,343.16443953199996,8,1,2.682200000000001,True
+3533,CHEMBL2336355,5160.0,nM,2013.0,COc1ccccc1NC(=O)/C=C/c1ccccc1,5.287350298372789,253.11027872,2,1,3.347100000000001,True
+3534,CHEMBL2047028,5160.0,nM,2012.0,C#Cc1cccc(NC(=O)c2cc(NC(=O)CCCCCC(=O)NO)ccc2OC)c1,5.287350298372789,423.17942089999997,5,4,3.3232000000000017,True
+3535,CHEMBL1812559,5160.0,nM,2011.0,O=C(/C=C/c1ccc([N+](=O)[O-])cc1)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,5.287350298372789,489.0436514720001,6,2,5.696000000000002,True
+3536,CHEMBL1828867,5170.0,nM,2011.0,O=C(Cc1ccc(F)cc1)NS(=O)(=O)c1ccc(F)cc1,5.2865094569060584,311.042770652,3,1,2.0124,True
+3537,CHEMBL109372,5170.0,nM,2002.0,COc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1OC,5.2865094569060584,357.068032556,5,1,4.659780000000002,True
+3538,CHEMBL1169856,5190.0,nM,2010.0,Cc1ccc(C2=NN(C(N)=S)C(c3ccccc3F)C2)cc1C,5.2848326421515415,327.120546796,2,1,3.837240000000002,True
+3539,CHEMBL364623,5200.0,nM,2006.0,Cc1cc(Nc2ncc(C(=O)Nc3c(C)cccc3Cl)s2)nc(C)n1,5.2839966563652006,373.07640881200007,6,2,4.507660000000002,True
+3540,CHEMBL1614712,5200.0,nM,2016.0,Nc1ncnc2c1c(-c1cccc(OCc3ccccc3)c1)cn2[C@H]1C[C@@H](CN2CCC2)C1,5.2839966563652006,439.23721054800006,6,1,4.916300000000004,True
+3541,CHEMBL3910361,5200.0,nM,2016.0,C#Cc1cccc(Nc2ncnc3cc4oc(=O)n(CCOC(=O)CBr)c4cc23)c1,5.2839966563652006,466.02766705999994,8,1,3.200700000000001,True
+3542,CHEMBL370808,5200.0,nM,2006.0,COc1ccc(C#CC(C)(C)N)cc1-c1[nH]nc2nc(Nc3ccc(F)cc3F)ncc12,5.2839966563652006,434.1666657,6,3,4.139100000000002,True
+3543,CHEMBL472943,5220.0,nM,2009.0,COc1cc2nccc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/C(C)N(C)C,5.282329496997739,442.15718190800004,5,2,5.224300000000005,True
+3544,CHEMBL113901,5220.0,nM,2003.0,COc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/C(C)N(C)C,5.282329496997739,467.15243087600004,6,2,5.095980000000004,True
+3545,CHEMBL3233763,5222.0,nM,2014.0,CN(C)CCCN(C)CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,5.282163132513076,450.14048628800003,7,2,4.049400000000002,True
+3546,CHEMBL3263372,5260.0,nM,2014.0,Cc1ccc(C2=NN(C3=NC(c4ccccc4)CS3)C(c3ccc4ccccc4c3)C2)cc1,5.279014255846262,447.1769188,4,0,7.143420000000006,True
+3547,CHEMBL245799,5260.0,nM,2007.0,N#Cc1cnc2ccc(-c3cccc(CN4CCOCC4)c3)cc2c1N[C@@H]1C[C@H]1c1ccccc1,5.279014255846262,460.226311516,5,1,5.573680000000005,True
+3548,CHEMBL1173667,5270.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc(O)cc1,5.278189384787454,365.015638396,3,2,4.093700000000002,True
+3549,CHEMBL3613691,5283.0,nM,2015.0,CN(C)c1ccc(/C=C/C(=O)c2ccc3ncc(C(N)=O)c(Nc4ccc(Cl)cc4)c3c2)cc1,5.277119389313061,470.150953656,5,2,5.6928000000000045,True
+3550,CHEMBL368278,5300.0,nM,1999.0,CCn1cnc2c(Nc3cccc(Cl)c3)nc(N[C@H]3CCC[C@@H](N)C3)nc21,5.275724130399211,385.17817144800006,7,3,3.9250000000000007,True
+3551,CHEMBL2029700,5300.0,nM,2012.0,Nc1nn2c(=O)cc(-c3ccccc3)[nH]c2c1/N=N/c1ccc2c(c1)OCO2,5.275724130399211,374.1127383079999,8,2,3.4159000000000015,True
+3552,CHEMBL2316155,5300.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccc(OC)c(O)c3)C2=O)cc(OC)c1,5.275724130399211,380.1623738679999,5,1,4.638000000000004,True
+3553,CHEMBL474543,5300.0,nM,2009.0,Clc1ccc2c(Nc3ccc(-c4nc5ccccc5s4)cc3)ccnc2c1,5.275724130399211,387.05969612800004,4,1,6.908500000000004,True
+3554,CHEMBL443268,5310.0,nM,2002.0,Cc1cc(C(=O)NCCN2CCOCC2)[nH]c1/C=C1\C(=O)N(C)c2ncnc(Nc3ccc(F)c(Cl)c3)c21,5.274905478918532,539.1847936240001,7,3,3.228220000000002,True
+3555,CHEMBL1241486,5320.0,nM,2008.0,COc1cc(-c2nn(C(C)C)c3ncnc(N)c23)ccc1NC(C)CO,5.274088367704953,356.196074008,8,3,2.4577000000000004,True
+3556,CHEMBL597304,5330.0,nM,2010.0,CCCCCCCCNC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.273272790973428,423.20457302799997,5,2,5.021100000000005,True
+3557,CHEMBL1958031,5340.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(Cl)cc3)CC2c2ccccc2)=N1,5.272458742971444,355.054610748,4,0,4.120500000000003,True
+3558,CHEMBL1958220,5350.0,nM,2012.0,COc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(Cl)cc3)C2)cc1,5.271646217978772,385.065175432,5,0,4.129100000000003,True
+3559,CHEMBL1821895,5350.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(O)cc3)C2)cc1,5.271646217978772,427.13544791199996,6,1,5.880000000000005,True
+3560,CHEMBL113985,5390.0,nM,2003.0,COc1cc(NC(=O)/C=C/CN2CCOCC2)cc2c(Nc3cccc(Br)c3)c(C#N)cnc12,5.268411234813262,521.1062517280001,7,2,4.448080000000003,True
+3561,CHEMBL472743,5390.0,nM,2009.0,COc1cc(NC(=O)/C=C/CN2CCOCC2)cc2c(Nc3cccc(Br)c3)ccnc12,5.268411234813262,496.1110027600001,6,2,4.576400000000003,True
+3562,CHEMBL309075,5400.0,nM,1991.0,NCCNC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1,5.267606240177031,391.083806264,7,2,1.3901999999999994,True
+3563,CHEMBL3325471,5400.0,nM,2014.0,COc1ccc2c(c1)cc(C1C(C#N)=C(N)N(c3cccnc3)C3=C1C(=O)CCC3)c1nnnn12,5.267606240177031,464.1709218800001,10,1,2.9858800000000008,True
+3564,CHEMBL2205030,5400.0,nM,2011.0,O=S1(=O)N=S(c2ccc(Br)cc2)c2ccncc21,5.267606240177031,341.91323156400006,3,0,2.766300000000001,True
+3565,CHEMBL123045,5400.0,nM,1997.0,O=[N+]([O-])c1cc(NCc2cc(O)ccc2O)ccc1O,5.267606240177031,276.074621484,6,4,2.3237,True
+3566,CHEMBL3742060,5430.0,nM,2015.0,Cc1ccc(-n2cc3c(-c4c(C)[nH]c(-c5ccccc5)c4-c4ccccc4)nnc(C)c3n2)cc1,5.265200170411154,455.2109958000001,4,1,7.0698600000000065,True
+3567,CHEMBL1958222,5460.0,nM,2012.0,COc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(C)cc3)C2)cc1,5.262807357295261,365.119797848,5,0,3.7841200000000033,True
+3568,CHEMBL2442320,5490.0,nM,2013.0,COc1cc(OC)c2c(=O)n(-c3ccc(F)c(Cl)c3)ccc2c1,5.2604276555499085,333.056799176,4,0,3.8004000000000024,True
+3569,CHEMBL37346,5500.0,nM,1997.0,Brc1cccc(Nc2ccnc3ccccc23)c1,5.259637310505756,298.010560452,2,1,4.740900000000003,True
+3570,CHEMBL3612572,5500.0,nM,2015.0,COCCn1c(=O)oc2cc3ncnc(Nc4ccc(OC)c(OC)c4)c3cc21,5.259637310505756,396.1433697399999,9,1,2.9449000000000014,True
+3571,CHEMBL3221547,5500.0,nM,2011.0,CCCOc1cc2ncnc(Nc3ccc(NC(=O)OCC)c(Cl)c3)c2cc1OC.Cl,5.259637310505756,466.11746060799993,7,2,5.8144000000000045,True
+3572,CHEMBL370266,5500.0,nM,2005.0,CONC(=O)c1cc(Nc2ncnn3cc(NC(=O)OCC4CCCO4)c(C(C)C)c23)c(F)cc1F,5.259637310505756,504.19327437199996,9,3,3.893200000000003,True
+3573,CHEMBL76599,5530.0,nM,1997.0,CC(C)(C)NC(=O)Nc1nc2nc(N)ncc2cc1-c1ccccc1,5.257274868695301,336.16985925999995,5,3,3.194000000000001,True
+3574,CHEMBL3263364,5530.0,nM,2014.0,COc1ccc(C2=NN(C3=NC(=O)CS3)C(c3cccc4ccccc34)C2)cc1,5.257274868695301,401.119797848,5,0,4.628900000000003,True
+3575,CHEMBL3234751,5540.0,nM,2014.0,Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1NC(=O)c1cnc(N(C)C)nc1,5.2564902352715706,555.2569579240001,7,2,4.121820000000003,True
+3576,CHEMBL1821892,5560.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(Br)cc3)C2)cc1,5.254925208417943,489.05104536,5,0,6.936900000000005,True
+3577,CHEMBL1958210,5580.0,nM,2012.0,Cc1ccc(C2CC(c3ccc(Br)cc3)=NN2C2=NC(=O)CS2)cc1,5.2533658010624205,413.019745232,4,0,4.538020000000005,True
+3578,CHEMBL2437459,5585.0,nM,2013.0,C=CC(=O)Nc1ccc(-n2c(=O)cnc3cnc(Nc4ccc(N5CCOCC5)cc4)nc32)cc1,5.252976822548372,469.18623759600007,9,2,2.8804000000000007,True
+3579,CHEMBL116423,5600.0,nM,1993.0,Cc1cc(C=C(C#N)C#N)cc(O)c1O,5.251811972993798,200.058577496,4,2,1.836780000000001,True
+3580,CHEMBL49596,5600.0,nM,1998.0,Cn1c(=O)c(-c2c(Cl)cccc2Cl)cc2cnc(N)nc21,5.251811972993798,320.02316630000007,5,1,2.8845,True
+3581,CHEMBL2029696,5600.0,nM,2012.0,O=C1NN(c2ccc(F)cc2)C(=O)/C1=C\c1cccc(OCc2ccccc2F)c1,5.251811972993798,406.11289881199997,3,1,4.005200000000003,True
+3582,CHEMBL115895,5600.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccccc2NC(C)=O)c1O,5.251811972993798,397.109627088,6,3,3.043780000000002,True
+3583,CHEMBL186802,5600.0,nM,2004.0,COc1cc2ncnc(Nc3cccc(NC(=O)c4ccccc4)c3)c2cc1OC,5.251811972993798,400.15354049999996,6,2,4.642900000000004,True
+3584,CHEMBL2316147,5600.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccc(F)cc3)C2=O)cc(OC)c1,5.251811972993798,352.147472752,3,0,5.062900000000004,True
+3585,CHEMBL50415,5600.0,nM,1992.0,O=C(Nc1ccccc1)c1cc2cc(O)c(O)cc2cn1,5.251811972993798,280.084792244,4,3,2.8983000000000017,True
+3586,CHEMBL468975,5600.0,nM,1995.0,C=C(CN(C)C)C(=O)c1ccccc1.Cl,5.251811972993798,225.092041812,2,0,2.4089000000000005,True
+3587,CHEMBL4290355,5600.0,nM,2018.0,COc1ccc(-c2nc3sc(-c4ccccc4)cn3n2)cc1,5.251811972993798,307.07793303600005,5,0,4.1334000000000035,True
+3588,CHEMBL250315,5600.0,nM,2007.0,COc1cc2ncnc(C#Cc3ccccc3)c2cc1OC,5.251811972993798,290.105527688,4,0,3.046800000000002,True
+3589,CHEMBL351920,5600.0,nM,1995.0,CC(=O)c1c(SSc2c(C(C)=O)c3ccccc3n2C)n(C)c2ccccc12,5.251811972993798,408.09661988000005,6,0,5.874600000000005,True
+3590,CHEMBL4218052,5610.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(N=C=S)c2)n1,5.251037138743839,482.12917265600004,9,1,5.160600000000004,True
+3591,CHEMBL1928890,5670.0,nM,2012.0,Clc1cccc(Nc2ncnc3ccc(NCc4ccc(Br)cc4)cc23)c1,5.246416941107094,438.02468629199996,4,2,6.401400000000002,True
+3592,CHEMBL2325105,5680.0,nM,2013.0,NC(=S)N1N=C(c2ccc(Br)cc2)CC1c1cccc2ccccc12,5.245651664288982,409.02483061199996,2,1,4.997000000000003,True
+3593,CHEMBL1277620,5700.0,nM,2011.0,COc1cc2ncnc(Nc3ccc(Br)cc3F)c2cc1OC,5.2441251443275085,377.01751697599997,5,1,4.292200000000003,True
+3594,CHEMBL4066118,5700.0,nM,2017.0,c1ccc2c(Cc3nnc(Cc4nc5ccccc5[nH]4)o3)cccc2c1,5.2441251443275085,340.13241113199996,4,1,4.280700000000003,True
+3595,CHEMBL3612575,5700.0,nM,2015.0,C#Cc1cccc(Nc2ncnc3cc4oc(=O)n(CCCC(=O)OCC)c4cc23)c1,5.2441251443275085,416.14845511999994,8,1,3.6059000000000028,True
+3596,CHEMBL381541,5700.0,nM,2006.0,C=CC(=O)Nc1ccc2c(c1)CNc1c(Nc3cccc(Br)c3)ncnc1O2,5.2441251443275085,437.048736852,6,3,4.825000000000002,True
+3597,CHEMBL1821890,5710.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(F)cc3)C2)cc1,5.243363891754152,429.13111147999996,5,0,6.313500000000005,True
+3598,CHEMBL1440725,5720.0,nM,2012.0,Cc1ccccc1-c1nnc(SCc2ccccc2)o1,5.242603971206974,282.082684068,4,0,4.337320000000003,True
+3599,CHEMBL1172915,5740.0,nM,2010.0,COc1ccc(C2CC(c3ccc(Cl)c(Cl)c3)=NN2C(N)=S)cc1,5.241088107602026,379.0312884600001,3,1,4.396700000000004,True
+3600,CHEMBL1170459,5760.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccc2ccccc2c1,5.239577516576788,351.12190602400005,6,0,3.509520000000002,True
+3601,CHEMBL592708,5780.0,nM,2010.0,COc1ccc(/C=N/NC2=NC(=O)CS2)cc1,5.238072161579471,249.057197592,5,1,1.2481,True
+3602,CHEMBL605957,5797.0,nM,2010.0,COc1cc(C2=C(c3c[nH]c4ccc(Br)cc34)C(=O)NC2=O)cc(OC)c1OC,5.236796699629228,456.032083744,5,2,3.5234000000000014,True
+3603,CHEMBL205454,5800.0,nM,2006.0,COc1ccc2c(c1)CNc1c(Nc3ccc(Cl)cc3)ncnc1O2,5.236572006437063,354.0883534000001,6,2,4.600000000000002,True
+3604,CHEMBL2018759,5800.0,nM,2012.0,COc1cc2ncnc(Nc3ccc(NC(=O)OC(C)C)c(C)c3)c2cc1OC,5.236572006437063,396.17975524799994,7,2,4.655920000000004,True
+3605,CHEMBL2064374,5800.0,nM,2012.0,CCOC(=O)c1ccc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)cc1,5.236572006437063,477.201218964,10,1,3.1803000000000017,True
+3606,CHEMBL592247,5830.0,nM,2010.0,Cc1cc(C)c(O)c(CN(Cc2ccc(O)cc2)C(=S)Nc2ccccc2)c1,5.234331445240986,392.155849008,3,3,5.113840000000004,True
+3607,CHEMBL603968,5840.0,nM,2010.0,CCCCCCCCOC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.2335871528875995,424.18858861599995,6,1,5.4481000000000055,True
+3608,CHEMBL253969,5853.4,nM,2016.0,NC(=O)c1c(OCc2c(F)cc(Br)cc2F)nsc1NC(=O)NCCCCN1CCCC1,5.232591796771347,531.0751291680001,6,3,3.859200000000003,True
+3609,CHEMBL4063701,5900.0,nM,2017.0,CCC(=O)N1CCC[C@@H](n2nc(-c3ccc(C(F)(F)F)cc3)c3c(N)ncnc32)C1,5.229147988357855,418.1728939520001,6,1,3.6678000000000015,True
+3610,CHEMBL116748,5900.0,nM,1995.0,O=[N+]([O-])c1ccc2c(NCc3ccccc3)ncnc2c1,5.229147988357855,280.096025624,5,1,3.150100000000001,True
+3611,CHEMBL1278149,5900.0,nM,2011.0,COc1cc2ncnc(Oc3ccc(Br)c(F)c3)c2cc1OC,5.229147988357855,378.001532564,5,0,4.340900000000003,True
+3612,CHEMBL1828868,5930.0,nM,2011.0,O=C(Cc1ccc(F)cc1)NS(=O)(=O)c1ccc(Cl)cc1,5.226945306635738,327.013220112,3,1,2.526700000000001,True
+3613,CHEMBL1958219,5950.0,nM,2012.0,COc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(F)cc3)C2)cc1,5.22548303427145,369.094725972,5,0,3.6148000000000025,True
+3614,CHEMBL1242472,5950.0,nM,2008.0,CCOc1ccc(-c2nn(C(C)C)c3ncnc(N)c23)cc1OC,5.22548303427145,327.169524912,7,1,3.0637000000000008,True
+3615,CHEMBL1241439,5960.0,nM,2008.0,CC(C)n1nc(-c2cc(C=O)co2)c2c(N)ncnc21,5.224753740259764,271.10692465600005,7,1,2.0618999999999996,True
+3616,CHEMBL3747776,5960.0,nM,2016.0,CC(=O)N1N=C(c2ccc(Br)cc2)CC1c1ccc(C(=O)OC(C)Cn2c([N+](=O)[O-])cnc2C)cc1,5.224753740259764,553.096080968,8,0,4.8053200000000045,True
+3617,CHEMBL372246,6000.0,nM,2005.0,C=CC(=O)Nc1cc2c(Nc3cc(Cl)c(Cl)cc3F)ncnc2cc1N1CCN(C)CC1,5.221848749616356,474.1137928720001,6,2,4.695600000000004,True
+3618,CHEMBL2385982,6000.0,nM,2013.0,CCOc1cc([N+](=O)[O-])c(C(=O)Nc2ccc(F)c(Cl)c2)cc1NC(=O)/C=C/CN(C)C,5.221848749616356,464.126275704,6,2,4.0946000000000025,True
+3619,CHEMBL489147,6000.0,nM,1992.0,COc1cc(C(C#N)=C(C#N)C#N)cc(O)c1O,5.221848749616356,241.048741084,6,2,1.43074,True
+3620,CHEMBL80155,6000.0,nM,1989.0,COc1cc(C=C(C#N)C#N)cc(O)c1O,5.221848749616356,216.053492116,5,2,1.53696,True
+3621,CHEMBL2385988,6000.0,nM,2013.0,CCOc1ccc(C(=O)Nc2nccc(-c3cccnc3)n2)cc1NC(=O)/C=C/CN(C)C,5.221848749616356,446.206638692,7,2,3.2459000000000016,True
+3622,CHEMBL381306,6000.0,nM,2006.0,Brc1ccc2c(c1)CNc1c(NCc3ccccc3)ncnc1O2,5.221848749616356,382.0429232,5,2,4.569000000000003,True
+3623,CHEMBL2385993,6000.0,nM,2013.0,Cc1ccc(NC(=O)c2ccc(CN3CCN(C)CC3)cc2)cc1C(=O)Nc1nccc(-c2cccc(F)c2)n1,5.221848749616356,538.2492524520001,6,2,4.843120000000004,True
+3624,CHEMBL1812556,6020.0,nM,2011.0,COc1cccc(/C=C/C(=O)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)c1,5.220403508742176,474.069137948,5,2,5.796400000000004,True
+3625,CHEMBL4202780,6070.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccccc2NC(=O)/C=C/CN(C)C)n1,5.216811308924743,551.241165628,9,2,4.482600000000002,True
+3626,CHEMBL329183,6100.0,nM,1996.0,O=[N+]([O-])c1ccc2c(Nc3cccc(F)c3)ncnc2c1,5.214670164989234,284.070953748,5,1,3.420700000000002,True
+3627,CHEMBL137422,6100.0,nM,1997.0,CNC(=O)c1c([Se][Se]c2c(C(=O)NC)c3ccccc3n2C)n(C)c2ccccc12,5.214670164989234,534.0073185440001,4,2,0.6634000000000013,True
+3628,CHEMBL2316150,6100.0,nM,2013.0,COc1cccc(/C=C2\CCC/C(=C\c3cc(OC)cc(OC)c3)C2=O)c1,5.214670164989234,364.16745924799994,4,0,4.932400000000005,True
+3629,CHEMBL161226,6100.0,nM,1995.0,CNC(=O)c1c(SSc2[nH]c3ccccc3c2C(=O)NC)[nH]c2ccccc12,5.214670164989234,410.08711781600005,4,4,4.1678000000000015,True
+3630,CHEMBL4217686,6120.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccc(NC(=O)CCO)cc2)n1,5.213248577854438,512.1938810879999,9,3,3.747200000000001,True
+3631,CHEMBL3088224,6130.0,nM,2013.0,Cc1ccc(C(=O)N/N=C(/Cn2c([N+](=O)[O-])cnc2C)c2ccc(Br)cc2)cc1,5.212539525481585,455.05930153599996,6,1,4.004940000000002,True
+3632,CHEMBL2018751,6150.0,nM,2012.0,COC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1Cl,5.211124884224583,388.09383270399996,7,2,4.222300000000002,True
+3633,CHEMBL3221558,6150.0,nM,2011.0,COC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1Cl.Cl,5.211124884224583,424.07051041599993,7,2,4.644100000000003,True
+3634,CHEMBL1956887,6160.0,nM,2012.0,Nc1nc(Nc2cccc(Br)c2)c2cc(Cc3ccc(-c4ccccc4)cc3)[nH]c2n1,5.210419287835574,469.09020774000004,4,3,6.304000000000005,True
+3635,CHEMBL2047027,6170.0,nM,2012.0,C#Cc1cccc(NC(=O)c2cccc(NC(=O)CCCCCC(=O)NO)c2)c1,5.209714835966759,393.168856216,4,4,3.3146000000000013,True
+3636,CHEMBL3915538,6238.0,nM,2015.0,Nc1ncnc2c1c(-c1ccc(Oc3ccccc3)cc1)nn2C[C@@H]1CCCN1C(=O)/C=C/CN1CCOCC1,5.204954629578875,539.264487916,9,1,3.747200000000002,True
+3637,CHEMBL31745,6266.2,nM,2004.0,CC#CC(=O)Nc1cnc2ncc(C#N)c(Nc3cccc(Br)c3)c2c1,5.202995747738671,405.022522104,5,2,3.969380000000002,True
+3638,CHEMBL1172573,6270.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc(F)cc1,5.202732459169283,367.011301964,2,1,4.527200000000002,True
+3639,CHEMBL1822064,6270.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc(OC)cc3)C2)cc1,5.202732459169283,475.112125624,6,0,6.836400000000006,True
+3640,CHEMBL597303,6280.0,nM,2010.0,CCCCCCCNC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.2020403562628035,409.18892296399997,5,2,4.631000000000004,True
+3641,CHEMBL485745,6300.0,nM,2008.0,Fc1ccc(-c2nn3ccccc3c2-c2ccncc2)cc1,5.200659450546418,289.101525604,3,0,4.202400000000003,True
+3642,CHEMBL204223,6300.0,nM,2006.0,COc1cc(OC)c2c(c1)Oc1ncnc(Nc3cccc(Br)c3)c1NC2,5.200659450546418,428.0484025040001,7,2,4.7177000000000024,True
+3643,CHEMBL3263374,6310.0,nM,2014.0,O=C1CSC(N2N=C(c3ccccc3)CC2c2ccc3ccccc3c2)=N1,5.199970640755867,371.10923316400005,4,0,4.620300000000004,True
+3644,CHEMBL1242379,6340.0,nM,2008.0,COc1ccc(-c2nn(C(C)(C)C)c3ncnc(N)c23)cc1OC,5.197910742118268,327.169524912,7,1,2.8477000000000006,True
+3645,CHEMBL3221259,6400.0,nM,2011.0,CCCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1Cl.Cl,5.1938200260161125,466.11746060799993,7,2,5.8144000000000045,True
+3646,CHEMBL2018754,6400.0,nM,2012.0,CCCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1Cl,5.1938200260161125,430.14078289599996,7,2,5.392600000000004,True
+3647,CHEMBL176470,6400.0,nM,2000.0,Nc1ncnc2c1c(-c1ccccc1)cn2-c1ccccc1CNCCO,5.1938200260161125,359.174610292,6,3,2.7516000000000003,True
+3648,CHEMBL483321,6400.0,nM,2017.0,COCC(=O)NC/C=C/c1ccc2ncnc(Nc3ccc(Oc4ccc(C)nc4)c(C)c3)c2c1,5.1938200260161125,469.211389724,7,2,4.953340000000003,True
+3649,CHEMBL1828869,6410.0,nM,2011.0,O=C(Cc1ccc(F)cc1)NS(=O)(=O)c1ccc(Br)cc1,5.193141970481181,370.96270453200003,3,1,2.6358000000000006,True
+3650,CHEMBL3233768,6414.0,nM,2014.0,C/C=C(\C)C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2s1,5.192871044407578,376.0560879680001,5,2,5.132100000000003,True
+3651,CHEMBL1173601,6430.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccccc1Br,5.191789027075778,426.93123584399996,2,1,5.1506000000000025,True
+3652,CHEMBL1242113,6450.0,nM,2008.0,CCn1nc(-c2ccc(OC)c(O)c2)c2c(N)ncnc21,5.1904402853647325,285.12257472000005,7,2,1.8095999999999999,True
+3653,CHEMBL1958038,6480.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(Br)cc3)CC2c2ccc(F)cc2)=N1,5.188424994129408,416.9946733560001,4,0,4.368700000000003,True
+3654,CHEMBL4210744,6490.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(N)c2)n1,5.187755303199631,440.17275172,8,2,4.0085000000000015,True
+3655,CHEMBL333553,6500.0,nM,1993.0,N#C/C(=C\c1cc(O)c(O)c(CSc2nc3ccccc3s2)c1)C(N)=O,5.187086643357143,383.0398332760001,7,3,3.3920800000000018,True
+3656,CHEMBL1173665,6560.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccccc1F,5.18309616062434,367.011301964,2,1,4.527200000000002,True
+3657,CHEMBL3747152,6580.0,nM,2016.0,CC(=O)N1N=C(c2ccc(F)cc2)CC1c1ccc(C(=O)OC(C)Cn2c([N+](=O)[O-])cnc2C)cc1,5.181774106386044,493.176147088,8,0,4.181920000000003,True
+3658,CHEMBL330879,6600.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccc3ccccc3c2)c1O,5.180456064458131,390.103813436,5,2,4.238580000000003,True
+3659,CHEMBL1812566,6630.0,nM,2011.0,COc1cccc(/C=C/C(=O)Nc2ccc3ncnc(Nc4cccc(Cl)c4)c3c2)c1,5.178486471595226,430.119653528,5,2,5.687300000000003,True
+3660,CHEMBL1958035,6670.0,nM,2012.0,Cc1ccc(C2CC(c3ccc(Cl)cc3)=NN2C2=NC(=O)CS2)cc1,5.175874166083451,369.070260812,4,0,4.428920000000004,True
+3661,CHEMBL56236,6680.0,nM,1997.0,Cc1cc(C)c(C)c(-c2cc3cnc(N)nc3nc2NC(=O)NC(C)(C)C)c1C,5.175223537524454,392.23245951599995,5,3,4.427680000000001,True
+3662,CHEMBL1241863,6700.0,nM,2008.0,CC(C)n1nc(-c2ccc3[nH]c(=O)ccc3c2)c2c(N)ncnc21,5.173925197299173,320.138559132,6,2,2.4978999999999996,True
+3663,CHEMBL3604939,6700.0,nM,2015.0,CN(C)C/C=C/C(=O)Nc1cccc(Oc2nc(Nc3n[nH]c4ccccc34)cc(N3CCN(C)CC3)n2)c1,5.173925197299173,527.2757212960001,9,3,3.696900000000002,True
+3664,CHEMBL1828865,6740.0,nM,2011.0,O=C(Cc1ccc(F)cc1)NS(=O)(=O)c1ccccc1,5.171340103464679,293.052192464,3,1,1.8733,True
+3665,CHEMBL2029692,6800.0,nM,2012.0,O=C(Cn1c(-c2ccccc2)cc(=O)n2ncnc12)NNC(=S)Nc1ccccc1,5.1674910872937625,419.11644378400007,7,3,1.5757999999999992,True
+3666,CHEMBL2316145,6800.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3cccc(Br)c3)C2=O)cc(OC)c1,5.1674910872937625,412.067406632,3,0,5.686300000000005,True
+3667,CHEMBL2064391,6800.0,nM,2012.0,CC(=O)c1cccc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)c1,5.1674910872937625,447.19065428000005,9,1,3.2062000000000017,True
+3668,CHEMBL3892960,6810.0,nM,2016.0,C=CC(=O)NC1CCC(n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cc(C)ccc32)C1,5.166852888087215,456.177310636,4,2,5.011620000000004,True
+3669,CHEMBL1173714,6820.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccc(C(C)C)cc1,5.166215625343521,343.15320615200005,6,0,3.479720000000002,True
+3670,CHEMBL604671,6820.0,nM,2010.0,O=C1CSC(N/N=C/c2ccc([N+](=O)[O-])cc2)=N1,5.166215625343521,264.031711116,6,1,1.1477,True
+3671,CHEMBL1172917,6850.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc(Br)cc1,5.1643094285075755,426.93123584399996,2,1,5.1506000000000025,True
+3672,CHEMBL1761929,6900.0,nM,2011.0,COC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1,5.161150909262744,354.13280505599994,7,2,3.568900000000002,True
+3673,CHEMBL160566,6900.0,nM,1995.0,Cn1c(SSc2c(C#N)c3ccccc3n2C)c(C#N)c2ccccc21,5.161150909262744,374.065988448,6,0,5.212760000000004,True
+3674,CHEMBL4215703,6900.0,nM,2018.0,Cc1cc(=O)n(-c2ccc(F)cc2)nc1C(=O)Nc1ccc(Oc2ncnc3ccsc23)c(F)c1,5.161150909262744,491.08636678,8,1,4.868420000000002,True
+3675,CHEMBL1242028,6900.0,nM,2008.0,CC(C)n1nc(-c2cc(F)c(O)cc2F)c2c(N)ncnc21,5.161150909262744,305.1088164760001,6,2,2.6402,True
+3676,CHEMBL1641993,6900.0,nM,2011.0,N#Cc1cnc(Nc2cccc(Br)c2)c2cc(NC(=O)CCN3CCOCC3)ccc12,5.161150909262744,479.095687044,6,2,4.273380000000003,True
+3677,CHEMBL342929,6900.0,nM,1997.0,CNC(=O)c1c(SSc2c(C(=O)NC)c3ccccc3n2C)n(C)c2ccccc12,5.161150909262744,438.11841794400004,6,2,4.188600000000004,True
+3678,CHEMBL334439,6900.0,nM,1997.0,CCN(CC)CCn1c([Se][Se]c2c(C(=O)NC)c3ccccc3n2CCN(CC)CC)c(C(=O)NC)c2ccccc21,5.161150909262744,704.185617248,6,2,2.2730000000000024,True
+3679,CHEMBL4106341,6920.0,nM,1996.0,Cc1[nH]c2ncnc(NC3CCCCC3)c2c1C,5.1598939055432425,244.16879663999998,3,2,3.319340000000002,True
+3680,CHEMBL1821894,6920.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(OC)cc3)C2)cc1,5.1598939055432425,441.15109797599996,6,0,6.183000000000005,True
+3681,CHEMBL117554,7000.0,nM,1995.0,Clc1ccc(CNc2ncnc3ccccc23)cc1,5.154901959985743,269.07197506399996,3,1,3.8953000000000015,True
+3682,CHEMBL57300,7000.0,nM,1991.0,N#CC(C#N)=C1CCc2c1ccc(O)c2O,5.154901959985743,212.058577496,4,2,1.8447600000000008,True
+3683,CHEMBL490775,7000.0,nM,1992.0,C[C@H](NC(=O)[C@H](C)NC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1)C(=O)O,5.154901959985743,491.09985025199995,8,3,1.4092999999999996,True
+3684,CHEMBL203529,7000.0,nM,2006.0,Fc1ccc2c(c1)CNc1c(Nc3ccccc3)ncnc1O2,5.154901959985743,308.107339256,5,2,4.077100000000002,True
+3685,CHEMBL311133,7000.0,nM,1991.0,C[C@@H](NC(=O)[C@@H](C)NC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1)C(=O)O,5.154901959985743,491.09985025199995,8,3,1.4092999999999996,True
+3686,CHEMBL3325478,7000.0,nM,2014.0,CCOC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2cc(C)ccc2n2nnnc12,5.154901959985743,495.2018876600001,10,1,3.3252200000000016,True
+3687,CHEMBL1241950,7000.0,nM,2008.0,CC(C)n1nc(-c2ccc3nc(NN)ccc3c2)c2c(N)ncnc21,5.154901959985743,334.16544257600003,8,3,2.4901999999999997,True
+3688,CHEMBL75188,7000.0,nM,1997.0,Cc1cc(C)c(C)c(-c2cc3cnc(NCCCN4CCN(C)CC4)nc3nc2NC(=O)NC(C)(C)C)c1C,5.154901959985743,532.3638080280001,7,3,4.894880000000003,True
+3689,CHEMBL46946,7000.0,nM,1991.0,O=CN/C=C/c1ccc(O)c(O)c1,5.154901959985743,179.058243148,3,3,0.8144999999999998,True
+3690,CHEMBL3221550,7050.0,nM,2011.0,CCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1.Cl,5.151810883008602,418.14078289599996,7,2,4.770900000000005,True
+3691,CHEMBL2018748,7050.0,nM,2012.0,CCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1,5.151810883008602,382.16410518399994,7,2,4.349100000000003,True
+3692,CHEMBL2316146,7100.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccc(Br)cc3)C2=O)cc(OC)c1,5.1487416512809245,412.067406632,3,0,5.686300000000005,True
+3693,CHEMBL58436,7100.0,nM,1997.0,c1cc(Nc2nccc(-c3cccnc3)n2)cc(OCCn2ccnc2)c1,5.1487416512809245,358.15420919600007,7,1,3.5577000000000014,True
+3694,CHEMBL523122,7130.0,nM,2009.0,COCCOc1cc2ncnc(Nc3c(Cl)ccc4c3OCO4)c2cc1NC(=O)[C@@H]1CCCN1,5.146910470148134,485.146596548,9,3,3.4712000000000005,True
+3695,CHEMBL2064397,7200.0,nM,2012.0,CN(c1ccccc1)c1ncnc2cc3oc(=O)n(CCCN4CCOCC4)c3cc12,5.142667503568732,419.19573966,8,0,3.0279000000000016,True
+3696,CHEMBL2018761,7200.0,nM,2012.0,COC(=O)Nc1cc(Nc2ncnc3cc(OC)c(OC)cc23)ccc1C,5.142667503568732,368.14845512,7,2,3.877320000000002,True
+3697,CHEMBL4282482,7200.0,nM,2018.0,Clc1ccc(-c2cn3nc(-c4ccccc4)nc3s2)cc1,5.142667503568732,311.028396,4,0,4.778200000000003,True
+3698,CHEMBL3221553,7200.0,nM,2011.0,COC(=O)Nc1cc(Nc2ncnc3cc(OC)c(OC)cc23)ccc1C.Cl,5.142667503568732,404.125132832,7,2,4.299120000000003,True
+3699,CHEMBL1812435,7220.0,nM,2011.0,COc1ccc(/C=C/C(=O)Nc2ccc3ncnc(Nc4cccc(Br)c4)c3c2)cc1,5.141462802430362,474.069137948,5,2,5.796400000000004,True
+3700,CHEMBL599524,7230.0,nM,2010.0,CCCCCCCOC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.140861702705468,410.172938552,6,1,5.058000000000005,True
+3701,CHEMBL4083815,7230.0,nM,2017.0,O=c1c2ccccc2nc(-c2ccccc2)n1-c1nnc(-c2ccccc2Cl)s1,5.140861702705468,416.049859716,6,0,5.2246000000000015,True
+3702,CHEMBL1173602,7280.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccccc1Cl,5.137868620686962,382.981751424,2,1,5.041500000000003,True
+3703,CHEMBL101683,7300.0,nM,2003.0,O=C(Nc1ccc(Cl)cc1)c1ccccc1NCc1ccncc1,5.136677139879544,337.09818981200004,3,2,4.599400000000003,True
+3704,CHEMBL3085377,7300.0,nM,2007.0,CCN(CC)[C@@](C)(C#Cc1ncnc2cc(OC)c(OC)cc12)c1ccccc1,5.136677139879544,389.210327104,5,0,4.255700000000004,True
+3705,CHEMBL540292,7300.0,nM,1995.0,CN(C)CC(CSc1ccccc1)C(=O)c1ccc(OCc2ccccc2)cc1.Cl,5.136677139879544,441.152927816,4,0,5.840200000000006,True
+3706,CHEMBL1172980,7320.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc(Cl)cc1,5.135488918941609,382.981751424,2,1,5.041500000000003,True
+3707,CHEMBL4205469,7370.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccc(N)cc2)n1,5.1325325121409495,440.17275172,8,2,4.0085000000000015,True
+3708,CHEMBL1998736,7370.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1ccccc1F,5.1325325121409495,241.090292224,1,1,3.4776000000000016,True
+3709,CHEMBL3747277,7370.0,nM,2016.0,CC(=O)N1N=C(c2ccc(Cl)cc2)CC1c1ccc(C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,5.1325325121409495,495.130946484,8,0,4.307720000000003,True
+3710,CHEMBL3133899,7380.0,nM,2013.0,C=CC(=O)N1CCc2c(sc3ncnc(Nc4ccc(CC)cc4)c23)C1,5.131943638176958,364.13578226,5,1,4.068000000000002,True
+3711,CHEMBL1172916,7380.0,nM,2010.0,Cc1ccc(C2CC(c3ccc(Cl)c(Cl)c3)=NN2C(N)=S)cc1,5.131943638176958,363.03637384000007,2,1,4.696520000000004,True
+3712,CHEMBL188386,7400.0,nM,2005.0,OCCCCNc1cncc(-c2cncc(Nc3cccc(Cl)c3)n2)c1,5.130768280269023,369.13563794000004,6,3,4.120000000000003,True
+3713,CHEMBL369967,7400.0,nM,2005.0,CCNCc1cn2ncnc(Nc3ccc4c(cnn4Cc4ccccc4)c3)c2c1CC,5.130768280269023,425.23279386400003,7,2,4.542800000000003,True
+3714,CHEMBL1241776,7400.0,nM,2008.0,CC(C)n1nc(-c2ccc3nc[nH]c(=O)c3c2)c2c(N)ncnc21,5.130768280269023,321.13380810000007,7,2,1.8928999999999996,True
+3715,CHEMBL4214620,7430.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(N=[N+]=[N-])c2)n1,5.129011186239425,466.16324965600006,8,1,5.368100000000004,True
+3716,CHEMBL1929308,7440.0,nM,2012.0,CC(C)(C)c1ccc(-c2nnc(SCc3ccccc3)o2)cc1,5.1284270644541206,324.12963425999993,4,0,5.326400000000005,True
+3717,CHEMBL3237934,7442.0,nM,2014.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc(NC(=O)CCN3CCN(C)CC3)c2)n1,5.1283103343144845,594.283364788,10,2,4.002300000000003,True
+3718,CHEMBL590524,7460.0,nM,2010.0,O=C1CSC(N/N=C/c2cccc(Br)c2)=N1,5.127261172527333,296.95714497600005,4,1,2.0020000000000002,True
+3719,CHEMBL1821893,7480.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc(C)cc3)C2)cc1,5.126098402135539,425.156183356,5,0,6.482820000000006,True
+3720,CHEMBL490687,7500.0,nM,2009.0,C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ccnc2cc1CC,5.1249387366083,383.12006812800007,3,2,5.847900000000004,True
+3721,CHEMBL113902,7500.0,nM,2003.0,C/C=C/C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cc1OCC,5.1249387366083,424.11023171600004,5,2,5.555880000000004,True
+3722,CHEMBL3612580,7500.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4ccc(OC)cc4)c3cc21,5.1249387366083,422.15901980399997,9,1,3.633200000000002,True
+3723,CHEMBL383121,7500.0,nM,2006.0,COc1ccc2c(c1)CNc1c(Nc3ccccc3)ncnc1O2,5.1249387366083,320.127325752,6,2,3.946600000000002,True
+3724,CHEMBL107472,7500.0,nM,1998.0,CNc1ncc2cc(-c3c(Cl)cccc3Cl)c(=O)n(C)c2n1,5.1249387366083,334.038816364,5,1,3.344000000000001,True
+3725,CHEMBL2316149,7500.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\C3CCCCC3)C2=O)cc(OC)c1,5.1249387366083,340.20384475599997,3,0,5.346900000000005,True
+3726,CHEMBL590525,7510.0,nM,2010.0,Cc1cccc(CN(Cc2ccc(O)cc2)C(=O)Nc2ccccc2)c1O,5.124360062995832,362.16304256399997,3,3,4.640520000000004,True
+3727,CHEMBL4211322,7590.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccccc2[N+](=O)[O-])n1,5.11975822410452,470.14693089599996,9,1,4.334500000000003,True
+3728,CHEMBL98798,7600.0,nM,2011.0,COc1cc2ncnc(Oc3cccc(Br)c3)c2cc1OC,5.1191864077192095,360.01095437600003,5,0,4.201800000000003,True
+3729,CHEMBL3221557,7600.0,nM,2011.0,CCCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1C.Cl,5.1191864077192095,446.17208302399996,7,2,5.469420000000006,True
+3730,CHEMBL428690,7600.0,nM,2002.0,CN1CC[C@H](c2c(O)cc(O)c3c(=O)cc(-c4ccccc4Cl)oc23)[C@H](O)C1,5.1191864077192095,401.10300041999994,6,3,3.3046000000000015,True
+3731,CHEMBL2018758,7600.0,nM,2012.0,CCCCOC(=O)Nc1ccc(Nc2ncnc3cc(OC)c(OC)cc23)cc1C,5.1191864077192095,410.19540531199993,7,2,5.047620000000005,True
+3732,CHEMBL1822065,7660.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc(O)cc3)C2)cc1,5.115771230367397,461.09647556,6,1,6.533400000000005,True
+3733,CHEMBL244948,7670.0,nM,2007.0,O=c1ccc2ccc(O)c(O)c2o1,5.115204636051019,178.026608672,4,2,1.2041999999999997,True
+3734,CHEMBL48650,7700.0,nM,1992.0,O=C(Nc1ccccc1)c1cc2ccc(O)c(O)c2cn1,5.113509274827519,280.084792244,4,3,2.8983000000000017,True
+3735,CHEMBL462338,7700.0,nM,2009.0,COc1nc(Nc2ccc(-c3nc4ccccc4s3)cc2)c2cc[nH]c2n1,5.113509274827519,373.09973110000004,6,2,4.986800000000002,True
+3736,CHEMBL1947045,7700.0,nM,2012.0,COc1cccc(Nc2ccnc(Nc3cccc(OC)c3)n2)c1,5.113509274827519,322.142975816,6,2,3.9810000000000016,True
+3737,CHEMBL3628796,7710.0,nM,2015.0,COc1cc2ncnc(Nc3ccc(NC(=O)Nc4cccc(Br)c4)cc3)c2cc1OC,5.112945621949042,493.0749516,6,3,5.797100000000004,True
+3738,CHEMBL1812555,7710.0,nM,2011.0,COc1ccccc1/C=C/C(=O)Nc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,5.112945621949042,474.069137948,5,2,5.796400000000003,True
+3739,CHEMBL242349,7710.0,nM,2007.0,COCCOc1cc2ncnc(NC3=CC(=O)C(OCc4cccc(OC)c4)=CC3=O)c2cc1OC,5.112945621949042,491.16925014,10,1,3.220500000000002,True
+3740,CHEMBL1173666,7780.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc([N+](=O)[O-])cc1,5.1090204030103115,394.00580198399996,4,1,4.296300000000002,True
+3741,CHEMBL1822061,7780.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc(Cl)cc3)C2)cc1,5.1090204030103115,479.06258858800004,5,0,7.481200000000005,True
+3742,CHEMBL325949,7800.0,nM,1994.0,Nc1cccc(-c2cc(=O)c3c(N)c(O)c(N)cc3o2)c1,5.107905397309518,283.095691276,6,4,1.9121999999999997,True
+3743,CHEMBL515598,7800.0,nM,2009.0,c1ccc2sc(-c3ccc(Nc4ncnc5[nH]cnc45)cc3)nc2c1,5.107905397309518,344.084415384,6,2,4.373200000000002,True
+3744,CHEMBL3612574,7800.0,nM,2015.0,CCOC(=O)CCCn1c(=O)oc2cc3ncnc(Nc4ccc(F)c(Cl)c4)c3cc21,5.107905397309518,444.100060956,8,1,4.417100000000003,True
+3745,CHEMBL604672,7820.0,nM,2010.0,O=C(Nc1ccccc1Br)c1ccc(N(CCCl)CCCl)cc1,5.1067932469401525,413.990130624,2,1,4.985400000000004,True
+3746,CHEMBL1830279,7830.0,nM,2011.0,COc1ccc(C(/C=C/c2ccccc2Cl)=N\NC(N)=S)cc1,5.106238237942057,345.070260812,3,2,3.5993000000000013,True
+3747,CHEMBL1173652,7830.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccccc1,5.106238237942057,301.10625596000006,6,0,2.35632,True
+3748,CHEMBL3742349,7880.0,nM,2015.0,CCOC(=O)c1nn(-c2ccc(C)cc2)cc1C(=O)c1c(C)[nH]c(-c2ccccc2)c1-c1ccccc1,5.103473782510445,489.2052417240001,5,1,6.558940000000006,True
+3749,CHEMBL2347973,7893.0,nM,2013.0,COC(=O)[C@@H](Nc1ncnc2oc(-c3ccccc3)c(-c3ccccc3)c12)c1ccccc1,5.102757897194635,435.158291532,6,1,5.8830000000000044,True
+3750,CHEMBL89505,7900.0,nM,1998.0,CC(C)(C)c1cc(/C=C2\C(=O)Nc3ccccc32)cc(C(C)(C)C)c1O,5.102372908709559,349.204179104,2,2,5.479900000000005,True
+3751,CHEMBL309016,7900.0,nM,1991.0,COc1cc(/C=C/[N+](=O)[O-])ccc1O,5.102372908709559,195.053157768,4,1,1.6481999999999999,True
+3752,CHEMBL3416616,7904.0,nM,2015.0,Brc1cc2c(NCc3ccccn3)ncnc2s1,5.102153068420427,319.9731293880001,5,1,3.4609000000000005,True
+3753,CHEMBL3805508,7920.0,nM,2016.0,c1ccc(COc2cccc(C3CC(c4ccc5c(c4)OCCO5)=NN3c3ccccc3)c2)cc1,5.101274818410507,462.194342692,5,0,6.392500000000006,True
+3754,CHEMBL1958211,7960.0,nM,2012.0,COc1ccc(C2CC(c3ccc(Br)cc3)=NN2C2=NC(=O)CS2)cc1,5.099086932262331,429.014659852,5,0,4.2382000000000035,True
+3755,CHEMBL119708,8000.0,nM,1995.0,O=[N+]([O-])c1cccc2ncnc(NCc3ccccc3)c12,5.096910013008057,280.096025624,5,1,3.150100000000001,True
+3756,CHEMBL3221541,8000.0,nM,2011.0,CCOC(=O)Nc1ccc(Nc2ncnc3cc(OCCN4CCOCC4)c(OC)cc23)cc1C.Cl,5.096910013008057,517.2091968039999,9,2,4.391620000000005,True
+3757,CHEMBL2316144,8000.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccccc3Br)C2=O)cc(OC)c1,5.096910013008057,412.067406632,3,0,5.686300000000005,True
+3758,CHEMBL135592,8000.0,nM,2003.0,C/N=N/Nc1ccc2ncnc(N(C)c3ccccc3)c2c1,5.096910013008057,292.143644512,5,1,3.806600000000002,True
+3759,CHEMBL1242753,8010.0,nM,2008.0,CCOc1cc(-c2nn(CCO)c3ncnc(N)c23)ccc1OC,5.0963674839157616,329.148789468,8,2,1.4750999999999999,True
+3760,CHEMBL377277,8068.0,nM,2006.0,COc1cc(OC(C)C)c2c(Nc3ccc(F)c(Cl)c3)ncnc2c1,5.0932341104592735,361.09933268400005,5,1,4.961700000000003,True
+3761,CHEMBL4216551,8070.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccc(NC(=O)/C=C/CN(C)C)cc2)n1,5.09312646527793,551.241165628,9,2,4.482600000000002,True
+3762,CHEMBL1173193,8090.0,nM,2010.0,COc1ccc(C2CC(c3ccc(Br)c(Br)c3)=NN2C(N)=S)cc1,5.092051478387726,466.93025730000005,3,1,4.614900000000004,True
+3763,CHEMBL3325476,8100.0,nM,2014.0,COC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2cc(Cl)ccc2n2nnnc12,5.091514981121351,501.1316151800001,10,1,3.280100000000002,True
+3764,CHEMBL1173653,8110.0,nM,2010.0,Cc1ccc(/C=C/C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,5.090979145788844,315.12190602400005,6,0,2.664740000000001,True
+3765,CHEMBL1958025,8140.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(F)cc3)CC2c2ccccc2)=N1,5.0893755951107975,339.084161288,4,0,3.606200000000002,True
+3766,CHEMBL1169870,8150.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Br)c(Br)c2)CC1c1ccc(Cl)cc1,5.088842391260024,470.880720264,2,1,5.259700000000003,True
+3767,CHEMBL1958033,8160.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(Cl)cc3)CC2c2ccc(Cl)cc2)=N1,5.088309841246137,389.01563839600004,4,0,4.773900000000004,True
+3768,CHEMBL337297,8180.0,nM,1994.0,CO[C@H]1[C@@H](N(C)C(=O)c2cnccn2)C[C@@H]2O[C@@]1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,5.087246696328677,572.217203376,8,1,4.696800000000004,True
+3769,CHEMBL3088218,8190.0,nM,2013.0,Cc1ncc([N+](=O)[O-])n1C/C(=N/NC(=O)c1ccncc1)c1ccc(Br)cc1,5.086716098239581,442.0389004400001,7,1,3.091520000000002,True
+3770,CHEMBL2325103,8250.0,nM,2013.0,NC(=S)N1N=C(c2ccc(F)cc2)CC1c1cccc2ccccc12,5.0835460514500745,349.104896732,2,1,4.373600000000002,True
+3771,CHEMBL401644,8270.0,nM,2007.0,COc1ccc2ncc(C#N)c(N[C@@H]3C[C@H]3c3ccccc3)c2c1,5.082494490447454,315.137162164,4,1,4.0830800000000025,True
+3772,CHEMBL1828866,8280.0,nM,2011.0,Cc1ccc(S(=O)(=O)NC(=O)Cc2ccc(F)cc2)cc1,5.081969663215119,307.06784252799997,3,1,2.1817200000000003,True
+3773,CHEMBL353823,8300.0,nM,2001.0,CC(C)(C)OC(=O)N1CCC(n2cc(-c3ccccc3)c3c(N)ncnc32)C1,5.080921907623925,379.2008250400001,6,1,3.862400000000002,True
+3774,CHEMBL4079829,8300.0,nM,2017.0,Nc1nc(N)c2c(n1)[nH]c1cccc(Sc3ccc(Cl)cc3)c12,5.080921907623925,341.050194064,5,3,4.080100000000001,True
+3775,CHEMBL1241492,8300.0,nM,2008.0,CC(C)n1nc(-c2ccc3nonc3c2)c2c(N)ncnc21,5.080921907623925,295.118158036,8,1,2.1925999999999997,True
+3776,CHEMBL1958029,8360.0,nM,2012.0,Cc1ccc(C2CC(c3ccc(F)cc3)=NN2C2=NC(=O)CS2)cc1,5.077793722560983,353.09981135199996,4,0,3.914620000000003,True
+3777,CHEMBL363130,8400.0,nM,2005.0,Cc1ccsc1C(=O)n1nc(Nc2ccc(S(N)(=O)=O)cc2)nc1N,5.075720713938118,378.056880308,9,3,1.3097199999999998,True
+3778,CHEMBL136492,8400.0,nM,2003.0,CN(c1ccccc1)c1ncnc2ccc(N)cc12,5.075720713938118,250.12184644799999,4,1,2.9799000000000007,True
+3779,CHEMBL2029694,8400.0,nM,2012.0,CCOc1ccc(-c2cc(C(F)(F)F)c(C#N)c(SCC(=O)NCC(=O)O)n2)cc1,5.075720713938118,439.081361652,6,2,3.330680000000001,True
+3780,CHEMBL4210237,8420.0,nM,2017.0,C=CC(=O)Nc1ccccc1Oc1nc(Nc2ccc(N3CCN(C)CC3)cc2OC)ncc1Cl,5.074687908500351,494.18331640400004,8,2,4.550800000000003,True
+3781,CHEMBL1822066,8430.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccc(Cl)cc4)cs3)C(c3ccc([N+](=O)[O-])cc3)C2)cc1,5.074172425375258,490.086639148,7,0,6.736000000000005,True
+3782,CHEMBL3393072,8490.0,nM,2015.0,O=C(Cc1c[nH]c2ccccc12)NNC(=S)Nc1ncccc1Br,5.071092309756047,403.01024316800004,3,4,2.8857,True
+3783,CHEMBL3891774,8500.0,nM,2016.0,O=C(Nc1ccc(Nc2ncnc3cc4oc(=O)n(CCOC(=O)CBr)c4cc23)cc1)NC1CCCCC1,5.070581074285707,582.122630064,9,3,4.673600000000004,True
+3784,CHEMBL3221546,8500.0,nM,2011.0,CCOC(=O)Nc1ccc(Nc2ncnc3cc(OCCN4CCOCC4)c(OC)cc23)cc1Cl.Cl,5.070581074285707,537.1545743879999,9,2,4.736600000000005,True
+3785,CHEMBL3747055,8540.0,nM,2016.0,COc1ccc(C2=NN(C(C)=O)C(c3ccc(C(=O)OCCn4c([N+](=O)[O-])cnc4C)cc3)C2)cc1,5.068542129310996,491.18048352000005,9,0,3.6629200000000024,True
+3786,CHEMBL589801,8540.0,nM,2010.0,Cc1cccc(CN(Cc2ccc(F)cc2)C(=S)Nc2ccccc2)c1O,5.068542129310996,380.135862512,2,2,5.238920000000005,True
+3787,CHEMBL1958036,8580.0,nM,2012.0,COc1ccc(C2CC(c3ccc(Cl)cc3)=NN2C2=NC(=O)CS2)cc1,5.066512712151295,385.06517543200005,5,0,4.129100000000004,True
+3788,CHEMBL2029699,8600.0,nM,2012.0,Cc1ccc(N2NC(=O)/C(=C/c3ccc(OCc4ccccc4)cc3)C2=O)cc1Cl,5.065501548756432,418.108420148,3,1,4.688820000000003,True
+3789,CHEMBL116438,8600.0,nM,2013.0,COc1cc(/C=C/C(=O)/C=C(O)/C=C/c2ccc(O)c(OC)c2)ccc1O,5.065501548756432,368.12598835999995,6,3,3.852600000000003,True
+3790,CHEMBL1821896,8630.0,nM,2011.0,COc1ccc(C2=NN(c3nc(-c4ccccc4)cs3)C(c3ccc([N+](=O)[O-])cc3)C2)cc1,5.06398920428479,456.12561149999993,7,0,6.082600000000005,True
+3791,CHEMBL140,8650.0,nM,2016.0,COc1cc(/C=C/C(=O)CC(=O)/C=C/c2ccc(O)c(OC)c2)ccc1O,5.062983892535186,368.12598835999995,6,2,3.3699000000000026,True
+3792,CHEMBL1830275,8660.0,nM,2011.0,COc1ccc(C(/C=C/c2ccccc2)=N\NC(N)=S)cc1,5.062482107982653,311.109233164,3,2,2.9459,True
+3793,CHEMBL3235204,8660.0,nM,2014.0,Cc1ccc2nc(Oc3ccc(Cl)cc3)c(/C=N/NC(=O)Cn3c([N+](=O)[O-])cnc3C)cc2c1,5.062482107982653,478.115630768,8,1,4.552340000000004,True
+3794,CHEMBL1242657,8700.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2[C@H]1CCNC1,5.060480747381382,314.12913732000004,7,3,1.4545999999999994,True
+3795,CHEMBL333454,8700.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccc(C)cc2)c1O,5.060480747381382,354.103813436,5,2,3.393800000000003,True
+3796,CHEMBL112925,8700.0,nM,1994.0,Nc1ccc(-c2cc(=O)c3cc(N)ccc3o2)cc1,5.060480747381382,252.089877624,4,2,2.6244000000000005,True
+3797,CHEMBL7775,8700.0,nM,1994.0,CN(c1ccccc1)c1cc2c(cc1Nc1ccccc1)C(=O)NC2=O,5.060480747381382,343.132076784,4,2,4.081700000000002,True
+3798,CHEMBL299194,8700.0,nM,1998.0,CN1CCN(CCCNc2ncc3cc(-c4c(Cl)cccc4Cl)c(=O)n(C)c3n2)CC1,5.060480747381382,460.154514812,7,1,3.351700000000001,True
+3799,CHEMBL120185,8700.0,nM,2004.0,CN1CCN(c2ccc3c(n2)nc(-c2ccc(F)cc2)n3-c2ccnc(NC3CCCC3)n2)CC1,5.060480747381382,472.2499211480001,8,1,4.122900000000003,True
+3800,CHEMBL611681,8710.0,nM,2010.0,CCCCCCNC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.059981844992336,395.1732729,5,2,4.2409000000000034,True
+3801,CHEMBL541988,8719.0,nM,2012.0,COc1cc2ncc(C(=O)O)c(Nc3cccc(Br)c3)c2cc1OC,5.059533322336471,402.02151906,5,2,4.456300000000002,True
+3802,CHEMBL3133898,8730.0,nM,2013.0,C=CC(=O)N1CCc2c(sc3ncnc(Nc4cccc(CC)c4)c23)C1,5.058985756294431,364.13578226,5,1,4.068000000000003,True
+3803,CHEMBL419409,8800.0,nM,2004.0,COc1ccc(C#CC(C)(C)N)cc1C(=O)c1ccc(Nc2ccc(F)cc2F)cc1,5.055517327849831,420.164934384,4,2,5.036800000000004,True
+3804,CHEMBL78224,8800.0,nM,1991.0,O=[N+]([O-])/C=C/c1ccc(O)c(O)c1,5.055517327849831,181.037507704,4,2,1.3451999999999997,True
+3805,CHEMBL543361,8800.0,nM,1995.0,CN(C)CC(CSCCN)C(=O)c1ccc(OCc2ccccc2)cc1.Cl,5.055517327849831,408.16382684800004,5,1,3.739800000000002,True
+3806,CHEMBL1812567,8800.0,nM,2013.0,O=C(/C=C/c1cccs1)Nc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,5.055517327849831,406.06550978,5,2,5.740200000000002,True
+3807,CHEMBL538757,8800.0,nM,1995.0,COC(=O)c1ccccc1SCC(CN(C)C)C(=O)c1ccc(OCc2ccccc2)cc1.Cl,5.055517327849831,499.15840711999994,6,0,5.6268000000000065,True
+3808,CHEMBL4205869,8870.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2cccc([N+](=O)[O-])c2)n1,5.052076380168273,470.14693089599996,9,1,4.334500000000003,True
+3809,CHEMBL432941,8880.0,nM,2000.0,COc1cccc(-c2ccc3c(c2)NC(=O)/C3=C\c2[nH]c3c(c2CCC(=O)O)CCCC3)c1,5.051587034221399,442.18925731199994,3,3,5.079000000000003,True
+3810,CHEMBL1958223,8890.0,nM,2012.0,COc1ccc(C2=NN(C3=NC(=O)CS3)C(c3ccc(OC)cc3)C2)cc1,5.051098239029786,381.114712468,6,0,3.484300000000003,True
+3811,CHEMBL379041,8900.0,nM,2006.0,Fc1ccc2c(c1)CNc1c(NCc3ccccc3)ncnc1O2,5.050609993355087,322.12298932000004,5,2,3.9456000000000016,True
+3812,CHEMBL1241771,8900.0,nM,2008.0,CC(C)n1nc(-c2ccc(C#N)c(F)c2)c2c(N)ncnc21,5.050609993355087,296.118572636,6,1,2.66718,True
+3813,CHEMBL1172823,8920.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Br)c(Br)c2)CC1c1ccc(F)cc1,5.049635145623877,454.910270804,2,1,4.745400000000003,True
+3814,CHEMBL48802,9000.0,nM,2016.0,C[S+]([O-])CCCCN=C=S,5.045757490560675,177.028205972,3,0,1.2479,True
+3815,CHEMBL488646,9000.0,nM,2008.0,COc1cc(C2=C(c3cn(COC(C)(C)C)c4ccccc34)CNC2=O)cc(OC)c1OC,5.045757490560675,450.21547205999997,6,1,4.480300000000003,True
+3816,CHEMBL202244,9000.0,nM,2006.0,COC(=O)c1c(OCCN2CCCC2)c2ccccc2c2oc3c(c12)C(=O)c1ccccc1C3=O,5.045757490560675,469.15253745599995,7,0,4.622600000000004,True
+3817,CHEMBL1241860,9000.0,nM,2008.0,CC(C)n1nc(-c2ccc(C=O)c(F)c2)c2c(N)ncnc21,5.045757490560675,299.11823828800004,6,1,2.6079999999999997,True
+3818,CHEMBL128027,9000.0,nM,2002.0,CCOc1cc2nc(C)nc(Nc3cccc(-c4csc(C)n4)c3)c2cc1OCC,5.045757490560675,420.16199700799996,7,1,5.911140000000005,True
+3819,CHEMBL1947122,9021.0,nM,2012.0,COc1cc2ncc(C(=O)O)c(Nc3cccc(Cl)c3)c2cc1OC,5.044745317179821,358.07203463999997,5,2,4.347200000000003,True
+3820,CHEMBL3805893,9040.0,nM,2016.0,c1ccc(COc2ccc(C3CC(c4ccc5c(c4)OCCO5)=NN3c3ccccc3)cc2)cc1,5.043831569524637,462.194342692,5,0,6.392500000000006,True
+3821,CHEMBL4204354,9040.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccc(N=C=S)cc2)n1,5.043831569524637,482.12917265600004,9,1,5.160600000000004,True
+3822,CHEMBL2336357,9050.0,nM,2013.0,COc1ccc(NC(=O)/C=C/c2ccccc2)cc1,5.043351420794797,253.11027872,2,1,3.347100000000001,True
+3823,CHEMBL1095464,9100.0,nM,2010.0,Cc1ccccc1Cc1cc2c(Nc3cccc(Br)c3)nc(N)nc2[nH]1,5.040958607678906,407.0745576760001,4,3,4.945420000000003,True
+3824,CHEMBL2018773,9100.0,nM,2012.0,CCN(CC)CCOc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OC,5.040958607678906,462.106666328,6,1,5.004200000000004,True
+3825,CHEMBL591213,9120.0,nM,2010.0,CCCCCCOC(=O)COc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,5.040005161671584,396.157288488,6,1,4.667900000000004,True
+3826,CHEMBL1240544,9140.0,nM,2008.0,C[C@@H](CN)n1nc(-c2ccc(Cl)c(O)c2)c2c(N)ncnc21,5.039053804266169,318.09958678000004,7,3,1.9542,True
+3827,CHEMBL3740247,9190.0,nM,2015.0,CC(=O)c1nn(-c2ccc(C)cc2)cc1C(=O)c1c(C)[nH]c(-c2ccccc2)c1-c1ccccc1,5.036684488613887,459.19467704000004,4,1,6.584840000000006,True
+3828,CHEMBL3746168,9260.0,nM,2016.0,CC(=O)N1N=C(c2ccc(Cl)cc2)CC1c1ccc(C(=O)OC(C)Cn2c([N+](=O)[O-])cnc2C)cc1,5.033389013318066,509.146596548,8,0,4.696220000000005,True
+3829,CHEMBL589068,9260.0,nM,2010.0,Cc1cc(C)c(O)c(CN(Cc2ccc(O)cc2)C(=O)Nc2ccccc2)c1,5.033389013318066,376.178692628,3,3,4.948940000000004,True
+3830,CHEMBL1947123,9284.0,nM,2012.0,COc1cc2ncc(C(=O)O)c(Nc3ccc(F)c(Cl)c3)c2cc1OC,5.03226486821612,376.06261282799994,5,2,4.486300000000003,True
+3831,CHEMBL3960786,9300.0,nM,2016.0,O=C(CBr)OCCn1c(=O)oc2cc3ncnc(Nc4ccc(NC(=O)N5CCCCC5)cc4)c3cc21,5.031517051446063,568.1069800000001,9,2,4.237200000000003,True
+3832,CHEMBL126483,9300.0,nM,2002.0,CCOc1cc2nc(CC)nc(Nc3cccc(-c4csc(C)n4)c3)c2cc1OCC,5.031517051446063,434.17764707199996,7,1,6.165120000000005,True
+3833,CHEMBL137635,9300.0,nM,2003.0,CN(c1ccccc1)c1ncnc2ccc(N/N=N/Cc3ccccn3)cc12,5.031517051446063,369.17019360800003,6,1,4.772000000000004,True
+3834,CHEMBL2283248,9350.0,nM,2013.0,CCOc1ccccc1NC(=O)/C=C/c1ccccc1,5.029188389127482,267.125928784,2,1,3.7372000000000023,True
+3835,CHEMBL4208167,9360.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccc([N+](=O)[O-])cc2)n1,5.028724151261895,470.14693089599996,9,1,4.334500000000003,True
+3836,CHEMBL1821877,9370.0,nM,2011.0,Clc1ccc(C2CC(c3ccc(Br)cc3)=NN2c2nc(-c3ccccc3)cs2)cc1,5.028260409112222,493.00150832400004,4,0,7.581700000000005,True
+3837,CHEMBL1241769,9380.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2CC1CCCN1,5.027797161620935,344.11523684400004,7,3,2.186499999999999,True
+3838,CHEMBL78049,9400.0,nM,1991.0,C/C(=C\c1ccc(O)c(O)c1)[N+](=O)[O-],5.026872146400301,195.053157768,4,2,1.7353000000000003,True
+3839,CHEMBL345203,9400.0,nM,1994.0,CNC(=O)CCc1c(SSc2[nH]c3ccccc3c2CCC(=O)NC)[nH]c2ccccc12,5.026872146400301,466.14971807200004,4,4,4.805800000000003,True
+3840,CHEMBL2018767,9450.0,nM,2012.0,CCN(CC)CCOc1cc2ncnc(Nc3ccc(C)c(Br)c3)c2cc1OC,5.0245681914907365,458.13173820400004,6,1,5.173520000000005,True
+3841,CHEMBL592710,9460.0,nM,2010.0,O=C(Nc1ccccc1Cl)c1ccc(N(CCCl)CCCl)cc1,5.024108863598207,370.040646204,2,1,4.876300000000003,True
+3842,CHEMBL89723,9500.0,nM,1998.0,CC(C)c1cc(/C=C2\C(=O)Nc3ccc(Cl)cc32)cc(C(C)C)c1O,5.022276394711152,355.13390662399996,2,2,5.785100000000004,True
+3843,CHEMBL3747079,9580.0,nM,2016.0,CC(=O)N1N=C(c2ccccc2)CC1c1ccc(C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,5.018634490921455,461.169918836,8,0,3.654320000000003,True
+3844,CHEMBL1828872,9590.0,nM,2011.0,O=C(Cc1ccc(Cl)cc1)NS(=O)(=O)c1ccc(F)cc1,5.0181813928293355,327.01322011200006,3,1,2.526700000000001,True
+3845,CHEMBL410659,9600.0,nM,2008.0,Nc1nccn2c1c(-c1ccc3ccc(-c4ccccc4)nc3c1)nc2[C@H]1C[C@@H](CN2CCC2)C1,5.017728766960432,460.2375448960001,6,1,5.393000000000005,True
+3846,CHEMBL379017,9601.0,nM,2006.0,COc1cc(OC2CCN(S(C)(=O)=O)CC2)c2c(Nc3ccc(F)c(Cl)c3)ncnc2c1,5.0176835303079335,480.1034320840001,7,1,3.9773000000000023,True
+3847,CHEMBL525527,9700.0,nM,2014.0,COc1cc2nc(Cl)nc(Nc3ccc(S(=O)(=O)Nc4nccs4)cc3)c2cc1OC,5.013228265733755,477.033223672,9,2,4.301300000000003,True
+3848,CHEMBL168555,9700.0,nM,2001.0,COc1ccc(CC(CO)n2cc(-c3cccc(OC)c3)c3c(N)ncnc32)cc1,5.013228265733755,404.1848406280001,7,2,3.4738000000000016,True
+3849,CHEMBL122260,9700.0,nM,1997.0,CNC(=O)c1cc(NCc2cc(O)ccc2O)ccc1O,5.013228265733755,288.111006992,5,5,1.7750999999999997,True
+3850,CHEMBL2029689,9700.0,nM,2012.0,O=S(=O)(c1ccc(/N=C/c2cc(Br)ccc2O)cc1)N1CCCCC1,5.013228265733755,422.029975568,4,1,4.079900000000003,True
+3851,CHEMBL4069284,9726.0,nM,2017.0,CCC(=O)Nc1cc(Nc2n[nH]c3ccccc23)ccc1N(C)CCN(C)C,5.012065734767841,380.23245951600006,5,3,3.652800000000002,True
+3852,CHEMBL4216025,9760.0,nM,2017.0,COc1cc(N2CCN(C)CC2)ccc1Nc1ncc(Cl)c(Oc2ccc(N=[N+]=[N-])cc2)n1,5.010550182333309,466.16324965600006,8,1,5.3681000000000045,True
+3853,CHEMBL1830277,9780.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccccc1)c1ccc(Cl)c(Cl)c1,5.009661145212398,349.020723776,2,2,4.244100000000002,True
+3854,CHEMBL3133893,9800.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(S(=O)(=O)Nc4ccccn4)cc3)c2c1,5.008773924307505,446.116109436,7,3,3.6937000000000015,True
+3855,CHEMBL206370,9800.0,nM,2006.0,COc1ccc2c(c1)CNc1c(Nc3cccc(-c4ccccc4)c3)ncnc1O2,5.008773924307505,396.15862588,6,2,5.6136000000000035,True
+3856,CHEMBL4286998,9800.0,nM,2018.0,c1ccc(-c2nc3sc(-c4ccccc4)cn3n2)cc1,5.008773924307505,277.067368352,4,0,4.124800000000003,True
+3857,CHEMBL1173262,9830.0,nM,2010.0,Cc1ccc(C2CC(c3ccc(Br)c(Br)c3)=NN2C(N)=S)cc1,5.0074464821678655,450.93534268000013,2,1,4.9147200000000035,True
+3858,CHEMBL1981977,9860.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1ccccc1Cl,5.006123085058789,257.060741684,1,1,3.991900000000002,True
+3859,CHEMBL2018765,9900.0,nM,2012.0,CCN(CC)CCOc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OC,5.00436480540245,418.157181908,6,1,4.895100000000004,True
+3860,CHEMBL488271,9900.0,nM,2008.0,CNC(=N)SCCCn1c(=O)c2n3ccc4cccc(c43)c3cc4ccccc4n3c=2c1=O,5.00436480540245,455.141595912,7,2,3.460350000000002,True
+3861,CHEMBL1241947,9900.0,nM,2008.0,Cc1cc(-c2nn(C(C)C)c3ncnc(N)c23)sc1C=O,5.00436480540245,301.0997311,7,1,2.83882,True
+3862,CHEMBL3917723,9941.0,nM,2017.0,COC(=O)CNC(=O)c1ccc(Nc2ncnc3cc(OCCN4CCCCC4)c(OC)cc23)cc1,5.002569926202528,493.23251909199996,9,2,3.1495000000000006,True
+3863,CHEMBL1683954,10000.0,nM,2011.0,Fc1cccc(COc2ccc(Nc3cc(Oc4ccccc4)ncn3)cc2Cl)c1,5.0,421.0993326840001,5,1,6.384000000000004,True
+3864,CHEMBL382862,10000.0,nM,2006.0,Brc1ccc2c(c1)CNc1c(Nc3ccccc3)ncnc1O2,5.0,368.027273136,5,2,4.700500000000003,True
+3865,CHEMBL2333986,10000.0,nM,2013.0,COc1cc2ncnc(Nc3ccccc3C(F)(F)F)c2cc1OC,5.0,349.10381134799997,5,1,4.409400000000002,True
+3866,CHEMBL520493,10000.0,nM,1992.0,N#C/C(=C/c1ccc(O)c(O)c1)C(=O)Nc1ccccc1Cl,5.0,314.04581989200005,4,3,3.2968800000000007,True
+3867,CHEMBL454002,10000.0,nM,1992.0,N#CC(C#N)=C(C#N)c1cc(O)cc(O)c1,5.0,211.0381764,5,2,1.4221399999999997,True
+3868,CHEMBL474267,10000.0,nM,1992.0,N#CC(C#N)=C(C#N)c1ccc(O)c(O)c1,5.0,211.0381764,5,2,1.4221399999999997,True
+3869,CHEMBL3608432,10000.0,nM,2015.0,C=CC(=O)N[C@@H]1CN(c2nc(Nc3cn(C)nc3C)c3ncn(C(C)C)c3n2)C[C@H]1F,5.0,427.22443467200003,9,2,2.0216199999999995,True
+3870,CHEMBL1241861,10000.0,nM,2008.0,CC(C)n1nc(-c2cc(F)c(C=O)c(F)c2)c2c(N)ncnc21,5.0,317.1088164760001,6,1,2.7470999999999997,True
+3871,CHEMBL47660,10000.0,nM,1991.0,N#C/C(=C\c1cc(O)ccc1O)C(N)=O,5.0,204.053492116,4,3,0.4900800000000001,True
+3872,CHEMBL3884319,10000.0,nM,2017.0,CC1(C)C(=O)N([C@H]2CCc3c(O)cccc32)c2nc(Nc3ccccc3)ncc21,5.0,386.174275944,5,2,4.2375000000000025,True
+3873,CHEMBL3676351,10000.0,nM,2014.0,C=CC(=O)Nc1cc2c(Nc3cc(C(=O)NOC)c(Br)cc3F)ncnc2cc1OCCNC(C)=O,5.0,560.0819081240002,8,4,3.2056000000000013,True
+3874,CHEMBL345211,10000.0,nM,1995.0,Cn1c(SSc2c(C(=O)NCC(=O)O)c3ccccc3n2C)c(C(=O)NCC(=O)O)c2ccccc21,5.0,526.0980764239999,8,4,3.098200000000001,True
+3875,CHEMBL131577,10000.0,nM,2003.0,Cc1cccc(Cl)c1NC(=O)c1cnc(NC(=O)C2CC2)s1,5.0,335.04952536800005,4,2,3.7057200000000012,True
+3876,CHEMBL1242117,10000.0,nM,2008.0,Cn1nc(-c2ccc3occc(=O)c3c2)c2c(N)ncnc21,5.0,293.09127459200005,7,1,1.7188999999999997,True
+3877,CHEMBL13629,10000.0,nM,2003.0,CCN(CC)CCNC(=O)c1c(C)[nH]c(/C=C2\C(=O)Nc3ccc(Br)cc32)c1C,5.0,458.131738204,3,3,3.9583400000000015,True
+3878,CHEMBL296407,10000.0,nM,1989.0,N#C/C(=C\c1ccc(O)c(O)c1)C(N)=O,5.0,204.053492116,4,3,0.4900799999999999,True
+3879,CHEMBL523586,10000.0,nM,2009.0,NC[C@H](Cc1cccc(F)c1)NC(=O)c1cc(Br)c(-c2ccnc3[nH]ccc23)s1,5.0,472.0368725160001,4,3,4.492800000000003,True
+3880,CHEMBL116919,10000.0,nM,1995.0,COc1ccc(CNc2ncnc3ccccc23)cc1,5.0,265.1215121,4,1,3.2505000000000015,True
+3881,CHEMBL1172957,10000.0,nM,2010.0,NS(=O)(=O)c1ccc(Nc2nc(N3CCOCC3)nc3[nH]cnc23)cc1,5.0,375.1113584040001,8,3,0.5805000000000002,True
+3882,CHEMBL3088225,10020.0,nM,2013.0,Cc1ncc([N+](=O)[O-])n1C/C(=N/NC(=O)c1ccccc1)c1ccc(Br)cc1,4.999132278468774,441.04365147199996,6,1,3.6965200000000022,True
+3883,CHEMBL2336361,10020.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1ccc(F)cc1,4.999132278468774,241.090292224,1,1,3.4776000000000016,True
+3884,CHEMBL47173,10100.0,nM,2018.0,O=C1Nc2ccccc2/C1=C/c1ccc(-c2cccs2)s1,4.995678626217358,309.0282059720001,3,1,4.969300000000001,True
+3885,CHEMBL307481,10100.0,nM,1991.0,O=[N+]([O-])/C=C/c1ccc(O)cc1,4.995678626217358,165.042593084,3,1,1.6395999999999997,True
+3886,CHEMBL3237939,10120.0,nM,2014.0,Cc1ccc(-n2nc(C)c(C3C(C#N)=C(N)N(c4cccnc4)C4=C3C(=O)CCC4)c2Cl)cc1,4.99481948749622,470.162187036,7,1,4.8423200000000035,True
+3887,CHEMBL1821880,10170.0,nM,2011.0,COc1ccc(C2CC(c3ccc(Br)cc3)=NN2c2nc(-c3ccccc3)cs2)cc1,4.992679047077256,489.0510453600001,5,0,6.936900000000007,True
+3888,CHEMBL1242027,10200.0,nM,2008.0,COc1cc(F)c(-c2nn(C(C)C)c3ncnc(N)c23)cc1F,4.991399828238082,319.12446654,6,1,2.9432,True
+3889,CHEMBL2283249,10230.0,nM,2013.0,CCOc1ccc(NC(=O)/C=C/c2ccccc2)cc1,4.99012436628784,267.125928784,2,1,3.7372000000000023,True
+3890,CHEMBL122785,10300.0,nM,1997.0,O=S(=O)(O)c1cc(NCc2cc(O)ccc2O)ccc1O,4.987162775294828,311.04635813600004,6,5,1.6621999999999997,True
+3891,CHEMBL473141,10320.0,nM,2009.0,CCOc1cc2nccc(Nc3cccc(Br)c3)c2cc1NC(=O)/C=C/CN1CCOCC1,4.9863203027088066,510.126652824,6,2,4.9665000000000035,True
+3892,CHEMBL116012,10320.0,nM,2003.0,CCOc1cc2ncc(C#N)c(Nc3cccc(Br)c3)c2cc1NC(=O)/C=C/CN1CCOCC1,4.9863203027088066,535.121901792,7,2,4.838180000000003,True
+3893,CHEMBL1828873,10340.0,nM,2011.0,O=C(Cc1ccc(Cl)cc1)NS(=O)(=O)c1ccc(Cl)cc1,4.985479461242076,342.98366957200005,3,1,3.0410000000000013,True
+3894,CHEMBL3234864,10350.0,nM,2014.0,Cc1ncc([N+](=O)[O-])n1CC(=O)N/N=C/c1cc2ccccc2nc1Oc1ccccc1,4.985059650207064,430.138953056,8,1,3.5905200000000024,True
+3895,CHEMBL153843,10400.0,nM,2002.0,O=C(Nc1cccc(C(F)(F)F)c1)c1ccccc1NCc1ccncc1,4.982966660701218,371.12454679200005,3,2,4.964800000000003,True
+3896,CHEMBL3325470,10400.0,nM,2014.0,Cc1ccc2c(c1)cc(C1C(C#N)=C(N)N(c3cccnc3)C3=C1C(=O)CCC3)c1nnnn12,4.982966660701218,448.17600726000006,9,1,3.285700000000001,True
+3897,CHEMBL1093100,10410.0,nM,2010.0,Cc1ccc(Sc2cccc3[nH]c4nc(N)nc(N)c4c23)cc1,4.982549270489463,321.10481648,5,3,3.73512,True
+3898,CHEMBL2159053,10490.0,nM,2012.0,COc1ccc(C2=NN(C(=O)c3ccc(Cl)cc3O)C(c3ccc(Cl)cc3)C2)cc1,4.979224511806442,440.06944779599996,4,1,5.699100000000005,True
+3899,CHEMBL1448,10500.0,nM,2010.0,O=C(Nc1ccc([N+](=O)[O-])cc1Cl)c1cc(Cl)ccc1O,4.978810700930062,325.986112096,4,2,3.859500000000001,True
+3900,CHEMBL498247,10500.0,nM,2000.0,CCC(C)[C@H]1[C@](C)(O)C(=O)[C@@]2(O)C[C@](C)(O)C[C@@H](C)[C@@H]2[C@]1(C)C(=O)/C=C/OC,4.978810700930062,396.25118887199994,6,3,2.2461,True
+3901,CHEMBL514771,10590.0,nM,2009.0,COc1cc2nccc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/C(C)N1CCOCC1,4.975104039892515,484.167746592,6,2,4.994900000000004,True
+3902,CHEMBL114073,10590.0,nM,2003.0,COc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/C(C)N1CCOCC1,4.975104039892515,509.16299556,7,2,4.8665800000000035,True
+3903,CHEMBL1173191,10640.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Br)c(Br)c2)CC1c1ccc([N+](=O)[O-])cc1,4.9730583720409705,481.90477082399997,4,1,4.514500000000003,True
+3904,CHEMBL3741762,10650.0,nM,2015.0,CN(C)C/C=C/C(=O)Nc1cccc(Nc2nc(N/N=C/c3ccc(F)cc3)ncc2Cl)c1,4.972650392225243,467.16366425600006,7,3,4.515000000000002,True
+3905,CHEMBL3746564,10690.0,nM,2016.0,CC(=O)N1N=C(c2ccc(I)cc2)CC1c1ccc(C(=O)OC(C)Cn2c([N+](=O)[O-])cnc2C)cc1,4.971022294791221,601.0822168679999,8,0,4.647420000000005,True
+3906,CHEMBL1958030,10690.0,nM,2012.0,COc1ccc(C2CC(c3ccc(F)cc3)=NN2C2=NC(=O)CS2)cc1,4.971022294791221,369.094725972,5,0,3.6148000000000025,True
+3907,CHEMBL55993,10700.0,nM,1991.0,Cc1cc(C)c(C(=O)/C(C#N)=C/c2ccc(O)c(O)c2)c(C)c1,4.97061622231479,307.120843404,4,2,3.812940000000003,True
+3908,CHEMBL592139,10780.0,nM,2010.0,O=C1CSC(N/N=C/c2cccc(Cl)c2)=N1,4.96738123914928,253.007660556,4,1,1.8929,True
+3909,CHEMBL1173713,10850.0,nM,2010.0,COc1ccc(/C=C/C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,4.964570261815452,331.11682064400003,7,0,2.3649200000000006,True
+3910,CHEMBL1257795,10900.0,nM,2010.0,N#Cc1ccc2c(c1)C(c1ccccc1F)=Nc1c[nH]nc1N2,4.962573502059376,303.09202354,4,2,3.646580000000001,True
+3911,CHEMBL1958027,10920.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(F)cc3)CC2c2ccc(Cl)cc2)=N1,4.961777361631282,373.04518893600005,4,0,4.259600000000003,True
+3912,CHEMBL3746268,10920.0,nM,2016.0,CC(=O)N1N=C(c2ccc(C)cc2)CC1c1ccc(C(=O)OCCn2c([N+](=O)[O-])cnc2C)cc1,4.961777361631282,475.1855689,8,0,3.962740000000003,True
+3913,CHEMBL1830262,10950.0,nM,2011.0,COc1cccc(/C=C/C(=N/NC(N)=S)c2ccccc2)c1,4.960585880823863,311.109233164,3,2,2.945900000000001,True
+3914,CHEMBL185327,11000.0,nM,2004.0,COc1cc2ncnc(Nc3cc(NC(=O)c4ccccc4)ccc3Cl)c2cc1OC,4.9586073148417755,434.114568148,6,2,5.296300000000003,True
+3915,CHEMBL1242470,11000.0,nM,2008.0,N#CCCCCn1nc(-c2ccc(F)c(O)c2)c2c(N)ncnc21,4.9586073148417755,326.1291373200001,7,2,2.6140799999999995,True
+3916,CHEMBL1242200,11000.0,nM,2008.0,COc1cc(Br)cc(-c2nn(C(C)C)c3ncnc(N)c23)c1,4.9586073148417755,361.0538222320001,6,1,3.427500000000001,True
+3917,CHEMBL3883652,11000.0,nM,2016.0,Cc1cccc(Nc2ccnc(Nc3ccc(N4CCN(C)CC4)cc3)n2)c1,4.9586073148417755,374.22189483200003,6,2,4.024020000000003,True
+3918,CHEMBL461782,11100.0,nM,2009.0,CCOC(=O)c1ccc(N2CCOCC2)c(NS(=O)(=O)c2cc(Br)c(Cl)s2)c1,4.9546770212133415,507.9529034559999,7,1,3.978100000000003,True
+3919,CHEMBL1928709,11220.0,nM,2012.0,COc1ccccc1CNc1ccc2ncnc(Nc3cccc(Br)c3)c2c1,4.9500071430798585,434.0742233280001,5,2,5.756600000000003,True
+3920,CHEMBL1821876,11240.0,nM,2011.0,Fc1ccc(C2CC(c3ccc(Br)cc3)=NN2c2nc(-c3ccccc3)cs2)cc1,4.949233688766958,477.0310588640001,4,0,7.0674000000000055,True
+3921,CHEMBL1173192,11270.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Br)c(Br)c2)CC1c1ccc(O)cc1,4.948076083953894,452.914607236,3,2,4.311900000000003,True
+3922,CHEMBL1828874,11290.0,nM,2011.0,O=C(Cc1ccc(Cl)cc1)NS(=O)(=O)c1ccc(Br)cc1,4.947306058075032,386.9331539920001,3,1,3.150100000000001,True
+3923,CHEMBL589825,11570.0,nM,2010.0,O=C(Nc1ccccc1F)c1ccc(N(CCCl)CCCl)cc1,4.936666641048251,354.07019674400004,2,1,4.362000000000003,True
+3924,CHEMBL2283251,11690.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1ccc(F)cc1F,4.93218548883816,259.080870412,1,1,3.6167000000000016,True
+3925,CHEMBL2047253,11700.0,nM,2012.0,Nc1nc2c(c(Nc3ccc(Cl)cc3F)n1)-c1ccccc1C2,4.931814138253839,326.073452284,4,2,4.166100000000002,True
+3926,CHEMBL3740257,11750.0,nM,2015.0,C=CC(=O)Nc1cccc(Nc2nc(N/N=C(\C)c3ccc(F)cc3F)ncc2Cl)c1,4.9299621333922445,442.11204328400004,6,3,5.112400000000003,True
+3927,CHEMBL1828870,11910.0,nM,2011.0,O=C(Cc1ccc(Cl)cc1)NS(=O)(=O)c1ccccc1,4.924088238517222,309.022641924,3,1,2.387600000000001,True
+3928,CHEMBL2426277,12000.0,nM,2013.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C)CC1,4.920818753952375,518.1945497840001,9,2,4.073200000000003,True
+3929,CHEMBL422531,12000.0,nM,1994.0,CN(C)C(=O)CCc1c(SSc2[nH]c3ccccc3c2CCC(=O)N(C)C)[nH]c2ccccc12,4.920818753952375,494.18101820000004,4,2,5.490200000000004,True
+3930,CHEMBL1241949,12000.0,nM,2008.0,CC(C)n1nc(-c2ccc3nc(N)ccc3c2)c2c(N)ncnc21,4.920818753952375,319.15454354400003,7,2,2.7867999999999995,True
+3931,CHEMBL1241773,12000.0,nM,2008.0,CC(=O)c1ccc(-c2nn(C(C)C)c3ncnc(N)c23)cc1,4.920818753952375,295.143310164,6,1,2859,True
+3932,CHEMBL91914,12000.0,nM,1996.0,O=[N+]([O-])c1ccc2c(Nc3ccccc3)ncnc2c1,4.920818753952375,266.08037556,5,1,3.281600000000001,True
+3933,CHEMBL1242380,12000.0,nM,2008.0,COc1ccc(-c2nn(C[C@H](C)CO)c3ncnc(N)c23)cc1OC,4.920818753952375,343.164439532,8,2,1.7210999999999999,True
+3934,CHEMBL1241675,12000.0,nM,2008.0,Nc1ncnc2c1c(-c1ccn3ccnc3c1)nn2C1CCCC1,4.920818753952375,319.15454354400003,7,1,2.838300000000001,True
+3935,CHEMBL1812491,12070.0,nM,2011.0,Cn1cccc1-c1nc2cc(NC(=O)CCl)ccc2[nH]1,4.91829272990265,288.07778871600004,3,2,2.745700000000001,True
+3936,CHEMBL1945445,12110.0,nM,2012.0,Cc1ccc(S(=O)(=O)NC(=O)c2cncc(Br)c2)cc1,4.916855856856948,353.967375312,4,1,2.2712200000000005,True
+3937,CHEMBL4083467,12120.0,nM,2017.0,Cc1nnc(-n2c(-c3ccccc3)nc3cc(Cl)ccc3c2=O)s1,4.916497380169734,354.034209652,6,0,3.8660200000000025,True
+3938,CHEMBL1830273,12240.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccccc1)c1ccc(Br)cc1,4.912218582190458,359.00918054799996,2,2,3.6998000000000024,True
+3939,CHEMBL3747570,12240.0,nM,2016.0,CC(=O)N1N=C(c2ccccc2)CC1c1ccc(C(=O)OC(C)Cn2c([N+](=O)[O-])cnc2C)cc1,4.912218582190458,475.1855689,8,0,4.042820000000003,True
+3940,CHEMBL1173251,12260.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Br)c(Br)c2)CC1c1ccccc1Cl,4.911509529817603,470.880720264,2,1,5.259700000000003,True
+3941,CHEMBL2336358,12290.0,nM,2013.0,Cc1ccccc1NC(=O)/C=C/c1ccccc1,4.910448117113546,237.1153641,1,1,3.6469200000000015,True
+3942,CHEMBL1929307,12320.0,nM,2012.0,COc1ccccc1-c1nnc(SCc2ccccc2)o1,4.909389292171594,298.07759868799997,5,0,4.037500000000002,True
+3943,CHEMBL1241677,12400.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2[C@@H]1CCNC1,4.906578314837764,330.09958678000004,7,3,1.9688999999999997,True
+3944,CHEMBL1241270,12400.0,nM,2008.0,Cc1ccc(-c2n[nH]c3ncnc(N)c23)cc1O,4.906578314837764,241.096359972,5,3,1.6161199999999998,True
+3945,CHEMBL1172951,12420.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1cccc(F)c1,4.905878404159439,319.096834148,6,0,2.49542,True
+3946,CHEMBL3088223,12450.0,nM,2013.0,Cc1ncc([N+](=O)[O-])n1C/C(=N/NC(=O)c1ccc(Cl)cc1)c1ccc(Br)cc1,4.904830648568245,475.00467912000005,6,1,4.349920000000003,True
+3947,CHEMBL55748,12500.0,nM,1991.0,N#CC(C#N)=C1C(=O)Nc2ccc(O)cc21,4.903089986991943,211.0381764,4,2,1.14506,True
+3948,CHEMBL337035,12500.0,nM,1994.0,CNC(=S)N(C)[C@H]1C[C@@H]2O[C@](C)([C@H]1OC)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4,4.903089986991943,539.199110788,6,2,4.570700000000003,True
+3949,CHEMBL118205,12500.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2nc3ccccc3o2)c1O,4.903089986991943,381.07832695999997,7,2,3.2265800000000016,True
+3950,CHEMBL201840,12600.0,nM,2006.0,COC(=O)c1c(OC)c2ccccc2c2oc3c(c12)C(=O)c1ccccc1C3=O,4.8996294548824375,386.07903816799995,6,0,4.156600000000004,True
+3951,CHEMBL1095465,12600.0,nM,2010.0,COc1ccc(OC)c(Cc2cc3c(Nc4cccc(Br)c4)nc(N)nc3[nH]2)c1,4.8996294548824375,453.0800369800001,6,3,4.654200000000002,True
+3952,CHEMBL1242288,12600.0,nM,2008.0,COc1ccc(-c2nn([C@@H]3CCNC3)c3ncnc(N)c23)cc1O,4.8996294548824375,326.149123816,8,3,1.3240999999999998,True
+3953,CHEMBL1929555,12620.0,nM,2012.0,Nc1nc(Nc2ccc(Cl)cc2)c2cc(Cc3cccc4ccccc34)[nH]c2n1,4.8989406450918835,399.125073256,4,3,5.681100000000003,True
+3954,CHEMBL1080506,12650.0,nM,2009.0,Cc1c(C(=O)NCCN2CCOCC2)[nH]c2cnnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c12,4.897909474488163,538.1895446560001,7,3,4.443420000000002,True
+3955,CHEMBL2336359,12690.0,nM,2013.0,Cc1ccc(NC(=O)/C=C/c2ccccc2)cc1,4.896538377905295,237.1153641,1,1,3.6469200000000015,True
+3956,CHEMBL1641994,12800.0,nM,2011.0,CCOC(=O)Nc1ccc2c(C#N)cnc(Nc3cccc(Br)c3)c2c1,4.892790030352131,410.03783782,5,2,5.180980000000003,True
+3957,CHEMBL2426286,12800.0,nM,2013.0,C=CC(=O)Nc1ccc(OC)c(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c1,4.892790030352131,420.1101514640001,7,2,4.321400000000002,True
+3958,CHEMBL1254364,12800.0,nM,2010.0,Cc1ccccc1Cc1cc2c(Nc3cccc(Br)c3)nc(N)nc2n1C,4.892790030352131,421.0902077400001,5,2,4.955820000000004,True
+3959,CHEMBL2335018,12800.0,nM,2013.0,CC(C)(C)C(=O)Nc1nc(Nc2cccc(C(F)(F)F)c2)c2cc(CCc3ccccn3)[nH]c2n1,4.892790030352131,482.2041940800001,5,3,5.885100000000005,True
+3960,CHEMBL1242030,12800.0,nM,2008.0,CC(C)n1nc(-c2ccc(NS(C)(=O)=O)cc2)c2c(N)ncnc21,4.892790030352131,346.12119481600007,7,2,2.0279,True
+3961,CHEMBL2283253,12880.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1cc(F)c(F)c(F)c1,4.890084136976206,277.0714486,1,1,3.7558000000000016,True
+3962,CHEMBL365805,13000.0,nM,2005.0,C=CC(=O)Nc1cc2c(Nc3cccc(Br)c3)ncnc2cc1N1CCN(C)CC1,4.886056647693163,466.1116714560001,6,2,4.012200000000003,True
+3963,CHEMBL1240545,13000.0,nM,2008.0,CC(C)n1nc(-c2ccc(CC#N)cc2)c2c(N)ncnc21,4.886056647693163,292.143644512,6,1,2.72248,True
+3964,CHEMBL135861,13000.0,nM,1997.0,CNC(=O)c1c([Se][Se]c2[nH]c3ccccc3c2C(=O)NC)[nH]c2ccccc12,4.886056647693163,505.97601841600004,2,4,0.6426000000000013,True
+3965,CHEMBL170438,13200.0,nM,2001.0,Nc1ncnc2c1c(-c1ccccc1)cn2C(CO)Cc1ccc(O)cc1,4.87942606879415,360.15862588,6,3,3.1622000000000012,True
+3966,CHEMBL2283252,13230.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1cc(F)cc(F)c1,4.878440155812499,259.080870412,1,1,3.6167000000000025,True
+3967,CHEMBL408565,13300.0,nM,2007.0,O=C1Nc2ccccc2/C1=C/c1cc2c([nH]1)CCC(Br)C2,4.876148359032914,342.0367752,1,2,3.7596000000000025,True
+3968,CHEMBL344652,13350.0,nM,2003.0,CN(C)/N=N/c1ccc2ncnc(N(C)c3ccccc3)c2c1,4.874518734299406,306.159294576,5,0,3.958000000000003,True
+3969,CHEMBL1173324,13370.0,nM,2010.0,NC(=S)N1N=C(c2ccc(Br)c(Br)c2)CC1c1ccccc1F,4.873868592738017,454.910270804,2,1,4.745400000000003,True
+3970,CHEMBL594790,13400.0,nM,2009.0,CCCCC(Cc1coc2nc(N)nc(N)c12)c1ccccc1OC,4.872895201635194,340.189926008,6,2,3.912300000000001,True
+3971,CHEMBL168829,13400.0,nM,2001.0,Nc1ncnc2c1c(-c1ccccc1)cn2C1CCNC1,4.872895201635194,279.148395544,5,2,2.2149,True
+3972,CHEMBL309598,13500.0,nM,1989.0,N#CC(C#N)=C(O)c1cc(O)c(O)c(O)c1,4.8696662315049934,218.032756672,6,4,1.1196599999999999,True
+3973,CHEMBL590877,13530.0,nM,2010.0,O=C1CSC(N/N=C/c2cccc(F)c2)=N1,4.868702203402377,237.037211096,4,1,1.3786,True
+3974,CHEMBL472942,13570.0,nM,2009.0,COc1cc2nccc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CCOCC1,4.867420152340262,470.152096528,6,2,4.606400000000003,True
+3975,CHEMBL113996,13570.0,nM,2003.0,COc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CCOCC1,4.867420152340262,495.147345496,7,2,4.478080000000003,True
+3976,CHEMBL383030,13600.0,nM,2006.0,COC(=O)c1c(OCCCN(C)C)c2ccccc2c2oc3c(c12)C(=O)c1ccccc1C3=O,4.866461091629782,457.15253745599995,7,0,4.478500000000004,True
+3977,CHEMBL2336335,13710.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1ccc(Cl)cc1,4.862962545210487,257.060741684,1,1,3.991900000000003,True
+3978,CHEMBL1828871,13730.0,nM,2011.0,Cc1ccc(S(=O)(=O)NC(=O)Cc2ccc(Cl)cc2)cc1,4.8623294627632445,323.038291988,3,1,2.6960200000000007,True
+3979,CHEMBL1173014,13870.0,nM,2010.0,COc1cccc(/C=C/C(=O)OCCn2c([N+](=O)[O-])cnc2C)c1,4.857923538926714,331.11682064400003,7,0,2.3649199999999997,True
+3980,CHEMBL1928887,13880.0,nM,2012.0,COc1ccccc1CNc1ccc2ncnc(Nc3cccc(Cl)c3)c2c1,4.857610533881164,390.12473890800004,5,2,5.647500000000003,True
+3981,CHEMBL2283256,13930.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1cc(Cl)cc(Cl)c1,4.856048883576038,291.021769332,1,1,4.645300000000002,True
+3982,CHEMBL358092,14000.0,nM,1995.0,COC(=O)c1ccc(-c2ccc(-c3ccccc3)cc2O)cc1,4.853871964321762,304.109944372,3,1,4.512800000000004,True
+3983,CHEMBL47986,14000.0,nM,1989.0,O=CN/C=C/c1cc(O)ccc1O,4.853871964321762,179.058243148,3,3,0.8144999999999998,True
+3984,CHEMBL453336,14000.0,nM,2008.0,COc1cc(C2=C(c3cn(COCc4ccccc4)c4ccccc34)CNC2=O)cc(OC)c1OC,4.853871964321762,484.19982199599997,6,1,4.882000000000004,True
+3985,CHEMBL432416,14100.0,nM,1994.0,Nc1ccc(-c2cc(=O)c3cc(N)c(O)cc3o2)cc1,4.85078088734462,268.084792244,5,3,2.33,True
+3986,CHEMBL1958032,14210.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(Cl)cc3)CC2c2ccc(F)cc2)=N1,4.8474059220725305,373.04518893600005,4,0,4.259600000000003,True
+3987,CHEMBL171256,14400.0,nM,2001.0,COc1ccc(CC(CO)n2cc(-c3ccccc3)c3c(N)ncnc32)cc1,4.841637507904751,374.1742759440001,6,2,3.465200000000001,True
+3988,CHEMBL1828877,14530.0,nM,2011.0,O=C(Cc1ccc(Br)cc1)NS(=O)(=O)c1ccc(F)cc1,4.837734385701979,370.96270453200003,3,1,2.6358000000000006,True
+3989,CHEMBL1172950,14530.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1cccc([N+](=O)[O-])c1,4.837734385701979,346.091334168,8,0,2.26452,True
+3990,CHEMBL2283245,14580.0,nM,2013.0,CC(C)c1ccc(NC(=O)/C=C/c2ccccc2)cc1,4.836242476018044,265.146664228,1,1,4.4619000000000035,True
+3991,CHEMBL1830131,14590.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1cccc(Cl)c1,4.835944708106547,257.060741684,1,1,3.991900000000002,True
+3992,CHEMBL3237942,14700.0,nM,2014.0,Cc1ccc(-n2nc(C)c(C3C(C#N)=C(N)N(c4cccnc4)C4=C3C(=O)CC(C)(C)C4)c2Cl)cc1,4.832682665251824,498.193487164,7,1,5.478420000000005,True
+3993,CHEMBL589120,14720.0,nM,2010.0,CN(C(=O)c1ccc(N(CCCl)CCCl)cc1)c1ccccc1,4.832092189998519,350.09526861999996,2,0,4.247200000000004,True
+3994,CHEMBL119923,14800.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSCc2ccc(Cl)cc2)c1O,4.8297382846050425,388.064841084,5,2,3.879880000000003,True
+3995,CHEMBL1830268,14830.0,nM,2011.0,COc1ccc(/C=C/C(=N/NC(N)=S)c2ccccc2)cc1,4.828858848971619,311.109233164,3,2,2.9459000000000017,True
+3996,CHEMBL1240565,15000.0,nM,2008.0,Cn1nc(-c2cnc3[nH]ccc3c2)c2c(N)ncnc21,4.823908740944318,265.107593352,6,2,1.4887999999999997,True
+3997,CHEMBL62756,15000.0,nM,1997.0,Nc1ncnc2c1ncn2-c1ccccc1,4.823908740944318,211.08579528799999,5,1,1.3977,True
+3998,CHEMBL1241588,15000.0,nM,2008.0,CC(C)n1nc(-c2ccc3c(c2)OCCO3)c2c(N)ncnc21,4.823908740944318,311.13822478400004,7,1,2.4276,True
+3999,CHEMBL206483,15000.0,nM,2006.0,Cc1cccc(-n2ncc3c(NCc4ccc5c(c4)OCO5)ncnc32)c1,4.823908740944318,359.13822478400004,7,1,3.4647200000000016,True
+4000,CHEMBL3798658,15000.0,nM,2016.0,O=C(Nc1cccc(C(O)c2ccccc2)c1)c1cc2ccccc2[nH]1,4.823908740944318,342.13682781600005,2,3,4.501900000000003,True
+4001,CHEMBL1945647,15020.0,nM,2012.0,Cc1ccc(S(=O)(=O)NC(=O)c2ccc(C)nc2Cl)cc1,4.8233300673318515,324.033540956,4,1,2.4705400000000006,True
+4002,CHEMBL1093099,15070.0,nM,2010.0,Nc1nc(N)c2c(n1)[nH]c1cccc(Sc3ccccc3)c12,4.821886747685368,307.089166416,5,3,3.426700000000001,True
+4003,CHEMBL1097190,15120.0,nM,2010.0,Cl.NC1CCc2[nH]c3ccc(OCCc4ccc(O)cc4)cc3c2C1,4.8204482088348115,358.144805656,3,3,3.732800000000002,True
+4004,CHEMBL1080272,15140.0,nM,2009.0,O=C(NCCN1CCCC1)c1cc2cnnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2[nH]1,4.8198741248359465,508.178979972,6,3,4.898600000000004,True
+4005,CHEMBL3747407,15160.0,nM,2016.0,CCOc1ccc(C2=NN(C(C)=O)C(c3ccc(C(=O)OCCn4c([N+](=O)[O-])cnc4C)cc3)C2)cc1,4.819300798703965,505.19613358400005,9,0,4.053020000000003,True
+4006,CHEMBL1173397,15240.0,nM,2010.0,COc1ccc(C2CC(c3ccc(C)c(C)c3)=NN2C(C)=O)cc1,4.8170150329964185,322.16812794399993,3,0,4.009640000000003,True
+4007,CHEMBL85021,15300.0,nM,1998.0,CC(C)c1cc(/C=C2\C(=O)Nc3ccccc32)cc(C(C)C)c1O,4.8153085691824025,321.172878976,2,2,5.131700000000004,True
+4008,CHEMBL2316148,15300.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccc(Cl)cc3)C2=O)cc(OC)c1,4.8153085691824025,368.11792221199994,3,0,5.577200000000005,True
+4009,CHEMBL3740102,15320.0,nM,2015.0,C/C(=N\Nc1ncc(Cl)c(Nc2cccc(NC(=O)/C=C/CN(C)C)c2)n1)c1ccc(F)cc1,4.814741234703415,481.17931432000006,7,3,4.905100000000003,True
+4010,CHEMBL1172603,15560.0,nM,2010.0,CC(=O)N1N=C(c2ccc(C)c(C)c2)CC1c1ccc(F)cc1,4.80799040734633,310.148141448,2,0,4.140140000000003,True
+4011,CHEMBL2335014,15600.0,nM,2013.0,Nc1nc(Nc2ccc(F)c(C(F)(F)F)c2)c2cc(CCc3ccccn3)[nH]c2n1,4.806875401645539,416.1372573920001,5,3,4.621800000000002,True
+4012,CHEMBL1242658,15600.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2[C@@H]1CCNC1,4.806875401645539,314.12913732000004,7,3,1.4545999999999994,True
+4013,CHEMBL1945452,15680.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(Br)cc1)c1cccnc1Cl,4.804653941651581,373.91275289600003,4,1,2.616200000000001,True
+4014,CHEMBL2283257,15740.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1ccccc1Br,4.802995271976954,301.010226104,1,1,4.101000000000002,True
+4015,CHEMBL1828878,15920.0,nM,2011.0,O=C(Cc1ccc(Br)cc1)NS(=O)(=O)c1ccc(Cl)cc1,4.79805693659835,386.93315399200003,3,1,3.150100000000001,True
+4016,CHEMBL128000,16000.0,nM,2008.0,O=C(/C=C/c1ccc(O)c(O)c1)c1ccc(O)cc1O,4.795880017344076,272.068473484,5,4,2.4051000000000005,True
+4017,CHEMBL157021,16000.0,nM,1994.0,NC(=O)CCc1c(SSc2[nH]c3ccccc3c2CCC(N)=O)[nH]c2ccccc12,4.795880017344076,438.11841794400004,4,4,4.284400000000002,True
+4018,CHEMBL1173248,16140.0,nM,2010.0,CC(=O)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc(Cl)cc1,4.7920964696139485,366.009346076,2,0,5.344400000000004,True
+4019,CHEMBL2283255,16170.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1ccc(Cl)cc1Cl,4.791289980093598,291.021769332,1,1,4.645300000000002,True
+4020,CHEMBL324030,16300.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSC2=NCCS2)c1O,4.787812395596042,349.05548334,7,2,2.1290800000000005,True
+4021,CHEMBL431001,16300.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3cccc(C(=O)O)c3)c2c1C,4.787812395596042,282.111675688,4,3,3.016540000000001,True
+4022,CHEMBL2335016,16300.0,nM,2013.0,CC(C)(C)C(=O)Nc1nc(Nc2ccc(F)c(Cl)c2)c2cc(CCc3ccccn3)[nH]c2n1,4.787812395596042,466.16841528800006,5,3,5.658800000000005,True
+4023,CHEMBL2437470,16338.0,nM,2013.0,C=CC(=O)Nc1ccc(-n2c(=O)c(C)nc3cnc(Nc4ccc(OC)cc4)nc32)cc1,4.786801108276392,428.1596885,8,2,3.3608200000000013,True
+4024,CHEMBL3982602,16460.0,nM,2016.0,C=CC(=O)N1CCC(n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cc(C)ccc32)CC1,4.783570169123749,456.177310636,4,1,4.965320000000004,True
+4025,CHEMBL1929302,16630.0,nM,2012.0,c1ccc(CSc2nnc(-c3ccccc3)o2)cc1,4.779107750780482,268.067034004,4,0,4.028900000000003,True
+4026,CHEMBL3325480,16700.0,nM,2014.0,CCOC(=O)C1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2cc(Cl)ccc2n2nnnc12,4.777283528852417,515.1472652440001,10,1,3.670200000000002,True
+4027,CHEMBL1958026,16920.0,nM,2012.0,O=C1CSC(N2N=C(c3ccc(F)cc3)CC2c2ccc(F)cc2)=N1,4.771599641296995,357.07473947600005,4,0,3.745300000000003,True
+4028,CHEMBL309392,17000.0,nM,1991.0,C[C@@H](NC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1)C(=O)N[C@H](C)C(=O)NCCN,4.769551078621727,533.158033824,9,4,0.39960000000000206,True
+4029,CHEMBL1241583,17000.0,nM,2008.0,CC(C)n1nc(-c2cccc(CC#N)c2)c2c(N)ncnc21,4.769551078621727,292.143644512,6,1,2.72248,True
+4030,CHEMBL1242203,17000.0,nM,2008.0,COc1ccc(-c2nn(C3CNC3)c3ncnc(N)c23)cc1O,4.769551078621727,312.13347375199993,8,3,0.9339999999999995,True
+4031,CHEMBL1173680,17190.0,nM,2010.0,COc1ccc(C2CC(c3ccc(Cl)c(Cl)c3)=NN2C(C)=O)cc1,4.7647241233129485,362.058883112,3,0,4.699600000000004,True
+4032,CHEMBL1828879,17260.0,nM,2011.0,O=C(Cc1ccc(Br)cc1)NS(=O)(=O)c1ccc(Br)cc1,4.762959208620809,430.88263841200006,3,1,3.2592000000000017,True
+4033,CHEMBL1173105,17310.0,nM,2010.0,COc1cc(OC)cc(C2CC(c3ccc(C)c(C)c3)=NN2C(C)=O)c1,4.761702932124607,352.178692628,4,0,4.018240000000003,True
+4034,CHEMBL1830267,17390.0,nM,2011.0,Cc1ccc(/C=C/C(=N/NC(N)=S)c2ccccc2)cc1,4.759700417997288,295.114318544,2,2,3.2457200000000013,True
+4035,CHEMBL1956885,17420.0,nM,2012.0,Nc1nc(Nc2cccc(Br)c2)c2cc(Cc3ccc(Cl)cc3)[nH]c2n1,4.758951849328357,427.01993526000007,4,3,5.290400000000002,True
+4036,CHEMBL1173319,17490.0,nM,2010.0,CC(=O)N1N=C(c2ccc(C)c(C)c2)CC1c1ccc(C)cc1,4.757210190521325,306.17321332399996,2,0,4.309460000000003,True
+4037,CHEMBL348554,17500.0,nM,1995.0,CN(C)CCNC(=O)c1c(SSc2c(C(=O)NCCN(C)C)c3ccccc3n2C)n(C)c2ccccc12,4.7569619513137065,552.2341163920001,8,2,4.052200000000003,True
+4038,CHEMBL589847,17510.0,nM,2010.0,O=C(NCc1ccccc1)c1ccc(N(CCCl)CCCl)cc1,4.756713853916554,350.09526862,2,1,3.9006000000000025,True
+4039,CHEMBL1828875,17810.0,nM,2011.0,O=C(Cc1ccc(Br)cc1)NS(=O)(=O)c1ccccc1,4.7493360805367555,352.972126344,3,1,2.4967000000000006,True
+4040,CHEMBL511449,17900.0,nM,2009.0,NS(=O)(=O)c1ccc(Nc2nc3ncnc(Nc4ccc(N5CCOCC5)cc4)c3s2)cc1,4.747146969020106,483.11472953200007,10,3,3.057500000000001,True
+4041,CHEMBL132466,18000.0,nM,2002.0,COc1cc2cc3ncc(C#N)c(Nc4ccc(F)c(Cl)c4)c3cc2cc1OC,4.7447274948966935,407.08368262,5,1,5.812980000000003,True
+4042,CHEMBL1242469,18000.0,nM,2008.0,N#CCCCn1nc(-c2ccc(F)c(O)c2)c2c(N)ncnc21,4.7447274948966935,312.11348725600004,7,2,2.22398,True
+4043,CHEMBL1242209,18000.0,nM,2008.0,Cc1ccc2ccc(-c3nn(C(C)C)c4ncnc(N)c34)cc2n1,4.7447274948966935,318.159294576,6,1,3.513020000000001,True
+4044,CHEMBL1242381,18000.0,nM,2008.0,COc1ccc(-c2nn(C[C@@H](C)CO)c3ncnc(N)c23)cc1OC,4.7447274948966935,343.164439532,8,2,1.7210999999999999,True
+4045,CHEMBL1241774,18000.0,nM,2008.0,CC(C)n1nc(-c2ccc3nccnc3c2)c2c(N)ncnc21,4.7447274948966935,305.13889348000004,7,1,2.5995999999999997,True
+4046,CHEMBL3237938,18020.0,nM,2014.0,Cc1nn(-c2ccccc2)c(Cl)c1C1C(C#N)=C(N)N(c2cccnc2)C2=C1C(=O)CCC2,4.744245213356956,456.14653697200004,7,1,4.533900000000003,True
+4047,CHEMBL589413,18120.0,nM,2010.0,CCCCN(Cc1cccc(Cl)c1O)C(=S)Nc1ccccc1,4.741841806659206,348.106311972,2,2,5.044700000000005,True
+4048,CHEMBL1945645,18150.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(Cl)cc1)c1ccc(Cl)nc1,4.74112337062787,329.96326847600005,4,1,2.5071000000000003,True
+4049,CHEMBL595757,18200.0,nM,2009.0,COc1ccccc1C(Cc1coc2nc(N)nc(N)c12)C(C)C,4.739928612014925,326.174275944,6,2,3.3781000000000008,True
+4050,CHEMBL2437474,18280.0,nM,2013.0,COc1ccc(-n2c(=O)cnc3cnc(Nc4cccc(N)c4)nc32)cc1,4.738023808602186,360.13347375200004,8,2,2.5100999999999996,True
+4051,CHEMBL3325472,18300.0,nM,2014.0,N#CC1=C(N)N(c2cccnc2)C2=C(C(=O)CCC2)C1c1cc2cc(Cl)ccc2n2nnnc12,4.73754891026957,468.12138484400015,9,1,3.6306800000000026,True
+4052,CHEMBL3098313,18300.0,nM,2014.0,CN(C)S(=O)(=O)c1ccc(Nc2nc(Cl)nc3cc4c(cc23)OCO4)cc1,4.73754891026957,406.05025364,7,1,3.0058000000000007,True
+4053,CHEMBL1173249,18350.0,nM,2010.0,CC(=O)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc(F)cc1,4.736363931411892,350.038896616,2,0,4.830100000000003,True
+4054,CHEMBL1828876,18350.0,nM,2011.0,Cc1ccc(S(=O)(=O)NC(=O)Cc2ccc(Br)cc2)cc1,4.736363931411892,366.987776408,3,1,2.8051200000000014,True
+4055,CHEMBL1173816,18450.0,nM,2010.0,CC(=O)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc(Br)cc1,4.734003629504921,409.958830496,2,0,5.453500000000004,True
+4056,CHEMBL48760,18500.0,nM,1998.0,CC(C)c1ccc(/C=C2/C(=O)Nc3ccccc32)cc1,4.732828271596986,263.131014164,1,1,4.302700000000002,True
+4057,CHEMBL2316156,18600.0,nM,2013.0,COc1ccc(/C=C2\CCC/C(=C\c3cc(OC)cc(OC)c3)C2=O)cc1,4.730487055782084,364.16745924799994,4,0,4.932400000000005,True
+4058,CHEMBL118109,18600.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2nc3ccccc3s2)c1O,4.730487055782084,397.05548334,7,2,3.695080000000002,True
+4059,CHEMBL3982407,18670.0,nM,2016.0,COc1cc(/C=C2\CCCCC2=O)cc(OC)c1,4.728855682050922,246.125594436,3,0,3.2303000000000024,True
+4060,CHEMBL1829273,18720.0,nM,2011.0,O=C(Cc1cccc(Br)c1)NS(=O)(=O)c1ccc(F)cc1,4.727694155597914,370.96270453200003,3,1,2.6358000000000006,True
+4061,CHEMBL3133907,18900.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccccc3CC)c2c1,4.723538195826756,318.148061196,4,2,4.0603000000000025,True
+4062,CHEMBL2426290,19000.0,nM,2013.0,COc1ccc(NC(=O)/C=C/CN(C)C)cc1Nc1ncc(F)c(-c2cnn3ccccc23)n1,4.721246399047171,461.19755122800007,8,2,3.738900000000002,True
+4063,CHEMBL87746,19000.0,nM,1998.0,COc1c(Br)cc(/C=C2\C(=O)Nc3ccccc32)cc1C(C)(C)C,4.721246399047171,385.06774098,2,1,5.247900000000004,True
+4064,CHEMBL1241271,19000.0,nM,2008.0,Cc1ccc(-c2nn(C)c3ncnc(N)c23)cc1O,4.721246399047171,255.112010036,6,2,1.6265199999999997,True
+4065,CHEMBL2424676,19000.0,nM,2013.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C)CC1,4.721246399047171,484.23352213600003,9,2,3.4198000000000013,True
+4066,CHEMBL1830264,19120.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccc(F)cc1)c1ccccc1,4.718512112059919,299.089246668,2,2,3.0764000000000014,True
+4067,CHEMBL589832,19260.0,nM,2010.0,O=C(Nc1ccc([N+](=O)[O-])cc1)c1ccc(N(CCCl)CCCl)cc1,4.715343717211486,381.064696764,4,1,4.131100000000003,True
+4068,CHEMBL2335013,19300.0,nM,2013.0,Nc1nc(Nc2cccc(C(F)(F)F)c2)c2cc(CCc3ccccn3)[nH]c2n1,4.714442690992227,398.1466792040001,5,3,4.482700000000002,True
+4069,CHEMBL86326,19300.0,nM,1998.0,COc1ccc(/C=C2\C(=O)Nc3ccc(Cl)cc32)cc1C(C)(C)C,4.714442690992227,341.11825655999996,2,1,5.138800000000004,True
+4070,CHEMBL1171822,19320.0,nM,2010.0,CC(=O)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccc(C)cc1,4.713992877920527,346.06396849199996,2,0,4.999420000000004,True
+4071,CHEMBL591051,19320.0,nM,2010.0,O=C1CSC(N/N=C/c2cccc(O)c2)=N1,4.713992877920527,235.041547528,5,2,0.9451,True
+4072,CHEMBL592224,19410.0,nM,2010.0,Cc1cc(C)c(O)c(CN(Cc2ccc(F)cc2)C(=S)Nc2ccccc2)c1,4.711974464611637,394.1515125760001,2,2,5.547340000000005,True
+4073,CHEMBL2047242,19600.0,nM,2012.0,Nc1nc2c(c(Nc3cccc(Cl)c3)n1)-c1ccccc1C2,4.707743928643524,308.082874096,4,2,4.027000000000001,True
+4074,CHEMBL1821879,19640.0,nM,2011.0,Cc1ccc(C2CC(c3ccc(Br)cc3)=NN2c2nc(-c3ccccc3)cs2)cc1,4.706858516549068,473.05613074000007,4,0,7.236720000000006,True
+4075,CHEMBL1830130,19690.0,nM,2013.0,Cc1cccc(NC(=O)/C=C/c2ccccc2)c1,4.705754283861882,237.1153641,1,1,3.6469200000000015,True
+4076,CHEMBL1173022,19730.0,nM,2010.0,CC(=O)N1N=C(c2ccc(C)c(C)c2)CC1c1ccc(Cl)cc1,4.704872914747809,326.11859090800004,2,0,4.654440000000005,True
+4077,CHEMBL1956886,19770.0,nM,2012.0,Nc1nc(Nc2cccc(Br)c2)c2cc(Cc3ccc(Cl)c(Cl)c3)[nH]c2n1,4.703993330686329,460.98096290800004,4,3,5.943800000000001,True
+4078,CHEMBL1945453,19830.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(Cl)cc1)c1cccnc1Cl,4.702677285794698,329.96326847600005,4,1,2.5071000000000003,True
+4079,CHEMBL2335379,19900.0,nM,2013.0,C#Cc1cccc(Nc2nc(N)nc3[nH]c(CCc4ccccn4)cc23)c1,4.7011469235902945,354.159294576,5,3,3.4452000000000016,True
+4080,CHEMBL2426289,20000.0,nM,2013.0,COc1ccc(NC(=O)/C=C/CN(C)C)cc1Nc1nccc(-c2cnn3ccccc23)n1,4.698970004336019,443.2069730400001,8,2,3.599800000000002,True
+4081,CHEMBL501368,20000.0,nM,1992.0,N#C/C(=C\c1cc(O)ccc1O)C(=O)O,4.698970004336019,205.037507704,4,3,1.0893799999999998,True
+4082,CHEMBL488101,20000.0,nM,1992.0,C[C@H](NC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1)C(=O)N[C@@H](C)C(=O)NCCN.Cl,4.698970004336019,569.134711536,9,4,0.8214000000000006,True
+4083,CHEMBL4060383,20000.0,nM,2017.0,Nc1nc(N)c2c(n1)[nH]c1cccc(Sc3ccc4ccccc4c3)c12,4.698970004336019,357.10481648,5,3,4.579900000000001,True
+4084,CHEMBL1683957,20000.0,nM,2011.0,Cc1c(Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)ncnc1-c1ccccc1,4.698970004336019,419.12006812800007,4,1,6.5671200000000045,True
+4085,CHEMBL66101,20000.0,nM,1994.0,COc1ccc(/C=C/c2cnc3cc(OC)c(OC)cc3c2)cc1,4.698970004336019,321.136493468,4,0,4.431000000000004,True
+4086,CHEMBL520839,20000.0,nM,1992.0,CCOc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccc(C)cc2)c1O,4.698970004336019,368.1194635,5,2,3.7839000000000023,True
+4087,CHEMBL1173398,20040.0,nM,2010.0,CC(=O)N1N=C(c2ccc(C)c(C)c2)CC1c1ccccc1,4.698102282804792,292.15756325999996,2,0,4.001040000000003,True
+4088,CHEMBL1945444,20190.0,nM,2012.0,O=C(NS(=O)(=O)c1ccccc1)c1cncc(Br)c1,4.69486368105636,339.951725248,4,1,1.9628,True
+4089,CHEMBL1830265,20480.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccc(Cl)cc1)c1ccccc1,4.688670047696207,315.059696128,2,2,3.590700000000002,True
+4090,CHEMBL1241943,20500.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2CCC1CCCNC1,4.688246138944246,372.14653697200004,7,3,2.8242000000000003,True
+4091,CHEMBL1173023,20610.0,nM,2010.0,CC(=O)N1N=C(c2ccc(C)c(C)c2)CC1c1ccc(Br)cc1,4.685922008220787,370.068075328,2,0,4.763540000000004,True
+4092,CHEMBL1641991,20800.0,nM,2011.0,CCC(=O)Nc1ccc2c(C#N)cnc(Nc3cccc(Br)c3)c2c1,4.681936665037238,394.0429232000001,4,2,4.961080000000003,True
+4093,CHEMBL2316152,20800.0,nM,2013.0,COc1cc(/C=C2\CCC/C(=C\c3ccccc3OC)C2=O)cc(OC)c1,4.681936665037238,364.16745924799994,4,0,4.932400000000005,True
+4094,CHEMBL4096329,20800.0,nM,2017.0,COc1ccc(Sc2cccc3[nH]c4nc(N)nc(N)c4c23)cc1,4.681936665037238,337.09973110000004,6,3,3.4353,True
+4095,CHEMBL1172878,20810.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccccc1Cl,4.681727919788373,335.067283608,6,0,3.0097200000000015,True
+4096,CHEMBL79808,21000.0,nM,1994.0,COC(=O)CCc1c(SSc2[nH]c3ccccc3c2CCC(=O)OC)[nH]c2ccccc12,4.6777807052660805,468.11774924799994,6,2,5.659800000000004,True
+4097,CHEMBL3736121,21000.0,nM,2015.0,CO[C@H]1CCN(c2nccc(Nc3cc4c(cn3)nc([C@@H](C)O)n4[C@H](C)C(F)(F)F)n2)C[C@H]1F,4.6777807052660805,483.20058592000004,9,2,3.7047000000000017,True
+4098,CHEMBL459729,21000.0,nM,2008.0,Cc1cc(C2CCN(CCCF)CC2)cc2[nH]c(-c3c(NCCn4cc(Cl)cn4)cc[nH]c3=O)nc12,4.6777807052660805,511.2262645120001,6,3,4.727620000000003,True
+4099,CHEMBL1242661,21000.0,nM,2008.0,CCOc1ccc2cc(-c3nn(C)c4ncnc(N)c34)ccc2c1,4.6777807052660805,319.143310164,6,1,3.1644000000000005,True
+4100,CHEMBL3234867,21020.0,nM,2014.0,Cc1ncc([N+](=O)[O-])n1CC(=O)N/N=C/c1cc2ccccc2nc1Oc1ccc(F)cc1,4.677367288307776,448.129531244,8,1,3.7296200000000024,True
+4101,CHEMBL3628816,21180.0,nM,2015.0,Clc1ccc2c(c1)SCc1cnc(Nc3ccccc3)nc1-2,4.674074044228534,325.04404606400004,4,1,5.146300000000003,True
+4102,CHEMBL160207,21200.0,nM,1995.0,CN(C)C(=O)c1c(SSc2c(C(=O)N(C)C)c3ccccc3n2C)n(C)c2ccccc12,4.673664139071248,466.14971807200004,6,0,4.873000000000005,True
+4103,CHEMBL1829274,21280.0,nM,2011.0,O=C(Cc1cccc(Br)c1)NS(=O)(=O)c1ccc(Cl)cc1,4.672028376376988,386.93315399200003,3,1,3.150100000000001,True
+4104,CHEMBL3746387,21310.0,nM,2016.0,COc1ccc(C2=NN(C(C)=O)C(c3ccc(C(=O)OC(C)Cn4c([N+](=O)[O-])cnc4C)cc3)C2)cc1,4.671416550285798,505.19613358400005,9,0,4.051420000000003,True
+4105,CHEMBL1171638,21480.0,nM,2010.0,CC(=O)N1N=C(c2ccc(C)c(C)c2)CC1c1ccccc1Cl,4.667965722972482,326.118590908,2,0,4.654440000000004,True
+4106,CHEMBL1945646,21560.0,nM,2012.0,Cc1ccc(C(=O)NS(=O)(=O)c2ccccc2)c(Cl)n1,4.666351243485299,310.0178908920001,4,1,2.16212,True
+4107,CHEMBL3628817,21560.0,nM,2015.0,COc1ccc(Nc2ncc3c(n2)-c2ccc(Cl)cc2SC3)cc1,4.666351243485299,355.054610748,5,1,5.154900000000002,True
+4108,CHEMBL600048,21710.0,nM,2010.0,Cc1cccc(CN(Cc2ccc(F)cc2)C(=O)Nc2ccccc2)c1O,4.66334017654558,364.15870613199996,2,2,5.074020000000004,True
+4109,CHEMBL1828882,21840.0,nM,2011.0,COc1ccc(CC(=O)NS(=O)(=O)c2ccc(F)cc2)cc1,4.660747365967301,323.062757148,4,1,1.8819000000000001,True
+4110,CHEMBL155607,22000.0,nM,1994.0,NC(=O)CCC1C(S)=Nc2ccccc21,4.657577319177793,220.067034004,2,2,2.0090999999999997,True
+4111,CHEMBL486437,22000.0,nM,2008.0,COc1cc(C2=C(c3cn(COCC[Si](C)(C)C)c4ccccc34)CNC2=O)cc(OC)c1OC,4.657577319177793,494.2236987179999,6,1,5.020000000000004,True
+4112,CHEMBL605161,22000.0,nM,2011.0,O=[N+]([O-])c1ccc2c(c1)S(=O)(=O)N=S2c1ccc(Br)cc1,4.657577319177793,385.90306080400006,4,0,3.2795000000000014,True
+4113,CHEMBL1683952,22000.0,nM,2011.0,Fc1cccc(COc2ccc(Nc3cc(-c4ccsc4)ncn3)cc2Cl)c1,4.657577319177793,411.0608390000001,5,1,6.320200000000003,True
+4114,CHEMBL606027,22040.0,nM,2010.0,CCCCN(Cc1cccc(Br)c1O)C(=S)Nc1ccccc1,4.656788409820253,392.05579639200005,2,2,5.153800000000005,True
+4115,CHEMBL3961202,22310.0,nM,2016.0,C=CC(=O)N(C)c1cccc(-n2c(NC(=O)c3cccc(C(F)(F)F)c3)nc3cc(C)ccc32)c1,4.6515004297161635,478.161660572,4,1,5.753820000000005,True
+4116,CHEMBL1821881,22360.0,nM,2011.0,Oc1ccc(C2CC(c3ccc(Br)cc3)=NN2c2nc(-c3ccccc3)cs2)cc1,4.6505282007856135,475.0353952960001,5,1,6.633900000000006,True
+4117,CHEMBL1830257,22360.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccccc1F)c1ccccc1,4.6505282007856135,299.089246668,2,2,3.0764000000000022,True
+4118,CHEMBL483108,22800.0,nM,2010.0,Nc1nc(Nc2ccc(F)c(Br)c2)c2cc(CCc3ccccc3)[nH]c2n1,4.642065152999546,425.06513586400007,4,3,4.970500000000003,True
+4119,CHEMBL504416,22800.0,nM,2008.0,Nc1nc(Nc2ccc(F)c(Cl)c2)c2cc(CCc3ccccc3)[nH]c2n1,4.642065152999546,381.11565144400004,4,3,4.861400000000002,True
+4120,CHEMBL590083,22810.0,nM,2010.0,CCCCNC(=O)c1ccc(N(CCCl)CCCl)cc1,4.641874714723351,316.11091868399996,2,1,3.5005000000000024,True
+4121,CHEMBL2426288,23000.0,nM,2013.0,COc1ccc(NC(=O)/C=C/CN(C)C)cc1Nc1ncc(Cl)c(-c2cnn3ccccc23)n1,4.638272163982408,477.16800068800006,8,2,4.253200000000002,True
+4122,CHEMBL529663,23000.0,nM,2008.0,COc1cc(C2=C(c3c[nH]c4ccccc34)CNC2=O)cc(OC)c1OC,4.638272163982408,364.14230711999994,4,2,3.234300000000001,True
+4123,CHEMBL3948546,23000.0,nM,2016.0,CC(C)c1ccccc1Nc1nc(N)nc2c1Cc1ccccc1-2,4.638272163982408,316.16879664,4,2,4.4970000000000026,True
+4124,CHEMBL2029693,23100.0,nM,2012.0,Cc1cccc(N2NC(=O)/C(=C/c3ccc(-c4ccccc4F)o3)C2=O)c1,4.636388020107856,362.10667055999994,3,1,3.855520000000003,True
+4125,CHEMBL3234865,23130.0,nM,2014.0,Cc1ccc(Oc2nc3ccccc3cc2/C=N/NC(=O)Cn2c([N+](=O)[O-])cnc2C)cc1,4.635824367229381,444.15460312,8,1,3.8989400000000023,True
+4126,CHEMBL1830129,23160.0,nM,2013.0,O=C(/C=C/c1ccccc1)Nc1ccccc1,4.635261444944602,223.099714036,1,1,3.3385000000000016,True
+4127,CHEMBL1830258,23270.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccccc1Cl)c1ccccc1,4.63320361671327,315.059696128,2,2,3.590700000000002,True
+4128,CHEMBL590568,23490.0,nM,2010.0,Cc1cccc(/C=N/NC2=NC(=O)CS2)c1,4.629116983222393,233.062282972,4,1,1.54792,True
+4129,CHEMBL1088348,23500.0,nM,2010.0,CC1=C(C(=O)Nc2ccc(C)cc2)C(c2ccc(O)cc2O)NC(NCc2ccccc2)=N1,4.628932137728262,442.2004906920001,6,5,4.109020000000003,True
+4130,CHEMBL4105434,23700.0,nM,2017.0,CCCCOC(=O)c1c(-c2ccccc2)nn2ccccc12,4.6252516539898965,294.136827816,4,0,3.9582000000000024,True
+4131,CHEMBL2426377,24000.0,nM,2013.0,COc1ccc(NC(=O)/C=C/CN(C)C)cc1Nc1ncc(C)c(-c2cnn3ccccc23)n1,4.619788758288394,457.2226231040001,8,2,3.908220000000002,True
+4132,CHEMBL2047248,24100.0,nM,2012.0,Nc1nc2c(c(Nc3cccc(Br)c3)n1)-c1ccccc1C2,4.617982957425132,352.03235851600004,4,2,4.136100000000002,True
+4133,CHEMBL1172418,24150.0,nM,2010.0,CC(=O)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccccc1Cl,4.617082864912469,366.009346076,2,0,5.344400000000004,True
+4134,CHEMBL1828884,24150.0,nM,2011.0,COc1ccc(CC(=O)NS(=O)(=O)c2ccc(Br)cc2)cc1,4.617082864912469,382.98269102800003,4,1,2.505300000000001,True
+4135,CHEMBL334026,24200.0,nM,1997.0,Clc1cccc(Nc2[nH]nc3ncnc(Oc4cccc(Cl)c4)c23)c1,4.616184634019569,371.034065332,5,2,5.1956000000000016,True
+4136,CHEMBL1328065,24300.0,nM,2018.0,Oc1ccccc1-c1nc(NCc2cccnc2)c2ccccc2n1,4.614393726401689,328.132411132,5,2,4.009500000000003,True
+4137,CHEMBL1172947,24320.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccccc1Br,4.614036429399302,379.01676802800006,6,0,3.118820000000002,True
+4138,CHEMBL1829275,24330.0,nM,2011.0,O=C(Cc1cccc(Br)c1)NS(=O)(=O)c1ccc(Br)cc1,4.613857891069181,430.88263841200006,3,1,3.2592000000000017,True
+4139,CHEMBL131653,24400.0,nM,1994.0,COC(=O)c1cc(NCc2cc(O)ccc2O)ccc1O,4.6126101736612695,289.09502258,6,4,2.2021,True
+4140,CHEMBL591440,24650.0,nM,2010.0,CCCCN(Cc1cc(Cl)cc(Cl)c1O)C(=S)Nc1ccccc1,4.608183076386752,382.06733962000004,2,2,5.698100000000004,True
+4141,CHEMBL1829271,24680.0,nM,2011.0,O=C(Cc1cccc(Br)c1)NS(=O)(=O)c1ccccc1,4.607654844638796,352.972126344,3,1,2.4967000000000006,True
+4142,CHEMBL1916951,24830.0,nM,2012.0,Cc1ccc(S(=O)(=O)NC(=O)c2cccnc2)cc1,4.605023280445436,276.056863244,4,1,1.50872,True
+4143,CHEMBL4095623,25000.0,nM,2017.0,c1ccc(Cc2nnc(Cc3nc4ccccc4[nH]3)o2)cc1,4.6020599913279625,290.116761068,4,1,3.1275000000000013,True
+4144,CHEMBL73820,25000.0,nM,1989.0,N#C/C(=C\c1ccc(O)c(O)c1)C(=O)O,4.6020599913279625,205.037507704,4,3,1.0893799999999998,True
+4145,CHEMBL1173789,25000.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccccc1[N+](=O)[O-],4.6020599913279625,346.091334168,8,0,2.26452,True
+4146,CHEMBL119156,25000.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccccn2)c1O,4.6020599913279625,341.08341234000005,6,2,2.4803800000000016,True
+4147,CHEMBL1242207,25000.0,nM,2008.0,CC(C)n1nc(-c2ccc3cnccc3c2)c2c(N)ncnc21,4.6020599913279625,304.143644512,6,1,3.2046,True
+4148,CHEMBL438075,25100.0,nM,2006.0,CC(=O)Nc1ccc(C#Cc2cncnc2Nc2ccc(OCc3cccc(F)c3)c(Cl)c2)cc1,4.600326278518962,486.12588178,5,2,5.949900000000003,True
+4149,CHEMBL1916949,25360.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(Cl)cc1)c1cccnc1,4.595850750790304,296.0022408280001,4,1,1.8537,True
+4150,CHEMBL1172602,25470.0,nM,2010.0,COc1cc(OC)cc(C2CC(c3ccc(Cl)c(Cl)c3)=NN2C(C)=O)c1,4.593971055036385,392.069447796,4,0,4.708200000000004,True
+4151,CHEMBL3746980,25580.0,nM,2016.0,CC(=O)N1N=C(c2ccc(C)cc2)CC1c1ccc(C(=O)OC(C)Cn2c([N+](=O)[O-])cnc2C)cc1,4.592099459857366,489.201218964,8,0,4.351240000000004,True
+4152,CHEMBL74645,25700.0,nM,1996.0,O=C(O)c1cccc(Nc2ncnc3[nH]c4c(c23)CCCC4)c1,4.590066876668706,308.127325752,4,3,3.278500000000002,True
+4153,CHEMBL2437475,25825.0,nM,2013.0,COc1ccc(-n2c(=O)cnc3cnc(Nc4ccc(N)cc4)nc32)cc1,4.587959669808342,360.13347375200004,8,2,2.5101000000000004,True
+4154,CHEMBL1946843,25900.0,nM,2012.0,CN(C)c1nc(N/N=C/c2cc(Br)c(O)c(Br)c2O)nc(Nc2ccc(F)cc2)n1,4.586700235918748,538.971625172,9,4,4.202500000000002,True
+4155,CHEMBL2047247,26000.0,nM,2012.0,Nc1nc2c(c(Nc3ccc(Cl)cc3)n1)-c1ccccc1C2,4.585026652029182,308.082874096,4,2,4.027000000000001,True
+4156,CHEMBL1830259,26000.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccccc1Br)c1ccccc1,4.585026652029182,359.00918054799996,2,2,3.6998000000000024,True
+4157,CHEMBL1242468,26000.0,nM,2008.0,C[C@@H](CN)n1nc(-c2ccc(F)c(O)c2)c2c(N)ncnc21,4.585026652029182,302.12913732000004,7,3,1.4399000000000002,True
+4158,CHEMBL56201,26000.0,nM,1991.0,CN1C(=O)C(=C(C#N)C#N)c2cc(O)ccc21,4.585026652029182,225.053826464,4,1,1.16936,True
+4159,CHEMBL1929314,26060.0,nM,2012.0,COc1cc(OC)cc(-c2nnc(SCc3ccccc3)o2)c1,4.584025588623434,328.088163372,6,0,4.046100000000003,True
+4160,CHEMBL1829272,26170.0,nM,2011.0,Cc1ccc(S(=O)(=O)NC(=O)Cc2cccc(Br)c2)cc1,4.5821962773601195,366.987776408,3,1,2.8051200000000014,True
+4161,CHEMBL1828880,26200.0,nM,2011.0,COc1ccc(CC(=O)NS(=O)(=O)c2ccccc2)cc1,4.581698708680253,305.07217896000003,4,1,1.7428000000000001,True
+4162,CHEMBL2437484,26283.0,nM,2013.0,COc1ccc(Nc2ncc3ncc(=O)n(-c4cccc(NC(=O)/C=C/CN(C)C)c4)c3n2)cc1,4.580325064946128,471.20188766000007,9,2,2.9842000000000013,True
+4163,CHEMBL1830266,26560.0,nM,2011.0,NC(=S)N/N=C(/C=C/c1ccc(Br)cc1)c1ccccc1,4.57577192930402,359.00918054799996,2,2,3.6998000000000024,True
+4164,CHEMBL2029698,26600.0,nM,2012.0,C=C(N/N=C/c1cn[nH]c1-c1ccccc1)[C@H](C)Cc1ccccc1,4.575118363368934,330.184446704,3,2,4.392700000000003,True
+4165,CHEMBL591050,26610.0,nM,2010.0,O=C1CSC(N/N=C/c2cccc([N+](=O)[O-])c2)=N1,4.5749551254486125,264.031711116,6,1,1.1477,True
+4166,CHEMBL1172877,26740.0,nM,2010.0,Cc1ncc([N+](=O)[O-])n1CCOC(=O)/C=C/c1ccccc1F,4.5728385970740355,319.096834148,6,0,2.49542,True
+4167,CHEMBL3745929,26920.0,nM,2016.0,CCOc1ccc(C2=NN(C(C)=O)C(c3ccc(C(=O)OC(C)Cn4c([N+](=O)[O-])cnc4C)cc3)C2)cc1,4.5699249444480605,519.211783648,9,0,4.441520000000004,True
+4168,CHEMBL306081,27000.0,nM,1997.0,Cc1[nH]c2ncnc(Nc3cccc(Cl)c3)c2c1C,4.568636235841012,272.082874096,3,2,3.9717400000000023,True
+4169,CHEMBL592240,27000.0,nM,2010.0,O=C1CSC(NN=C2CCCCCCC2)=N1,4.568636235841012,239.109233164,4,1,2.3057000000000007,True
+4170,CHEMBL1945450,27050.0,nM,2012.0,Cc1ccc(S(=O)(=O)NC(=O)c2cccnc2Cl)cc1,4.567832730557412,310.017890892,4,1,2.16212,True
+4171,CHEMBL122721,27200.0,nM,1997.0,CCCCCCCCCCCCCCNC(=O)c1cc(NCc2cc(O)ccc2O)ccc1O,4.565431095965801,470.31445782399993,5,5,6.846400000000009,True
+4172,CHEMBL1095445,27200.0,nM,2010.0,Nc1nc(Nc2cccc(C(F)(F)F)c2)c2cc(Cc3ccc(Cl)cc3Cl)[nH]c2n1,4.565431095965801,451.05783546800006,4,3,6.200100000000002,True
+4173,CHEMBL592210,27350.0,nM,2010.0,Cc1cc(C)c(O)c(CN(Cc2ccc(F)cc2)C(=O)Nc2ccccc2)c1,4.5630426693305495,378.174356196,2,2,5.382440000000004,True
+4174,CHEMBL498248,27500.0,nM,2000.0,CO[C@H](C)c1c(O)cc2c(c1O)C(=O)c1c(O)cc(O)cc1C2=O,4.560667306169737,330.073952788,7,4,1.9918000000000007,True
+4175,CHEMBL1945451,28660.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(F)cc1)c1cccnc1Cl,4.542723813938673,313.992819016,4,1,1.9928,True
+4176,CHEMBL1172419,28690.0,nM,2010.0,CC(=O)N1N=C(c2ccc(Cl)c(Cl)c2)CC1c1ccccc1,4.5422694517540005,332.04831842799996,2,0,4.691000000000003,True
+4177,CHEMBL279481,29000.0,nM,1999.0,O=C1NC(=O)c2c1c1c3cccc(O)c3[nH]c1c1[nH]c3c(O)cccc3c21,4.537602002101044,357.074955832,4,5,3.2504,True
+4178,CHEMBL187007,29000.0,nM,2004.0,COc1cc2ncnc(Nc3cc(NC(=O)c4cccc(N(C)C)c4)ccc3Cl)c2cc1OC,4.537602002101044,477.156767308,7,2,5.362300000000005,True
+4179,CHEMBL1242118,29000.0,nM,2008.0,CC(C)n1nc(-c2ccc3occc(=O)c3c2)c2c(N)ncnc21,4.537602002101044,321.12257472000005,7,1,2.7627999999999995,True
+4180,CHEMBL1945644,29070.0,nM,2012.0,O=C(NS(=O)(=O)c1ccc(Br)cc1)c1ccc(Cl)nc1,4.536554968229572,373.91275289600003,4,1,2.616200000000001,True
+4181,CHEMBL86531,29100.0,nM,2000.0,NS(=O)(=O)c1ccc2c(c1)/C(=C/c1[nH]c3c(c1CCC(=O)O)CCCC3)C(=O)N2,4.536107011014092,415.120191772,4,4,2.0508,True
+4182,CHEMBL187431,29400.0,nM,2004.0,Cc1ccc(Nc2ncnn3c(C)ccc23)cc1O,4.531652669587841,254.116761068,5,2,2.795340000000001,True
+4183,CHEMBL1910273,29500.0,nM,2011.0,Nc1scc2c1c(Nc1ccc(S(N)(=O)=O)cc1)nc1ncnc(N)c12,4.5301779840218375,387.05721465600016,9,4,1.7948999999999997,True
+4184,CHEMBL602645,29830.0,nM,2010.0,CCCN(CCC)C(=O)c1ccc(N(CCCl)CCCl)cc1,4.525346746637936,344.142218812,2,0,4.232800000000004,True
+4185,CHEMBL2283259,29850.0,nM,2013.0,CC(C)(C)NC(=O)/C=C/c1ccccc1,4.525055664534612,203.131014164,1,1,2.6145000000000005,True
+4186,CHEMBL2312645,30000.0,nM,2013.0,COc1ccccc1CNc1ncc(C(=O)NC2CCN(C)CC2)c(NC2CCCC2)n1,4.5228787452803365,438.27432432800003,7,3,3.275800000000001,True
+4187,CHEMBL2312646,30000.0,nM,2013.0,CN1CCC(NC(=O)c2cnc(NCc3cc(Cl)ccc3Cl)nc2NC2CCCC2)CC1,4.5228787452803365,476.18581494,6,3,4.574000000000003,True
+4188,CHEMBL2312649,30000.0,nM,2013.0,CN1CCC(NC(=O)c2cnc(Nc3cc(Cl)cc(Cl)c3)nc2NC2CCC(N(C)C)CC2)CC1,4.5228787452803365,519.2280141,7,3,4.6357000000000035,True
+4189,CHEMBL2312652,30000.0,nM,2013.0,CN1CCC(NC(=O)c2cnc(Nc3cc(Cl)cc(Cl)c3)nc2N[C@@H]2COC[C@H]2O)CC1,4.5228787452803365,480.14434405199995,8,4,2.5226000000000006,True
+4190,CHEMBL2064388,30000.0,nM,2012.0,O=c1oc2cc3ncnc(Nc4ccccc4O)c3cc2n1CCCN1CCOCC1,4.5228787452803365,421.17500421600005,9,2,2.7092,True
+4191,CHEMBL2337371,30800.0,nM,2013.0,CC(C)(C)C(=O)Nc1nc(Nc2cccc(F)c2)c2c(n1)[nH]c1cccc(Cl)c12,4.511449283499557,411.12621612800007,4,3,5.631800000000003,True
+4192,CHEMBL366831,31000.0,nM,2000.0,CNc1ncnc2c1c(-c1ccccc1)cn2-c1ccccc1,4.508638306165727,300.137496512,4,1,4.129200000000003,True
+4193,CHEMBL201865,31000.0,nM,2006.0,COC(=O)c1c(OCCN(C)C)c2ccccc2c2oc3c(c12)C(=O)c1ccccc1C3=O,4.508638306165727,443.13688739199995,7,0,4.088400000000004,True
+4194,CHEMBL589119,31180.0,nM,2010.0,CCCCN(CCCC)C(=O)c1ccc(N(CCCl)CCCl)cc1,4.506123889147177,372.17351894,2,0,5.013000000000005,True
+4195,CHEMBL1254363,31200.0,nM,2010.0,Cc1ccccc1Cc1cc2c(N(C)c3cccc(Br)c3)nc(N)nc2[nH]1,4.5058454059815585,421.0902077400001,4,2,4.969720000000003,True
+4196,CHEMBL592141,31250.0,nM,2010.0,COc1cccc(/C=N/NC2=NC(=O)CS2)c1,4.505149978319906,249.057197592,5,1,1.2480999999999998,True
+4197,CHEMBL589259,31430.0,nM,2010.0,CC(C)(C)NC(=O)c1ccc(N(CCCl)CCCl)cc1,4.50265561898242,316.11091868399996,2,1,3.4989000000000026,True
+4198,CHEMBL4068254,31800.0,nM,2017.0,c1ccc(-c2nnc(Cc3nc4ccccc4[nH]3)o2)cc1,4.497572880015566,276.101111004,4,1,3.2037000000000013,True
+4199,CHEMBL172517,31800.0,nM,2018.0,CCOc1cc(O)c2c(=O)cc(-c3ccccc3)oc2c1,4.497572880015566,282.089208928,4,1,3.564300000000002,True
+4200,CHEMBL589590,31940.0,nM,2010.0,CCCCN(Cc1cc(Br)cc(Br)c1O)C(=S)Nc1ccccc1,4.495665088197536,469.96630846,2,2,5.916300000000004,True
+4201,CHEMBL201511,32000.0,nM,2006.0,COc1cc(C2=C(c3c[nH]c4ccccc34)C(=O)NC2=O)cc(OC)c1OC,4.494850021680094,378.1215716759999,5,2,2.7609000000000004,True
+4202,CHEMBL1171273,32000.0,nM,2010.0,COc1ccccc1/C=C/C(=O)OCCn1c([N+](=O)[O-])cnc1C,4.494850021680094,331.11682064400003,7,0,2.3649199999999997,True
+4203,CHEMBL348116,32000.0,nM,1994.0,N#CCc1c(SSc2[nH]c3ccccc3c2CC#N)[nH]c2ccccc12,4.494850021680094,374.06598844800004,4,2,5.580760000000003,True
+4204,CHEMBL591706,32120.0,nM,2010.0,CCCCN(Cc1cccc(Cl)c1O)C(=O)Nc1ccccc1,4.493224463393356,332.129155592,2,2,4.879800000000005,True
+4205,CHEMBL3237941,32130.0,nM,2014.0,Cc1nn(-c2ccccc2)c(Cl)c1C1C(C#N)=C(N)N(c2cccnc2)C2=C1C(=O)CC(C)(C)C2,4.493089274448481,484.17783710000003,7,1,5.170000000000004,True
+4206,CHEMBL1828883,32850.0,nM,2011.0,COc1ccc(CC(=O)NS(=O)(=O)c2ccc(Cl)cc2)cc1,4.4834646261042,339.033206608,4,1,2.3962000000000003,True
+4207,CHEMBL1830260,33000.0,nM,2011.0,COc1ccccc1/C=C/C(=N/NC(N)=S)c1ccccc1,4.481486060122113,311.109233164,3,2,2.945900000000001,True
+4208,CHEMBL3353411,33000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2nccc(-c3c[nH]c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,4.481486060122113,485.2539232320001,7,3,4.499400000000003,True
+4209,CHEMBL1094784,33100.0,nM,2010.0,FC(F)(F)c1cccc(Nc2ncnc3[nH]c(Cc4ccc(Cl)cc4Cl)cc23)c1,4.480172006224281,436.046936436,3,2,6.617900000000002,True
+4210,CHEMBL4083493,33200.0,nM,2017.0,Clc1ccc2nc(Cc3nnc(-c4ccccc4Cl)o3)[nH]c2c1,4.478861916295964,344.0231663,4,1,4.510500000000001,True
+4211,CHEMBL2437477,33885.0,nM,2013.0,C=CC(=O)Nc1ccc(Nc2ncc3ncc(=O)n(-c4ccc(OC)cc4)c3n2)cc1,4.469992510023956,414.144038436,8,2,3.0524000000000013,True
+4212,CHEMBL3800448,34000.0,nM,2016.0,CC(O)c1cccc(NC(=O)c2cc3ccccc3[nH]2)c1,4.4685210829577455,280.121177752,2,3,3.4735000000000005,True
+4213,CHEMBL1242756,34000.0,nM,2008.0,Cn1nc(-c2ccc3ncccc3c2)c2c(N)ncnc21,4.4685210829577455,276.112344384,6,1,2.1606999999999994,True
+4214,CHEMBL1929312,34250.0,nM,2012.0,Cc1ccc(-c2nnc(SCc3ccccc3)o2)c(O)c1,4.465339424171557,298.07759868799997,5,1,4.042920000000001,True
+4215,CHEMBL3098318,34600.0,nM,2014.0,NS(=O)(=O)c1ccc(Nc2nc(Cl)nc3cc4c(cc23)OCO4)cc1,4.460923901207224,378.018953512,7,2,2.4029,True
+4216,CHEMBL3798556,35000.0,nM,2016.0,CC(O)c1ccc(NC(=O)c2cc3ccccc3[nH]2)cc1,4.455931955649723,280.121177752,2,3,3.4735000000000014,True
+4217,CHEMBL521155,35000.0,nM,2009.0,Nc1ncnc2c1ncn2CC(=O)c1c[nH]c2ccccc12,4.455931955649723,292.10725900399996,6,2,1.7727,True
+4218,CHEMBL76904,35000.0,nM,1989.0,N#CC(C#N)=Cc1ccc(O)c(O)c1,4.455931955649723,186.042927432,4,2,1.52836,True
+4219,CHEMBL589503,35290.0,nM,2010.0,O=C(NC1CCCC1)c1ccc(N(CCCl)CCCl)cc1,4.452348341640032,328.11091868399996,2,1,3.6430000000000025,True
+4220,CHEMBL1944923,35800.0,nM,2012.0,CC(=O)Nc1ccc(S(=O)(=O)Nc2nc3ccccc3nc2Nc2ccc(C(=O)O)cc2)cc1,4.4461169733561245,477.11068970800005,7,4,3.8308000000000018,True
+4221,CHEMBL118321,36000.0,nM,1993.0,COc1cc(C=C(C#N)C#N)cc(CSc2ccccc2C(=O)O)c1O,4.443697499232713,366.0674279279999,6,2,3.8218600000000023,True
+4222,CHEMBL589165,36000.0,nM,2010.0,O=C1CSC(NN=C2CCCCCC2)=N1,4.443697499232713,225.0935831,4,1,1.9156000000000002,True
+4223,CHEMBL3098319,36000.0,nM,2014.0,COc1cc2nc(Cl)nc(Nc3ccc(N(C)C)cc3)c2cc1OC,4.443697499232713,358.11965352799996,6,1,4.110000000000002,True
+4224,CHEMBL590962,36880.0,nM,2010.0,CCCCN(Cc1cccc(Br)c1O)C(=O)Nc1ccccc1,4.433209087618408,376.07864001200005,2,2,4.9889000000000046,True
+4225,CHEMBL76905,37000.0,nM,1989.0,N#CC(C#N)=Cc1cc(O)cc(O)c1,4.431798275933005,186.042927432,4,2,1.52836,True
+4226,CHEMBL119987,37000.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2ccccc2C(=O)O)c1O,4.431798275933005,384.07799261199995,6,3,2.783580000000001,True
+4227,CHEMBL524820,37500.0,nM,2000.0,C[C@@H](O)c1c(O)cc2c(c1O)C(=O)c1c(O)cc(O)cc1C2=O,4.425968732272281,316.058302724,7,5,1.3376999999999997,True
+4228,CHEMBL3098326,37600.0,nM,2014.0,COc1cc2nc(Cl)nc(Nc3ccc(NC(C)=O)cc3)c2cc1OC,4.424812155072338,372.098918084,6,2,4.0024000000000015,True
+4229,CHEMBL3799332,38000.0,nM,2016.0,O=C(Nc1ccc(C(O)c2ccccc2)cc1)c1cc2ccccc2[nH]1,4.420216403383191,342.13682781600005,2,3,4.501900000000003,True
+4230,CHEMBL1929304,38320.0,nM,2012.0,O=[N+]([O-])c1ccccc1-c1nnc(SCc2ccccc2)o1,4.4165744995934935,313.052112212,6,0,3.9371000000000027,True
+4231,CHEMBL1929306,38430.0,nM,2012.0,CCOc1ccccc1-c1nnc(SCc2ccccc2)o1,4.4153296155356525,312.09324875199997,5,0,4.427600000000003,True
+4232,CHEMBL2283258,38460.0,nM,2013.0,CCCCCCCCCCCCNC(=O)/C=C/c1ccccc1,4.4149907200975385,315.256214676,1,1,5.736900000000006,True
+4233,CHEMBL1828881,38520.0,nM,2011.0,COc1ccc(CC(=O)NS(=O)(=O)c2ccc(C)cc2)cc1,4.414313721547504,319.08782902400003,4,1,2.0512200000000003,True
+4234,CHEMBL4251297,38730.0,nM,2017.0,Oc1ccc(Nc2nnnc3sc4c(c23)CCC4)cc1,4.411952503013917,284.073182004,6,2,3.0242000000000013,True
+4235,CHEMBL2337364,38900.0,nM,2013.0,Nc1nc(Nc2ccc(Cl)cc2F)c2c(n1)[nH]c1cccc(Cl)c12,4.410050398674292,361.0297289,4,3,4.8828000000000005,True
+4236,CHEMBL2337368,39200.0,nM,2013.0,CC(C)c1ccc(Nc2nc(NC(=O)C(C)(C)C)nc3[nH]c4cccc(Cl)c4c23)cc1,4.406713932979542,435.182588132,4,3,6.616100000000005,True
+4237,CHEMBL4074782,39700.0,nM,2017.0,Cc1ccccc1-c1nnc(Cc2nc3ccccc3[nH]2)o1,4.401209493236885,290.11676106799996,4,1,3.5121200000000012,True
+4238,CHEMBL483234,40000.0,nM,1992.0,C[C@H](NC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1)C(=O)N[C@@H](C)C(=O)OC(C)(C)C,4.3979400086720375,547.162450508,9,2,2.6664000000000003,True
+4239,CHEMBL291313,40000.0,nM,1991.0,N#CC(C#N)=C1C(=O)Nc2ccc([N+](=O)[O-])cc21,4.3979400086720375,240.028339988,5,1,1.3476599999999999,True
+4240,CHEMBL312451,40000.0,nM,1991.0,C[C@@H](NC(=O)c1ccc(S(=O)(=O)Oc2ccc(/C=C/[N+](=O)[O-])cc2)cc1)C(=O)N[C@H](C)C(=O)OC(C)(C)C,4.3979400086720375,547.162450508,9,2,2.6664000000000003,True
+4241,CHEMBL498249,41000.0,nM,2000.0,CO[C@H](C)c1c(O)cc2c(c1O)C(=O)c1c(cc(O)c(O)c1O)C2=O,4.3872161432802645,346.06886740799996,8,5,1.6974000000000014,True
+4242,CHEMBL591053,41000.0,nM,2010.0,O=C1CSC(NN=C2CCCCC2)=N1,4.3872161432802645,211.077933036,4,1,1.5255,True
+4243,CHEMBL123046,41900.0,nM,1997.0,Oc1ccc(NCc2cc(O)ccc2O)cc1,4.377785977033705,231.089543276,4,4,2.4154999999999998,True
+4244,CHEMBL2337362,42000.0,nM,2013.0,CC(C)c1ccc(Nc2nc(N)nc3[nH]c4cccc(Cl)c4c23)cc1,4.376750709602098,351.125073256,4,3,5.213700000000003,True
+4245,CHEMBL2047245,42600.0,nM,2012.0,CC(C)c1ccc(Nc2nc(N)nc3c2-c2ccccc2C3)cc1,4.370590400897282,316.16879664,4,2,4.4970000000000026,True
+4246,CHEMBL591437,43210.0,nM,2010.0,CCCCN(Cc1cccc(C)c1O)C(=S)Nc1ccccc1,4.3644157336887694,328.160934388,2,2,4.699720000000005,True
+4247,CHEMBL3133912,43700.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(S(=O)(=O)Nc4nccs4)cc3)c2c1,4.359518563029578,452.07253037199996,8,3,3.755200000000001,True
+4248,CHEMBL327725,44000.0,nM,2003.0,CC(O)C(/N=C1/C=C(O)/C(=N\C(C(=O)O)C(C)O)C=C1O)C(=O)O,4.356547323513812,342.1063155359999,8,6,-0.5661999999999994,True
+4249,CHEMBL314146,44000.0,nM,1998.0,CCc1ccc(/C=C2\C(=O)Nc3ccccc32)s1,4.356547323513812,255.071785036,2,1,3.803200000000002,True
+4250,CHEMBL1242665,45000.0,nM,2008.0,CC(C)n1nc(-c2ccn3ccnc3c2)c2c(N)ncnc21,4.346787486224656,293.13889348000004,7,1,2.3041,True
+4251,CHEMBL59099,45000.0,nM,1997.0,NCCCNC(=O)c1cccc(Nc2nccc(-c3cccnc3)n2)c1,4.346787486224656,348.16985926000007,6,3,2.3607999999999993,True
+4252,CHEMBL4102214,45000.0,nM,2017.0,c1ccc(C(c2ccccc2)c2nnc(Cc3nc4ccccc4[nH]3)o2)cc1,4.346787486224656,366.148061196,4,1,4.716900000000003,True
+4253,CHEMBL4279863,45000.0,nM,2018.0,O=C(N/N=C/c1cccn1CCCN1CCCC1)Nc1ccc(Oc2ccnc3[nH]ccc23)cc1,4.346787486224656,471.23827316800003,6,3,4.798200000000004,True
+4254,CHEMBL3799956,45000.0,nM,2016.0,O=C(c1ccccc1)c1cccc(NC(=O)c2cc3ccccc3[nH]2)c1,4.346787486224656,340.12117775200005,2,2,4.651200000000003,True
+4255,CHEMBL4102942,45100.0,nM,2017.0,Clc1ccc(-c2nnc(Cc3nc4ccc(Cl)cc4[nH]3)o2)c(Cl)c1,4.345823458122039,377.98419394800004,4,1,5.163900000000002,True
+4256,CHEMBL3970063,45100.0,nM,2016.0,Nc1nc(Nc2cccc(Cl)c2)c2c(n1)-c1ccccc1C2,4.345823458122039,308.082874096,4,2,4.027000000000001,True
+4257,CHEMBL1641997,45200.0,nM,2011.0,N#Cc1cnc(Nc2cccc(Br)c2)c2cc(NC(=O)c3ccoc3)ccc12,4.3448615651886175,432.022187756,5,2,5.457880000000002,True
+4258,CHEMBL4238771,45500.0,nM,2018.0,Clc1ccc(SCc2n[nH]c(-c3ccc(Cl)cc3)n2)cc1,4.3419886033428865,335.005073712,3,1,5.070800000000003,True
+4259,CHEMBL1095463,45600.0,nM,2010.0,CC(C)c1ccc(Nc2nc(N)nc3[nH]c(Cc4ccc(Cl)cc4Cl)cc23)cc1,4.341035157335565,425.117401032,4,3,6.304700000000003,True
+4260,CHEMBL3628818,45700.0,nM,2015.0,Clc1ccc(Nc2ncc3c(n2)-c2ccc(Cl)cc2SC3)cc1,4.34008379993015,359.00507371200007,4,1,5.799700000000002,True
+4261,CHEMBL363607,45800.0,nM,2005.0,Cc1ccc(F)c(C(=O)n2nc(Nc3ccc(S(N)(=O)=O)cc3)nc2C)c1F,4.339134521996131,407.08636678,7,2,2.2526399999999995,True
+4262,CHEMBL3353406,46000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(C#N)c(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,4.337242168318426,524.264822264,9,2,4.381480000000003,True
+4263,CHEMBL4087921,46300.0,nM,2017.0,c1ccc(OCc2nnc(Cc3nc4ccccc4[nH]3)o2)cc1,4.334419008982047,306.111675688,5,1,3.1157000000000012,True
+4264,CHEMBL1683951,47000.0,nM,2011.0,Fc1cccc(COc2ccc(Nc3cc(-c4cccnc4)ncn3)cc2Cl)c1,4.327902142064284,406.09966703200007,5,1,5.653700000000003,True
+4265,CHEMBL157304,47000.0,nM,1994.0,N#CCCc1c(SSc2[nH]c3ccccc3c2CCC#N)[nH]c2ccccc12,4.327902142064284,402.09728857600004,4,2,6.360960000000005,True
+4266,CHEMBL76985,47000.0,nM,1989.0,N#C/C(=C\c1ccc(C=O)cc1)C(=O)O,4.327902142064284,201.042593084,3,1,1.49068,True
+4267,CHEMBL1077095,47900.0,nM,2010.0,CC1=C(C(=O)Nc2cccc([N+](=O)[O-])c2)C(c2ccc(O)cc2O)NC(NN)=N1,4.3196644865854354,398.1338676760001,9,6,1.3822999999999994,True
+4268,CHEMBL1910275,47900.0,nM,2011.0,Cc1c(C#N)c(NCCO)nc2nc(NCCO)nc(N)c12,4.3196644865854354,303.14437278400004,9,5,-0.4045000000000007,True
+4269,CHEMBL2029691,48600.0,nM,2012.0,O=C(Cc1ccc(F)cc1)Nc1cc(SC[C@@H](O)CO)cc([N+](=O)[O-])c1,4.313363730737707,380.084220864,6,3,2.3604000000000003,True
+4270,CHEMBL3799345,49000.0,nM,2016.0,O=C(c1ccccc1)c1ccc(NC(=O)c2cc3ccccc3[nH]2)cc1,4.309803919971486,340.12117775200005,2,2,4.651200000000003,True
+4271,CHEMBL278287,49000.0,nM,1996.0,Cc1ccc(N(C)C(=O)c2ccccc2)cc1Nc1nccc(-c2cccnc2)n1,4.309803919971486,395.17461029200007,5,1,4.867220000000004,True
+4272,CHEMBL299763,50000.0,nM,1997.0,COc1cc(OC)cc(-c2cc3cnc(N)nc3nc2NC(=O)NC(C)(C)C)c1,4.301029995663981,396.190988628,7,3,3.2112000000000016,True
+4273,CHEMBL3797839,50000.0,nM,2016.0,CC(=O)c1ccc(NC(=O)c2cc3ccccc3[nH]2)cc1,4.301029995663981,278.105527688,2,2,3.6228000000000016,True
+4274,CHEMBL57553,50000.0,nM,1997.0,Nc1cccc(Nc2nccc(-c3cccnc3)n2)c1,4.301029995663981,263.117095416,5,2,2.8644000000000007,True
+4275,CHEMBL490570,50000.0,nM,1992.0,CC(C)(C)c1cc(/C=C(\C#N)C(N)=O)cc(C(C)(C)C)c1O,4.301029995663981,300.18377800799993,3,2,3.3794800000000023,True
+4276,CHEMBL4095195,50000.0,nM,2017.0,Cc1ccccc1Cc1nnc(Cc2nc3ccccc3[nH]2)o1,4.301029995663981,304.132411132,4,1,3.435920000000002,True
+4277,CHEMBL8223,50000.0,nM,1994.0,CCN(CC)c1ccc(Nc2cc3c(cc2Nc2ccc(N(CC)CC)cc2)C(=O)NC3=O)cc1,4.301029995663981,471.26342529600004,6,3,5.749800000000005,True
+4278,CHEMBL4246256,52110.0,nM,2017.0,Oc1cccc(Nc2nnnc3sc4c(c23)CCC4)c1,4.283078926833238,284.073182004,6,2,3.0242000000000004,True
+4279,CHEMBL1254199,53100.0,nM,2010.0,CN(c1cccc(Br)c1)c1nc(N)nc2[nH]c(Cc3ccccc3)cc12,4.274905478918532,407.074557676,4,2,4.661300000000002,True
+4280,CHEMBL3133911,53300.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(S(=O)(=O)NC(=N)N)cc3)c2c1,4.2732727909734285,411.11135840400004,7,5,1.6696699999999998,True
+4281,CHEMBL3133906,53600.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(OC)cc3OC)c2c1,4.270835210307229,350.13789043599996,6,2,3.515100000000002,True
+4282,CHEMBL1242752,54200.0,nM,2008.0,CCOc1cc(-c2nn(C(C)C)c3ncnc(N)c23)ccc1OC,4.266000713461613,327.169524912,7,1,3.0637000000000008,True
+4283,CHEMBL77243,55000.0,nM,1989.0,CCCCc1cc(/C=C(\C#N)C(N)=O)cc(CCCC)c1O,4.259637310505756,300.18377800799993,3,2,3.4696800000000017,True
+4284,CHEMBL1094475,55200.0,nM,2010.0,C#Cc1cccc(Nc2nc(N)nc3[nH]c(Cc4ccc(Cl)cc4Cl)cc23)c1,4.2580609222708015,407.07045084,4,3,5.162600000000002,True
+4285,CHEMBL1087055,55600.0,nM,2010.0,CC1=C(C(=O)Nc2cccc([N+](=O)[O-])c2)C(c2ccc(O)cc2O)NC(SCc2ccccc2)=N1,4.254925208417943,490.131090804,8,4,4.852400000000003,True
+4286,CHEMBL1641996,55600.0,nM,2011.0,N#Cc1cnc(Nc2cccc(Br)c2)c2cc(NC(=O)c3ccco3)ccc12,4.254925208417943,432.022187756,5,2,5.457880000000002,True
+4287,CHEMBL602890,56000.0,nM,2010.0,COc1cc(/C=C2\SC(=N)NC2=O)ccc1OCCCOc1cc(C)cc(C)c1,4.251811972993798,412.14567824799997,6,2,4.298610000000004,True
+4288,CHEMBL1097368,56100.0,nM,2010.0,c1ccc(CCc2cc3c(Nc4ccc5[nH]ccc5c4)ncnc3[nH]2)cc1,4.251037138743839,353.1640456080001,3,3,4.9680000000000035,True
+4289,CHEMBL431996,56500.0,nM,2000.0,O=C(O)CCc1c(/C=C2\C(=O)Nc3ccc(C(=O)O)cc32)[nH]c2c1CCCC2,4.24795155218056,380.13722174000003,3,4,3.101600000000002,True
+4290,CHEMBL603198,56500.0,nM,2009.0,COc1ccccc1C(Cc1coc2nc(N)nc(N)c12)C1CC1,4.24795155218056,324.15862588,6,2,3.1321000000000003,True
+4291,CHEMBL3800262,57000.0,nM,2016.0,CC(=O)c1cccc(NC(=O)c2cc3ccccc3[nH]2)c1,4.2441251443275085,278.105527688,2,2,3.6228000000000007,True
+4292,CHEMBL2337369,58700.0,nM,2013.0,CC(C)(C)C(=O)Nc1nc(Nc2ccc(Cl)cc2)c2c(n1)[nH]c1cccc(Cl)c12,4.231361898752386,427.09666558800006,4,3,6.146100000000002,True
+4293,CHEMBL7699,58800.0,nM,1999.0,O=c1c(-c2cccc(Cl)c2)coc2cc(O)ccc12,4.230622673923862,272.02402182800006,3,1,3.819000000000001,True
+4294,CHEMBL56964,60000.0,nM,1991.0,COc1cc2c(cc1O)NC(=O)C2=C(C#N)C#N,4.221848749616356,241.048741084,5,2,1.1536599999999997,True
+4295,CHEMBL309625,60000.0,nM,1989.0,N#CC(C#N)=C(N)/C(C#N)=C/c1ccc(O)c([N+](=O)[O-])c1,4.221848749616356,281.054889084,7,2,1.4673399999999999,True
+4296,CHEMBL326044,60000.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSCCCC(=O)O)c1O,4.221848749616356,350.09364267599994,6,3,1.89108,True
+4297,CHEMBL311119,60000.0,nM,1989.0,N#CC(C#N)=Cc1ccc(C=O)cc1,4.221848749616356,182.048012812,3,0,1.9296599999999997,True
+4298,CHEMBL1084117,60900.0,nM,2010.0,CC1=C(C(=O)Nc2ccc(C)cc2)C(c2ccc(O)cc2O)NC(Nc2ccc([N+](=O)[O-])cc2Cl)=N1,4.215382707367125,507.13094648400005,8,5,4.992920000000004,True
+4299,CHEMBL4065301,61000.0,nM,2017.0,COc1cccc(-c2nnc(Cc3nc4ccccc4[nH]3)o2)c1OC,4.214670164989233,336.12224037199996,6,1,3.220900000000001,True
+4300,CHEMBL3098315,61500.0,nM,2014.0,COc1cc2nc(Cl)nc(Nc3ccc(S(C)(=O)=O)cc3)c2cc1OC,4.211124884224583,393.05500467199994,7,1,3.4475000000000025,True
+4301,CHEMBL2337363,63600.0,nM,2013.0,Nc1nc(Nc2ccc(Cl)cc2)c2c(n1)[nH]c1cccc(Cl)c12,4.196542884351587,343.03915071200004,4,3,4.7437000000000005,True
+4302,CHEMBL20926,65000.0,nM,1997.0,Cc1ccc(NC(=O)c2ccccc2)cc1Nc1nccc(-c2cccnc2)n1,4.187086643357143,381.15896022800007,5,2,4.842920000000003,True
+4303,CHEMBL2064400,65000.0,nM,2012.0,O=c1oc2cc3ncnc(NCc4ccccc4)c3cc2n1CCCN1CCOCC1,4.187086643357143,419.19573966,8,1,2.8721000000000014,True
+4304,CHEMBL4068814,65400.0,nM,2017.0,CC(=O)c1ccccc1-c1nnc(Cc2nc3ccccc3[nH]2)o1,4.184422251675732,318.111675688,5,1,3.4063000000000017,True
+4305,CHEMBL1910278,66100.0,nM,2011.0,Nc1scc2c1c(NCCO)nc1nc(NCCO)nc(N)c12,4.1797985405143585,335.11644378400007,10,6,0.2122999999999995,True
+4306,CHEMBL3098312,67200.0,nM,2014.0,COc1cc2nc(Cl)nc(Nc3ccc(S(=O)(=O)N(C)C)cc3)c2cc1OC,4.172630726946175,422.081553768,7,1,3.2943000000000016,True
+4307,CHEMBL154969,68000.0,nM,1994.0,CONC(=O)CCc1c(SSc2[nH]c3ccccc3c2CCC(=O)NOC)[nH]c2ccccc12,4.167491087293763,498.139547312,6,4,4.669000000000003,True
+4308,CHEMBL1956892,69200.0,nM,2012.0,COc1ccc(OC)c(Cn2ccc3c(Nc4cccc(Br)c4)nc(N)nc32)c1,4.1598939055432425,453.0800369800001,7,2,4.585100000000002,True
+4309,CHEMBL4094647,70000.0,nM,2017.0,Nc1ccc(O)c(-c2nnc(Cc3nc4ccccc4[nH]3)o2)c1,4.154901959985743,307.106924656,6,3,2.4915000000000003,True
+4310,CHEMBL78249,70000.0,nM,1995.0,N#CC(Cc1ccc(O)c(O)c1)C(=N)S,4.154901959985743,222.04629856,4,4,1.6871500000000001,True
+4311,CHEMBL1241775,70000.0,nM,2008.0,CC(C)n1nc(-c2cnc3nccnc3c2)c2c(N)ncnc21,4.154901959985743,306.13414244800003,8,1,1.9945999999999997,True
+4312,CHEMBL3353409,71000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(C)c(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,4.1487416512809245,513.28522336,8,2,4.818220000000004,True
+4313,CHEMBL2029697,72400.0,nM,2012.0,Cc1nn(C)cc1C(=O)Nc1ccn(Cc2c(F)cccc2Cl)n1,4.140261433802853,347.09491600000007,5,1,3.0181200000000015,True
+4314,CHEMBL4074726,73500.0,nM,2017.0,c1ccc(-c2nnc(Cc3nc4ccccc4[nH]3)o2)nc1,4.133712660915805,277.096359972,5,1,2.5987,True
+4315,CHEMBL2029690,74300.0,nM,2012.0,Cc1ccc(N2NC(=O)/C(=C\c3ccc(-c4cc([N+](=O)[O-])ccc4O)o3)C2=O)cc1C,4.129011186239425,419.11173526399995,6,2,3.6386400000000014,True
+4316,CHEMBL277430,75000.0,nM,1996.0,Cc1ccc(N(C(=O)c2ccccc2)C(=O)c2ccccc2)cc1Nc1nccc(-c2cccnc2)n1,4.1249387366083,485.18517497600016,6,1,6.077820000000005,True
+4317,CHEMBL76642,75000.0,nM,1989.0,N#C/C(=C/c1cc(O)ccc1O)C(=O)O,4.1249387366083,205.037507704,4,3,1.0893799999999998,True
+4318,CHEMBL331026,75000.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSc2nc3ccccc3[nH]2)c1O,4.1249387366083,380.094311372,6,3,2.9616800000000016,True
+4319,CHEMBL2064379,75000.0,nM,2012.0,Cc1cc(C)cc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)c1,4.1249387366083,433.211389724,8,1,3.620440000000002,True
+4320,CHEMBL520515,75000.0,nM,2009.0,Nc1ncnc2c1ncn2CC(=O)c1ccccc1,4.1249387366083,253.096359972,6,1,1.2914,True
+4321,CHEMBL414013,75000.0,nM,1995.0,COc1cc2c(cc1OC)Nc1ncnc(O)c1C2,4.1249387366083,259.095691276,6,2,1.8471999999999997,True
+4322,CHEMBL73625,75100.0,nM,1996.0,Cc1[nH]c2ncnc(Nc3ccccc3Cl)c2c1C,4.124360062995832,272.082874096,3,2,3.9717400000000023,True
+4323,CHEMBL1944928,76400.0,nM,2012.0,COc1ccc2c3oc(=O)cc(O)c3c(=O)n(C)c2c1,4.11690664142431,273.06372245200004,6,1,1.3590999999999998,True
+4324,CHEMBL3133910,76500.0,nM,2013.0,C=CC(=O)Nc1ccc2ncnc(Nc3ccc(S(N)(=O)=O)cc3)c2c1,4.116338564846382,369.08956034,6,3,2.1452999999999998,True
+4325,CHEMBL3335245,76700.0,nM,2014.0,CCOc1cc(Br)c(Br)c(/C=N/c2ccc3[nH]c(=O)[nH]c3c2)c1O,4.115204636051019,452.93236547600003,4,3,4.236100000000002,True
+4326,CHEMBL309937,77500.0,nM,1996.0,CCc1ccc(Nc2ncnc3[nH]c(C)c(C)c23)cc1,4.110698297493689,266.153146576,3,2,3.880740000000002,True
+4327,CHEMBL2064396,79000.0,nM,2012.0,CC(C)(C)c1ccc(Nc2ncnc3cc4oc(=O)n(CCCN5CCOCC5)c4cc23)cc1,4.102372908709558,461.242689852,8,1,4.3011000000000035,True
+4328,CHEMBL3805409,81200.0,nM,2016.0,Clc1cccc(C2CC(c3ccc4c(c3)OCCO4)=NN2c2ccccc2)c1,4.090443970758825,390.1135055280001,4,0,5.466900000000004,True
+4329,CHEMBL1944641,81600.0,nM,2012.0,Cc1ccc(-n2c(SCC(=O)Nc3ccccc3Cl)nc3sc(C)c(C)c3c2=O)cc1,4.088309841246139,469.06854656,6,1,5.756660000000004,True
+4330,CHEMBL485246,82000.0,nM,2009.0,Nc1ncnc2ncn(CC(=O)c3c[nH]c4ccccc34)c12,4.086186147616283,292.10725900399996,6,2,1.7726999999999995,True
+4331,CHEMBL2337366,82900.0,nM,2013.0,COc1cccc(Nc2nc(N)nc3[nH]c4cccc(Cl)c4c23)c1,4.081445469449727,339.088687748,5,3,4.098900000000001,True
+4332,CHEMBL2029695,83900.0,nM,2012.0,Cn1c(NCc2cccc(C(F)(F)F)c2)cc(=O)n(C)c1=O,4.0762380391713,313.10381134799997,5,1,1.7148999999999999,True
+4333,CHEMBL150177,84800.0,nM,1999.0,Cc1[nH]c(/C=C2\C(=O)Nc3ccc(S(N)(=O)=O)cc32)c(C)c1CCC(=O)O,4.071604147743286,389.104541708,4,4,1.7888400000000002,True
+4334,CHEMBL334032,85000.0,nM,1993.0,COc1cc(C=C(C#N)C#N)cc(CS(=O)(=O)c2ccc(C)cc2)c1O,4.070581074285707,368.08307799199997,6,1,3.1136800000000027,True
+4335,CHEMBL1944930,85600.0,nM,2012.0,O=c1c2c(-c3ccccc3)c3c(nc2nc2[nH]nc(S)n12)-c1ccccc1CC3,4.067526235322847,397.09973110000004,6,2,3.687100000000002,True
+4336,CHEMBL2335377,85900.0,nM,2013.0,Nc1nc(Nc2ccc(F)c(Br)c2)c2cc(CCc3ccccn3)[nH]c2n1,4.066006836168758,426.06038483200007,5,3,4.365500000000003,True
+4337,CHEMBL4087489,86200.0,nM,2017.0,C1=CC2=C(Cc3nnc(Cc4nc5ccccc5[nH]4)o3)CNC2C=C1,4.064492734175287,331.14331016400007,5,2,2.4736000000000002,True
+4338,CHEMBL3335244,88670.0,nM,2014.0,COc1cc(Br)c(Br)c(/C=N/c2ccc3[nH]c(=O)[nH]c3c2)c1O,4.052223291535261,438.91671541200003,4,3,3.8460000000000014,True
+4339,CHEMBL504135,89000.0,nM,2009.0,Nc1ncnc2c1ncn2CC(=O)c1ccccn1,4.050609993355088,254.09160894,7,1,0.6863999999999999,True
+4340,CHEMBL158119,89000.0,nM,1994.0,O=[N+]([O-])CCc1c(SSc2[nH]c3ccccc3c2CC[N+](=O)[O-])[nH]c2ccccc12,4.050609993355088,442.076947056,6,2,5.087000000000003,True
+4341,CHEMBL1947046,90400.0,nM,2012.0,COc1ccccc1Nc1ccnc(Nc2ccccc2OC)n1,4.043831569524636,322.142975816,6,2,3.9810000000000016,True
+4342,CHEMBL1094808,91700.0,nM,2010.0,Nc1nc(Nc2ccc(C(F)(F)F)c(F)c2)c2cc(Cc3ccc(Cl)cc3Cl)[nH]c2n1,4.037630664329979,469.0484136560001,4,3,6.339200000000002,True
+4343,CHEMBL1944931,92400.0,nM,2012.0,CCOC(=O)c1ccc(NC(=O)CSc2nnc(CNc3ccc(OC)cc3)n2-c2ccccc2)cc1,4.0343280287798935,517.1783753440001,9,2,4.795500000000004,True
+4344,CHEMBL501256,93000.0,nM,2009.0,Nc1ncnc2c1ncn2CC(=O)c1cccnc1,4.031517051446064,254.09160894,7,1,0.6864000000000001,True
+4345,CHEMBL1910268,93300.0,nM,2011.0,N#Cc1cc2c(N)ncnc2nc1NCCO,4.0301183562535,230.09160894,7,3,-0.11712000000000022,True
+4346,CHEMBL1087054,93500.0,nM,2010.0,CC1=C(C(=O)Nc2ccc(C)cc2)C(c2ccc(O)cc2O)NC(SCc2ccccc2)=N1,4.029188389127483,459.1616626600001,6,4,5.252620000000006,True
+4347,CHEMBL77085,96000.0,nM,1989.0,N#CC(C#N)=Cc1cc(O)ccc1[N+](=O)[O-],4.017728766960432,215.03309102,5,1,1.73096,True
+4348,CHEMBL10,96000.0,nM,1999.0,C[S+]([O-])c1ccc(-c2nc(-c3ccc(F)cc3)c(-c3ccncc3)[nH]2)cc1,4.017728766960432,377.0998113520001,3,1,4.6822000000000035,True
+4349,CHEMBL120719,96000.0,nM,1993.0,COc1cc(C=C(C#N)C#N)cc(CSCC(=O)O)c1O,4.017728766960432,304.051777864,6,2,2.1491599999999997,True
+4350,CHEMBL1095776,96400.0,nM,2010.0,CC(C)c1ccccc1Nc1nc(N)nc2[nH]c(Cc3ccc(Cl)cc3Cl)cc12,4.015922966097169,425.117401032,4,3,6.304700000000003,True
+4351,CHEMBL3902576,98800.0,nM,2016.0,Nc1nc(Nc2cccc(Br)c2)c2c(n1)-c1ccccc1C2,4.005243055412373,352.03235851600004,4,2,4.136100000000002,True
+4352,CHEMBL1956891,99900.0,nM,2012.0,Nc1nc(Nc2cccc(Br)c2)c2ccn(Cc3ccc(Cl)cc3)c2n1,4.000434511774018,427.01993526000007,5,2,5.221300000000002,True
+4353,CHEMBL1242846,100000.0,nM,2008.0,COc1ncc(-c2nn(C(C)C)c3ncnc(N)c23)c(OC)n1,4.0,315.144372784,9,1,1.4635999999999996,True
+4354,CHEMBL1242471,100000.0,nM,2008.0,CCOc1ccc(-c2n[nH]c3ncnc(N)c23)cc1OC,4.0,285.12257472,6,2,2.0094,True
+4355,CHEMBL1242844,100000.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2CC1CCNCC1,4.0,342.16043744800004,7,3,1.9197999999999995,True
+4356,CHEMBL1242845,100000.0,nM,2008.0,Cc1nn(-c2ccccc2)nc1Cn1nc(-c2ccc(F)c(O)c2)c2c(N)ncnc21,4.0,416.15093538400004,9,2,2.85762,True
+4357,CHEMBL1241299,100000.0,nM,2008.0,Cn1nc(-c2ccc(Br)c(O)c2)c2c(N)ncnc21,4.0,319.0068720400001,6,2,2.0805999999999996,True
+4358,CHEMBL1241482,100000.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(F)c(O)c1)nn2Cc1ocnc1-c1ccccc1,4.0,402.12405194,8,2,3.623500000000001,True
+4359,CHEMBL422540,100000.0,nM,1995.0,c1ccc(-c2c(SSc3[nH]c4ccccc4c3-c3ccccc3)[nH]c3ccccc23)cc1,4.0,448.10679064000004,2,2,8.7826,True
+4360,CHEMBL324371,100000.0,nM,1995.0,CN(c1ccccc1)c1ncnc2ccccc12,4.0,235.110947416,3,0,3.397700000000002,True
+4361,CHEMBL154911,100000.0,nM,1994.0,O=C(CCC1C(S)=Nc2ccccc21)NCc1ccccc1,4.0,310.113984196,2,2,3.840200000000002,True
+4362,CHEMBL1241772,100000.0,nM,2008.0,CC(C)n1nc(-c2ccc(C#N)nc2)c2c(N)ncnc21,4.0,279.12324341600004,7,1,1.9230799999999997,True
+4363,CHEMBL1241680,100000.0,nM,2008.0,CC(C)n1nc(-c2ccc(F)c(C#N)c2)c2c(N)ncnc21,4.0,296.118572636,6,1,2.66718,True
+4364,CHEMBL57690,100000.0,nM,1997.0,c1ccc(Nc2nccc(-c3cccnc3)n2)cc1,4.0,248.106196384,4,1,3.2822000000000013,True
+4365,CHEMBL299707,100000.0,nM,1997.0,COc1ccccc1C(=O)Nc1cccc(Nc2nccc(-c3cccnc3)n2)c1,4.0,397.15387484800004,6,2,4.5431000000000035,True
+4366,CHEMBL1241679,100000.0,nM,2008.0,CC(C)n1nc(-c2cccc(C#N)c2)c2c(N)ncnc21,4.0,278.127994448,6,1,2.52808,True
+4367,CHEMBL1241390,100000.0,nM,2008.0,CC(C)n1nc(-c2cccnc2)c2c(N)ncnc21,4.0,254.12799444799998,6,1,2.0514,True
+4368,CHEMBL1241391,100000.0,nM,2008.0,CC(C)n1nc(-c2cncnc2)c2c(N)ncnc21,4.0,255.12324341599998,7,1,1.4463999999999997,True
+4369,CHEMBL1241862,100000.0,nM,2008.0,CC(C)n1nc(-c2ccc(C(N)=O)c(Cl)c2)c2c(N)ncnc21,4.0,330.0995867800001,6,2,2.4087000000000005,True
+4370,CHEMBL1241582,100000.0,nM,2008.0,CC(C)n1nc(-c2cccc(CO)c2)c2c(N)ncnc21,4.0,283.143310164,6,2,2.1487,True
+4371,CHEMBL1242031,100000.0,nM,2008.0,CC(C)n1nc(-c2cccc(S(N)(=O)=O)c2)c2c(N)ncnc21,4.0,332.10554475200007,7,2,1.3038,True
+4372,CHEMBL1242032,100000.0,nM,2008.0,CC(C)n1nc(-c2ccc(S(N)(=O)=O)cc2)c2c(N)ncnc21,4.0,332.10554475200007,7,2,1.3038,True
+4373,CHEMBL1241859,100000.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc(Cl)c(O)c1)nn2CC1CCNCC1,4.0,358.13088690800004,7,3,2.4341,True
+4374,CHEMBL56081,100000.0,nM,1997.0,O=[N+]([O-])c1cccc(Nc2nccc(-c3cccnc3)n2)c1,4.0,293.09127459200005,6,1,3.1904000000000012,True
+4375,CHEMBL1241300,100000.0,nM,2008.0,COc1ccc(-c2n[nH]c3ncnc(N)c23)cc1O,4.0,257.091274592,6,3,1.3162999999999996,True
+4376,CHEMBL1241301,100000.0,nM,2008.0,COc1ccc(-c2nn(C)c3ncnc(N)c23)cc1O,4.0,271.106924656,7,2,1.3266999999999998,True
+4377,CHEMBL1241948,100000.0,nM,2008.0,CC(C)n1nc(-c2cccc(NS(C)(=O)=O)c2)c2c(N)ncnc21,4.0,346.12119481600007,7,2,2.0279,True
+4378,CHEMBL1242378,100000.0,nM,2008.0,C[C@H](CN)n1nc(-c2ccc(F)c(O)c2)c2c(N)ncnc21,4.0,302.12913732000004,7,3,1.4399000000000002,True
+4379,CHEMBL155389,100000.0,nM,1994.0,O=C(CC1C(S)=Nc2ccccc21)NCc1ccccc1,4.0,296.098334132,2,2,3.4501000000000017,True
+4380,CHEMBL3361128,100000.0,nM,2015.0,O=C1/C(=C\c2ccc(O)c(O)c2)Oc2ccccc21,4.0,254.0579088,4,2,2.7140000000000013,True
+4381,CHEMBL1241683,100000.0,nM,2008.0,CC(C)n1nc(-c2ccc3nc(Cl)ccc3c2)c2c(N)ncnc21,4.0,338.10467216000006,6,1,3.8580000000000014,True
+4382,CHEMBL27085,100000.0,nM,2002.0,Cc1nc(O)c2c(ccc3[nH]c(Nc4c(Cl)cccc4Cl)nc32)c1C,4.0,372.054466428,4,3,5.483940000000003,True
+4383,CHEMBL1242033,100000.0,nM,2008.0,CC(C)n1nc(-c2ccc3nccc(NC(=O)OC(C)(C)C)c3c2)c2c(N)ncnc21,4.0,419.2069730400001,8,2,4.551600000000002,True
+4384,CHEMBL1242034,100000.0,nM,2008.0,CC(C)n1nc(-c2ccc3nccc(N)c3c2)c2c(N)ncnc21,4.0,319.15454354400003,7,2,2.7868000000000004,True
+4385,CHEMBL1242119,100000.0,nM,2008.0,Nc1ncnc2c1c(-c1ccc3occc(=O)c3c1)nn2C1CCCC1,4.0,347.13822478400004,7,1,3.2970000000000015,True
+4386,CHEMBL543600,100000.0,nM,1995.0,CC(CN(C)C)C(=O)c1ccc(OS(=O)(=O)c2ccc(C(=O)O)cc2)cc1.Cl,4.0,427.08563610399995,6,1,2.954700000000001,True
+4387,CHEMBL1242208,100000.0,nM,2008.0,CC(C)n1nc(-c2ccc3ccncc3c2)c2c(N)ncnc21,4.0,304.143644512,6,1,3.2046,True
+4388,CHEMBL1241684,100000.0,nM,2008.0,CC(C)n1nc(-c2cc3cc(C=O)ccc3s2)c2c(N)ncnc21,4.0,337.0997311000001,7,1,3.683600000000002,True
+4389,CHEMBL1242663,100000.0,nM,2008.0,CC(C)n1nc(-c2cc3ccccc3nc2Cl)c2c(N)ncnc21,4.0,338.10467216000006,6,1,3.8580000000000014,True
+4390,CHEMBL1241682,100000.0,nM,2008.0,Cc1ccc2cc(-c3nn(C(C)C)c4ncnc(N)c34)ccc2n1,4.0,318.159294576,6,1,3.513020000000001,True
+4391,CHEMBL357400,102000.0,nM,1996.0,COc1cc(/C=C(\C#N)C(=O)NCCCCNC(=O)/C(C#N)=C/c2cc(Br)c(O)c(OC)c2)cc(Br)c1O,3.991399828238082,646.006258688,8,4,4.166760000000004,True
+4392,CHEMBL2335378,110600.0,nM,2013.0,Nc1nc(Nc2ccc(F)c(Cl)c2)c2cc(CCc3ccccn3)[nH]c2n1,3.9562448730313213,382.11090041200003,5,3,4.256400000000002,True
+4393,CHEMBL594810,111400.0,nM,2009.0,COc1ccccc1C(=Cc1coc2nc(=N)[nH]c(N)c12)C(C)C,3.9531148091622894,324.15862588,5,3,3.4227700000000016,True
+4394,CHEMBL1929554,112100.0,nM,2012.0,Nc1nc(Nc2ccc(Cl)cc2F)c2cc(Cc3cccc4ccccc34)[nH]c2n1,3.9503943874050265,417.11565144400004,4,3,5.820200000000003,True
+4395,CHEMBL1929556,112700.0,nM,2012.0,COc1ccc(OC)c(Cc2cc3c(Nc4ccc(Cl)cc4F)nc(N)nc3[nH]2)c1,3.948076083953893,427.1211307480001,6,3,4.684200000000002,True
+4396,CHEMBL1956889,113300.0,nM,2012.0,Cc1ccccc1Cn1ccc2c(Nc3cccc(Br)c3)nc(N)nc21,3.945770090136602,407.07455767600004,5,2,4.876320000000002,True
+4397,CHEMBL2337367,114700.0,nM,2013.0,CC(C)(C)C(=O)Nc1nc(Nc2ccccc2)c2c(n1)[nH]c1cccc(Cl)c12,3.940436582098732,393.13563794,4,3,5.492700000000003,True
+4398,CHEMBL482715,122000.0,nM,2008.0,Nc1nc(Nc2ccc(F)c(C(F)(F)F)c2)c2cc(CCc3ccccc3)[nH]c2n1,3.913640169325252,415.1420084240001,4,3,5.2268000000000026,True
+4399,CHEMBL308134,125000.0,nM,1989.0,N#CC(C#N)=Cc1ccc(O)c([N+](=O)[O-])c1,3.903089986991944,215.03309102,5,1,1.7309600000000003,True
+4400,CHEMBL424625,125000.0,nM,1993.0,COc1cc(/C=C(\C#N)C(N)=O)cc(CSCCC(=O)O)c1O,3.903089986991944,336.07799261199995,6,3,1.5009800000000002,True
+4401,CHEMBL2337372,130500.0,nM,2013.0,COc1cccc(Nc2nc(NC(=O)C(C)(C)C)nc3[nH]c4cccc(Cl)c4c23)c1,3.884389488325701,423.146202624,5,3,5.501300000000003,True
+4402,CHEMBL1254444,143500.0,nM,2010.0,COc1ccc(OC)c(Cc2cc3c(N(C)c4cccc(Br)c4)nc(N)nc3[nH]2)c1,3.843148098929989,467.09568704400016,6,2,4.678500000000002,True
+4403,CHEMBL3353404,145000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,3.8386319977650247,520.210199848,9,2,4.319200000000003,True
+4404,CHEMBL77298,153000.0,nM,1989.0,COc1cc(C=C(C#N)C#N)cc(Br)c1O,3.8153085691824016,277.969089564,4,1,2.5938600000000007,True
+4405,CHEMBL307179,160000.0,nM,1989.0,COc1cc(C=C(C#N)C#N)cc([N+](=O)[O-])c1O,3.7958800173440754,245.043655704,6,1,1.73956,True
+4406,CHEMBL6976,160000.0,nM,1995.0,COc1cc2c(cc1OC)Nc1ncn(C)c(=O)c1C2,3.7958800173440754,273.11134134,6,1,1.4452999999999996,True
+4407,CHEMBL595497,160300.0,nM,2009.0,CCCC(=Cc1coc2nc(=N)[nH]c(N)c12)c1ccccc1OC,3.795066477645856,324.15862588,5,3,3.5668700000000007,True
+4408,CHEMBL1095131,161600.0,nM,2010.0,Nc1nc(Nc2cccc(F)c2)c2cc(Cc3ccc(Cl)cc3Cl)[nH]c2n1,3.791558643561433,401.061029028,4,3,5.320400000000001,True
+4409,CHEMBL76602,165000.0,nM,1989.0,N#C/C(=C\c1ccc(O)cc1)C(=O)O,3.782516055786093,189.042593084,3,2,1.3837799999999998,True
+4410,CHEMBL1956888,166400.0,nM,2012.0,Nc1nc(Nc2cccc(Br)c2)c2ccn(Cc3ccccc3)c2n1,3.7788466780452947,393.05890761200004,5,2,4.5679000000000025,True
+4411,CHEMBL4088617,167300.0,nM,2017.0,Nc1nc(N)c2c(n1)[nH]c1cccc(Sc3cccc4ccccc34)c12,3.776504059037605,357.10481648,5,3,4.579900000000002,True
+4412,CHEMBL535,172100.0,nM,2010.0,CCN(CC)CCNC(=O)c1c(C)[nH]c(/C=C2\C(=O)Nc3ccc(F)cc32)c1C,3.76421912967244,398.211804324,3,3,3.3349400000000013,True
+4413,CHEMBL3805849,192000.0,nM,2016.0,Clc1ccc(C2CC(c3ccc4c(c3)OCCO4)=NN2c2ccccc2)cc1Cl,3.7166987712964503,424.07453317600005,4,0,6.120300000000004,True
+4414,CHEMBL477,195000.0,nM,1997.0,Nc1ncnc2c1ncn2[C@@H]1O[C@H](CO)[C@@H](O)[C@H]1O,3.7099653886374817,267.096753896,9,4,-1.9800000000000006,True
+4415,CHEMBL77869,200000.0,nM,1989.0,COc1cc(C=C(C#N)C#N)ccc1O,3.6989700043360183,200.058577496,4,1,1.8313599999999997,True
+4416,CHEMBL56281,225000.0,nM,1991.0,N#CC(C#N)=Cc1cccnc1,3.647817481888637,155.04834716,3,0,1.5121599999999997,True
+4417,CHEMBL310958,225000.0,nM,1989.0,N#CC(C#N)=NNc1ccc(O)cc1,3.647817481888637,186.054160812,5,2,1.20726,True
+4418,CHEMBL79064,230000.0,nM,1989.0,N#CC(C#N)=C(O)c1ccc(O)cc1,3.638272163982407,186.042927432,4,2,1.7084599999999999,True
+4419,CHEMBL3985894,232700.0,nM,2016.0,Nc1nc(Nc2ccccc2)c2c(n1)-c1ccccc1C2,3.6332036167132697,274.121846448,4,2,3.3736000000000015,True
+4420,CHEMBL26001,250000.0,nM,1991.0,O=P(O)(O)C(O)c1ccc2ccccc2c1,3.6020599913279625,238.03949546200002,2,3,2.008399999999999,True
+4421,CHEMBL77737,250000.0,nM,1989.0,N#CC(C#N)=Cc1ccncc1,3.6020599913279625,155.04834716,3,0,1.51216,True
+4422,CHEMBL1254286,253600.0,nM,2010.0,CN(c1cccc(Br)c1)c1nc(N)nc2c1cc(Cc1ccccc1)n2C,3.595850750790305,421.09020774000004,5,1,4.671700000000003,True
+4423,CHEMBL310514,260000.0,nM,1989.0,N#CC(C#N)=Cc1ccc[nH]1,3.585026652029182,143.04834716,2,1,1.4452599999999998,True
+4424,CHEMBL3734988,261000.0,nM,2015.0,C[C@@H](O)c1nc2cnc(Nc3ccnc(N4CC[C@H](O)[C@H](F)C4)n3)cc2n1[C@H](C)C(F)(F)F,3.5833594926617187,469.18493585600004,9,3,3.050600000000001,True
+4425,CHEMBL76979,264000.0,nM,1989.0,COc1cc(/C=C(\C#N)C(=O)O)cc(OC)c1O,3.5783960731301687,249.063722452,5,2,1.40098,True
+4426,CHEMBL2047241,276100.0,nM,2012.0,Nc1nc2c(c(Nc3ccc(F)cc3)n1)-c1ccccc1C2,3.558933593360737,292.112424636,4,2,3.5127000000000015,True
+4427,CHEMBL258726,320000.0,nM,2007.0,CC(C)(C)c1cc(C=C2C(=O)C=CC2=O)cc(C(C)(C)C)c1O,3.4948500216800937,312.17254462799997,3,1,4.078600000000004,True
+4428,CHEMBL307250,325000.0,nM,1989.0,COc1cc(/C=C(\C#N)C(=O)O)ccc1O,3.4881166390211256,219.053157768,4,2,1.39238,True
+4429,CHEMBL77814,350000.0,nM,1989.0,N#CC(C#N)=CNc1ccc(O)cc1,3.4559319556497243,185.058911844,4,2,1.7351599999999998,True
+4430,CHEMBL78005,350000.0,nM,1989.0,N#CC(C#N)=Cc1ccc2c(c1)OCO2,3.4559319556497243,198.042927432,4,0,1.84586,True
+4431,CHEMBL3353403,357000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CC[C@@H](N(C)C)C1,3.4473317838878064,532.210199848,9,2,4.461700000000003,True
+4432,CHEMBL122522,370000.0,nM,1993.0,COc1cc(C=C(C#N)C#N)cc(CSc2ccccc2)c1O,3.4317982759330046,322.07759868799997,5,1,4.123660000000004,True
+4433,CHEMBL310400,375000.0,nM,1989.0,N#CC(C#N)=Cc1cccc(O)c1,3.425968732272281,170.048012812,3,1,1.8227599999999997,True
+4434,CHEMBL449114,400000.0,nM,1992.0,N#CC(C#N)=C(C#N)c1cccc(O)c1,3.397940008672037,195.04326178,4,1,1.71654,True
+4435,CHEMBL78174,430000.0,nM,1989.0,N#CC(C#N)=Cc1ccc(C(=O)O)cc1,3.3665315444204134,198.042927432,3,1,1.81536,True
+4436,CHEMBL280074,440000.0,nM,2000.0,Cn1cnc2c(NCc3ccccc3)nc(NCCO)nc21,3.3565473235138117,298.154209196,7,3,1.3795999999999995,True
+4437,CHEMBL437612,440000.0,nM,2007.0,Cc1cc(C=C2C(=O)C=CC2=O)cc(C)c1O,3.3565473235138117,228.078644244,3,1,2.1004400000000003,True
+4438,CHEMBL77387,450000.0,nM,1989.0,N#CC(C#N)=Cc1ccc([N+](=O)[O-])c(O)c1,3.346787486224656,215.03309102,5,1,1.7309599999999998,True
+4439,CHEMBL311564,450000.0,nM,1989.0,COc1ccc(C(O)=C(C#N)C#N)cc1,3.346787486224656,200.058577496,4,1,2.0114600000000005,True
+4440,CHEMBL120667,450000.0,nM,1997.0,Cc1c(C)n(C)c2ncnc(Nc3cccc(Cl)c3)c12,3.346787486224656,286.09852416,4,1,3.982140000000003,True
+4441,CHEMBL77778,450000.0,nM,1989.0,N#CC(C#N)=Cc1ccc(/C=C/C(=O)O)cc1,3.346787486224656,224.058577496,3,1,2.2149599999999996,True
+4442,CHEMBL78150,460000.0,nM,1989.0,CC(C)(C)c1cc(C=C(C#N)C#N)cc(C(C)(C)C)c1O,3.3372421683184257,282.17321332399996,3,1,4.417760000000005,True
+4443,CHEMBL3353410,480000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C,3.3187587626244124,499.2695732960001,8,2,4.509800000000003,True
+4444,CHEMBL7981,500000.0,nM,1999.0,COc1cc(OC)c2c(=O)c(-c3cccc(Cl)c3)coc2c1,3.3010299956639813,316.05023657600003,4,0,4.130600000000002,True
+4445,CHEMBL306988,500000.0,nM,1989.0,CC(=C(C#N)C#N)c1ccc(NC(=O)CCC(=O)O)cc1,3.3010299956639813,283.095691276,4,2,2.3105600000000006,True
+4446,CHEMBL604879,529300.0,nM,2009.0,CCCCC(=Cc1coc2nc(=N)[nH]c(N)c12)c1ccccc1OC,3.2762981060087317,338.174275944,5,3,3.956970000000002,True
+4447,CHEMBL293482,532000.0,nM,1991.0,N#CC(C#N)=Cc1ncc[nH]1,3.274088367704952,144.043596128,3,1,0.8402599999999998,True
+4448,CHEMBL305695,560000.0,nM,1989.0,N#CC(C#N)=Cc1ccc(O)cc1,3.2518119729937998,170.048012812,3,1,1.82276,True
+4449,CHEMBL76082,560000.0,nM,1989.0,N#CC(C#N)=Cc1cc2c(cc1[N+](=O)[O-])OCO2,3.2518119729937998,243.02800564,6,0,1.7540600000000002,True
+4450,CHEMBL1242973,590000.0,nM,2000.0,COC(=O)[C@@]1(Cc2ccc(O)c(CC=C(C)C)c2)OC(=O)C(O)=C1c1ccc(O)cc1,3.229147988357856,424.1522031079999,7,3,3.5869000000000018,True
+4451,CHEMBL77825,600000.0,nM,1989.0,COc1ccc(NN=C(C#N)C#N)cc1,3.2218487496163566,200.069810876,5,1,1.5102599999999997,True
+4452,CHEMBL450319,600000.0,nM,1992.0,N#CC(C#N)=C(C#N)c1ccc(O)cc1,3.2218487496163566,195.04326178,4,1,1.7165399999999997,True
+4453,CHEMBL489349,600000.0,nM,1992.0,N#CC(C#N)=C(C#N)c1ccc(C=O)cc1,3.2218487496163566,207.04326178,4,0,1.82344,True
+4454,CHEMBL76557,625000.0,nM,1989.0,N#CCNC(=O)/C(C#N)=C/c1ccc(O)cc1,3.2041199826559246,227.069476528,4,2,0.93896,True
+4455,CHEMBL307248,640000.0,nM,1989.0,N#CC(C#N)=Cc1ccc(NC(=O)CCC(=O)O)cc1,3.1938200260161125,269.080041212,4,2,1.9204599999999998,True
+4456,CHEMBL3353412,786000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCNC,3.104577453960592,485.2539232320001,8,3,4.167600000000002,True
+4457,CHEMBL308048,800000.0,nM,1989.0,N#C/C(=C\c1ccc(O)cc1)C(N)=O,3.096910013008056,188.058577496,3,2,0.7844799999999998,True
+4458,CHEMBL57170,800000.0,nM,1991.0,COc1ccc(C=C(C#N)C#N)cc1F,3.096910013008056,202.054241064,3,0,2.2648600000000005,True
+4459,CHEMBL59150,820000.0,nM,1996.0,N#CC(C#N)=C(N)/C(C#N)=C/c1ccc2[nH]ccc2c1,3.0861861476162837,259.085795288,4,2,2.33484,True
+4460,CHEMBL78184,833000.0,nM,1989.0,N#C/C(=C\c1ccc(F)cc1)C(=O)O,3.0793549985932116,191.038256652,2,1,1.8172799999999998,True
+4461,CHEMBL77524,833000.0,nM,1989.0,COc1ccc(/C=C(\C#N)C(=O)O)cc1,3.0793549985932116,203.058243148,3,1,1.68678,True
+4462,CHEMBL77595,850000.0,nM,1989.0,N#C/C(=C\c1ccccc1)C(=O)O,3.0705810742857067,173.047678464,2,1,1.6781799999999996,True
+4463,CHEMBL421877,850000.0,nM,1989.0,COc1cc(C=C(C#N)C#N)cc(OC)c1O,3.0705810742857067,230.06914218,5,1,1.83996,True
+4464,CHEMBL1009,900000.0,nM,1989.0,N[C@@H](Cc1ccc(O)c(O)c1)C(=O)O,3.045757490560675,197.068807832,4,4,0.052200000000000135,True
+4465,CHEMBL489148,900000.0,nM,1992.0,COc1cc(C(C#N)=C(C#N)C#N)cc(OC)c1O,3.045757490560675,255.064391148,6,1,1.73374,True
+4466,CHEMBL3353405,938000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CC(N(C)C)C1,3.027797161620936,518.1945497840001,9,2,4.071600000000002,True
+4467,CHEMBL77197,1100000.0,nM,1989.0,COc1cc(/C(C)=C(\C#N)C(=O)O)ccc1O,2.958607314841774,233.068807832,4,2,1.78248,True
+4468,CHEMBL145,1200000.0,nM,1989.0,O=C(O)/C=C/c1ccc(O)c(O)c1,2.920818753952375,180.042258736,3,3,1.1956,True
+4469,CHEMBL292648,1200000.0,nM,1991.0,N#CC(C#N)=C1CCCc2c(O)cccc21,2.920818753952375,210.07931294,3,1,2.5292600000000007,True
+4470,CHEMBL57712,1300000.0,nM,1989.0,N#CC(C#N)=Cc1cc[n+]([O-])cc1,2.886056647693163,171.04326178,3,0,0.75056,True
+4471,CHEMBL309866,1300000.0,nM,1989.0,N#C/C(=C\c1ccc([N+](=O)[O-])cc1)C(=O)O,2.886056647693163,218.032756672,4,1,1.5863800000000001,True
+4472,CHEMBL77381,1360000.0,nM,1989.0,N#C/C(=C/c1ccc[nH]1)C(=O)O,2.8664610916297817,162.042927432,2,2,1.0062799999999998,True
+4473,CHEMBL308339,1400000.0,nM,1989.0,N#CC(C#N)=C1C(=O)NC(=O)NC1=O,2.853871964321762,190.012689924,5,2,-1.30384,True
+4474,CHEMBL57663,1400000.0,nM,1991.0,N#CC(C#N)=Cc1ccc(C#N)cc1,2.853871964321762,179.04834716,3,0,1.9888399999999997,True
+4475,CHEMBL298810,1480000.0,nM,1991.0,N#CC(C#N)=Cc1cc[nH]n1,2.8297382846050425,144.043596128,3,1,0.8402599999999998,True
+4476,CHEMBL308133,1500000.0,nM,1989.0,O=C(O)C(=Cc1ccc(O)cc1)C(=O)O,2.8239087409443187,208.037173356,3,3,0.9448000000000001,True
+4477,CHEMBL3353396,1600000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C(=O)[C@H](C)N)CC1,2.7958800173440754,575.2160135,10,3,3.3172000000000006,True
+4478,CHEMBL294681,1800000.0,nM,1991.0,C[S+]([O-])c1ccc(C=C(C#N)C#N)cc1,2.744727494896693,216.035733876,3,0,1.8545600000000002,True
+4479,CHEMBL294213,2200000.0,nM,1991.0,N#CC(C#N)=Cc1ccc2[nH]ccc2c1,2.6575773191777934,193.063997224,2,1,2.59846,True
+4480,CHEMBL75718,2400000.0,nM,1989.0,N#C/C=C/c1ccc(O)cc1,2.6197887582883936,145.052763844,2,1,1.9289799999999997,True
+4481,CHEMBL120564,2600000.0,nM,1993.0,COc1cc(C=C(C#N)C#N)cc(C)c1O,2.585026652029182,214.07422756,4,1,2.1397800000000005,True
+4482,CHEMBL66879,3000000.0,nM,1989.0,O=C(O)/C=C/c1ccc(O)cc1,2.5228787452803374,164.047344116,2,2,1.49,True
+4483,CHEMBL261238,5000000.0,nM,2007.0,CN(c1cccnc1)c1cc2c(Nc3ccc(F)c(Cl)c3)c(C#N)cnc2cn1,2.3010299956639813,404.09525034800004,6,1,5.200480000000003,True
+4484,CHEMBL3353398,5600000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C(=O)[C@H]2CCCCN2)CC1,2.2518119729937998,615.247313628,10,3,4.112100000000002,True
+4485,CHEMBL3353397,6060000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C(=O)[C@@H]2CCCCN2)CC1,2.217527375833714,615.247313628,10,3,4.112100000000002,True
+4486,CHEMBL76587,6500000.0,nM,1989.0,N#CC(C#N)Cc1ccc(O)cc1,2.1870866433571443,172.063662876,3,1,1.5980599999999998,True
+4487,CHEMBL3353399,7500000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C(=O)CNC)CC1,2.1249387366083,575.2160135,10,3,3.1894,True
+4488,CHEMBL3353402,9000000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C(=O)[C@@H](C)N)CC1,2.045757490560675,575.2160135,10,3,3.3172000000000006,True
+4489,CHEMBL3353395,10000000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C(=O)CN(C)C)CC1,2.0,589.231663564,10,2,3.531600000000002,True
+4490,CHEMBL3353401,10300000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C(=O)N2CCNCC2)CC1,1.9871627752948282,616.242562596,10,3,3.4686000000000012,True
+4491,CHEMBL3353400,11000000.0,nM,2014.0,C=CC(=O)Nc1cc(Nc2ncc(Cl)c(-c3cnn4ccccc34)n2)c(OC)cc1N1CCN(C(=O)[C@H](C)O)CC1,1.9586073148417744,576.2000290880001,10,3,3.3508000000000013,True
+4492,CHEMBL45068,25000000.0,nM,2006.0,O=C(CCc1ccc(O)cc1)c1c(O)cc(O)cc1O,1.6020599913279625,274.084123548,5,4,2.324500000000001,True
diff --git a/teachopencadd/talktorials/018_machine_learning_splitting_schemes/images/butina.png b/teachopencadd/talktorials/018_machine_learning_splitting_schemes/images/butina.png
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diff --git a/teachopencadd/talktorials/018_machine_learning_splitting_schemes/talktorial.ipynb b/teachopencadd/talktorials/018_machine_learning_splitting_schemes/talktorial.ipynb
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@@ -0,0 +1,3093 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# T018 · Performance of ligand-based machine learning methods for the classification of active/inactive compounds, considering various validation approaches\n",
+    "\n",
+    "Supervisior:\n",
+    "\n",
+    "* JProf. Dr. Andrea Volkamer; AG Volkamer:  Institut für Physiologie - Charité Universitätsmedizin\n",
+    "\n",
+    "\n",
+    "Author:\n",
+    "\n",
+    "* Hee-yeong Kim; WiSe20/21; Freie Universität Berlin; Bioinformatik (M.Sc.)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Aim of this project work\n",
+    "Currently, the application and evaluation of Machine Learning (ML) based approaches, especially in the field of CADD is still state-of-art (see [Mathai, Neann *et al.*, <i>IJMS</i> (2020), <b>21.10</b>, 3585](https://www.mdpi.com/1422-0067/21/10/3585), [Wang, Chen *et al.*, <i>Briefings in bioinformatics</i> (2019), <b>20.06</b>, 2066-2087](https://academic.oup.com/bib/article-abstract/20/6/2066/5066711), [Mathai, Neann *et al.*, <i>Briefings in bioinformatics</i> (2019), <b>21.3</b>,791-802](https://academic.oup.com/bib/article/21/3/791/5428023)).\n",
+    "\n",
+    "* Search for appropriate strategies for QSAR models applied on chemical compounds.\n",
+    "* Assess the performance and predictive power of ML-methods.\n",
+    "* Splitting schemes: cluster-based split approaches (see [Stahl, Martin *et al.*, <i>J. Chem. Inf. Model.</i> (2005), <b>45.3</b>, 542-548](https://pubs.acs.org/doi/abs/10.1021/ci050011h), [Martin, Eric J. *et al.*, <i>J. Chem. Inf. Model</i> (2017), <b>57.8</b>, 2077-2088](https://pubs.acs.org/doi/abs/10.1021/acs.jcim.7b00166), [Leonard, J. *et al.*, <i>QSAR and Combinatorial Science</i> (2006), <b>25.3</b>, 235-251](https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200510161), [Stanforth, Robert W. *et al.*, <i>QSAR and Combinatorial Science</i> (2007), <b>26.7</b>, 837-844](https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200630086), [He, Linnan *et al.*, <i>J. Mol. Graph</i> (2005), <b>23.6</b>, 503-523](https://www.sciencedirect.com/science/article/abs/pii/S1093326305000173)) and cross validation (CV) by random and time-split (see [Sheridan, Robert P., <i>J. Chem. Inf. Model</i> (2013), <b>53.4</b>, 783-790](https://pubs.acs.org/doi/abs/10.1021/ci400084k)).\n",
+    "* Compare the different splitting methods and observe the performance of the models based on some performance metrics."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "![Workflow](images/workflow.png)\n",
+    "*Figure 1:* \n",
+    "Workflow of this notebook. It can be mainly partitioned into data creation (left) and methods (right). The methods comprise the different model evaluation approaches and performance metrics."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Theory\n",
+    "\n",
+    "### Biological Background\n",
+    "#### Epidermal growth factor receptor (EGFR)\n",
+    "* Transmembrane glycoprotein is located at the cell surface and binds to the epidermal growth factor.\n",
+    "* Activated by binding to a ligand, which induces cell proliferation and prevents the apoptotic cell death. \n",
+    "* Mutations are associated with a number of cancers (non-small cell lung cancer (NSCLC) (40-80%), glioblastoma, head and neck cancer as well as breast cancer (25-30%), see [Herbst, Roy S., <i>IJROBP</i> (2004), <b>43</b>, S21-S26](https://www.sciencedirect.com/science/article/pii/S0360301604003311).\n",
+    "* Importance of its investigation for research and therapeutic issues.\n",
+    "\n",
+    "Computer-Aided Drug Design (CADD) uses computational approaches to discover, enhance, develop and analyze drugs and similar biologically active molecules. It can be described by three major approaches: ligand-based, structure-based and system-based drug discovery methods.\n",
+    "\n",
+    "* Ligand-based approach: Structural similar molecules have similar properties and thus similar biological activity.\n",
+    "* Prediction of active and inactive compounds (activation or inhibition of the target protein)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### Data Acquisition and preparation\n",
+    "For the data acquisition and filtering step, the preimplemented talktorials, [001_query_chembl](https://projects.volkamerlab.org/teachopencadd/talktorials/T001_query_chembl.html) and [002_compound_adme](https://projects.volkamerlab.org/teachopencadd/talktorials/T002_compound_adme.html), provided by the research group of [Volkamer Lab](https://projects.volkamerlab.org/teachopencadd/) were used. Talktorial [007_compound_activity_machine_learning](https://projects.volkamerlab.org/teachopencadd/talktorials/T007_compound_activity_machine_learning.html) is used as framework of this notebook and functions for Butina Clustering are taken from [005_compound_clustering](https://projects.volkamerlab.org/teachopencadd/talktorials/T005_compound_clustering.html).\n",
+    "\n",
+    "1. Choose the target data (EGFR Kinase: P00533) and fetch and download the bioactivity information and the compounds (ChEMBL ID, SMILES) from ChEMBL data base.\n",
+    "\n",
+    "Add \"document_year\" in the function from 001_query_cembl to fetch the publishing year of the compounds along with bioactivity data from ChEMBL:\n",
+    "\n",
+    "bioactivities = bioactivities_api.filter(\n",
+    "    target_chembl_id=chembl_id, type=\"IC50\", relation=\"=\", assay_type=\"B\").only(\n",
+    "    \n",
+    "    \"activity_id\",\n",
+    "    \"assay_chembl_id\",\n",
+    "    \"assay_description\",\n",
+    "    \"assay_type\",\n",
+    "    \"molecule_chembl_id\",\n",
+    "    \"type\",\n",
+    "    \"standard_units\",\n",
+    "    \"relation\",\n",
+    "    \"standard_value\",\n",
+    "    \"target_chembl_id\",\n",
+    "    \"target_organism\",\n",
+    "    \"document_year\"\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "2. Filter the compounds according to Lipinski's Rule of Five, to estimate the bioavailability of compounds solely based on their chemical structure.\n",
+    "3. Selected compounds as candidates for further investigation, if not more than one rule was violated.\n",
+    "\n",
+    "The final composed EGFR data set comprises following parameters for each compound:\n",
+    "\n",
+    "* CHEMBL-ID\n",
+    "* Publishing year\n",
+    "* SMILES representation (Simplified Molecular Input Line Entry Specification)\n",
+    "* pIC50 value: -log10(IC50), with IC50 = Concentration of a drug to inhibit a process by 50% (in vitro).\n",
+    "* Molecular weight\n",
+    "* Number of hydrogen bond acceptors (HBAs)\n",
+    "* Number of hydrogen bond donors (HBDs)\n",
+    "* log(p) (octanol-water coefficient): Used as measure of hydrophobicity.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### Molecule encoding\n",
+    "It is a crucial step in CADD to encode the molecules to an abstract and interpretable representation for the computer while keeping important information of certain structural properties. Usually, molecular fingerprints are used to describe small molecules and are represented by bit vectors, where each fingerprint bit corresponds to a fragment of the molecule.\n",
+    "\n",
+    "\n",
+    "![fingerprint vector](images/fp_.png)\n",
+    "*Figure 2:* \n",
+    "Examplary visualization of a molecular fingerprint as bit vector: each bit corresponds to a fragment of the molecules, encoded with 1 for its presence, otherwise 0. The figure is taken from: [ChemAxon](https://chemaxon.com/news/chemaxon-us-user-group-meeting-ugm-san-diego-september-24-25-2013).\n",
+    "\n",
+    "RDKit provides various functions generating [molecular fingerprints](https://www.rdkit.org/docs/GettingStartedInPython.html#fingerprinting-and-molecular-similarity). The method section here is done with MACCS only, a comparision of the ML-methods between MACCS and Morgan is withdrawable from 007.\n",
+    "\n",
+    "* **MACCS keys**: 166 bit structure fingerprints, where each bit corresponds to a predefined structural feature (substructure or fragment). \n",
+    "* **Morgan fingerprints or Extended-Connectivity Fingerprints (ECFPs)**: Circular topological fingerprints, generated by considering the “circular” environment of each atom up to a given radius or diameter (see [here](https://chem.libretexts.org/Courses/Intercollegiate_Courses/Cheminformatics_OLCC_(2019)/6%3A_Molecular_Similarity/6.1%3A_Molecular_Descriptors) for a general overview of molecular descriptor types)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### Machine Learning (ML) Approaches\n",
+    "\n",
+    "In Machine Learning, supervised learning describes methods to learn the mapping function from the input to the output. The goal is to approximate the mapping function good enough, to predict for new input data the output variables with a specific accuracy.\n",
+    "\n",
+    "The here introduced ML-appraoches are commonly used in drug discovery, consisting of:\n",
+    "\n",
+    "* **Random Forest (RF)**: Classification method that randomly builds an ensemble of uncorrelated decision trees, aims to minimize the entropy in each split and predicts on the majority or mean occurance of a class. \n",
+    "\n",
+    "* **Support Vector Machine (SVM)**: A mathematical method to find a hyperplane in an n-dimensional space (n=#features) to separate data points with maximum margin, i.e the maximum distance between data points of both classes. Nonlinearly separable samples are projected onto another higher dimensional space by using different types of kernel functions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### Data Splitting Schemes\n",
+    "The use of Machine Learning methods to overcome financial restrictions, limited sources or more sophisticated problems in medicine and economy, increased over the last decades. Therefore more advanced techniques were developed with high performance, like CNNs but still represent an incomprehensible black box in their decision making process. This brought up the need for approaches to infer the performance of the models and assess their reliability and 'realistic' predictive power on new data.\n",
+    "\n",
+    "#### Role of Train/Test and Validation Set in ML\n",
+    "The data we want to predict on is usually divided in three parts:\n",
+    "\n",
+    "* Training Set: Train the model by fitting on the data.\n",
+    "\n",
+    "* Validation Set: Validation of the performance of the models is tested and used to adjust the model hyperparameters (e.g. number of layers in an NN).\n",
+    "\n",
+    "* Test Set: Evaluate the performance on unlabeled data to assess their true performance. Usually used to compare models.\n",
+    "\n",
+    "In our case, the role of validation and test sets are identical, since this project does not aim to compare the models itself but assess their performance depending on the data splitting scheme."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### Random Splitting Schemes\n",
+    "* **Single random Split**: As the name already implies, it splits the data into train and test set by a given percentage. Usually, a split of 80% for train and 20% for test is applied.\n",
+    "\n",
+    "* **k-fold Cross Validation (CV)**: The data is partitioned into k folds. In each of the k partitions, k-1 parts are used as training set, while the remaining k-th part serves as test set.\n",
+    "\n",
+    "![k-fold Cross Validation](images/cv.png)\n",
+    "*Figure 3:* \n",
+    "Example of internal data splitting for 5-fold Cross Validation. The figure is taken from: [Scikit-learn](https://scikit-learn.org/stable/modules/cross_validation.html)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### Time-based Splitting\n",
+    "* Type of Cross Validation to deal with time-related data (data is sorted by time in ascending order).\n",
+    "* Splits train/test sets in a 'sliding window' approach.\n",
+    "* In each split, the test indices must be higher than before.\n",
+    "* Simulating the process of prospective validation (see [Sheridan, Robert P., <i>J. Chem. Inf. Model</i> (2013), <b>53.4</b>, 783-790](https://pubs.acs.org/doi/abs/10.1021/ci400084k)).\n",
+    "\n",
+    "![time-split Cross Validation](images/timesplit_cv.png)\n",
+    "*Figure 3:* \n",
+    "Time based Cross Validation approach. The test set in each fold is colored in orange. The figure is taken from: [towardsdatascience](https://towardsdatascience.com/time-based-cross-validation-d259b13d42b8)\n",
+    "\n",
+    "Scikit-learn has a [TimeSeriesSplit](https://scikitlearn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html) method with the main drawback, that the splitting process is not interferable. Therefore two functions are implemented in this notebook, a naive (recommended) implementation and another version, where the splits are infered such that the train and test sets are disjoint w.r.t. the year."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### Cluster-based Splitting\n",
+    "\n",
+    "General idea is to use an algorithm to cluster the compounds based on their sturctural features to get: \n",
+    "* Train set: Largest clusters are used to cover a wide chemical space.\n",
+    "* Test set: Small remaining clusters and/or singletons are used to provide a 'realistic' model evaluation with unseen, structural diverse molecules."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "**Algorithms**:\n",
+    "\n",
+    "1. **Butina Clustering** [butina1999]: Clustering technique based on fingerprints and Tanimoto similarity.\n",
+    "\n",
+    "![Butina clustering algorithm](images/butina.png)\n",
+    "*Figure 4:* \n",
+    "Schematic overview of the Butina clustering algorithm. The illustrations are taken from talktorial 005 of the Volkamer lab: [005_compound_clustering](https://projects.volkamerlab.org/teachopencadd/talktorials/T005_compound_clustering.html)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "2. **K-means**: Is a very common clustering technique, that aims to partition n observations into k clusters, where each observation belongs to the cluster with the smallest (euclidian) distance.\n",
+    "\n",
+    "![K-means clustering algorithm](images/kmeans.png)\n",
+    "*Figure 5:* \n",
+    "Demonstration of the K-means algorithm for three centroids (circles) and some samples (squares). The figure is taken from: [wikipedia](https://en.wikipedia.org/wiki/K-means_clustering)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### Performance metrics\n",
+    "\n",
+    "**Accuracy**: ACC = (TP + TN)/(TP + TN + FP + FN)\n",
+    "* _Informal:_ The fraction of predictions the model got right. The number of correct predictions divided by the total number of predictions.\n",
+    "\n",
+    "**Sensitivity**: TruePositiveRate = TP/(FN + TP)\n",
+    "*  _Informal:_ Measures the proportion of true positives that are correctly identified\n",
+    "\n",
+    "**Specificity**: TrueNegativeRate = TN/(FP + TN)\n",
+    "*  _Informal:_ Measures the proportion of true negatives\n",
+    "\n",
+    "**Area under the ROC curve (AUC)**: AUC ranges in value from 0 to 1. A model whose predictions are 100% wrong has an AUC of 0.0; one whose predictions are 100% correct has an AUC of 1.0.\n",
+    "\n",
+    "**Receiver operating characteristic (ROC) Curve Plot**: is a graph showing the performance of a classification model at all classification thresholds.\n",
+    "\n",
+    "This curve plots two parameters:\n",
+    "* True Positive Rate (y-axis)\n",
+    "* False Positive Rate (x-axis)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### References\n",
+    "\n",
+    "* Similarity-Based Methods and Machine Learning Approaches for Target Prediction in Early Drug Discovery: Performance and Scope: [Mathai, Neann *et al.*, <i>IJMS</i> (2020), <b>21.10</b>, 3585](https://www.mdpi.com/1422-0067/21/10/3585)\n",
+    "* Review and comparative assessment of similarity-based methods for prediction of drug–protein interactions in the druggable human proteome: [Wang, Chen *et al.*, <i>Briefings in bioinformatics</i> (2019), <b>20.06</b>, 2066-2087](https://academic.oup.com/bib/article-abstract/20/6/2066/5066711)\n",
+    "* Validation strategies for target prediction methods: [Mathai, Neann *et al.*, <i>Briefings in bioinformatics</i> (2019), <b>21.3</b>,791-802](https://academic.oup.com/bib/article/21/3/791/5428023)\n",
+    "* Database clustering with a combination of fingerprint and maximum common substructure methods: [Stahl, Martin *et al.*, <i>J. Chem. Inf. Model.</i> (2005), <b>45.3</b>, 542-548](https://pubs.acs.org/doi/abs/10.1021/ci050011h)\n",
+    "* Profile-QSAR 2.0: kinase virtual screening accuracy comparable to four-concentration IC50s for realistically novel compounds: [Martin, Eric J. *et al.*, <i>J. Chem. Inf. Model</i> (2017), <b>57.8</b>, 2077-2088](https://pubs.acs.org/doi/abs/10.1021/acs.jcim.7b00166)\n",
+    "* On selection of training and test sets for the development of predictive QSAR models: [Leonard, J. *et al.*, <i>QSAR and Combinatorial Science</i> (2006), <b>25.3</b>, 235-251](https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200510161)\n",
+    "* A measure of domain of applicability for QSAR modelling based on intelligent K‐means clustering: [Stanforth, Robert W. *et al.*, <i>QSAR and Combinatorial Science</i> (2007), <b>26.7</b>, 837-844](https://onlinelibrary.wiley.com/doi/abs/10.1002/qsar.200630086)\n",
+    "* Assessing the reliability of a QSAR model's predictions: [He, Linnan *et al.*, <i>J. Mol. Graph</i> (2005), <b>23.6</b>, 503-523](https://www.sciencedirect.com/science/article/abs/pii/S1093326305000173)\n",
+    "* Time-split cross-validation as a method for estimating the goodness of prospective prediction: [Sheridan, Robert P., <i>J. Chem. Inf. Model</i> (2013), <b>53.4</b>, 783-790](https://pubs.acs.org/doi/abs/10.1021/ci400084k)\n",
+    "* Review of epidermal growth factor receptor biology: [Herbst, Roy S., <i>IJROBP</i> (2004), <b>59.2</b>, S21-S26](https://www.sciencedirect.com/science/article/pii/S0360301604003311)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Practice and Results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "#Molecule Encoding\n",
+    "from rdkit import Chem\n",
+    "from rdkit import DataStructs\n",
+    "from rdkit.Chem import MACCSkeys\n",
+    "from rdkit.Chem.AllChem import GetMorganFingerprintAsBitVect\n",
+    "#ML-approaches\n",
+    "from sklearn import svm, metrics, clone\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.neural_network import MLPClassifier\n",
+    "#CV and Random Division\n",
+    "from sklearn.model_selection import KFold, train_test_split, cross_validate\n",
+    "#Time-split CV\n",
+    "from sklearn.model_selection import TimeSeriesSplit\n",
+    "#Cluster-based splits\n",
+    "import math\n",
+    "from rdkit.ML.Cluster import Butina\n",
+    "from rdkit.Chem import Descriptors\n",
+    "from rdkit.ML.Descriptors import MoleculeDescriptors\n",
+    "from sklearn.cluster import KMeans\n",
+    "import kneed\n",
+    "from kneed import KneeLocator #find appropriate number of cluster centers for kmeans\n",
+    "#Performance Metrics\n",
+    "from sklearn.metrics import auc, accuracy_score, recall_score\n",
+    "from sklearn.metrics import roc_curve, roc_auc_score\n",
+    "#Plotting\n",
+    "import matplotlib.pyplot as plt\n",
+    "from rdkit.Chem import Draw\n",
+    "#Display Images\n",
+    "from IPython.display import Image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#global parameter(s)\n",
+    "SEED = 22 #fixed seed for reproducible results\n",
+    "N_FOLDS = 10 #for random- and time-split CV\n",
+    "cut_off = 0.1 #for similarity-based clustering"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "### 1. Load compound data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of molecules :  4493\n",
+      "Number of features :  11\n"
+     ]
+    }
+   ],
+   "source": [
+    "path_to_data = 'data/EGFR_compounds_lipinski_timeseries.csv'\n",
+    "chembl_df = pd.read_csv(path_to_data, index_col=0)\n",
+    "\n",
+    "print(\"Number of molecules : \", chembl_df.shape[0])\n",
+    "print(\"Number of features : \", chembl_df.shape[1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>molecule_chembl_id</th>\n",
+       "      <th>document_year</th>\n",
+       "      <th>smiles</th>\n",
+       "      <th>pIC50</th>\n",
+       "      <th>molecular_weight</th>\n",
+       "      <th>n_hba</th>\n",
+       "      <th>n_hbd</th>\n",
+       "      <th>logp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>CHEMBL63786</td>\n",
+       "      <td>1996</td>\n",
+       "      <td>Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1</td>\n",
+       "      <td>11.522879</td>\n",
+       "      <td>349.021459</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.2891</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>CHEMBL53711</td>\n",
+       "      <td>1998</td>\n",
+       "      <td>CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1</td>\n",
+       "      <td>11.221849</td>\n",
+       "      <td>343.043258</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3.5969</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>CHEMBL35820</td>\n",
+       "      <td>1997</td>\n",
+       "      <td>CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC</td>\n",
+       "      <td>11.221849</td>\n",
+       "      <td>387.058239</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.9333</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>CHEMBL66031</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>Brc1cccc(Nc2ncnc3cc4[nH]cnc4cc23)c1</td>\n",
+       "      <td>11.096910</td>\n",
+       "      <td>339.011957</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4.0122</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>CHEMBL53753</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1</td>\n",
+       "      <td>11.096910</td>\n",
+       "      <td>329.027607</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3.5726</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  molecule_chembl_id  document_year                               smiles  \\\n",
+       "0        CHEMBL63786           1996    Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1   \n",
+       "1        CHEMBL53711           1998   CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1   \n",
+       "2        CHEMBL35820           1997  CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC   \n",
+       "3        CHEMBL66031           1999  Brc1cccc(Nc2ncnc3cc4[nH]cnc4cc23)c1   \n",
+       "4        CHEMBL53753           1999      CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1   \n",
+       "\n",
+       "       pIC50  molecular_weight  n_hba  n_hbd    logp  \n",
+       "0  11.522879        349.021459      3      1  5.2891  \n",
+       "1  11.221849        343.043258      5      1  3.5969  \n",
+       "2  11.221849        387.058239      5      1  4.9333  \n",
+       "3  11.096910        339.011957      4      2  4.0122  \n",
+       "4  11.096910        329.027607      5      2  3.5726  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Keep only the columns we want\n",
+    "chembl_df = chembl_df.drop(columns=[\"IC50\",\"units\",\"ro5_fulfilled\"])\n",
+    "#convert document_year to int\n",
+    "chembl_df[\"document_year\"] = chembl_df[\"document_year\"].astype(int)\n",
+    "chembl_df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### 2. Data preparation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "#### Data labeling\n",
+    "Classify each compound as active or inactive based on the pIC50 value.\n",
+    "\n",
+    "A common cut-off value to discretize pIC50 data is 6.3, which is also used here.\n",
+    "Note that there are several other suggestions for an activity cut-off ranging from an pIC50 value of 5 to 7 in the literature. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of active compounds: 2555\n",
+      "Number of inactive compounds: 1938\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>molecule_chembl_id</th>\n",
+       "      <th>document_year</th>\n",
+       "      <th>smiles</th>\n",
+       "      <th>pIC50</th>\n",
+       "      <th>molecular_weight</th>\n",
+       "      <th>n_hba</th>\n",
+       "      <th>n_hbd</th>\n",
+       "      <th>logp</th>\n",
+       "      <th>activity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>CHEMBL63786</td>\n",
+       "      <td>1996</td>\n",
+       "      <td>Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1</td>\n",
+       "      <td>11.522879</td>\n",
+       "      <td>349.021459</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.2891</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>CHEMBL53711</td>\n",
+       "      <td>1998</td>\n",
+       "      <td>CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1</td>\n",
+       "      <td>11.221849</td>\n",
+       "      <td>343.043258</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3.5969</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>CHEMBL35820</td>\n",
+       "      <td>1997</td>\n",
+       "      <td>CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC</td>\n",
+       "      <td>11.221849</td>\n",
+       "      <td>387.058239</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.9333</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>CHEMBL66031</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>Brc1cccc(Nc2ncnc3cc4[nH]cnc4cc23)c1</td>\n",
+       "      <td>11.096910</td>\n",
+       "      <td>339.011957</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4.0122</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>CHEMBL53753</td>\n",
+       "      <td>1999</td>\n",
+       "      <td>CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1</td>\n",
+       "      <td>11.096910</td>\n",
+       "      <td>329.027607</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3.5726</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  molecule_chembl_id  document_year                               smiles  \\\n",
+       "0        CHEMBL63786           1996    Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1   \n",
+       "1        CHEMBL53711           1998   CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1   \n",
+       "2        CHEMBL35820           1997  CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC   \n",
+       "3        CHEMBL66031           1999  Brc1cccc(Nc2ncnc3cc4[nH]cnc4cc23)c1   \n",
+       "4        CHEMBL53753           1999      CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1   \n",
+       "\n",
+       "       pIC50  molecular_weight  n_hba  n_hbd    logp  activity  \n",
+       "0  11.522879        349.021459      3      1  5.2891       1.0  \n",
+       "1  11.221849        343.043258      5      1  3.5969       1.0  \n",
+       "2  11.221849        387.058239      5      1  4.9333       1.0  \n",
+       "3  11.096910        339.011957      4      2  4.0122       1.0  \n",
+       "4  11.096910        329.027607      5      2  3.5726       1.0  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Add column for activity\n",
+    "chembl_df[\"activity\"] = np.zeros(len(chembl_df))\n",
+    "\n",
+    "# Assign binary activity score (activity = 1)\n",
+    "chembl_df.loc[chembl_df[chembl_df.pIC50 >= 6.3].index, \"activity\"] = 1.0\n",
+    "\n",
+    "print(\"Number of active compounds:\", int(chembl_df.activity.sum()))\n",
+    "print(\"Number of inactive compounds:\", len(chembl_df) - int(chembl_df.activity.sum()))\n",
+    "chembl_df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### Molecule encoding"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def smiles_to_fp(smiles, method=\"maccs\", n_bits=2048):\n",
+    "    \"\"\"\n",
+    "    Encode a molecule from a SMILES string into a fingerprint.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    smiles : str\n",
+    "        The SMILES string defining the molecule.\n",
+    "\n",
+    "    method : str\n",
+    "        The type of fingerprint to use. Default is MACCS keys.\n",
+    "\n",
+    "    n_bits : int\n",
+    "        The length of the fingerprint.\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    array\n",
+    "        The fingerprint array.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    # convert smiles to RDKit mol object\n",
+    "    mol = Chem.MolFromSmiles(smiles)\n",
+    "    if method == \"morgan2\":\n",
+    "        return GetMorganFingerprintAsBitVect(mol, 2, nBits=n_bits)\n",
+    "    if method == \"morgan3\":\n",
+    "        return GetMorganFingerprintAsBitVect(mol, 3, nBits=n_bits)\n",
+    "    else: #default maccs\n",
+    "        return MACCSkeys.GenMACCSKeys(mol)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "compound_df = chembl_df.copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>molecule_chembl_id</th>\n",
+       "      <th>document_year</th>\n",
+       "      <th>smiles</th>\n",
+       "      <th>pIC50</th>\n",
+       "      <th>molecular_weight</th>\n",
+       "      <th>n_hba</th>\n",
+       "      <th>n_hbd</th>\n",
+       "      <th>logp</th>\n",
+       "      <th>activity</th>\n",
+       "      <th>fp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>CHEMBL63786</td>\n",
+       "      <td>1996</td>\n",
+       "      <td>Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1</td>\n",
+       "      <td>11.522879</td>\n",
+       "      <td>349.021459</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.2891</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>CHEMBL53711</td>\n",
+       "      <td>1998</td>\n",
+       "      <td>CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1</td>\n",
+       "      <td>11.221849</td>\n",
+       "      <td>343.043258</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3.5969</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>CHEMBL35820</td>\n",
+       "      <td>1997</td>\n",
+       "      <td>CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC</td>\n",
+       "      <td>11.221849</td>\n",
+       "      <td>387.058239</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.9333</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  molecule_chembl_id  document_year                               smiles  \\\n",
+       "0        CHEMBL63786           1996    Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1   \n",
+       "1        CHEMBL53711           1998   CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1   \n",
+       "2        CHEMBL35820           1997  CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC   \n",
+       "\n",
+       "       pIC50  molecular_weight  n_hba  n_hbd    logp  activity  \\\n",
+       "0  11.522879        349.021459      3      1  5.2891       1.0   \n",
+       "1  11.221849        343.043258      5      1  3.5969       1.0   \n",
+       "2  11.221849        387.058239      5      1  4.9333       1.0   \n",
+       "\n",
+       "                                                  fp  \n",
+       "0  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...  \n",
+       "1  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...  \n",
+       "2  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Add column for fingerprint\n",
+    "compound_df[\"fp\"] = compound_df[\"smiles\"].apply(smiles_to_fp)\n",
+    "compound_df.head(3)\n",
+    "\n",
+    "#Command to calc. another fp type\n",
+    "#compound_df[\"fp_morgan2\"] = compound_df[\"smiles\"].apply(smiles_to_fp, args=('morgan2',))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### 3. Methods\n",
+    "\n",
+    "#### 3.1 Machine Learning (ML) Models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Set model parameter\n",
+    "param = {\n",
+    "    \"n_estimators\": 100,  # number of trees\n",
+    "    \"criterion\": \"entropy\",  # cost function\n",
+    "}\n",
+    "model_RF = RandomForestClassifier(**param)\n",
+    "models = [{\"label\": \"Model_RF\", \"model\": model_RF}]\n",
+    "\n",
+    "model_SVM = svm.SVC(kernel=\"rbf\", C=1, gamma=0.1, probability=True)\n",
+    "models.append({\"label\": \"Model_SVM\", \"model\": model_SVM})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### 3.2 Model evaluation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def model_performance(ml_model, test_x, test_y, verbose=True):\n",
+    "    \"\"\"\n",
+    "    Helper function to calculate model performance\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    ml_model: sklearn model object\n",
+    "        The machine learning model to train.\n",
+    "    test_x: list\n",
+    "        Molecular fingerprints for test set.\n",
+    "    test_y: list\n",
+    "        Associated activity labels for test set.\n",
+    "    verbose: bool\n",
+    "        Print performance measure (default = True)\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    tuple:\n",
+    "        Accuracy, sensitivity, specificity, auc on test set.\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Prediction probability on test set\n",
+    "    test_prob = ml_model.predict_proba(test_x)[:, 1]\n",
+    "\n",
+    "    # Prediction class on test set\n",
+    "    test_pred = ml_model.predict(test_x)\n",
+    "\n",
+    "    # Performance of model on test set\n",
+    "    accuracy = accuracy_score(test_y, test_pred)\n",
+    "    sens = recall_score(test_y, test_pred)\n",
+    "    spec = recall_score(test_y, test_pred, pos_label=0)\n",
+    "    auc = roc_auc_score(test_y, test_prob)\n",
+    "\n",
+    "    if verbose:\n",
+    "        print(f\"Sensitivity: {sens:.2f}\")\n",
+    "        print(f\"Specificity: {spec:.2f}\")\n",
+    "        print(f\"AUC: {auc:.2f}\")\n",
+    "\n",
+    "    return accuracy, sens, spec, auc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def plot_roc_curves_for_models(models, test_x, test_y, save_png=False):\n",
+    "    \"\"\"\n",
+    "    Helper function to plot customized roc curve.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    models: dict\n",
+    "        Dictionary of pretrained machine learning models.\n",
+    "    test_x: list\n",
+    "        Molecular fingerprints for test set.\n",
+    "    test_y: list\n",
+    "        Associated activity labels for test set.\n",
+    "    save_png: bool\n",
+    "        Save image to disk (default = False)\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    fig:\n",
+    "        Figure.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    fig, ax = plt.subplots()\n",
+    "\n",
+    "    # Below for loop iterates through your models list\n",
+    "    for model in models:\n",
+    "        # Select the model\n",
+    "        ml_model = model[\"model\"]\n",
+    "        # Prediction probability on test set\n",
+    "        test_prob = ml_model.predict_proba(test_x)[:, 1]\n",
+    "        # Prediction class on test set\n",
+    "        test_pred = ml_model.predict(test_x)\n",
+    "        # Compute False postive rate and True positive rate\n",
+    "        fpr, tpr, thresholds = metrics.roc_curve(test_y, test_prob)\n",
+    "        # Calculate Area under the curve to display on the plot\n",
+    "        auc = roc_auc_score(test_y, test_prob)\n",
+    "        # Plot the computed values\n",
+    "        ax.plot(fpr, tpr, label=(f\"{model['label']} AUC area = {auc:.2f}\"))\n",
+    "\n",
+    "    # Custom settings for the plot\n",
+    "    ax.plot([0, 1], [0, 1], \"r--\")\n",
+    "    ax.set_xlabel(\"False Positive Rate\")\n",
+    "    ax.set_ylabel(\"True Positive Rate\")\n",
+    "    ax.set_title(\"Receiver Operating Characteristic\")\n",
+    "    ax.legend(loc=\"lower right\")\n",
+    "    # Save plot\n",
+    "    if save_png:\n",
+    "        fig.savefig(\"roc_auc_\"+str(ml_model), dpi=300, bbox_inches=\"tight\", transparent=True)\n",
+    "    return fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def plot_roc_curves_for_singlemodel(models, test_x, test_y, model_type, title_, save_png=False):\n",
+    "    fig, ax = plt.subplots()\n",
+    "    \n",
+    "    for i in range(len(test_x)):\n",
+    "        # Prediction probability on test set\n",
+    "        test_prob = models[i].predict_proba(test_x[i])[:, 1]\n",
+    "        # Prediction class on test set\n",
+    "        test_pred = models[i].predict(test_x[i])\n",
+    "        # Compute False postive rate and True positive rate\n",
+    "        fpr, tpr, thresholds = metrics.roc_curve(test_y[i], test_prob)\n",
+    "        # Calculate Area under the curve to display on the plot\n",
+    "        auc = roc_auc_score(test_y[i], test_prob)\n",
+    "        # Plot the computed values\n",
+    "        ax.plot(fpr, tpr, label=(f\"{model_type[i]}: AUC area = {auc:.2f}\"))\n",
+    "\n",
+    "    # Custom settings for the plot\n",
+    "    ax.plot([0, 1], [0, 1], \"r--\")\n",
+    "    ax.set_xlabel(\"False Positive Rate\")\n",
+    "    ax.set_ylabel(\"True Positive Rate\")\n",
+    "    ax.set_title(title_)\n",
+    "    ax.legend(loc=\"lower right\")\n",
+    "    # Save plot\n",
+    "    if save_png:\n",
+    "        fig.savefig(\"roc_auc_\"+str(ml_model), dpi=300, bbox_inches=\"tight\", transparent=True)\n",
+    "    return fig"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "#### Random Split"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def random_split(X_set, Y_set, testsize):\n",
+    "    x_train, x_test, y_train, y_test = train_test_split(X_set, Y_set, test_size=testsize, shuffle=True, random_state=SEED)\n",
+    "    return x_train, x_test, y_train, y_test"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "#### k-Fold Cross Validation\n",
+    "\n",
+    "[KFold()](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html)_ will randomly pick the datapoints which would become part of the train and test set. Not completely randomly, if random_state is set to an integer value. It influences which points appear in each set and the same random_state always results in the same split."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def cross_validation(ml_model, df, n_folds=5, verbose=False):\n",
+    "    \"\"\"\n",
+    "    Machine learning model training and validation in a cross-validation loop.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    ml_model: sklearn model object\n",
+    "        The machine learning model to train.\n",
+    "    df: pd.DataFrame\n",
+    "        Data set with fingerprints and their associated activity labels.\n",
+    "    n_folds: int, optional\n",
+    "        Number of folds for cross-validation.\n",
+    "    verbose: bool, optional\n",
+    "        Performance measures are printed.\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    List of lists:\n",
+    "        accuracy, sensitivity, speicificty, auc for each fold.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    # Shuffle the indices for the k-fold cross-validation\n",
+    "    kf = KFold(n_splits=n_folds, shuffle=True, random_state=SEED)\n",
+    "\n",
+    "    # Results for each of the cross-validation folds\n",
+    "    acc_per_fold = []\n",
+    "    sens_per_fold = []\n",
+    "    spec_per_fold = []\n",
+    "    auc_per_fold = []\n",
+    "\n",
+    "    # Loop over the folds\n",
+    "    for train_index, test_index in kf.split(df):\n",
+    "        # clone model -- we want a fresh copy per fold!\n",
+    "        fold_model = clone(ml_model)\n",
+    "        # Training\n",
+    "\n",
+    "        # Convert the fingerprint and the label to a list\n",
+    "        train_x = df.iloc[train_index].fp.tolist()\n",
+    "        train_y = df.iloc[train_index].activity.tolist()\n",
+    "\n",
+    "        # Fit the model\n",
+    "        fold_model.fit(train_x, train_y)\n",
+    "\n",
+    "        # Testing\n",
+    "\n",
+    "        # Convert the fingerprint and the label to a list\n",
+    "        test_x = df.iloc[test_index].fp.tolist()\n",
+    "        test_y = df.iloc[test_index].activity.tolist()\n",
+    "\n",
+    "        # Performance for each fold\n",
+    "        accuracy, sens, spec, auc = model_performance(fold_model, test_x, test_y, verbose)\n",
+    "\n",
+    "        # Save results\n",
+    "        acc_per_fold.append(accuracy)\n",
+    "        sens_per_fold.append(sens)\n",
+    "        spec_per_fold.append(spec)\n",
+    "        auc_per_fold.append(auc)\n",
+    "\n",
+    "    # Print statistics of results\n",
+    "    print(\n",
+    "        f\"Mean accuracy: {np.mean(acc_per_fold):.2f} \\t\"\n",
+    "        f\"and std : {np.std(acc_per_fold):.2f} \\n\"\n",
+    "        f\"Mean sensitivity: {np.mean(sens_per_fold):.2f} \\t\"\n",
+    "        f\"and std : {np.std(sens_per_fold):.2f} \\n\"\n",
+    "        f\"Mean specificity: {np.mean(spec_per_fold):.2f} \\t\"\n",
+    "        f\"and std : {np.std(spec_per_fold):.2f} \\n\"\n",
+    "        f\"Mean AUC: {np.mean(auc_per_fold):.2f} \\t\"\n",
+    "        f\"and std : {np.std(auc_per_fold):.2f} \\n\"\n",
+    "    )\n",
+    "\n",
+    "    return acc_per_fold, sens_per_fold, spec_per_fold, auc_per_fold"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "#### Naive Time-split cross validation \n",
+    "\n",
+    "Provides train/test indices to split time series data samples that are observed at fixed time intervals. In each split, test indices must be higher than before, and thus shuffling is inappropriate."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def naive_timesplit_CV(ml_model, df, n_folds=5, get_sets=False, verbose=False):\n",
+    "    \"\"\"\n",
+    "    Machine learning model training and validation in a time-split cross-validation loop.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    ml_model: sklearn model object\n",
+    "        The machine learning model to train.\n",
+    "    df: pd.DataFrame\n",
+    "        Data set with fingerprints and their associated activity labels.\n",
+    "    n_folds: int, optional\n",
+    "        Number of folds for cross-validation.\n",
+    "    get_sets: bool, optional\n",
+    "        Returns\n",
+    "        -------\n",
+    "        List of lists:\n",
+    "            train and test sets used to perform time-split CV.\n",
+    "    verbose: bool, optional\n",
+    "        Performance measures are printed.\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    List of lists:\n",
+    "        accuracy, sensitivity, specificity, auc for each fold.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    tscv = TimeSeriesSplit(max_train_size=None, n_splits=n_folds)\n",
+    "    acc_per_fold = []\n",
+    "    sens_per_fold = []\n",
+    "    spec_per_fold = []\n",
+    "    auc_per_fold = [] \n",
+    "    plot_train = []\n",
+    "    plot_test = []\n",
+    "    for train_index, test_index in tscv.split(df):\n",
+    "        #print(\"TRAIN:\", train_index, \"TEST:\", test_index)\n",
+    "        time_model = clone(ml_model)\n",
+    "        \n",
+    "        train_x = df.iloc[train_index].fp.tolist()\n",
+    "        train_y = df.iloc[train_index].activity.tolist()\n",
+    "        \n",
+    "        plot_train.append(df.iloc[train_index])\n",
+    "        \n",
+    "        # Train the model\n",
+    "        time_model.fit(train_x, train_y)\n",
+    "       \n",
+    "        # Convert the fingerprint and the label to a list\n",
+    "        test_x = df.iloc[test_index].fp.tolist()\n",
+    "        test_y = df.iloc[test_index].activity.tolist()\n",
+    "        \n",
+    "        plot_test.append(df.iloc[test_index])\n",
+    "        # Performance for each fold\n",
+    "        accuracy, sens, spec, auc = model_performance(time_model, test_x, test_y, verbose)\n",
+    "\n",
+    "        acc_per_fold.append(accuracy)\n",
+    "        sens_per_fold.append(sens)\n",
+    "        spec_per_fold.append(spec)\n",
+    "        auc_per_fold.append(auc)\n",
+    "\n",
+    "    if get_sets:\n",
+    "        return plot_train, plot_test\n",
+    "    else: \n",
+    "        # Print statistics of results\n",
+    "        print(\n",
+    "            f\"Mean accuracy: {np.mean(acc_per_fold):.2f} \\t\"\n",
+    "            f\"and std : {np.std(acc_per_fold):.2f} \\n\"\n",
+    "            f\"Mean sensitivity: {np.mean(sens_per_fold):.2f} \\t\"\n",
+    "            f\"and std : {np.std(sens_per_fold):.2f} \\n\"\n",
+    "            f\"Mean specificity: {np.mean(spec_per_fold):.2f} \\t\"\n",
+    "            f\"and std : {np.std(spec_per_fold):.2f} \\n\"\n",
+    "            f\"Mean AUC: {np.mean(auc_per_fold):.2f} \\t\"\n",
+    "            f\"and std : {np.std(auc_per_fold):.2f} \\n\"\n",
+    "        )\n",
+    "        return acc_per_fold, sens_per_fold, spec_per_fold, auc_per_fold"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### Modified Time-split cross validation \n",
+    "\n",
+    "Train/test indices are splitted such that the fixed time intervals are distinct in both sets to guarentee that in each split, test indices are higher than the train indices."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def timesplit_CV(ml_model, df, n_folds=5, get_sets=False, verbose=False):\n",
+    "    \"\"\"\n",
+    "    Machine learning model training and validation in a time-splot cross-validation loop for distinct years in both sets.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    ml_model: sklearn model object\n",
+    "        The machine learning model to train.\n",
+    "    df: pd.DataFrame\n",
+    "        Data set with fingerprints and their associated activity labels.\n",
+    "    n_folds: int, optional\n",
+    "        Number of folds for cross-validation.\n",
+    "    get_sets: bool, optional\n",
+    "        Returns\n",
+    "        -------\n",
+    "        List of lists:\n",
+    "            train and test sets used to perform time-split CV.\n",
+    "    verbose: bool, optional\n",
+    "        Performance measures are printed.\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    List of lists:\n",
+    "        accuracy, sensitivity, speicificty, auc for each fold.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    tscv = TimeSeriesSplit(max_train_size=None, n_splits=n_folds)\n",
+    "    acc_per_fold = []\n",
+    "    sens_per_fold = []\n",
+    "    spec_per_fold = []\n",
+    "    auc_per_fold = [] \n",
+    "    plot_train = []\n",
+    "    plot_test = []\n",
+    "    for train_index, test_index in tscv.split(df):\n",
+    "        #print(\"TRAIN:\", train_index, \"TEST:\", test_index)\n",
+    "        time_model = clone(ml_model)        \n",
+    "        #split sets at years\n",
+    "        left_interval = df.iloc[train_index].document_year.tolist()\n",
+    "        right_interval = df.iloc[test_index].document_year.tolist()\n",
+    "        if list(set(left_interval)&set(right_interval)) != []: #if intersection not empty\n",
+    "            inters=[]\n",
+    "            intersection = list(set(left_interval)&set(right_interval))\n",
+    "            #get molecule index by intersection (document year)\n",
+    "            l =df.loc[train_index].document_year[df.loc[train_index].document_year == intersection[0]].count()\n",
+    "            r =df.loc[test_index].document_year[df.loc[test_index].document_year == intersection[0]].count()\n",
+    "            inter = df.document_year[df.document_year == intersection[0]].index.tolist()\n",
+    "            #molecules are continuously numbered, therefore get them by considering the first and last numbers\n",
+    "            pos = np.where(df.index==inter[0])[0]\n",
+    "            pos_n = np.where(df.index==inter[-1:])[0]\n",
+    "            #fill the numbers inbetween\n",
+    "            inters.extend(range(pos[0],pos_n[0]+1))\n",
+    "            #assign compounds belonging to the year to the largest set\n",
+    "            if l >= r:\n",
+    "                #delete compounds corresponding to the considered year\n",
+    "                train_index = [i for i in train_index if i not in inters]\n",
+    "                #add all compounds (indices) corresponding to the year to the training set\n",
+    "                train_index = np.append(inters, train_index)\n",
+    "                #remove intersecting molecule indices in training set from test set\n",
+    "                test_index = [j for j in test_index if j not in train_index]\n",
+    "            else:\n",
+    "                #delete compounds corresponding to the considered year\n",
+    "                test_index = [k for k in test_index if k not in inters]\n",
+    "                #add all compounds (indices) corresponding to the year to the test set\n",
+    "                test_index = np.append(inters, test_index)\n",
+    "                #remove intersecting molecule indices in test set from training set\n",
+    "                train_index = [l for l in train_index if l not in test_index]\n",
+    "            \n",
+    "        else: pass\n",
+    "        \n",
+    "        train_x = df.iloc[train_index].fp.tolist()\n",
+    "        train_y = df.iloc[train_index].activity.tolist()\n",
+    "        \n",
+    "        plot_train.append(df.iloc[train_index])\n",
+    "        # Train the model\n",
+    "        time_model.fit(train_x, train_y)\n",
+    "       \n",
+    "        # Convert the fingerprint and the label to a list\n",
+    "        test_x = df.iloc[test_index].fp.tolist()\n",
+    "        test_y = df.iloc[test_index].activity.tolist()\n",
+    "        \n",
+    "        plot_test.append(df.iloc[test_index])\n",
+    "        # Performance for each fold\n",
+    "        accuracy, sens, spec, auc = model_performance(time_model, test_x, test_y, verbose)\n",
+    "\n",
+    "        acc_per_fold.append(accuracy)\n",
+    "        sens_per_fold.append(sens)\n",
+    "        spec_per_fold.append(spec)\n",
+    "        auc_per_fold.append(auc)\n",
+    "\n",
+    "    if get_sets:\n",
+    "        return plot_train, plot_test\n",
+    "    else: \n",
+    "        # Print statistics of results\n",
+    "        print(\n",
+    "            f\"Mean accuracy: {np.mean(acc_per_fold):.2f} \\t\"\n",
+    "            f\"and std : {np.std(acc_per_fold):.2f} \\n\"\n",
+    "            f\"Mean sensitivity: {np.mean(sens_per_fold):.2f} \\t\"\n",
+    "            f\"and std : {np.std(sens_per_fold):.2f} \\n\"\n",
+    "            f\"Mean specificity: {np.mean(spec_per_fold):.2f} \\t\"\n",
+    "            f\"and std : {np.std(spec_per_fold):.2f} \\n\"\n",
+    "            f\"Mean AUC: {np.mean(auc_per_fold):.2f} \\t\"\n",
+    "            f\"and std : {np.std(auc_per_fold):.2f} \\n\"\n",
+    "        )\n",
+    "        return acc_per_fold, sens_per_fold, spec_per_fold, auc_per_fold"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "#### Plot the data splitting of train and test sets and plot the accuracy per fold for cross validation methods. \n",
+    "To get the respective sets, set get_sets parameter to True (default=False)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def plot_cv_data(train_timeset, test_timeset, nfolds, title_):\n",
+    "    \"\"\"\n",
+    "    Plots train and test sets used for time-split cross validation in a histogram: sample sizes over years.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    train_timeset: pd.Dataframe\n",
+    "        Data set sorted by year (ascending order) with document year and Id for each molecule.\n",
+    "    train_timeset: pd.Dataframe\n",
+    "        Data set sorted by year (ascending order) with document year and Id for each molecule. \n",
+    "    n_folds: int, optional\n",
+    "        Number of folds for cross-validation.\n",
+    "    title_: string\n",
+    "        Set title of plot\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    plot:\n",
+    "        Displays subfigures, one for each fold in the cross validation.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    df_list=[]\n",
+    "    for i in range(len(train_timeset)):\n",
+    "        df_years = []\n",
+    "        #group the molecules by years in ascending order and count the members\n",
+    "        years = train_timeset[i].groupby(train_timeset[i][\"document_year\"]).count()\n",
+    "        years_test = test_timeset[i].groupby(test_timeset[i][\"document_year\"]).count()\n",
+    "        df_years = pd.DataFrame(years.molecule_chembl_id.tolist(), index = years.index.tolist(), columns=['train'])\n",
+    "        #add a new colum to the dataframe initilized with zeros\n",
+    "        df_years['test'] = 0\n",
+    "        for ind in years_test.index.tolist():\n",
+    "            #put the number of members to the respective year (position)\n",
+    "            df_years.at[ind, 'test'] = years_test.loc[ind, :][0]\n",
+    "        df_list.append(df_years)\n",
+    "    #plot the distribution of training and test samples\n",
+    "    #nrow = math.ceil(len(train_timeset)/nfolds)\n",
+    "    ncol=nfolds\n",
+    "    print(title_)\n",
+    "    fig, axes = plt.subplots(1, ncol, figsize=(18,5))\n",
+    "    for i in range(len(train_timeset)):\n",
+    "        df_list[i].plot(kind='bar', ax=axes[i], title=str(i+1)+'-fold')\n",
+    "    return plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def plot_cv_accuracy(acc_list, model_list, title_):\n",
+    "    \"\"\"\n",
+    "    Plots accuracy of cross validation at each fold.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    acc_list: list of lists\n",
+    "        Each list contains the accuracy per fold for the respective model type i (i-th entry in model_list)\n",
+    "    model_list: list of strings\n",
+    "        Each string specifies the used model and evaluation method (random CV, time-split CV).\n",
+    "        Displayed as legend in the plots.\n",
+    "    title_: string\n",
+    "        Set title of plot\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    plot:\n",
+    "        Plots accuracy of each model per fold.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    df_acc = pd.DataFrame(acc_list).T\n",
+    "    #assign the model and evaluation method\n",
+    "    df_acc.columns = model_list\n",
+    "    n_models = int(len(model_list)/3)\n",
+    "    nrow=math.ceil(n_models/3)\n",
+    "    print(title_)\n",
+    "    fig, axes = plt.subplots(nrow, n_models, figsize=(18,5))\n",
+    "    #plot the accuracy for all evaluation methods belonging to a model\n",
+    "    for i in range(n_models):\n",
+    "        ax = df_acc.iloc[:, i::n_models].plot(style='o-', ax=axes[i], title=models_method[i][:-10])\n",
+    "        ax.set(xlabel='n-folds', ylabel='accuracy')\n",
+    "    return plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "**Cluster-based Split**\n",
+    "\n",
+    "**1) Butina Clustering**\n",
+    "\n",
+    "* Convert SMILES to Fingerprints (maccs)\n",
+    "* Calculate Tanimoto dissimilarity matrix (1-similarity)\n",
+    "* Cluster the molecules based on exclusion spheres using RDKit _Butina.ClusterData()_.\n",
+    "* Assign the compound from the clusters to train and test set with an ratio approximately 80:20.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def Tanimoto_distance_matrix(df_fps):\n",
+    "    \"\"\"\n",
+    "    Calculate the pairwise Tanimoto distance (1-similarity) of the compounds.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    df_fps: list of lists\n",
+    "        A list containing the fingerprint representation of each molecule as list.\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    List of lists:\n",
+    "        Distance matrix.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    dissimilarity_matrix = []\n",
+    "    # Notice we are skipping the first and last items in the list because we don't need to compare them against themselves\n",
+    "    for i in range(1, len(df_fps)):\n",
+    "        # Compare the current fingerprint against all the previous ones in the list\n",
+    "        similarities = DataStructs.BulkTanimotoSimilarity(df_fps[i], df_fps[:i])\n",
+    "        # Since we need a distance matrix, calculate 1-x for every element in similarity matrix\n",
+    "        dissimilarity_matrix.extend([1 - x for x in similarities])\n",
+    "    return dissimilarity_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def cluster_fingerprints(fingerprints, cutoff=0.2):\n",
+    "    \"\"\"\n",
+    "    Cluster fingerprints by a given cut-off value with Butina Clustering technique and \n",
+    "    the corresponding Tanimoto similarity based distance matrix.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    figerprints: list of lists\n",
+    "        Each sublist contains the pairwise distance from one to all other molecules.\n",
+    "        Distance is defined by 1-Tanimoto Similarity.\n",
+    "        Output of the function Tanimoto_distance_matrix().\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "    List of tuples:\n",
+    "        Each tuple represents a cluster and contains the molecule IDs belonging to it.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    # Calculate Tanimoto distance matrix\n",
+    "    distance_matrix = Tanimoto_distance_matrix(fingerprints)\n",
+    "    # Now cluster the data with the implemented Butina algorithm:\n",
+    "    clusters = Butina.ClusterData(distance_matrix, len(fingerprints), cutoff, isDistData=True)\n",
+    "    clusters = sorted(clusters, key=len, reverse=True)\n",
+    "    num_singletons = sum(1 for c in clusters if len(c) == 1)\n",
+    "    largest_clust = len(clusters[0])\n",
+    "    print('Size of largest cluster: ', largest_clust)\n",
+    "    print('Number of Singletons: ', num_singletons)\n",
+    "    return clusters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def fingerprint_split(df_compounds, cluster_set):\n",
+    "    \"\"\"\n",
+    "    Splits the clusters into train and test set by assigning at least all singletons to the test set.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    df_compounds: pd.Dataframe\n",
+    "        Data set with fingerprints and their associated activity labels.\n",
+    "    cluster_set: List of  tuples\n",
+    "        Each tuple represents the membership of the molecules.\n",
+    "        Output of the function cluster_fingerprints().\n",
+    "\n",
+    "    Returns\n",
+    "    -------\n",
+    "        Lists:\n",
+    "            train and test set with their activity label.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    train_data=[]; train_label=[]; singletons=[]; s_label=[]\n",
+    "    for i in range(len(cluster_set)):\n",
+    "        if len(cluster_set[i]) <= 1: \n",
+    "            singletons.append(df_compounds.fp[cluster_set[i][0]])\n",
+    "            s_label.append(df_compounds.activity[cluster_set[i][0]])\n",
+    "        else:\n",
+    "            train_data.append(df_compounds.fp.loc[list(cluster_set[i])].tolist())\n",
+    "            train_label.append(df_compounds.activity.loc[list(cluster_set[i])].tolist())\n",
+    "    return [x for xi in train_data for x in xi], [y for yi in train_label for y in yi], singletons, s_label"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "**2) K-means**\n",
+    "\n",
+    "\n",
+    "* Convert SMILES to a set of physicochemical properties (=200).\n",
+    "* Cluster the molecules based on the properties using Scikit-learn _KMeans()_ function.\n",
+    "* Choose an appropiate initial k (empirically or elbow method)\n",
+    "* Assign the compound from the clusters to train and test set with ratio approximately 80:20."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def elbow_method(features_list, show_image=False):\n",
+    "    \"\"\"\n",
+    "    Selects an appropriate number of cluster centers for kmeans using KneeLocator().\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    features_list: np.array\n",
+    "        Contains features of each molecule.\n",
+    "    show_image: bool, optional\n",
+    "        Shows image with knee point.\n",
+    "        \n",
+    "    Returns\n",
+    "    -------\n",
+    "        Int:\n",
+    "            Optimal number of cluster centers.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    sse = []\n",
+    "    for k in range(1, 11):\n",
+    "        kmeans = KMeans(n_clusters=k)\n",
+    "        kmeans.fit(features_list)\n",
+    "        sse.append(kmeans.inertia_)\n",
+    "    if show_image==True:\n",
+    "        plt.style.use(\"fivethirtyeight\")\n",
+    "        plt.plot(range(1, 11), sse)\n",
+    "        plt.xticks(range(1, 11))\n",
+    "        plt.xlabel(\"Number of Clusters\")\n",
+    "        plt.ylabel(\"SSE\")\n",
+    "        plt.show()\n",
+    "    kl = KneeLocator(range(1, 11), sse, curve=\"convex\", direction=\"decreasing\")\n",
+    "    return kl.elbow"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def cluster_features(df, number_of_centers, elbowmethod=False):\n",
+    "    \"\"\"\n",
+    "    Cluster SMILES by their physicochemical properties with kemans.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    df: pd.Dataframe\n",
+    "        Data set with SMILES and molecule IDs.\n",
+    "    number_of_centers: int, ignored if elbowmethod=True\n",
+    "        Define the number of cluster centers for kmeans.\n",
+    "    elbowmethod: bool, optional\n",
+    "        Uses elbow-method to determine the optimal number of cluster centers of the data.\n",
+    "        \n",
+    "    Returns\n",
+    "    -------\n",
+    "        List of lists:\n",
+    "            Each sublist belongs to a cluster and contains the corresponding molecule member IDs.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    features=[x[0] for x in Descriptors._descList]\n",
+    "    calc = MoleculeDescriptors.MolecularDescriptorCalculator(features)\n",
+    "    df['physchem'] = df['smiles'].apply(lambda sm: calc.CalcDescriptors(Chem.MolFromSmiles(sm)))\n",
+    "    p = df.physchem.tolist()\n",
+    "    physicochems =np.array([list(elem) for elem in p])\n",
+    "    physicochems = np.nan_to_num(physicochems)\n",
+    "    if elbowmethod:\n",
+    "        number_of_centers = elbow_method(physicochems, show_image=True)\n",
+    "        kmeans = KMeans(n_clusters=number_of_centers, random_state=0).fit(physicochems)\n",
+    "        print('Size of clusters: ', np.bincount(kmeans.labels_[kmeans.labels_>=0]))\n",
+    "    else:\n",
+    "        kmeans = KMeans(n_clusters=number_of_centers, random_state=0).fit(physicochems)\n",
+    "        print('Size of clusters: ', np.bincount(kmeans.labels_[kmeans.labels_>=0]))\n",
+    "    clus = kmeans.labels_\n",
+    "    df['cluster_member'] = clus\n",
+    "    members=[]\n",
+    "    for mem in np.unique(clus):\n",
+    "        members.append(df.cluster_member[df.cluster_member == mem].index.tolist())\n",
+    "    return members"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### Example for K-means clustering with elbow-method:\n",
+    "\n",
+    "The algorithm finds the knee (or elbow) point of a curve. It is defined as the point of maximum curvature in a system. Identifying this location in a curve then can be used, to select an appropriate value of k in K-means clustering (see https://www.kaggle.com/kevinarvai/knee-elbow-point-detection).\n",
+    "\n",
+    "The SSE values for each Cluster (sum of squared error or inertia) is calculated by k-means. The smaller the value becomes the denser the cluster points are."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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mJgbbt29HYGBgpefcK6VSWavzqyvKWYPVKemm7aN3ZGjn3xpSiVDu8Q1VV02xrpqxxrqssSaAddVUc62rWgG1ZcsWbNmyxWzfmjVryj1WEMr/JVwemUyGdu3aAQB69uyJ48eP47PPPsOnn35a7eewRn08ZXCRCbijLWomydAYcCKjEMEeMpErIyJqPKoMqD/++KMh6gAAGAwGaLWVD4U1BjYSAf1b2eGHq/mmfbtTChhQREQ1UGVAtW7dul5eeN68eYiMjISPjw/UajU2b96MhIQEbNy4sV5er6FF+MrNAmpPSgFe7+kiYkVERI1LrZokCgsL8dtvvyE1NRUBAQHo0qVLtc9NS0vDxIkTcfv2bbi4uCAoKAibN29G//79a1OS1bBsNz+RXojb+Xp42ksrOIOIiEqrMqD27duHuLg4vPnmm/D09DTtv3jxIqKjo3Hp0iXTvqFDhyI2NhZSadW/hFesWHGPJTcOnvZS9HS3xYn0kqmO9qYU4N8BjiJWRUTUeFT5Oah169bh2LFjZuEEAC+++CIuXryIUaNGYeHChRgwYAC2bt2KL7/8st6KbWwsFzHktEdERNVXZUCdOHECAwcONNt35swZHD9+HMOHD8fnn3+OCRMmYOPGjQgJCcGmTZvqrdjGxnJ28303C6AzcHZzIqLqqDKgbt++DX9/f7N9+/btgyAIZWYuHzRoEC5evFi3FTZiPd1s4SYveYvvaI04ervxdykSETWEKgNKLpejoMB8wtPk5GQIgoDQ0FCz/a6urk2iTbyuSCUC+nMRQyKie1JlQPn7+2P//v2m7by8PCQmJqJr165wdnY2OzY1NRUeHh51X2UjZjnMt5sBRURULVV28Y0fPx4xMTGYPHkywsLCsG3bNuTk5GDMmDFljj148CA6d+5cL4U2Vv197CARiiaNBYAzWTr8nauHjyPbzYmIKlPlFVRUVBTGjx+PDRs24KWXXsKePXsQHR2N8ePHmx33119/ITExEREREfVWbGPkKpegj8UMEhzmIyKqWpVXUIIgYMmSJZgxYwauXbsGPz8/eHl5lTnO3d0d+/fvR/v27eul0MYswtcOyaWaI3anFGBcR34eioioMtWeScLDw6PM/aX4+Hhs3LgRqamp6NChAyZNmgQnJ6c6L7Kxi/CV4+3jJduHbmqg0Rshl1Z/Yl0iouamyiG+999/Hx4eHkhLSzPbv27dOgwdOhRr167F3r178dlnn+Gxxx7D9evX663YxqprS1t425e81bk6I5LS+KFdIqLKVBlQ8fHxeOyxx8yG9TQaDWbNmgUXFxds3boVKSkpWLlyJdRqNZYtW1avBTdGgiCUmVWC3XxERJWrMqAuX76M4OBgs32HDh1CTk4Opk6divDwcDg6OuKpp57CqFGjcPDgwfqqtVHjtEdERDVTZUBlZWXB29vbbF98fDwEQSgzBVKPHj2QmppatxU2EY+0ksOm1C0nZbYOV+7oxCuIiMjKVRlQnp6epuXeiyUlJcHJyanM8hoSiQQyGRflK4+LTIK+Xmw3JyKqrioDqlevXli/fj1UKhUA4M8//8SJEycQHh5eZnn38+fPw8fHp34qbQIsZ5VgQBERVazKgHrttdeQmpqKXr164YknnsATTzwBQRDw8ssvmx1nNBqxfft2hISE1FuxjV2En3lAxadqkKcziFQNEZF1qzKggoKCsHXrVgQHByM9PR19+vRBXFwcHnjgAbPj4uPj4eTkhCFDhtRbsY1dxxY28HMqmeKoQA8k3OLkukRE5anWB3VDQ0OxcePGSo8JDw/H4cOH66SopkoQBET62uHrc7mmfXtSCjDRXcSiiIisVJVXUFS3IiyW39iVUgAj1zAkIiqDAdXA+nnLIS81kfl1tR7X8jnlERGRJQZUA3O0laCft/lVVEIml94gIrLEgBKB5awSiVkMKCIiSwwoEVgG1Mk7EtzRst2ciKg0BpQI2rnYoL1LSQOlzijgwE3OzUdEVBoDSiSW3Xxzj2Ujo0AvUjVERNaHASWSp+63N9u+ptbjmf2Z0OrZc05EBDCgRNPHU47nLZZ9T0rT4pUkFYz8YBQRkXgBtWzZMjz66KPw8/ODv78/oqKicPbsWbHKEcXC0BYIv898qG+tMg/Lz6hFqoiIyHqIFlAJCQkYP348du3ahW3btsHGxgbDhg1DVlaWWCU1OFuJgNWPtoSfnXkH39zf7mD3Dc50TkTNm2gBFRcXh2eeeQaBgYEICgrCF198gfT0dCQnJ4tVkihc5RIsC9TARVYym4TBCIw/lIm/sgpFrIyISFxWcw9KrVbDYDBAoVCIXUqDa+tgxDePtISk1IxHOYVGjN6bwc4+Imq2BJVKZRV35MeNG4dLly7h4MGDkEornllBqVQ2YFUNa8NNGyy9bL7qbk8XPZZ30cDWav6UICKqGwEBAZU+Xq3lNurb66+/juTkZOzcubPScAKq/oEqo1Qqa3V+fSmua057IzJsVPjmQp7psRN3pFjxjzs+flBRZgXjhqrL2rCu6rPGmgDWVVPNtS7R/y6fNWsWtmzZgm3btqFt27ZilyMqQRCwuK8CD3mbX0V9q8zDZ2dzKziLiKhpEjWgZsyYgc2bN2Pbtm3o0KGDmKVYDVuJgDWPtsT9zuZXkm8cy8aeFHb2EVHzIVpATZ8+HevXr0dsbCwUCgXS0tKQlpYGtZqfAWppJ8WGAW5wsTXv7Hv+IDv7iKj5EC2gYmNjkZOTg6FDh6Jjx46mr08++USskqxKR4UtVrKzj4iaMdGaJFQqlVgv3WgM8LXDuw+0wKyj2aZ919R6jN2fiR8HukMm5Uq8RNR0id4kQZWbFOiIZzs4mO07nKbF9GTO2UdETRsDysoJgoDFoQo8aNHZt+ZCHlaws4+ImjAGVCMgkwr4tpzOvjns7COiJowB1UhU1Nk3/mAmzqnY2UdETQ8DqhEpr7PvDjv7iKiJYkA1MgN87fDOAy3M9l3N0eM/B7gaLxE1LQyoRigm0BH/sejsS0zV4jV29hFRE8KAaoQEQcCScjr7Vl/Iw+fs7COiJoIB1UjJpEVz9rW16Oybzc4+ImoiGFCNmFslnX3n2dlHRI0cA6qR66SwxdcVdPZlsrOPiBoxBlQTEOFrh7ctOvuusLOPiBo5BlQTMTnQEWMDzDv7EtjZR0SNGAOqiRAEAUv7KhDmxc4+ImoaGFBNiEwq4NvHWqKNU9nOvr3s7COiRoYB1cQUd/Y5l7MaLzv7iKgxYUA1QZ1dbfH1w+zsI6LGjQHVREX62eGtYBezfezsI6LGhAHVhE0JcsIz5XT2/Y+dfUTUCDCgmjBBELCsrwJ9LTr7vrmQhy/+YmcfEVk3BlQTV1Fn3+tHs7Hvb3b2EZH1YkA1A+4VdPY9dzATF9jZR0RWigHVTHR2tUXswy1RqrEPd7RGRLGzj4isFAOqGRnoZ4e3Hii/s6/QwKYJIrIuDKhmZmqQE8aws4+IGgEGVDNTUWffqvN5+JKdfURkRRhQzZD8bmdfa4vOvllHs7GfnX1EZCVEDajExESMHj0anTt3hkKhwLp168Qsp1kp7uxzsjHv7BvHzj4ishKiBlRubi4CAwPx/vvvw97eXsxSmqVAV1vEPuJaprNv9N4MZGkMotVFRASIHFCRkZGYO3cuhg4dComEo41ieNzPvsycfZdz9Hj2QCZ0zCgiEhFTgTC1S9nOvl9vabDwkgw6tp8TkUgElUplFb+BfHx8sGjRIowZM6bS45RKZQNV1LxoDcCUP+U4ece8caKV3ID/+OrwpJcOcv45Q0R1KCAgoNLHbRqojjpT1Q9UGaVSWavz64u11LW5jR6P/fQPrqtLZpa4qZHg/UsyrLpph6lBThjXyRHOtuImlbW8X5assS5rrAlgXTXVXOvi38RkUtzZp5AJZR5Lyzfgjd/uoOvGVCw4cYdNFERU7xhQZCbQ1RYJQz3xXEcH2AplR39VWiMWnsxBl42peONYNlLzOI8fEdUPUQNKrVbj1KlTOHXqFAwGA1JSUnDq1CncuHFDzLKaPV8nG3wQ5oqtwQWYEuQEB5uyV1S5OiM++VONbptS8cphFa7m6ESolIiaMlED6sSJEwgPD0d4eDjy8/OxYMEChIeH47333hOzLLrLQ27Eu31a4M+RXvhfD2e0KGfoT2sAVp7PRe8taZj4ayb+yuKHfImobojaJNGvXz+oVCoxS6BqaGknxes9XfBSFyesOpeLT8+ocTvf/B6U3ghsvJSPjZfyMai1HV7t5oxeHrIKnpGIqGq8B0XV5mwrwX+7OuOPEd5Y2rcF/Czm8iu243oBHtv+D57alY74WxrOkk5E94QBRTVmbyNgfCcnHH/aC5/3c0XHFuVfiB+4qcHgnekYuCMdO2/kM6iIqEYYUHTPbCUCRrd3QNJTnljzaEv0cLMt97ij/2gxem8mHtp6G1su50HP2SmIqBoYUFRrEkHAkLb2ODDYA3GRbnjQu/x7T2eydBh/KAsPxKVhzYVcaPQMKiKqGAOK6owgCHjMxw47/uWBnU+4Y6CvvNzjLufo8d9EFXpuTsWKM2rkFvJDv0RUFgOK6kWolxzfR7jj1yEeeKqtPco2qAM38wyYdTQb3TalYckfOVBxdgoiKoUBRfWqm5sMqx5tiWPDPfFMgAPK+cwvMjQGvHP8DrpuSsX837JxO5+zUxARA4oaSPsWtvj0IVecGOGFFzs7wl5aNqlyCo344HTR7BSvJatwXc3ZKYiaMwYUNSg/JxssDFXg1EgvvNrNCS62ZYOqQA989Vcuem1Ow+T4LCizOTsFUXPEgCJReNhL8UbvFjg10htv9HKBWzmLTemMwPqLeegTdxvjDmTijwytCJUSkVgYUCQqhVyCV7s74/QoL7wf0gI+DmVnpzAC+PFqPh7e9g9G7k7HoQwpMgt4n4qoqWt0CxZS0+RgI8GkQCc839ER31/Kw4enc3DpTtkQ2vO3Bnv+lmP6X6nopLBBXy8ZQr3k6Oslg5+jFIJQXr8gETVGDCiyKjKpgLEdHPHv9g7Ydi0fS0+p8Wdm+fegzql0OKfSYdX5PACAj4MUfb1lCPWUoa+XHJ1dbSBhYBE1WgwoskpSiYCn7nfAsLb22J2iwdI/cnD0n8rvQf2dp8fmy/nYfDkfANBCJiDUs+QKq6e7DPJyugeJyDoxoMiqCYKAgX52iPSV43CaFj9ezceh6zlQ5kpQ1URJ2VojdqVosCtFAwCQS4Fe7jL09Sq6wnrAQwZFOc0ZRGQdGFDUKAiCgAe95XjQWw6l2z/wbOOPY7e1SErTIClNi9/TtdBU0Teh0QNJaVokpWkBqCEACHS1QZiXHKF3Q6uVY/lLiBBRw2NAUaPUQibBAF87DPC1AwBo9EacTC8Kn6TbWhxJ00Clrfway4iiCWzPZOnw1blcAEAbJ6kprPp6ydChhQ0bL4hEwoCiJkEuFRDiJUeIlxzTABiMRpxT6ZCcVnKVlZJbdWv6NbUe19T5+P5S0X2slnJJUWB5ytDXW47ubrawlTCwiBoCA4qaJIkgINDVFoGutni+kyMA4Ia6OLC0SE7T4Kyq6qmUMjUG/Hy9AD9fLwAA2EsFBHvYItRLjjAvGYI9ZXC25X0sovrAgKJmw8/JBn5ONhjp7wAAyNIYcOS2BkmpWiTf1uJ4uhZVrfyRrzciPlWL+NSijkKpAHRtaYsQTxkcCmzQQciDQibAVS4xfSlkEsjYPUhUYwwoarZc5RI87mePx/3sAQD5OiOOp5dcYR29rcWdwsrvY+mNwMmMQpzMKAQgA65klXuck40AhVwChVwCV4sAK/5qISu1ffcYBxuB98Co2WJAEd1lb1PSKQg4Q28w4kxWoWlYMClNg9T8e1uzSq0zQq3TV+s+WGkyCUxXYa7FASeXwFUuwNVyX6mAc5EJ/JAyNXoMKKIKSCUCurnJ0M1NhomBgNFoxDW13hRWyWlaXMiu3yVBtAYgLd+AtBoGowBAIRfgKNjB49xtKGRFIaeQC2hh+r5kX/F2C5kELrYCpGwEISvAgCKqJkEQ0NbZBm2dbRDdvug+VnqBHslpWvyZWYgraZkw2rtApTUgS2NAlsZY9F+tAYaqPlVcx4xA0etDgpSCmi1XIgBwlgmlQk2CFjKh3FBrYdonmAKOXZ1NbmoAABf9SURBVI5UVxhQRLXgbifFk23s8WQbeyiVaQgIaFnmGIPRiJzCorBSaYrCqyjE7gbY3RAr/l5Val9VHz6uD0YAd7RG3NHqcR01L6D4fptLJaFWkCVFO1k+HG0EONgIsLcR4GgjwN5GYtpnKwHvvzVzDCiieiYRBLSQFQ2twblm5+brKg6xMldqd49RaQzIqaK5oz4V329DbmVHyYELmZU+j1TA3dAqCqySL4kp0MzDrWjb8e7jDpV+SSCXMgCtHQOKyIrZ2wiwt5HWeAqmQoMRKo0BJy9cgeK+1lBpS0Kt6L9GqLQGZBfv0xYdn60VN9xK0xuBO4XGKjsp75VEABykAhxsBdhLi0JO0MnhovwHMokAmQSwlQpm38slRVd2MundfRIBMundfZK7x0rvfl9qv63Ffplpf/FzlXxvIzA4i4keULGxsfj444+RlpaGTp06YcGCBQgLCxO7LKJGzVYiwMNeirYORgR4ymp0rs5gxJ1SoVVxqBmg0hhNj2drDcjWGqucxNdaGIzFV3ulK5YCanFXbhYAU5jZ3g1HGOxg/0cqpIIAG0nR1aWNpCjMbCQCpIL5PqnlYxLA5u65NoJwdxum5yu9r+Sc4uco/bhw93WKznXVCAiox/dC1ICKi4vDzJkzsXTpUoSGhiI2NhYjR45EcnIy/Pz8xCyNqNmykQhoaSdFS7uan2swGnFHax5aKq2x6L+aklBLyciG1N4JeToj8nVG5OoMyNcZkXf3K1dnhL6xJF0dM6JoYmON3nh3CwAkEOWGZBXe6ShBv3p8flEDavny5fj3v/+NZ599FgCwePFi7Nu3DytXrsSbb74pZmlEdA8kglDUDCGv/H6bUvkPAgLcKn0urb4ksPJ0BtP3+XcDLL9UmOVXcEzZ40uO0d7bR9qolPqeIEW0gNJqtTh58iReeukls/2PPfYYjhw5IlJVRGQtZNKi+zUKOQDU/TIoOoOxTKBduHIdXj6+KDQYodUDWoOx6HtDUWBq7+437TMYUai3eNxw93F92e+1d78vNJ1b9F9Nqe8b05VjfS9OI1pAZWRkQK/Xw8PDw2y/h4cHbt++XeF5SqWyVq9b2/PrC+uqGdZVfdZYE2B9dckBdHUBkHO9/AMEFP1GruffynojoDMChYbi/wrQGovumRU/pjcCBgB6o2C2r+RLsNi++4Wyj5mezyhAj7LPZTACuvKeD4Cn3Firf8eAgMrvYIneJGHZrWI0GivtYKnqB6qMUqms1fn1hXXVDOuqPmusCWBdNdVc6xJtnQA3NzdIpdIyV0vp6ellrqqIiKj5ES2gZDIZevTogQMHDpjtP3DgAEJCQkSqioiIrIWoQ3xTpkzBiy++iN69eyMkJAQrV65EamoqnnvuOTHLIiIiKyBqQA0fPhyZmZlYvHgx0tLS0LlzZ2zcuBGtW7cWsywiIrICojdJvPDCC3jhhRfELoOIiKyMaPegiIiIKiOoVKpG9LEwIiJqLngFRUREVokBRUREVokBRUREVokBRUREVokBRUREVqnJB1RiYiJGjx6Nzp07Q6FQYN26dWKXhGXLluHRRx+Fn58f/P39ERUVhbNnz4pdFr766iuEhYXBz88Pfn5+iIiIwK5du8Quq4ylS5dCoVDgtddeE7WOBQsWQKFQmH116NBB1JqKpaamYtKkSfD394eXlxdCQkKQkJAgak1du3Yt834pFAqMGjVK1Lr0ej3eeecddOvWDV5eXujWrRveeecd6HQ6UesCgJycHMycORNdunSBt7c3IiMjcfz48QatoarfoUajEQsWLECnTp3g7e2NQYMG4a+//qqT1xb9g7r1LTc3F4GBgYiOjsakSZPELgcAkJCQgPHjx6NXr14wGo147733MGzYMBw5cgSurq6i1dWqVSvMnz8f/v7+MBgM+O677zBmzBgcPHgQXbp0Ea2u0o4dO4bVq1cjKChI7FIAFM2uv337dtO2VFrfK+RUTaVSYeDAgQgNDcXGjRvh5uaGa9euiT4J84EDB6DXl6wKm5qaikceeQTDhg0TsSrgww8/RGxsLFasWIHAwECcOXMGMTExkMlk+N///idqbf/9739x5swZrFixAj4+Pvj+++8xbNgwJCcno1WrVg1SQ1W/Qz/66CMsX74cy5cvR0BAABYtWoSnnnoKx44dg7NzJatWVkOz+hyUj48PFi1ahDFjxohdihm1Wo3WrVtj3bp1+Ne//iV2OWbatm2LN9980yrmR8zOzsbDDz+Mjz76CIsWLUJgYCAWL14sWj0LFizAtm3bkJSUJFoN5XnrrbeQmJholVe/pS1ZsgQff/wxzp07BwcHB9HqiIqKgqurKz7//HPTvkmTJiErKwvff/+9aHXl5+fD19cXa9aswaBBg0z7H374YURERGDOnDkNXpPl71Cj0YhOnTphwoQJmD59uqnugIAAvP3227X+vdHkh/gaA7VaDYPBAIVCIXYpJnq9Hlu2bEFubi769OkjdjkAgGnTpmHo0KF4+OGHxS7F5OrVq+jcuTO6deuG559/HlevXhW7JOzYsQO9e/fGc889h/bt2+Ohhx7Cl19+CaPRev4WNRqN+PbbbxEVFSVqOAFAaGgoEhIScOHCBQDAuXPnEB8fj4iICFHr0ul00Ov1sLOzM9tvb29vNX8UXbt2DWlpaXjsscdM++zt7REWFlYnK6M3+SG+xmDmzJno2rWrVQTBmTNnEBkZiYKCAjg6OmLt2rVWMZy2evVqXL58GV988YXYpZgEBwfjs88+Q0BAANLT07F48WJERkYiOTkZLVu2FK2uq1ev4uuvv8bkyZMxbdo0nD59GjNmzAAATJw4UbS6Sjtw4ACuXbuGsWPHil0Kpk2bBrVajZCQEEilUuh0OkyfPl30OUKdnZ3Rp08fLFmyBJ07d4aXlxc2b96Mo0ePol27dqLWViwtLQ0Ayl0Z/datW7V+fgaUyF5//XUkJydj586dVnH/IiAgAPHx8cjOzsa2bdsQExOD7du3IzAwULSalEol3nrrLfzyyy+QyWSi1WHJ8i/s4OBg9OjRA+vXr8fUqVNFqgowGAzo2bMn3nzzTQBA9+7dcfnyZcTGxlpNQK1evRq9evVCt27dxC4FcXFx2LBhA2JjY9GpUyecPn0aM2fOROvWrfGf//xH1Nq++OILTJkyBYGBgZBKpejevTtGjBiBP/74Q9S6LNV0ZfTqYkCJaNasWYiLi8NPP/2Etm3bil0OgKKFJIv/OuvZsyeOHz+Ozz77DJ9++qloNR09ehQZGRno27evaZ9er8fhw4excuVK3Lx5E3K5XLT6ijk5OaFTp064fPmyqHV4eXmhY8eOZvs6dOiAlJQUkSoy988//+Dnn3/GkiVLxC4FADB37lxMnToVTz/9NAAgKCgIN27cwAcffCB6QN1///34+eefkZubi5ycHHh7e+O5555DmzZtRK2rmJeXFwDg9u3b8PX1Ne2vq5XReQ9KJDNmzMDmzZuxbds2q2lNLo/BYIBWqxW1hkGDBuHw4cOIj483ffXs2RNPP/004uPjreaqqqCgAEql0vR/WrGEhobi4sWLZvsuXrwIPz8/kSoyt379esjlcgwfPlzsUgAAeXl5ZUYvpFIpDAaDSBWV5ejoCG9vb6hUKuzbtw9PPPGE2CUBANq0aQMvLy+zldELCgqQlJRUJyujN/krKLVabfqL1mAwICUlBadOnYKrq6to/4edPn06vv/+e6xduxYKhcI0juvo6AgnJydRagKAefPmITIyEj4+PlCr1di8eTMSEhKwceNG0WoCYPq8TGkODg5wdXUVdehxzpw5ePzxx+Hr62u6B5WXl4fo6GjRagKAyZMnIzIyEkuWLMHw4cNx6tQpfPnll3jjjTdErQsoGvpZs2YNhg8fXusW5Lry+OOP48MPP0SbNm3QqVMnnDp1CsuXL8fo0aPFLg379u2DwWBAQEAArly5gjfeeAMBAQEN2olc1e/QmJgYLF26FAEBAWjfvj2WLFkCR0dHjBgxotav3eTbzOPj4zF48OAy+6Ojo7FixQoRKkKF3XozZszArFmzGriaEjExMYiPj8ft27fh4uKCoKAg/Pe//0X//v1Fq6kigwYNEr3N/Pnnn8fhw4eRkZEBd3d3BAcHY/bs2ejUqZNoNRXbtWsX3nrrLVy8eBG+vr6YMGECXnzxxTq5L1Abv/76K4YMGYJ9+/ahd+/eotZSLCcnB++++y62b9+O9PR0eHl54emnn8b//ve/Mh10De2HH37A/PnzcfPmTbi6umLIkCGYM2cOWrRo0WA1VPU71Gg04v3338c333wDlUqF3r17Y8mSJXXyx2OTDygiImqceA+KiIisEgOKiIisEgOKiIisEgOKiIisEgOKiIisEgOKiIisEgOKmh2FQoH/+7//E7uMarty5QpGjBiBNm3a1Omim9euXbOaRTyJysOAojq3bt06KBQKeHp6ljv/29NPP42uXbuKUFnj9NJLL+H48eOYOXMmvvjiCzz44INVnvPLL78gKioK7du3h4eHBwICAjB69Gj89NNPDVBxEbVajQULFiA+Pr7BXpOaFgYU1RutVotly5aJXUajptfrkZSUhFGjRiEmJgZRUVGVTixsNBoxdepUREdHIyUlBRMnTsSyZcswZcoUZGdnY+zYsdi0aVOD1J6bm4uFCxeKvtQ8NV5Nfi4+Ek/Xrl2xdu1avPLKK2YzHTcHRqMRGo2m1lPlZGZmQq/XV3tqm08++QRr167FhAkTsHDhQkgkJX+DTps2Dbt37zZbdr0x0uv10Ov1VjNJMNUfXkFRvXnllVcAoMqrqMruhXTt2hUxMTGm7eLhw4SEBLz++uto3749WrdujSlTpqCgoAC5ubmYNm0a2rVrh9atW2P69OnQ6XTlvm5cXBxCQkLg5eWFsLCwcpdIv3PnDubMmYOuXbvC09MTXbp0wbx586DRaMyOK76v9eOPPyIsLAyenp7YsmVLpT93UlISBg8eDB8fH/j6+mLYsGH47bffTI8vWLAAAQEBAICFCxeWO2luafn5+fjggw8QEBCABQsWmIVTscjISPzrX/+q8DliYmLKHX4tft+vXbtm2nfy5EmMHDkS/v7+8Pb2Rvfu3fHiiy8iNzcX165dMy35Ubr20v+WqampePnll9GpUyd4enqiV69e+Oijj8xW/i3+38YHH3yA2NhY9OrVC56enqbVWn/44Qc8+uij8PPzQ+vWrREWFoaFCxdW+PNR48IrKKo3vr6++Pe//10vV1GzZs2Cu7s7ZsyYgZMnT2LdunVwcHDA1atXYW9vj9mzZ+PXX39FbGws2rVrh8mTJ5udf+TIEfzwww948cUX4eTkhNWrV2PMmDHYunWr6R5Pfn4+nnzySVy7dg3jxo3D/fffj9OnT+PTTz/FhQsXsH79erPnTEpKwtatWzFhwgR4eXlVuoxKYmIinnrqKbRq1QrTp0+HwWDAqlWrMGjQIOzYsQPBwcEYPHgw3N3d8dprr+HJJ58sd8LO0pKTk5GVlYVJkybBxqZ+/6+dnp6Op556Cm5ubnj55ZehUCiQkpKCX375Bbm5uXB3d8fixYvL1H7//fcDKFoTasCAAdDpdHj22Wfh7e2NpKQkvPnmm7h16xbef/99s9fbuHEj1Go1xo0bBycnJ3h7e+PgwYN4/vnnER4ejrlz50IqlUKpVOLw4cP1+rNTw2FAUb169dVXsX79eixbtqxO70e5ubkhLi7ONDv39evXERsbi5EjR+LLL78EAIwfPx4hISFYu3ZtmYA6e/Ysdu3aZVqzZsyYMejVqxfmz5+P3bt3AwA+++wzKJVKHDx40GwBwM6dO2P69Ok4fPgwwsLCTPvPnz+PQ4cOVWuV2NmzZ8PR0RF79+6Fu7s7gKLZofv06YM5c+Zg586d6NKlCzw8PPDaa68hKCgIUVFRlT7n+fPnARQtuFffjhw5gqysLMTFxaFnz56m/a+//rrp+yFDhlRY+zvvvAONRoPExER4enoCAJ577jl4e3vj008/RUxMjNmifNevX8fvv/8Ob29v076VK1fC2dkZcXFxVrEaNdU9DvFRvfLz8zNdRdXliq7PPPOM2dIRwcHBMBqNGDt2rNlxvXv3xpUrV8qc37NnT7MF1Vq2bImRI0fi6NGjUKlUAIqGj0JCQuDu7o6MjAzT1yOPPAKgaOmI0kJCQqoVTmlpaTh58iSio6NN4QQArVq1wogRI3DkyBFTDTWRk5MDAA2yzlLxa+zcuROFhYU1OtdoNGLr1q0YOHAgpFKp2Xvbv39/GAwGJCYmmp0zaNAgs3AqriE3Nxf79++v3Q9DVosBRfXu1VdfBVD1vaiasBwudHFxqXB/fn5+mXtG/v7+ZZ6zeN+NGzcAAJcuXcLBgwfh7+9v9hUcHAygaJirtMq660q7fv06AJQ7BNixY0cYjUZTDTVRHBrFQVWf+vXrh8GDB2PhwoVo164doqKi8M0330CtVld5bnp6OlQqFdauXVvmvR06dKjpmNLKe2/Hjx8Pf39/jBw5Ep07d8akSZOwY8cOs3tY1LhxiI/qXemrqOLGidIqW0SvomW3KxrSKa8xAECZX1rlvablMQaDAeHh4eXWDBRd8ZRmb29f7nE1UZtfrsXDkGfPnsWTTz55T89R0b+FZeefIAj49ttv8fvvv2Pnzp04ePAgpk2bhqVLl2Lfvn2mYbvyFP+bjhgxAs8880y5x7Rr185su7z31svLCwkJCThw4AD27t2Lffv2YcOGDYiIiMDGjRtFX5yRao8BRQ2i9L0oS66urgCA7Oxss/0ajQapqan1Us/FixfL7Cte1trPzw9A0Q19tVptGtKrK61btwYAXLhwocxjSqUSgiCYaqiJ0NBQKBQKbN68Ga+++uo93ZdRKBRl/h2Akqs+S71790bv3r0xe/Zs7NmzByNHjsSaNWswffr0CgPC3d0dLi4u0Ol0tX5vZTIZBg4ciIEDB8JoNGL+/Pn48MMPceTIEYSGhtbquUl8HOKjBlH6Kurvv/82e8zZ2Rnu7u5lZhxYuXJlvX1m58SJEzh69KhpOzMzE5s2bcIDDzxgauUePnw4jh8/jp9//rnM+fn5+dUaziqPl5cXevTogQ0bNiAjI8O0/9atW9i0aRNCQkIqbSeviL29PV555RVcuHABs2fPLvdqbO/evdi5c2eFz9GuXTvcuXMHf/zxh2mfWq3Ghg0bzI5TqVRlnr979+6mxwDAwcHBbLuYVCrFkCFDsH37dpw8ebJMDdnZ2dW6r5WZmWm2LQiC6R7gvdzDI+vDKyhqMMVXUefOnStzhTBu3DgsWbIEkydPxgMPPIATJ07g0KFDcHNzq5daAgMDERUVhYkTJ5razHNycjB37lzTMS+99BJ2796NsWPHYtSoUejduzc0Gg0uXryIH374wRRo9+Ldd9/FsGHDMGDAADz77LMwGo34+uuvUVhYiLfffvuef66XXnoJFy5cwOeff46EhAQMGzYM3t7eyMjIwJ49e5CQkIDY2NgKzx8xYgTmz5+PZ555BpMmTYJOp8PatWvh7u5u1uSyfv16xMbG4sknn8T999+P/Px8rFu3DlKp1HQfycnJCQEBAYiLi0P79u3RsmVLtGnTBsHBwZg3bx4SExPx+OOPY+zYsQgMDEROTg7Onj2Ln376CcePH4eXl1eVP2tmZibCw8Ph4+ODW7du4auvvoK3t3e1poMi68eAogbj5+eHMWPGYNWqVWUemz59OjIzMxEXF4cff/wRDz30ELZu3VrlZ3/uVUhICPr164f3338fV69ehb+/P9auXYt+/fqZjrG3t8e2bdvw0UcfIS4uDlu2bIGjoyPatm2LmJgY04do78WDDz6IrVu34r333sOiRYsgCAKCg4OxatWqew49oOgq4tNPP8UTTzyBVatWYcWKFcjOzoarqyuCg4Px3XffVfpBXYVCgbVr12L27NmYN28e7rvvPsTExMDFxQVTpkwxq//EiRP44YcfcPv2bTg7O6Nbt25YtGiRWf3Lly/HrFmzMGfOHGg0GkRHRyM4OBju7u7Yt28fFi9ejB07duCbb75BixYt0L59e8ycOdM07FuZUaNGYc2aNVi1ahVUKhU8PT0RERGBGTNmNEgnI9U/QaVSseWFiIisDu9BERGRVWJAERGRVWJAERGRVWJAERGRVWJAERGRVWJAERGRVWJAERGRVWJAERGRVWJAERGRVWJAERGRVfp/Yjapdj0kbxoAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of clusters:  [4475   16    2]\n",
+      "#clusters for this data:  3\n"
+     ]
+    }
+   ],
+   "source": [
+    "c = cluster_features(compound_df, 0, True)\n",
+    "print('#clusters for this data: ', len(c))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def feature_split(df, feature_list):\n",
+    "    \"\"\"\n",
+    "    Splits the clusters into train and test set such that the training set is approximately 80%.\n",
+    "\n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    df: pd.Dataframe\n",
+    "        Data set with fingerprints and their associated activity labels.\n",
+    "    feature_list: list of lists\n",
+    "        Each sublist contains the features for a molecule.\n",
+    "        Output of function cluster_features().\n",
+    "        \n",
+    "    Returns\n",
+    "    -------\n",
+    "        Lists:\n",
+    "            train and test set with their activity label.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    count=1\n",
+    "    cond = len(feature_list[0]) #set to the first cluster\n",
+    "    #if the train set is smaller than 80%\n",
+    "    while cond/len(df) <= 0.8:\n",
+    "        cond+=len(feature_list[count]) #append the next cluster\n",
+    "        count+=1\n",
+    "    train_ind = feature_list[:count]\n",
+    "    test_ind = feature_list[count:]\n",
+    "    train_index = [x for xi in train_ind for x in xi] #flat list of lists\n",
+    "    test_index = [y for yi in test_ind for y in yi] \n",
+    "    xtrain = df.loc[train_index].fp.tolist() #get fingerprints from dataframe at respective indices\n",
+    "    ytrain = df.loc[train_index].activity.tolist() #get activity labels from dataframe at respective indices\n",
+    "    xtest = df.loc[test_index].fp.tolist()\n",
+    "    ytest = df.loc[test_index].activity.tolist()\n",
+    "    return xtrain, ytrain, xtest, ytest"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "### 4. Results\n",
+    "#### 4.1 Performace on random selected sets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fit model on single split with train/test split of 80.0% to 20.0%\n",
+      "\n",
+      "======= \n",
+      "Model_RF\n",
+      "accuracy:  0.814238042269188\n",
+      "sensitivity:  0.8921568627450981\n",
+      "specifity:  0.712082262210797\n",
+      "AUC score:  0.8953223448762538\n",
+      "\n",
+      "======= \n",
+      "Model_SVM\n",
+      "accuracy:  0.8275862068965517\n",
+      "sensitivity:  0.9098039215686274\n",
+      "specifity:  0.7197943444730077\n",
+      "AUC score:  0.8846212006653561\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Divide the set into training and test set for random split\n",
+    "fingerprint_model = compound_df.fp.tolist()\n",
+    "label_model = compound_df.activity.tolist()\n",
+    "test_size=0.2\n",
+    "x_train, x_test, y_train, y_test = random_split(fingerprint_model, label_model, test_size)\n",
+    "print(f\"Fit model on single split with train/test split of {round((100-test_size*100),2)}% to {round(test_size*100,2)}%\")\n",
+    "for model in models:\n",
+    "    print(\"\\n======= \")\n",
+    "    print(f\"{model['label']}\")\n",
+    "    model['model'].fit(x_train, y_train)\n",
+    "    # Calculate model performance results\n",
+    "    accuracy, sens, spec, auc = model_performance(model['model'], x_test, y_test, False)\n",
+    "    print('accuracy: ',accuracy)\n",
+    "    print('sensitivity: ', sens)\n",
+    "    print('specifity: ', spec)\n",
+    "    print('AUC score: ', auc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10-fold Cross Validation performance: \n",
+      "\n",
+      "======= \n",
+      "Model_RF\n",
+      "Mean accuracy: 0.83 \tand std : 0.01 \n",
+      "Mean sensitivity: 0.88 \tand std : 0.02 \n",
+      "Mean specificity: 0.77 \tand std : 0.03 \n",
+      "Mean AUC: 0.90 \tand std : 0.01 \n",
+      "\n",
+      "\n",
+      "======= \n",
+      "Model_SVM\n",
+      "Mean accuracy: 0.85 \tand std : 0.01 \n",
+      "Mean sensitivity: 0.90 \tand std : 0.02 \n",
+      "Mean specificity: 0.77 \tand std : 0.03 \n",
+      "Mean AUC: 0.90 \tand std : 0.02 \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"{N_FOLDS}-fold Cross Validation performance: \")\n",
+    "models_acc=[] #store accuracy per fold \n",
+    "models_method=[] #store model and evaluation method\n",
+    "for model in models:\n",
+    "    print(\"\\n======= \")\n",
+    "    print(f\"{model['label']}\")\n",
+    "    acc,_,_,_ = cross_validation(model[\"model\"],compound_df, n_folds=N_FOLDS)\n",
+    "    models_method.append((f\"{model['label']}+random CV\"))\n",
+    "    models_acc.append(acc)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "#### 4.2 Performace on Time-split CV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Sort the dataframe by document year in ascending order and reindex the row numbering into continuous numbers.\n",
+    "compounds_set_time = compound_df.sort_values(by=['document_year'])\n",
+    "compounds_set_time = compounds_set_time.reset_index(drop=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "#### Naive Time-split CV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10-fold (naive) Time-Split Cross Validation performance: \n",
+      "\n",
+      "======= \n",
+      "Model_RF\n",
+      "Mean accuracy: 0.76 \tand std : 0.04 \n",
+      "Mean sensitivity: 0.82 \tand std : 0.04 \n",
+      "Mean specificity: 0.65 \tand std : 0.11 \n",
+      "Mean AUC: 0.80 \tand std : 0.05 \n",
+      "\n",
+      "\n",
+      "======= \n",
+      "Model_SVM\n",
+      "Mean accuracy: 0.73 \tand std : 0.08 \n",
+      "Mean sensitivity: 0.74 \tand std : 0.10 \n",
+      "Mean specificity: 0.70 \tand std : 0.12 \n",
+      "Mean AUC: 0.79 \tand std : 0.05 \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"{N_FOLDS}-fold (naive) Time-Split Cross Validation performance: \")\n",
+    "for model in models:\n",
+    "    print(\"\\n======= \")\n",
+    "    print(f\"{model['label']}\")\n",
+    "    acc,_,_,_ = naive_timesplit_CV(model[\"model\"], compounds_set_time, n_folds=N_FOLDS)\n",
+    "    models_method.append(f\"{model['label']}+Time-split CV (naive)\")\n",
+    "    models_acc.append(acc)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "#### Time-split CV for fixed split points"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10-fold Time-Split Cross Validation performance: \n",
+      "\n",
+      "======= \n",
+      "Model_RF\n",
+      "Mean accuracy: 0.71 \tand std : 0.04 \n",
+      "Mean sensitivity: 0.77 \tand std : 0.07 \n",
+      "Mean specificity: 0.64 \tand std : 0.09 \n",
+      "Mean AUC: 0.77 \tand std : 0.04 \n",
+      "\n",
+      "\n",
+      "======= \n",
+      "Model_SVM\n",
+      "Mean accuracy: 0.69 \tand std : 0.06 \n",
+      "Mean sensitivity: 0.70 \tand std : 0.10 \n",
+      "Mean specificity: 0.68 \tand std : 0.11 \n",
+      "Mean AUC: 0.76 \tand std : 0.04 \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"{N_FOLDS}-fold Time-Split Cross Validation performance: \")\n",
+    "for model in models:\n",
+    "    print(\"\\n======= \")\n",
+    "    print(f\"{model['label']}\")\n",
+    "    acc,_,_,_ = timesplit_CV(model[\"model\"], compounds_set_time, n_folds=N_FOLDS)\n",
+    "    models_method.append(f\"{model['label']}+Time-split CV\")\n",
+    "    models_acc.append(acc)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "#### 4.3 Performace on rational selection\n",
+    "\n",
+    "**1) Butina Clustering**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of largets cluster:  52\n",
+      "Number of Singletons:  989\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Convert fingerprints to list\n",
+    "df_fingerprints = compound_df.fp.tolist()\n",
+    "\n",
+    "# Run the clustering procedure for the dataset\n",
+    "clusters = cluster_fingerprints(df_fingerprints, cutoff=cut_off)# user-defined cut-off for similarity"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fit model on cluster-based split with train/test split of 77.99% to 22.01%\n",
+      "\n",
+      "======= \n",
+      "Model_RF\n",
+      "accuracy:  0.7573306370070778\n",
+      "sensitivity:  0.8824742268041237\n",
+      "specifity:  0.6369047619047619\n",
+      "AUC score:  0.8593110783832433\n",
+      "\n",
+      "======= \n",
+      "Model_SVM\n",
+      "accuracy:  0.7714863498483316\n",
+      "sensitivity:  0.8762886597938144\n",
+      "specifity:  0.6706349206349206\n",
+      "AUC score:  0.8475515463917526\n"
+     ]
+    }
+   ],
+   "source": [
+    "butina_xtrain, butina_ytrain, butina_xtest, butina_ytest = fingerprint_split(compound_df, clusters)\n",
+    "testsize = len(butina_ytest)/(len(butina_ytest)+len(butina_ytrain))*100\n",
+    "print(f\"Fit model on cluster-based split with train/test split of {round(100-testsize,2)}% to {round(testsize,2)}%\")\n",
+    "butina_models=[]\n",
+    "butina_performance=[]\n",
+    "for model in models:\n",
+    "    print(\"\\n======= \")\n",
+    "    print(f\"{model['label']}\")\n",
+    "    butina_model = clone(model[\"model\"])\n",
+    "    butina_model.fit(butina_xtrain, butina_ytrain)\n",
+    "    butina_models.append(butina_model)\n",
+    "    # Calculate model performance results\n",
+    "    accuracy, sens, spec, auc = model_performance(butina_model, butina_xtest, butina_ytest, False)\n",
+    "    butina_performance.append([accuracy,sens,spec,auc])\n",
+    "    print('accuracy: ',accuracy)\n",
+    "    print('sensitivity: ', sens)\n",
+    "    print('specifity: ', spec)\n",
+    "    print('AUC score: ', auc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>RF Butina Clustering</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.757331</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sensitivity</th>\n",
+       "      <td>0.882474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>specificity</th>\n",
+       "      <td>0.636905</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>auc</th>\n",
+       "      <td>0.859311</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             RF Butina Clustering\n",
+       "accuracy                 0.757331\n",
+       "sensitivity              0.882474\n",
+       "specificity              0.636905\n",
+       "auc                      0.859311"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#store results of models\n",
+    "df_results_RF = pd.DataFrame(butina_performance[0])\n",
+    "df_results_SVM = pd.DataFrame(butina_performance[1])\n",
+    "df_results_RF.index=['accuracy','sensitivity','specificity','auc']\n",
+    "df_results_SVM.index=['accuracy','sensitivity','specificity','auc']\n",
+    "df_results_RF.columns = ['RF Butina Clustering']\n",
+    "df_results_SVM.columns = ['SVM Butina Clustering']\n",
+    "df_results_RF"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "**2) K-means**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Size of clusters:  [3484    1    1    4    1   19    1    4   28    8    1    2    6   29\n",
+      "    4    2   94    1    4    9  215   36   53    1    1    1   10  459\n",
+      "    5    7    2]\n",
+      "Fit model on cluster-based split with train/test split of 80.01% to 19.99%\n",
+      "\n",
+      "======= \n",
+      "Model_RF\n",
+      "accuracy:  0.7962138084632516\n",
+      "sensitivity:  0.8666666666666667\n",
+      "specifity:  0.6305970149253731\n",
+      "AUC score:  0.8238480217957831\n",
+      "\n",
+      "======= \n",
+      "Model_SVM\n",
+      "accuracy:  0.821826280623608\n",
+      "sensitivity:  0.9063492063492063\n",
+      "specifity:  0.6231343283582089\n",
+      "AUC score:  0.8250799573560768\n"
+     ]
+    }
+   ],
+   "source": [
+    "num_clusters = 31\n",
+    "features = cluster_features(compound_df, num_clusters)\n",
+    "kmeans_xtrain, kmeans_ytrain, kmeans_xtest, kmeans_ytest = feature_split(compound_df, features)\n",
+    "testsize_ = len(kmeans_ytest)/(len(kmeans_ytest)+len(kmeans_ytrain))*100\n",
+    "print(f\"Fit model on cluster-based split with train/test split of {round(100-testsize_,2)}% to {round(testsize_,2)}%\")\n",
+    "kmeans_models=[]\n",
+    "kmeans_performance=[]\n",
+    "for model in models:\n",
+    "    print(\"\\n======= \")\n",
+    "    print(f\"{model['label']}\")\n",
+    "    kmeans_model = clone(model[\"model\"])\n",
+    "    kmeans_model.fit(kmeans_xtrain, kmeans_ytrain)\n",
+    "    kmeans_models.append(kmeans_model)\n",
+    "    # Calculate model performance results\n",
+    "    accuracy, sens, spec, auc = model_performance(kmeans_model, kmeans_xtest, kmeans_ytest, False)\n",
+    "    kmeans_performance.append([accuracy, sens, spec, auc])\n",
+    "    print('accuracy: ',accuracy)\n",
+    "    print('sensitivity: ', sens)\n",
+    "    print('specifity: ', spec)\n",
+    "    print('AUC score: ', auc)\n",
+    "#add new column to dataframes of the performance of the models\n",
+    "df_results_RF['RF K-means Clustering'] = kmeans_performance[0]\n",
+    "df_results_SVM['SVM K-means Clustering'] = kmeans_performance[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "Create test set with random split method with same ratio for rational split from Butina Clustering"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fit model on single split with train/test split of 80.0% to 20.0%\n",
+      "\n",
+      "======= \n",
+      "Model_RF\n",
+      "accuracy:  0.8068756319514662\n",
+      "sensitivity:  0.8835978835978836\n",
+      "specifity:  0.7037914691943128\n",
+      "AUC score:  0.8855788761002031\n",
+      "\n",
+      "======= \n",
+      "Model_SVM\n",
+      "accuracy:  0.8220424671385238\n",
+      "sensitivity:  0.9065255731922398\n",
+      "specifity:  0.7085308056872038\n",
+      "AUC score:  0.8812720980967428\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Divide the set into training and test set for random split\n",
+    "fingerprint_model = compound_df.fp.tolist()\n",
+    "label_model = compound_df.activity.tolist()\n",
+    "static_xtrain, static_xtest, static_ytrain, static_ytest = random_split(fingerprint_model, label_model,(testsize/100))\n",
+    "print(f\"Fit model on single split with train/test split of {round((100-test_size*100),2)}% to {round(test_size*100,2)}%\")\n",
+    "static_models=[]\n",
+    "static_performance = []\n",
+    "for model in models:\n",
+    "    print(\"\\n======= \")\n",
+    "    print(f\"{model['label']}\")\n",
+    "    static_model = clone(model[\"model\"])\n",
+    "    static_model.fit(static_xtrain, static_ytrain)\n",
+    "    static_models.append(static_model)\n",
+    "    # Calculate model performance results\n",
+    "    accuracy, sens, spec, auc = model_performance(static_model, static_xtest, static_ytest, False)\n",
+    "    static_performance.append([accuracy, sens, spec, auc])\n",
+    "    print('accuracy: ',accuracy)\n",
+    "    print('sensitivity: ', sens)\n",
+    "    print('specifity: ', spec)\n",
+    "    print('AUC score: ', auc)\n",
+    "#add new column to dataframes of the performance of the models\n",
+    "df_results_RF['RF static Clustering'] = static_performance[0]\n",
+    "df_results_SVM['SVM static Clustering'] = static_performance[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### 5. Discussion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### 5.1 Cross Validation methods"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Distribution of train/test split done in naive and modified time-split CV over years for each fold (n folds=3).\n",
+    "The histogram shows, that the intersection year between train and test set will be assigned to the majority of one of the sets. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data selection in time-split CV (naive)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1296x360 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_time, test_time = naive_timesplit_CV(model_RF, compounds_set_time, n_folds=3, get_sets=True)\n",
+    "plot_cv_data(train_time, test_time, 3, 'Data selection in time-split CV (naive)')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data selection in time-split CV (split by years)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1296x360 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_time, test_time = timesplit_CV(model_RF, compounds_set_time, n_folds=3, get_sets=True)\n",
+    "plot_cv_data(train_time, test_time, 3, 'Data selection in time-split CV (split by years)')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Accuracy of Cross Validation methods per fold."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy per fold\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1296x360 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_cv_accuracy(models_acc, models_method, 'Accuracy per fold')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "In time-split CV, the data is partitioned relative to the number of folds.\n",
+    "\n",
+    "\n",
+    "* The performance on random split is much better than for time series splits, which seems compared to the others to be very optimistic.\n",
+    "* In random CV the data samples are shuffled and thus more homogenously distributed.\n",
+    "* More structural diverse molecules were published at a specific year.\n",
+    "\n",
+    "A large difference in the performance of both time-based splitting methods could indicate:\n",
+    "* Split ratio in train and test set was nearly 50% (if number of samples in test set is low, it is crucial for the predictive performance)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### 5.2 Single Random vs. Cluster-based Split"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Since it is not guaranteed that both clustering methods will generate the same test size, the main aim was to set the cut-off for Butina Clustering and the number of cluster centers for K-means such that the train/test split ratio is as close as possible for this data set. \n",
+    "\n",
+    "This resulted in test sizes of\n",
+    "* 22.01% for Butina clustering\n",
+    "* 22% for random single split\n",
+    "* 19.99% for K-means clustering\n",
+    "\n",
+    "the maximal deviation between the sets is therefore 2.2%."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>RF Butina Clustering</th>\n",
+       "      <th>RF K-means Clustering</th>\n",
+       "      <th>RF static Clustering</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.757331</td>\n",
+       "      <td>0.796214</td>\n",
+       "      <td>0.806876</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sensitivity</th>\n",
+       "      <td>0.882474</td>\n",
+       "      <td>0.866667</td>\n",
+       "      <td>0.883598</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>specificity</th>\n",
+       "      <td>0.636905</td>\n",
+       "      <td>0.630597</td>\n",
+       "      <td>0.703791</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>auc</th>\n",
+       "      <td>0.859311</td>\n",
+       "      <td>0.823848</td>\n",
+       "      <td>0.885579</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             RF Butina Clustering  RF K-means Clustering  RF static Clustering\n",
+       "accuracy                 0.757331               0.796214              0.806876\n",
+       "sensitivity              0.882474               0.866667              0.883598\n",
+       "specificity              0.636905               0.630597              0.703791\n",
+       "auc                      0.859311               0.823848              0.885579"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_roc_curves_for_singlemodel([static_models[0], butina_models[0], kmeans_models[0]], \n",
+    "                                [static_xtest, butina_xtest, kmeans_xtest], \n",
+    "                                [static_ytest, butina_ytest, kmeans_ytest], \n",
+    "                                ['Static Split','Butina Split ','K-means Split'],\n",
+    "                                'ROC Curve Plot for RF');\n",
+    "df_results_RF"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Based on the prior results it is to be expected that the random split shows for both RF and SVM the best performance. \n",
+    "\n",
+    "* Accuracy of the models is higher for K-means clustering: The sum of the True Postivies and True Negatives (correct predictions) is therefore higher.\n",
+    "* AUC value of the models is higher for Butina clustering: The higher auc value indicates that the models tend to better differentiate the samples of the two classes.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SVM Butina Clustering</th>\n",
+       "      <th>SVM K-means Clustering</th>\n",
+       "      <th>SVM static Clustering</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.771486</td>\n",
+       "      <td>0.821826</td>\n",
+       "      <td>0.822042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sensitivity</th>\n",
+       "      <td>0.876289</td>\n",
+       "      <td>0.906349</td>\n",
+       "      <td>0.906526</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>specificity</th>\n",
+       "      <td>0.670635</td>\n",
+       "      <td>0.623134</td>\n",
+       "      <td>0.708531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>auc</th>\n",
+       "      <td>0.847552</td>\n",
+       "      <td>0.825080</td>\n",
+       "      <td>0.881272</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             SVM Butina Clustering  SVM K-means Clustering  \\\n",
+       "accuracy                  0.771486                0.821826   \n",
+       "sensitivity               0.876289                0.906349   \n",
+       "specificity               0.670635                0.623134   \n",
+       "auc                       0.847552                0.825080   \n",
+       "\n",
+       "             SVM static Clustering  \n",
+       "accuracy                  0.822042  \n",
+       "sensitivity               0.906526  \n",
+       "specificity               0.708531  \n",
+       "auc                       0.881272  "
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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ajcyfP5+2bdvy6KOPUrduXex2O0eOHGH//v2oVCpmzZrl0vvrww8/RKlUsnjxYpo3b07Lli2pX78+fn5+xMbGsn//fi5duuRxOKfq1auzefNmXnzxRSZNmsTnn39O27ZtKVeuHEajkTNnznDgwAHMZjMdOnTIvK5fv34sXLiQjz76iD///JO6dety+fJlvv/+e7p06eIggN7y7LPP8v777zNr1iwsFgvDhg1z6R4+duxYTp06xcqVK9m5cydt2rShfPny3L59m0uXLhEdHc2gQYNcHnLPD/z9/fn000958cUX6datG126dKFy5cqcPHmSnTt3EhQUxKJFixyW+Nq3b8+CBQuYPHkyp0+fzpwBjx07Ntd2NG3alKioKObOnUuLFi3o1q0bgYGB7N69m2PHjlGnTh0mTJiQ5/cLcO7cOd5++22Cg4Np0aIFVatWRaVS8c8//7Bjxw4SExOpVq2a27N3LVu2pFatWpkPH88//3yODiJZadCgwT37jIsLQtQETgwaNIhPP/2UzZs3M2rUqMwlIUmSmDRpEt26dWPx4sXs378/89xS+fLleeWVVxgyZIjbczYZgtevXz+WL1/OgQMHOHr0KCaTiZCQEBo0aMAbb7yRozv03TRq1IhDhw7xv//9j+3bt7Nr1y4SEhLQarVEREQwYMAA+vfv77C0ExISwrZt25g4cWLme6hbty7Lly8nKCgoT6IWFhbGY489lhnb0F1UC5VKxcqVK9m4cSOrV6/mxx9/JCUlhVKlSlGxYkVGjx7Nc889l2s7csMTTzzBzp07mTt3Lr/88gtbtmwhNDSUPn36MG7cOCpXruzQvm3btnz44YcsX76cJUuWZC7x5kXUACZOnEiDBg344osvWL9+PSaTiYiICMaMGcPIkSOzXRb0hmeffZbAwED27NnDyZMn+e2330hJSaFEiRLUrl2bzp078/LLL+Pv7++2j/79+2c652TM3AQFi5SQkCAXtBECgUAgEPgCsacmEAgEgiKDEDWBQCAQFBmEqAkEAoGgyCBETSAQCARFBiFqAoFAICgyCFETCAQCQZFBiJpAIBAIigxC1HLA2/QfRR1xP5wR98QRcT8cEffDmfy8J0LUBAKBQFBkEKImEAgEgiKDEDWBQCAQFBkKVNT279/Pc889R+3atQkODmb16tU5XvPnn3/SuXNnwsPDqV27NjNnzkSWRfhKgUAgEBSwqKWmplKnTh1mzJiBXq/PsX1SUhLdu3enTJky/Pzzz8yYMYOPP/6YhQsX3gNrBQKBQFDYKdDUMx07dqRjx45AenLKnFi/fj0Gg4FFixah1+upU6cO586d49NPP2XEiBE+TecuEAgE3uBuxUiWwWKX2R9j4u9Um1O9JFtRyP+VK2UjpU2nUMmGfLO1IPBLuk2JhJuoy9SGkPzL8n1f5VM7dOgQLVq0cJjVdejQgWnTpnHlyhWnfE8CgUCQgWxJJjH2D/5OTiNDfg7EmNDKqbTne2KkCoD3D8Y2WSbRLGO0ut8GOf1voveAu8okSaaD/oTX493XBED85XNYhailc/PmTcqVK+dQFhoamlknRE0gKB7IdivWhBPEJd3mttHOnOMpKCUI0vwnShHKGNprfueOHEgj9VkA1EDlu/qpctf/S8m3c2+Q5t9/ghyRZBmlMS3f+r+vRA1wWmLMmPJnt/SY14N+4vCkI+J+OCPuiSPe3A9ZBrubOsmeRszN3wg1HeIfWxlApoXmWGZ9iX//LSztvv8q3PDYFoEPkWVw8btc7s5VrpqNefqbqV69utu6+0rUypQpw82bNx3Kbt9Of7rKmLG5IrsbkBPnz5/P0/VFDXE/nBH35D9MNpnvjv5F6bLl3bbZftVIYspt6qou8OetBBprLhKkcH5yL61MopnuPBUAlBCh/Cf/DC8kmP+d7imxosTOOakeiZTCz5xKcNodJP5b4iyVGkdw2p2CMtU9sozmWDy6n2+QPLgWsr+jzFjTArEElsq3v5n7StSaNm3KpEmTMBqN6HQ6AHbv3k3ZsmWJiIgoYOsEgvufG2k2DNnsDR25bWbjJQPbrxop56dAumsP6o7ZTppVBnRwPC6zXIWVGSH/o5vfIfQKMw9Dut+1HQjJr3eSPbsM9VFrAgFIscqE6hRU0dzhml8bTMpgADSGZJQ2q0f96VQKqgep8FM5z0xiY2MJCwv7r0CWUZ45CmkpIKXfQ6UlGIXdcf1SSk2m9YGduXyHvkX2C3AsMBmRbFbMHXuBn39msXTzNur/bUR58i8ASvyiJ23x0v+u1+pQqtSQjysbBSpqKSkp/PVX+pu32+1cv36d48ePU7JkSSpWrMj777/P4cOH2bp1KwC9evVi5syZDBs2jDFjxnDhwgXmz5/PuHHjhOejQJADdlnG9q9e/XjdyLIzqaRY0gtSrTIn4i1e9fdPmvOi4QOqGJpoz1NJdZvnAn4lXJWYZ7tz4pKlDKetD2C0yzQvoyFEd9dJJVlGYb6NMewp7KpArAG1CNL70cVmRHH1ApL9P69DxeVz1Nq1A5QqlOeO+8y+IJ/15BtslaqhuHMLe9kILG07Z9vWXr4y9iq1cu7UbEb78cdoZ81BMhozi1V7DqA4fwlby5Z5NdtjClTUjhw5wtNPP535evr06UyfPp0+ffqwaNEiYmJiuHTpUmZ9UFAQmzZtYsyYMbRr147g4GCGDx/OiBEjCsJ8gaBAsNpljsdZSDS724mC/bFm/rhlJkSnwC7Dxku5cw9XYaWc6g6VVLfwk0yZ5QEKI/0DdnPNVjpzQayH/8FcjeEpCXZ/bpQdjE6tQZaUpOmrU8I/hDrBKuplfai1WtAtnITy/AnsJUOB/wI7KK9dzFc7CxJro0ecC80mZL8AzM8ORi4d7vMxlfv3o4+KQnn2rFOdrFajPHPmnoqalJCQIMJxZIPYL3FE3A9nsrsnCSY7t43OZ5NsMnxzyYDJJqO46/dYlmHeiRQAyvo5x0Yw2yDO5F7MvCVAMjA2eBODAncBYJQdn3PV2FBK+fsTcT6oF6Eh1QjzU7puIKlQBtVB0riY8xjSwGpGdegXdCvnASDr/ZEMqfloccFifrwHSP9+N2Q7sn8glo49wb/EPbVDiotDN3EiGjeRoKytWmGYNw97jRpOdfn5O3Jf7akJBIUVi13Gftdv//UUG42/ic1FTzLVVDeopLrt2iVQglD/RHr4R/OPrVRuzc3kmYADDq91kmd7SLlCUqEs3QxtnbFISl1mccO728gyUsw1VCf/D+Wpw8i6jP2a3Y5dpSWjOvqb62F8LGiyUoVcMhv3yhywWCyo1WqncsXtGGy1HsTauHX24+v8sDVohhxcQBuQWZFl1F99hW7CBBTx8U7V9lKlME6diqVPH5fej/mNEDWBwAV/JVm5lJzzD/y6i2msvegH+zzzzKuousUDqlge0v5FQ81lbtsdn677BOzLlb2FEU3NkUhKHZI+HEVgDUBCkhRgtaI4dxwpKQH13u0obv6DXCIYTAaUV+790QhbtXrIqvSfQslmRUpJwtx9ALJfCWzV6oDeP4cesqcorW4ozp5FHxWFav9+l/Xm55/HOHkycqm8P3DlFiFqgmJJotnOrutGDt40o8/isfbRyRSHWVdeUWAnXHmHd0puoJv/Id91fI+QNCWR9GWR1CXIGnHDnnYdVfhjKBMtqH77CSklCTnNji5Bg/Ttche9ySjibzkX37iaL7YDWOs1wfzsYGdL9P7pe0zCycwjtHPmoJ0xA8ni7FBkq1kTw7x593TvzB1C1ARFHqNVZmx0AtuvGqkSqOT/bnnn5ecNOsnERyFLifQ/zB2bHwD+ChMayXlfrbChCu+AptoroPQDqxnpThxIEpL078+EbEe9fyekJIHi3z0dezCaRZ8VnNFZsFWqiumFkdgrPJBeoPcXouUjZJXKSdBknQ7TuHGYRowATeEIqSJETVAk+S3WxJoLaSSbZTZd/s/zL+6W75wsMghVJNK3xF6aas/zqP7PzPKSyryHAlKGNHFdIcvYUy+jrtgD1AGu23iAlJSA6nYaup9+g8B42PEhqqMHcr7wHmEvFYq5+0BQuHYikbVabLUfgoDC5jhf9DAPG4Zm7VqUp04BYHnsMQyzZyMXsvCEQtQERY4ryVa67biNyUeTo/bltC7LtRhprdhLf+XKXPWrCKyFbDOirtiVrMt6Cn1ZFMH10/egPEC6HYPy7HG467Cw8uwxVL/9hL2s68AEyut/5cpuX2IPLo29XCXsZSthbdouvVClwl6pGmhc33dBAaFWY5g3D78BAzB+8AGWbt0K5SxYiJqgSHEuwULTTTdzbngXSgnefijQwbUeoFKAkqci9GiV6RW2hD8x/Tkd2ZSLwLfqIBS6MFD5o9CFoo54FoWf+1BSmAyQmu7ar4i9jur4wXR/f1lGvW0Nks2KrEtf3pRyCA57r8XrcteXCW3bMYdWUrpHoaJAUzoKsqA4cQLtRx9hWLgQtM4PFbZmzUg+etRlXWFBiJrgvsVolVn4Zwon4s3cMcnsvWHK8RqtEr59ojQSElUDlZTSuTkblQVb0lmMf7zhlX3KMm3Q1hgGshL1wX2o9v2K7OcPGIAVLq+RzCZU/7fXo/5zEjNfYQ8t6/BacesG1npNsD3YPLNMVqqw1W6IXC6CO+fPUzokLGs3gsJMSgq6GTPQLFqEZLNhr1YN0/jxrtsWYkEDIWqC+5QDMSY6f+/ZjClcr+CDpkHUKqmmTknn80KeYIs/4lE7SVsG9QMvoCzVCIU2BMWls/hNcva8K4zYQ8ti6dQb+7+CJIeUwV6xqphNFXFU27ejHzcOxfXrmWXauXOx9OqFvWrVArQsdwhRE9x3nEmweCxooToFW58oTY1g78VMlmVkww3shhtY/lqRbVtJE4K29hsoghugvHgK5bFdKM8cQ3XE9Xme/MTS4jFQ/ft+7XZQKrG07wpK13/u9tJhkDVgraDII12/jn7cONTbtzvXmUyov/kG09ixBWBZ3hCiJrivkGWZj0+meNR2SpNAXq0dkLkn5tU4dium4+9hiz/ssl4Vbyf4JzOSBRRWgL+BKK/H8cgW/xKQlook2zFH9kHW6NK9H6vUxFazwX8NlSrhXCHIGasVzWefoZs+HSnVOfqKvUIFDB9+iLVz9sGOCytC1ASFHqtd5oWf4/n5H6Nbj8aIACXvPxyEv1qieZiGEmrvl8xkSxLW2D3IpnhsCSexJ55021Z/xoYydzGCMQ4cA+oczvSo1NhqNig8oZEERQLl4cPoR41CeeKEU52sVGIeNgzj+PEQcP/O3IWoCQo1VrtM6S+zD0HVvbKe5e3yFpZHlmXSfnsZrMk5tlXdsaO77P15AeOrb2NtlZNXoECQDyQmopsyBc3SpUiyc7gca5MmGObOxV6/fgEY51uEqAkKLQkmO312xeXY7tlq+lyPIVsN2NOuYvy/kTm2VcXb8fvTiv6v/w5wy5ICkMl6zkyS09uYO/UGnR5zZF/Q6hAI7jXqTZvQvfkmiljnANtyYCDGSZMwDxhQZByChKgJCh030mycvmOhx87sBS1QIzGzWTBPVPRc1KTbMah3bcZiOUdKuVMeXxf0sxndtXShktUa7OUiMLzzMWh1RSpgraDoofz1V5eCZu7VC+O0achhRev4hRA1QYFis8skW2QO3jTz7E85z8oALvYJp6RWgcLbaAayjP7DMZg1/5DSPuc4df5HLEh2UMfa0dySMXfsibnfa96NKRAUMMaJE1F/+y2KW+mBpG1VqmCcMwdr+/YFbFn+IERNUGDMPpbM1D+SPG6vkuDbJ0sT4uGBaQBSk1EdOYCUdAc54Sp3mt7EWipnQQtda0RhBFutBzG/PICUilUhINDzcQWCwkJwMMYPPkA/bBimUaMwRUWBPvdL9oUdIWqCfCUmzcbmywZOxFvwvyvFy9qLaSSaPc/v0jJMw9JHS1HWXXbkrFjMcPsG8obBpIXasZRRQDiA+30DVbwdzd92Ao5YkctGkDJ5cc5eigJBIUCKj0e9ejXmESNcxmO09OqFtWlT5AjXcUCLEkLUBPmCXZZpufkmZxLylkm5UWk1UQ1K8FSE+ydLKekO6q2rUNz8GwDVsWgA0mopSW6mJjshkwgkQPMMCikQuVoAtqcfImVM09MAACAASURBVFVbdJ9iBUUMWUa9Zk16Fuq4OOTQUCzPPefcTpKKhaCBEDVBPuCJG74r2pTVUjFASZcIPa3LavBT5eyNJSXE4T+yp8s6S0j2e24BiS2Qu7+HHfB9QhqBIH9RnDuHfvRohyzUunffxdqpE3LJkgVoWcEiRE3gE1ItdlacS+OdQ4m5uv6vPuEeBReW/rmC6vA+JJMB5emjKC+4PyCdXVoMP9XTyF2H5MZUgaBgMRjSs1AvWOCUtFNx+zaaTz7B9O67BWRcwSNETeAThv56h61XjNm2qRigZFidAAetCdMr6FhBh38OEUCk+FsoLp5Cv/C9HG2xhEjceUyDrHMUNVWZjmhqvoKkLpFjHwJBYUS1eze6qCiUly451ck6HaaxYzG9Vrw9dIWoCfKM0SrnKGi3+5dDlTVhmQeo9nyHbvlsz215fjiJyhWAc8QPRUg9IWiC+xIpNhbdO++g2bDBZb2lQweMs2djr1LlHltW+CgaR8gFBUrrre6TcnaqqOPOgNwJmvLUHx4Lmq10GIlzZpOoXIorQQNQ+FXy2gaBoECx29EsW0aJJk1cCpo9LIy05ctJ27BBCNq/iJmaIE903n6L84nOHo47I0vzUGkN6lyIGQB2G/qZ2Ue9t5cOw9ImEnNICmnmrXDc/T6CuupLKAJr5s4WgaAAUJw4ke4I8n//51QnSxLmQYMwvvsuBAUVgHWFF69ETZZltm7dyq+//sqtW7cYP348derUISkpiX379tGkSRNCQ0Pzy1ZBISHVYmfWsWTmn3CdAqZrZR1Ny+Q+BYry9BH0M0a7rbdVq4u1XhPMXV7AculLLFe3um2rCKiKrslCJG+jjwgEBYxu6lSXgmarXx/D/PnYGjcuAKsKPx6LWnJyMs888wzR0dFoNBosFgsvvfQSAH5+fkRFRfH888/zbjH2uikujP4tgXUX3eddWf5o7iPmS3E33QqaqfcrWJ7ql/nacmEplqvrs+sNbf2JQtAE9yWGmTNR/fILkjF9v1r298f49tuYBw8GlVhkc4fHe2qTJ0/m6NGj/O9//+PkyZPId6UvUKlUdOnShZ07d+aLkYKCxS7LrDyXypxjyTTZ55etoF3oE+59TMa70H/4hts6S8demf+33votW0HTPjgV//bfo9AXrWCtguKDXLkypnHjALBERpJ88CDm4cOFoOWAx3fnu+++Y9CgQTz11FPEx8c71VetWpV169b51DhBwZJqsbPqfBrjD3p29iz2xXK5yjLtgNnZi9LS+klMg8Y7lLlL4KlrNBtlcL282SAQ3CusVlS//IK1QweX1aYRI7A9+KDbeoEzHotafHx8tuk1JEnCZDL5xChBwZNmtfP4tlucupNzmKuTvcOoEJCHp0dZRv39WtR7vkMRf8uhytRvhMMMDUC2mbFc3ejUje6hmULQBPcNd2ehTtm2DVurVs6NNBohaF7i8S9RhQoVOHv2rNv66Ohoqlat6hOjBAXPrr9NHgna9idL503QbFZ0C99D9cd+l9XWB1s4lZkvLnEqU1fqibLkg7m3QyC4VyQmops6Fc2SJZlZqPVRUaT8+itoRADtvOLxr1GvXr345JNP6NatW6Z4ZWzAf/nll2zevJnJkyfnj5WCe0KS2c7Le+K5abRzLM7isk2Y1k73qiVoFa7l6WyCDLtDSogDYxqqw/vQrvs8x/Zyacc9MVm2Y73u7O0o+VXw2haB4J4iy+lZqN96yylpp/LsWbSffIJptHuvX4FneCxqUVFRREdH8+STT1K7dm0kSWLChAncuXOHa9eu8fjjjzNs2DCvDViyZAkfffQRsbGx1KpVi+nTp9OyZUu37devX8+CBQu4ePEiJUqU4NFHH2XKlCmEFbHsrfeaRLOdiNU3sm2z++lQAu5coXr1it51brWguHAK/ZxxSGbPl6gNUTNB6fgVNZ+Z77KtMqSZdzYJBPcQ6fJl9GPGoP7pJ5f15l69MPfte4+tKpp4LGparZZNmzaxevVqtmzZQnJyMnfu3KFKlSqMGTOG559/HoXCuwAl33zzDW+++SZz5syhefPmLFmyhN69exMdHU3Fis4/nNHR0QwePJgpU6YQGRnJrVu3eOONN3jllVfYutX9WSVBzvx6I3uxWda2JA+V1nD+Tg4dmU2ofv8F3RcfYA8rDxaz0z5ZThhGTMLW6BEnQZOtaVhvOP8o6BrPQ6HN/TECgSDfMJsJX76cEsuWZbrm301Rz0JdEHi1GaJQKHjhhRd44YUXfDL4J598Qt++fenfvz8As2bNYteuXSxbtoz33nMOXPv7779Trlw5hg8fDkDlypV59dVXGT9+vFNbgXckW9wn7OxbzY8eD/jl3IksE/BKp8yXiti/vbLBFlED06Dx2Cu53puVbQayJomRNCVRlKjh1TgCwb1AeeAA+qgogs6ccaqT1WpMI0dieuONIp2FuiDweGrVrFkzduzY4bb+xx9/pFkzz5eAzGYzR48epX2WJ5T27dtz8OBBtzbExsby/fffI8sycXFxfPPNNzz++OMejyvwnE0dQzj1TDifts45N5Pi8jkCBrTzqn9ZqcIWUYO0yYtJ+XIPhslfOAiaLNuwJfyJ4f9GkfrzExj293PqQ/fQDCSFh9mwBYJ7gBQfj374cAI6d0bpQtCsrVqRsm9fenoYIWg+x+OZ2rlz50hKSnJbn5yczPnz5z0eOC4uDpvN5hRWKzQ0lJs3XQfIbdq0KUuWLOHVV1/FYDBgtVpp164dixYtynYsb+zKj+sLOxdSJYYecfzj6hxqpULaNVLTIOu7z3o/Sh3dT8R3Kzway1C6LPEPtuJm88dB+veZygxkvceyTMm4JegNx932ZVMGc/EfM84W3nuK+nfEW4rz/agxdCgaF+GtLEFBXB81irjIyPRcf8X4HkHeviPZHS/zavkxu3BDf/31FwEBAd5057JPWZbdjnPmzBnefPNNxo4dS/v27YmNjWXChAmMGjWKzz9370mX3Q3IifPnz+fp+sLMpktpfH0hjR3XnffTSgSWoHp1532qrPdDceksftkImmHktPS9NaUKuUw5UCgIAnIKwWo33MBw3b2gAWhDHy4Un01R/o7khuJ+PxTTpkGnTg5l5uefxzh5MqVKlULs/ubvdyRbUVu3bh3r1/8XimjBggWsXbvWqV1CQoLLpcTsCAkJQalUOs3Kbt++7TYo8ty5c2nUqBGvv/46APXq1cPPz48nn3ySCRMmUKGCcOv2lKO3zQzc497ro6yf85Ke8o/9VNj/E9r96TnJFH+dQXnlnNs+Ulbszjb7dHbIFtfBkgFQ+aMq2wlNledz1bdAkJ/YmjXDNGAA2hUrsNWsyfmoKMo++2xBm1VsyFbU4uLiMg9cS5LEjRs3SEx0DJkkSRL+/v707t2bCRMmeDywRqOhYcOG7N69m27dumWW7969my5duri8xmAwoFQ6/thmvL47FqUgZ977P/dLyVUDlbxcy9+hTLP6YzQ7N+LJDoBx2HtYG7XKtaABIDsf/FZXeQFVuSdQaENy369A4COkq1eRK7nO0WecNAl71aqYBw8m5cqVe2xZ8SZbURs6dChDhw4FoGbNmsyePZunn37aZ4MPHz6cwYMH07hxY5o1a8ayZcuIiYlh4MCBAAwePBggc2nxiSeeYOTIkSxdupQOHToQExPDW2+9xYMPPujyCIDANXdMdn5x48I/sKYfc1sEOywBSwlxaHY6h6VyheG1Kdgebp0n++yGGIyHHQ+hKkpUQ1PF2VFEILjXZGShVn/7LSn792OvVs25UXAw5tdeu/fGCTzfU8suRFZu6dGjB/Hx8cyaNYvY2Fhq167NunXrqPTv08/169cd2vfr14+UlBQWL17Mu+++S2BgIK1bt+b999/3uW1Fmd9inQWtTVktH7cKJqKE81dCcdn9EuPdGEZMyrOg2RJOYvxjjIsakT5GUMDY7WhWrEA3aRLSv05z+jfeIHXz5rytSgh8ipSQkOD1up3ZbCY5ORm73e5UV9SShBbFTe/SK/7GmuVTP/tsOGEu9tEUF/5E9/F7KBJuO5SbnhmMrEs/uyaXDMFWrwlocp8YFEC2Gkjb291lnar8U2hrjshT//lFUfyO5IWieD+yy0Kd9sUXWJ55xu21RfF+5JUCcxTJytq1a/noo484c+aM2z0sV2lpBIUDm13mgyNJToLWvpzWWdCsFrTLZqPe73w20Vr3YSyRfXxun+nUDJflki4MTbVBPh9PIMiRlBR0M2agWbQIyWZzqrbVr+96+VFQYHh8+Hrt2rUMGTKEwMBAxo4diyzLDBo0iKFDh1KqVCnq16/PnDlz8tNWQR75/HQqc447exW+UMMxWoji3HECXn7cpaAByIHBPrdNttuw3XY+dK8Ma4e+xQokpc7nYwoE2aHavp0SzZujXbjQSdBkf38M06aRsns3tkaNCshCgSs8nql9/PHHtGjRgu3btxMfH8/MmTOJjIykbdu2jB49mkcffRSbiycZQeHh8C2zy/LuVe4SNVnGb9rrbvuwK5RYWz/pE3tkWcZ261esMT9jux3tVC/5VUBbOyrb85ECga+Rrl9HP3486m3bXNZbIiMxzJyJLI4QFUo8nqlduHCBrl27pl/0b+BiqzXd7bp06dIMGDAg2wPQgoLH1YLxrOaOx6DV2792e725ywucHjYVW93GPrHHfOELTCc/cCloAPrGc5EUap+MJRDkiNWK5pNPKNG8uUtBs1eoQOpXX5G2erUQtEKMxzM1Pz+/zCfmgIAAlEolMTExmfUhISFO3oqCws20pkG8UtsxCoyrHGe2SlUxvPsJaHWYfRTax/zXl1ivbXJbrwishaQO9MlYAoEn+PXti3rnTqdyWanEPGwYxvHjIRdRkwT3Fo9natWqVeP06dMAqFQq6taty/r167Hb7ZjNZjZu3CjOit1nhOsVIMtoP32fgP6PEtD/Uac29jLlMExZClrf7WnZks5jubzGbb3kXwltnXE+G08g8ATLc885lVkffpiUPXswTpkiBO0+wWNRe+KJJ9i6dSvGf3MCRUVFsXfvXqpUqUKNGjXYv38/r4nDhvcd6u++Qn1wt9t64wjfngG0m+Iw/p/r74m+2Rf4tduGX7MvUPiV8+m4AkFOWLp3x9KhAwByYCCGuXNJ3bkTe/36BWyZwBu8ynwdFRWV+bpr165s2rSJLVu2oFQqeeKJJ+jw7xdCUPgw2WS+uWRwKCv991m0GxZne529ouvcZrnFFn/EZbnuoQ9R+LsOOSQQ+BSTCbQuzlRKEsbZs5FnzsT4/vvIYWH33jZBnvHqnFpW2rZtS9u2bX1liyAf2XbFUdDqplwjcsmbbtvbKjyA4e0F4GU28xyxO0cz0bdaLeI5CvIfsxntxx+jWb6clL17kUs5x8u3V6mC4bPPCsA4ga/Ik6jdzcWLF5k3bx4LFy70VZcCH2GXZV765b+I/HVTrnHs/1wLWuoHK5DDyoPKd16HtvijWK5txJZ0FiyOgZRVZUWAYkH+k5GFOiNpp27iRAzit6pI4tFjeGJiIidOnHDp3Xjs2DEGDBhAs2bNWLPG/ea/oOA4dee/iPcBVgM7j33gsp2lxWPI5Sv7VNBkayrG4xOxxf3uJGiAiJknyFfcZaHWrFqF8sCBArRMkF9kO1OzWCxERUWxZs2azDiPTZo04csvv0Sj0TB27Fg2bdqEVqvl+eefZ8SIwhmbr7hz02ADWWbNqY/pfcs5ageApXkHTIPf8fnY9tSrYHd96BtA4R/h8zEFAmQZ9Zo16CZMQBEX51RtL1UK6Y77fIKC+5dsRW3+/PmsWrWKBg0a0KxZM65cucLOnTsZPnw4N27c4Nq1a0RFRTFkyBBKly59r2wWeMm848l88Ndat4Jmq1onXdDyZdbkPl62qtyTqMpH5sOYguKM4ty59ODD+/e7rM/IQu1qT01w/5OtqK1fv542bdqwefPmzIPX8+bNY/LkyVSrVo3o6GjKly9/TwwV5I6zCRZ+jTGz5Z8f3bYxvjbZJw4hsiwjG2OwxR8FuxHzhWUgW7K0ktA3+wLJr4IIfyXwLQYD2jlz0C5YgGTJ+r0DW82aGObOxdaqVQEYJ7hXZCtqV69e5dVXX3X48enevTuTJ09m5MiRQtAKOQdiTHT+/jaSbCfQZnSqt1WqimHcHCiRtwDFsiUZ8/nPsd7aBy7GuRtFYE0U/uKQvsC3qHbvRhcVhfLSJac6WafDNHYsptdeA42mAKwT3EuyFTWTyURQkGNswMDA9NBFInpI4WfF2VQA+sY6L8Okzl2LHJL7czj21KuYLyzFFud6SdMdCj/xvRH4Fv3rr6NZudJlnaVDB4yzZ2OvUuUeWyUoKHJ06Xe3RCSWjgo3JpvM9qvps6bGyS6eXv1L5Lpva9z/YTr2rtfXKQKqoq46MNfjCgSusD3wgFOZPSwM44wZWLp1Ex62xYwcRW3UqFGMGTMm83VGctB+/fqhVDomlpQkiUsupv+Ce4fJJtNz5232xfzncShlcdaQ1RrQ+WW91GOsMT/l0EICZJRl2oJsQRX6CMrQR5CUYulH4HvMw4ejWbcO5alTyJKEedAgjO++C1lWmQTFg2xFrXv37mJGdp8xYt8dB0ED6HHrd4fX5mcG57p/hS0ZW+wet/Xaum+jCmuT6/4FAq9RqzHMm4d+3Lh0R5DGvkmNJLg/yVbUli1bdq/sEPiIrVnCYfW8eZDyZt+dxwmOd967kLRl0D08T0QGEeQbqu3b0SxZQtqaNS7jNtqaNSNlzx6x1CjwXZgsQcHxT6qNNRfSOHXHgunf5OM6m5mvTn1Ml7g/nNrLQbk7nyPbzOiMZ5zKtXXGCkET5AtZs1BrFyzANM5NWiIhaAKEqN33mG0yddbFOJTVSv2bY7+PR+nm4LO1YXOvx5FlG8ajzvEiFQEPoAiq6XV/AkG2WK1oPv8c3fTpSCkpmcXaOXOw9OyJvapvs0cIig5C1O5jTsZbeGTLTafyV2787FbQjK+8CVq9V+PYDTFYb+zEnnjKqU7XaA6SQjiACHyH8vBh9KNGoTxxwrnSakV54IAQNYFbhKjdx0w5nOiy/NE7zuIDYBg5FVujR3Ls1xqzC1v8EWRrMrbb7s+hKYLqIqm8E0iBwC2JieimTkWzZAmS7PxQZn34YQzz5omknYJsEaJ2nzLh90R2XHfMTaaQ7cy7vIYHU686tU9ZuDnbyCGybMOefAHLtU3Zejfeja6+92fVBAInZBn1pk3o3noLRWysc3VgIMZJkzAPGOD7/H6CIocQtfuQ6FgTH59McSqfeedHhl/Z7lRueG1KjqGwTCenY7u1z2Mb1FWeR9KU9Li9QOAK6fJl9GPGoP7J9dlHc69eGKdNE1moBR7jtajFxsby22+/cevWLSIjIylXrhw2m43U1FQCAgJQiCepfOdEvHOwVoChmisuy221G2bbn914y2NBM+gbEliuMeqKPTxqLxC4QzN/ProZM5CMLuKSVqmCcc4crO3bF4BlgvsZr0Rt8uTJLFy4EIvFgiRJ1KhRg3LlypGcnEzdunWZMGECQ4YMyS9bBdmw7rEQVJud9yEMUTMhp5BY1lS3Vdo641GWeQQkFZIk8c/585SOqJ5XcwUCFNeuOQmarFZjGjkS0xtvgF7s1wq8x+Np1aeffsq8efMYOHAga9euzQyXBRAcHExkZCTffvttvhgp+I9rKVbGRjs6iLxcy5+O5TUozp90KDcOHIPtwWa5GkcZ9ijaB6eiCm+HpFCLyDICn2OcMAF7mTKZr62tWpGybx+md98VgibINR6L2vLly+nZsyczZ87k4YcfdqqvV68eFy5c8KlxAmde+DneqUwh2/Eb/zyKRMc62T8gV2NI/hHo6r6JKsT5cxYIfEZwMMYPPsBeqhRpn35K6nffYa8pzjwK8obHonb16lVat27ttj4oKIiEhASfGCVwzYEYE0fjHPfTXojZy6LPe6C4+Y/zBQqlc5kLbEnOUUIEAl+gOHcO3cSJ4MJFH8DSsyfJf/yBpW9fERFE4BM8FrXg4GBu3nQ+6JvB6dOnCQ8P99qAJUuW0KBBA8LCwmjbti0HDhzItr3ZbGbatGk0aNCAMmXKUK9ePT777DOvx73fWHcxjc7f33YoezjpIsvPfO6yvazRYa9aJ9s+7alXSP35Ccxn5vvMToEASM9CPXUqAa1aof3oI9Rff+26nSRBcN6S1AoEd+OxqD322GN8+eWXLmdjp0+f5n//+x9PPvmkV4N/8803vPnmm7zxxhvs3buXpk2b0rt3b65du+b2mpdffpldu3axYMECfv/9d1asWEHdunW9Gvd+4+1DCby61zko8TtXNru9xvDmPORg9/EYLVe/wXDQdbR+Sanz3kiB4F8CDx4koGVLdLNnI1nSVxZ0776LFO+8dC4Q+BqPvR/fffddfv75Zx555BGefPJJJEli3bp1fP3112zatImwsDDGuQs06oZPPvmEvn370r9/fwBmzZrFrl27WLZsGe+9955T+59//plffvmFI0eOEBKS/oMdERHh1Zj3G5eSrHz6p7N3okK287SLYMW28pUxvP8FqN2HrpJlGfOFL9zWq8I75M5YQbFGio1F98471NiwwalOEReH+uuvMQ8bVgCWCYoTHs/UypYty+7du2nVqhVr1qxBlmW++uortmzZQpcuXdi5cyelSnke/d1sNnP06FHaZzmH0r59ew4edB2aadu2bTz00EN88skn1KlTh0aNGjFu3DhSUpwPIhcVzidaXZZ/UdLZKcf40lgMH6zIQdDsmE5Mdluvrf8e6gpdvLZTUIyx29EsXUqJJk3QuBA0e1gYacuXYx46tACMExQ3vDqnFh4ezueff47NZuPGjRvY7XbKli2LWq32euC4uDhsNhuhoaEO5aGhoW737i5fvkx0dDRarZaVK1eSmJjIuHHjiImJYeVK5zxfGZw/f95r+3x5fV4YelBPeibp/1hY10ivLauc2l7Ul8Scg60q8zXK3P7NqfxOqf4Y/B+GBCAh+z4K8n4UVorrPdGfO0fE9OnoT550qpMliVu9evH3sGHYAgKgGHtHF9fvR3bk5Z5Ur+7+rKzHonbo0CGaNm0KgFKppEKFCrk26G6ynn+SZdntmSi73Y4kSSxevJigf1O1z5o1ix49enDz5k3K3HXm5W6yuwE5cf78+TxdnxfOJFiIszgKfMcKWvpzHv31i07tI5q2zLFPW3wyxizh9RQlqlOhYR+PbCrI+1FYKZb3JCUF3YwZaBYtQrLZnKpt9etjmD8fbePGPFAA5hUmiuX3Iwfy8554vPzYqVMn6tevz6RJkzh27FieBw4JCUGpVDrNym7fvu00e8sgLCyMsmXLZgoaQI0aNQC4fv16nm0qbHT87pZTWetwLZodzks85m79cz2Otu5bub5WUPxQbd9OiebN0S5c6CRosr8/10aPJmX3bmyNGxeQhYLijMei9tlnn1GnTh0+/fRT2rVrx8MPP8z06dM5e/ZsrgbWaDQ0bNiQ3bt3O5Tv3r2bZs1cR8Fo3rw5MTExDntoFy+mz1gqVqyYKzsKK+8eSiTJ4ny2Z3i9AHCRK83SOmfPU9luw3zZ0bVaUfIhFH7lcm2noJghy2iWL0fh4iHS8tRTJB88SGzfvqASsdIFBYPHovbss8+ydu1azp07x/z586lYsSJz5syhRYsWtGrVinnz5nH58mWvBh8+fDhfffUVK1eu5OzZs4wfP56YmBgGDhwIwODBgxk8+D+38169elGqVCmGDx/O6dOniY6O5s0336Rr165uZ3f3I+svprHwT2fnlwUtg1GYTSgv/OlQbnhjJnLpnM8I2m7/hj3heJZSceBV4AWShGHWLGTdf8c+7BUqkLpmDWmrViH7aFtCIMgtXofUDw4O5sUXX2TTpk2cPn2amTNnEhQUxJQpU2js5XJDjx49mD59OrNmzaJ169ZER0ezbt06KlWqBKQvKd69rBgQEMDmzZtJSkqiffv2DBw4kFatWrFw4UJv30ah5bdYE6+4OJMG8GINPwJefcKpXNb7e9S3Pem0U5kyqLZ3BgqKPXLlypjGjUNWKjG99hrJ0dFYvTyjKhDkF3laIyhVqhRVqlQhIiKC48ePk5aW5nUfgwYNYtCgQS7rtm3b5lRWvXp1Nm3a5PU49wMWu8yLLmI7AhzuEYbqmLPXIpDtIWuHdi4iFakr9fTYPkExIjER9Q8/YHn2WZfVphEjsDzxBPY62UetEQjuNV6LmizL7Nu3j2+++YZvv/2W+Ph4SpYsSe/evenZU/xA5oW/U23cMtqdynd0Lk3VIBWajcuc6mwVqiCHls3VeJpqg5BUfrm6VlBEyZKFOqVCBWytWjm302iEoAkKJV659G/cuJEtW7Zw8+ZNAgIC6Ny5Mz179qR9+/YolZ4FzxV4x76uZahvu412+kyUV53P+RimLS8AqwRFEcWlS+jGjEG9a1dmmT4qipRffwWN+wP9AkFhwmNR69SpE3q9no4dO9KjRw86deqEVqvNT9uKFQarzEcnHJ1DIgKU1CulRjt/IaozR52veW3KvTJPUJQxm9F+9BHa2bOdknYqz55Fs3SpiAYiuG/wWNQ+//xzIiMj8ff3zClB4DmXk608se0WMQbnpUeSElAd2e/yOnuNevlsmaCoo9y/H31UFEoXR3NktRrTqFGYBwy494YJBLnEY1F75pln8tOOYs26i2kuBS1Ur0C9x3U2cVOPl5ADS3o8hmxNw3ptY65tFBQtpLg4dBMnolm92mW9tVUrDPPmYf83uIFAcL/gVtQyPAy7d+/u8DonMtoLPCfe5GKGBsxvEYw2aqlTecpn20HvnYOH+cLiXNkmKGLIMuqvvkI3YQIKF6lg7CEhGKdMwdKnj0jaKbgvcStqL730EpIkERkZiUaj4aWXXsqxM0mShKh5ybYrBj475Zxa5nCPMGr95vwgYX2wudeCBmB3ld1aFeh1P4L7F8XZRc2eygAAIABJREFUs+ijolDtd72cbX7+eYyTJyN7kW1DIChsuBW1Q4cOAenhrO5+LfAdKRY7A/c4Py1/VNtKvYWjUZ474VRn7vmy1+PYUy5hT7nkVK4Kbe51X4L7FFlGP2QIqiNHnKpstWphmDsXW8ucA2ILBIUdt6KWNYKyiDLte47HWTBnWXmsbLjJsEWjXbaXVWrsEZ5/DrJsw3zmI6w3djjV6R7+GEktZmrFBknCOGMGAZ06ZRbJOh2mceMwjRghXPYFRQaPw2Q1a9aMHTucfxwz+PHHH90GIha4Ztg+x3BY/lYjFw66FjSAtDlfu61zhfXGLpeCBiBpgr3qS3D/Y2vWDNO/noyWxx4jOToaU1SUEDRBkcJj78dz586RlJTktj45OVkkwvOSv1P/S9tRxXCT89kJ2lsLPA6HBWBLOIn5zFyXdcoybVHoik4AaMFd2O0ojh/H3rChy2rjpElY27XD2qWLcAQRFEm8CmjsLnknwF9//UVAQECeDSpOWO9aenzln59dt3m4DSkrdmOv9aB3fce47k9bZxzauuO96ktwf6A4cQL/jh0J6NgRhbss08HBWLt2FYImKLJkO1Nbt24d69evz3y9YMEC1q5d69QuISGBo0eP0r59e99bWAxoe+cU4645n0ezPtgc42uTc9WnbDM4lWnrjEcV3i5X/QkKMS6yUOujokjdskWIl6DYka2oxcXFZSYBlSSJGzdukJiY6NBGkiT8/f3p3bs3EyZMyD9LixjJFntmqs+F553jN8oqNcbh7/lsPGVIUyFoRRDVtm3ox493Stqp2rsX9bp1bqPsCwRFlWxFbejQoQz9N+ZbzZo1mT17Nk8//fQ9MayoM/H39IcDld1K7bR/nOqNYz4Erd5n46nCHvVZX4KCR7p+Hf24cai3b3dZb3nqKayuousLBEUcjx1FzrqIDSfIPX/ctgAw+6JzmCJLu6ex1fRuD+1ubEnnsMXuzvX1gkKM1Yrms8/QTZ+OlOp8aN9eoQKGWbNE0k5BsSVPSUIFueNqipVjcRZKWlIY8fdOp3rTi6NB4XVS8kzM5z7Ji3mCQory8GH0o0ahPOF8KF9WKjEPG4Zx/HgQDluCYoxbUQsPD0ehUHDlyhXUajXh4eHZej9C+v7aP/84L6UJHFlxNhWl3cat/YOd6mw1H8yToAHYDTecyiR9eJ76FBQgiYnopkxBs3Qpkov05dYmTTDMnYu9fv0CME4gKFy4FbUhQ4YgSVJm8s+M14K8c9NgJ+q6670Qw2vv+3w8ZVh7FIG1fN6v4B4gywR06YLy2DHnqqAgjJMmYe7fP88PQgJBUcGtqE2aNCnb14K80SzJ+RyR5dGnoYTvI31oqw9GksSP3n2JJGEaORK/LAHFzb17Y5w2DblMmQIyTCAonPjkl85qtfqim2KFq2Uk0wuv+6Zzi/vIL4L7D0v37lg6dADA9sADpG7ahGHxYiFoAoELPBa1H374galTpzqULVq0iEqVKhEeHs7AgQMxZkkFL3DNw38doGvcYYcyw+tTQKXOU7+y3YLp3Gd56kNQcEh37ripkDDMmYNx3DhS9u/H2k6cNxQI3OGx9+OCBQuIiIjIfH3s2DHeeecdmjRpQtWqVVm7di116tRh7Nix+WJoUUF59DdG7Jrlk75kWcaecBxb/B9Yb+5FduEgAgpQan0yniB/yMhCrdqxg5RDh1zmM5MrV8b09tsFYJ1AcH/hsaidP3+eLl26ZL7esGEDJUuWZPPmzej1evz8/NiwYYMQtRz457vNVHVRLgeW9LgP2XwHw5G3kFMv59hWWaY1klLnuYGCe4eLLNS6iRMxLFxYwIYJBPcvHi8/pqSkOAQs/vnnn+nQoQN6fXrUiwcffJD/Z++8w5q62gD+S4AAihpFQaYIKqIgKAquFlc/cdStUOseKKJVcdfRKs466qx1VFtx1FFn1dpaoThwobhnBUdbQUGUPZJ8f1BSQkIIAqJ4f8/D85Bzzz15cwj3Pec973j8+HHxS1iGSMmS809sglr7346eyO11807MehZOyqlPdFJoiAwwrCcsMt5GxHfuUL5zZ8oFBCgVGoBk61b0zpwpRckEBN5tdFZqVlZWXL16FYDo6Ghu3rxJ61y2/RcvXmBkJOwItPH01ClavlTNzDLZvi/6kxeAnm6b5sxHuwvuBOhbeFPuw92IxEJ8/VtFaiqGc+di0rIl+qdPq12W1a0r1DcTECgCOj/xevXqxZIlS3j27Bk3btygYsWKdMiViicyMhJ7e/sSEbIsIHr2Dw02z1JrH9a+AeX0dVtbyOIvI395U+M1g5r90a/eDpF+eUQGQkaJtxH9EycwmjABvagotWtCFWoBgeJBZ6U2ceJEUlJS+PXXX6lUqRKLFy9GKs2OqXrx4gXHjx9n9OjRJSbou47hNs3nJJbOTjrdr5DLSLs+T61d38IbSd2xQmD8W4woJgajzz9H8tNPGq9ntmtH6pIlKOzs3qxgAgJlEJ2VmoGBAUFBQQQFBaldq1y5Mo8ePSpWwcoaopQktbZpzScy3aSSTvdn/LkJsvKOIUZSa6ig0N5W5HIkmzdjNHs2Ig1V4+Xm5qQtXEhmt25C3TMBgWLitQ5cUlNTlTkeLS0tlc4iAroz1d6Xk9aeTNehr+zlLbIeq6/yDew+QWRQofiFEyg6CgXlu3VDPyxM/ZJIRMawYaTNmAGVdFvUCAgI6EahMopcu3aN7t27Y2trS5MmTWjSpAm2trb06NFD6UQioBvnK9YqsI889R/Srs4mLWK82jVReVsk9v1LQjSB4kAkIlNDJXiZiwvJx4+TtnixoNAEBEoAnXdqkZGRdOrUCblcTq9evahbty4KhYI7d+5w4MABOnTowJEjR3B1ff06YGUZBeppsQoi/eZS5C+va7wmqeVXVJEESpiMgAAku3ahd/MmivLlSZs+nQw/P9AXPFIFBEoKnXdqc+fORSqVcu7cOdauXcvYsWMZN24ca9eu5dy5c0ilUrU0WrqwceNGGjRogLm5OV5eXpzRMUYnPDwcU1NTmjVrVuj3LA3kGnSajYme9nvyUWgGtr3RN21cHGIJFAdyueZ2AwNSv/6azI8/JvHcOTJGjRIUmoBACaOzUjt//jxDhgzB1tZW7ZqNjQ1Dhgzh3LlzhXrzvXv3MnXqVCZMmEBYWBgeHh707t27wCDuhIQERo4ciZeXV6Her9SQZSG5q26eneKW/3lY+t1vNLaLjCzQt/642EQTKAJZWUhWr8Zp0CBIT9fYRebpSUpwMApr6zcrm4DAe4rOSk0mkyHREj8jkUiQ57dizYc1a9bQt29fBg4ciKOjI4sXL8bc3JxNmzZpvW/06NF88sknNGnSpFDvV1roXT2v1iYRi6hdSXMCY3lqDFlPDqq1GzVZhXGz7xAbCdnZSxu9iAhMWrfGeMYMyt+6heGKFaUtkoCAAIVQaq6urmzZsoWXL1+qXXv58iXBwcGFOk/LyMggMjKSNnkO09u0aaN1x7dx40ZiY2PfqRyT4mfqiYajjFUVk0KeQeY/v5F8wpvU8IFq/UWGZohNagl10Uqbly8xmjiR8u3aoXftmrLZcOlSxH/+WYqCCQgIQCEcRaZNm0aPHj3w8PCgf//+1K5dG8hOdLxt2zbi4uJYtmyZzm8cFxeHTCajWrVqKu3VqlUjNjZW4z03btxg0aJF/Pbbb8qK3Lpw7949nfuWxP3SR4+omaftgUFllXErP9+MceqlfMeIrTSAzPvqhUVLg6LOxzuJQkHl337DZtkyJHFxapdlBgY8DQvjZSGtFWWV9/I7ogVhPtQpypzk6B9N6KzUPvjgA3bv3s20adNYunSpyjUnJyfWrl1Ly5YtCy1c3sBhhUKhMZg4PT2doUOHEhQUhF0hMy9om4CCuHfvXpHuj9h7kIYnD6i0rbL6H02qGVK7dvY5i0KeScqTK/mOoWfqiZ1zu9eWoTgp6ny8i4iiozGeOBGD48c1Xo9r3x6DlSsxMzdHMAy/n98RbQjzoU5JzkmhXLFatWpFeHg4jx49UmYQsbW11eg8UhCmpqbo6emp7cqeP3+utnsDePr0Kbdv3yYgIICAgAAA5HI5CoUCU1NTdu/erWbKLG1ko3rglRyv1p4mlvBju/9qZsmehYNCpnkQsSEGtj1KSkQBbWRkYLhqFYaLFyPSUABXZm9P2tKlRFlbU9vcvBQEFBAQyItOSi0hIYFHjx5RpUoVrK2tX1uR5UYikeDm5kZISAjdunVTtoeEhKjUbcvB0tJSzd3/u+++IyQkhK1btxZZnmLn171U0qDQABJcmlPFKNt8Kk+NIf3GfLU+hs7TERmZIS5ni0hfyNjyptE7cwbjwED0bt9Wu6YwMCB93DjSAwPB2BgE05KAwFuDVqWWlZVFYGAg27dvV3o2Nm7cmO+//x5LS8siv3lAQAAjRozA3d0dT09PNm3axNOnTxk8eDAAI0aMAGDdunUYGBhQr149lfurVq2KoaGhWvvbgOQ3zclrT9T8kIm9/4utkyepn5OJDM3QN/ugxGQT0IJCgfHYsUi2bNF4OatFC1KXLUPu6PiGBRMQENAFrUptxYoVBAcHU79+fZo3b05UVBTHjx9n8uTJbN26tchv3qNHD+Lj41m8eDExMTE4OTmxa9cu5a7ryZMnRX6P0kIS+5da243A1Xi4Oqs2KtSjsg1q9C4psQQKQiRCoSFAWl6lCmlz55L5ySdC8mEBgbcYrUpt165dNG/enEOHDiEWZ7uSL1q0iEWLFpGQkKAsPVMUhg0bxrBhwzReO3z4sNZ7p02bxrRp04osQ3Hz6vJF8lY069R0DjvzKjQNiCvWxUAIri5V0mbNwuDnnxH/e96b0a8faXPmoKhSpYA7BQQEShutQU8PHz6kW7duSoUG0KdPHxQKBdHR0SUt2ztLxOkItbYnkso63SsyFB6cpY5UStr8+cgcHUk6fJjU1asFhSYg8I6gVamlp6er7cYq/ZtZXFMQtkA23hG71drq2FuVgiQC+aEfEoLxmDEazb8AmT17knTyJLIWLd6wZAICAkWhQO/H/ApQCoUp8yHpJQbyLJWmeTW6sbpl0U21AkVHFBOD0fTpSPbsAbIdPzJ9fTV0FIGWtHACAgJvJwUqtXHjxjFx4kTla8W/K9tPP/1ULauHSCQiKiqqmEV8txC/UM820c6zLuUNhPRWpYpcjuT77zH68kuVKtRGM2aQ1b49isq6mYcFBATebrQqte7duws7smLgr/ofUL+0hXiPEV+7hnFgIPoXLqhdE8XFoX/8OJm9BY9TAYGygFalVlC2fAF1MlJTKZfr9bXy1igKkadSoBhJSsJo4UIka9cikqlnbJG5uJC6fDkyd/dSEE5AQKAkECoWFiOiuBik8wJKWwwBQP/oUYwnTUKsIdZRUb48aZ9/TsaIEULRTgGBMobwH12M6J/9Xa1Njhi7CsJO7U0hevIE46lTMfj5Z43XMzt1InXRIqFop4BAGUVQasWI3v0bam3nK9XCt5IwzSWOXI5k7VqMFixAlJSkftnamtSvviKrY8dSEE5AQOBNITxti4vMDPQvnVZrju3pLzjbvAlEIvRDQ9UUmkJPjwx/f9KmTgWTvHleBAQEyhqCn3kxIf4rWq1tdO1BGJYTMuy/EUQiUhcvRmFkpGzKatyYpNBQ0ubOFRSagMB7gqDUioPUFIyWTFZrPmTaiI62RhpuECgJFHZ2pE+ejKJiRVKXLSP511+Ru7iUtlgCAgJvkEIrtZiYGPbv38+GDRv4+++/AZDJZLx69UpZnuZ9w+CPw4gTE1TaHhhVw7aGBbYm2i28Cpl68UmB/BFFRyP59tt8r6ePHk3ihQtkDBkCYmHNJiDwvlGoM7U5c+awevVqMjMzEYlE1KlTB0tLSxITE6lfvz4zZ85k5MiRJSXrW4vo+VO1tnMVa2FfUfv0yl7eJOPWkpISq2yRpwq1zNkZWcuW6v0kEhRCFWoBgfcWnZXaN998w9dff42fnx9t27bFx8dHeU0qldKpUycOHTr0Xio1g9/3qbXNqOnDaodyGnpnkxUTprHidVmyCGdlZZGcnFzkcUTPnqF38SKpFSrAnDkAyJ88ISs+Ht6CwHYjIyMhwXcuhPlQRZgPdXSZk/Lly6P/GnGkOt+xefNmevbsyaJFi4iPj1e77uzszB9//FFoAd51RPHPEOUxu46v1Z+HxtX4wMIw3/syH6ln8gcQVywbFZWzsrJITExEKpW+vvdnVhaiv/9GnJgIGipNyxUKFP9WjShNDA0NMTISzk5zEOZDFWE+1CloThQKBQkJCVSoUKHQik3nbcGjR4/44IMP8r1eqVIlEhIS8r1eVhFpqHAdbVQ134BrecoT0m+vQJ54T+2aXtXmGNj0KHYZS4Pk5OTXV2gKBaK4OMS3biGOU08QrdDXR25rK9Q4ExAoo4hEIqRS6WtZenRWgVKplNh/KwFr4tatW1SvXr3QApRFfqnihqbqafL056SeHwXyDLVrBg5DkNToU/LCvUFeS6GlpSF+/FhjADWA3NQUhaWlkN5KQKCM87oWHp13au3ateOHH37QuBu7desWwcHBdOjQ4bWEeJfRu3tN5XVYpbpkijU/cGVxFzUqNJFhNQxse5WIfO8Mcnm2qfH2bY0KTWFkhKx2bRS2toJCExAQyBednw4zZszgxIkTtGzZkg4dOiASidi1axc//vgj+/btw9zcnMmT1WO1yjqGP32n8lpEdr05iVjDKiOvQhPpo1e5AZJafohEZcdBpNC8eoX4yRNE6elqlxRiMQpzcxRmZoKLvoCAQIHo/JSwsLAgJCSEFi1asGPHDhQKBdu3b+fAgQN06dKFX3/9lSrv4RmHwqSiyusX+uUB6F87f8/HHPQtvTFym4/YxK4kRHs3UCgQ//WXZoVWoQLyunVRVK9eZhXaw4cPkUqlXL58uVTlOHnyJFKplLh/zzDzvhYQeFco1JOievXqrFu3jocPH3Lt2jWuXLnCw4cPWb9+PebvaWyQTKH6erZdTwCGOpUvBWneQUQi5DY2Kk0KAwPkdnbIHRzAMH8P0pLg+fPnTJgwARcXF8zMzKhduzZdunQhJCRE2cfFxYVVq1YVeuxOnToxadIklTZra2vu3LmDSxEyn5w6dYouXbpgb2+PhYUFbm5uDB8+nFe5KnwXFk9PT+7cuaNcqG7btg0rK00nxbrz7NkzzM3NcXZ21pioQSqVcuDAAbV2f39/lRAigKioKEaPHk39+vUxMzPDxcWFAQMGcO7cuSLJ+K7x+PFjfHx8sLS0xN7ensmTJ5ORoX7EkZuYmBj8/PyUccYtWrRg165dKn3u379P3759sbe3x9ramnbt2nH8+PGS/CjFxmsdTujp6WEtlO7g72QZphlyTHO1PTE0RQSU01ddLygyXiJPfvhG5XtnMDFBbmqKKC4ORdWqKCwsSu3crH///qSmprJ69Wpq1qzJ8+fPOX36tMYwluJAT0+vSAvC27dv06tXLwYPHsyCBQsoX748Dx484PDhwwU+3LQhkUiKfaG6fft2vL29uX79Or///jsfffTRa41z+fJlunbtSp06dViyZAl169YlOTmZX3/9lcmTJxdraFFGRgYSiaTYxitOZDIZPj4+VK5cmSNHjvDixQv8/f1RKBQsXrw43/tGjhzJixcv2L59O1WrVuXQoUOMGDECKysrWrRoAYCPjw92dnYcOHCA8uXLs2nTJvr27cu5c+eoWbPmm/qIr4XOO7UVK1YU+LNy5cqSlPWt40xMOgqFevue/5mqvM6KDSMlfCBZfx1+Q5K9hchkoGXnoLC0RF6nDgobm1JTaAkJCYSHh/Pll1/i5eWFra0tjRo1YsyYMfTsmb0D79SpE48fP2bmzJlIpVKkUikA8fHxDB06lHr16lG9enWaNm3K1q1blWP7+/tz+vRpNmzYoLzv4cOHGs2Pd+/exdfXF1tbW6ysrPjoo4+4cUO9rBHAiRMnqFKlCgsWLKB+/frY2dnRpk0bli5dStWqVYH/TIm//PILLVu2xNzcHC8vLyIjI/Odi9zmx5MnTxIQEKAM05BKpSxYsKDQ87t161Z8fX3x8fEhODi40PdDdvzSqFGjqFGjBseOHaNDhw7UrFkTZ2dnAgMDNe70crh06RLdu3fH3t4eGxsbvL29OX/+vEofqVTKhg0b6NevH5aWlsz5N9j/9u3b9OnTB2tra2rVqsXQoUOJiYkp1NjFzYkTJ7h16xbr1q3Dzc2N1q1bM3v2bLZs2aJ1l37+/HmGDRtG48aNsbOzY8yYMVhZWXHp0iUA4uLi+PPPPxk7diwuLi7Y29vz5ZdfkpWVxdWrV0v0MxUHOj89vvzyy3yviUQiFAoFIpGIzz77rDjkeidIz2t7BOwr6vFhnqDrjAc/gIYcjyLDaiUm21vFy5eInzyh4nkpkFhA5+KLdUwYXDhzmYmJCSYmJhw5coSmTZtqDA7dunUrLVu25NNPP2Xo0KHK9rS0NFxdXRk7diwVK1YkNDSU8ePHY2Njg5eXFwsXLuTPP/+kdu3azJo1C4CqVavyJE9l7n/++Qdvb288PT3Zt28flSpVIiIiAplMplFmc3Nznj9/TlhYGB9++KHWzzdz5kwWLlyIhYUFixYtok+fPkRGRlKunPbzX09PTxYsWEBQUJBS+ZYvn21eX7BgAYsWLSowRvXMmTPEx8fTrl07nJycWLJkCc+fP1cqXl25evUqt27dYsOGDehpyCaTs8jQRGJiIj4+PixcuBCRSMSGDRvo3bs3ly5dwtT0v4XookWLmDVrFnPnzgXg6dOndOzYkf79+xMUFERmZiZBQUF88sknHD9+HLFYrHXsnLnSNCe9e/fW+nkDAwOZMGGCxmvnz5/H0dFRxWrWtm1b0tPTiYyMzPf70LRpU/bv30/Hjh2RSqUcPXqUuLg4vLy8AKhSpQqOjo7s3LmTRo0aYWxszPfff4+JiQmenp5a5X0b0FmpPX2qnt9QJpPx6NEj1q9fT2RkJDt27ChW4d52Fpz6ixFZqu7nuz8yxSCP56MiTT2+T2xSE32LtiUqX6mTkZHt1fiOpAjS19dnzZo1jB07lh9++IEGDRrg6elJt27daNy4MQCVK1dGLBZToUIFpXkuLS0NS0tLlQXdoEGDCAsLY8+ePXh5eVGpUiUMDAwoV66cVrPexo0bKVeuHD/88IPS7FWrVq18+3fr1o3ff/+dLl26UK1aNRo1asQHH3yAr6+vmsKYNGkSbdtmf+fWrFlDvXr12LNnDwMGDNA6LxKJhIoVKyISidRkNzU1pXbt2lrvB9iyZQs9evTAwMAAOzs73N3d2bFjB2PGjCnw3tw8ePAAgDp16hTqPkD50M7hq6++4uDBgxw/flzlzK579+4qczJv3jycnZ2ZPXu2sm3dunXY2dlx+fJl3N3dtY7dtWtXjfI0bNiQkydPapW5cuXK+V6LjY2lWjXVhbGpqSl6enpaY4o3b97M0KFDsbe3R19fH0NDQzZu3EiDBg2A7E3Kvn376NevHzY2NojFYipXrsyePXveiVhknc2PhoaGaj/lypWjbt26LFu2DEtLS5U/elnnaYqMfg/VD06lhgVPqaHrXIwar0JsWLhV6jtDVhbiO3cQ37r1zii0HLp27crt27f58ccfadeuHefPn6ddu3YsXbpU630ymYwlS5bQvHlzatasiZWVFYcOHVLbiRXE1atXadasmc7nOHp6enzzzTfcvHmToKAgbGxsWLVqFU2aNOHWrVsqfT08PJS/m5iYUL9+fW7fvl0o+fLi5+fHhQsXtPZ59eoVBw8eVFEcvr6+KuZZXVFosvfryLNnzxg3bhzu7u7Y2tpibW3Ns2fP1P5GDRs2VHl95coVzpw5g5WVlfKnfv36QLbDSmHGzo2xsTH29vZaf7QpNcg/QFlb4PLcuXOJi4vjwIEDhISEMGbMGPz9/bl2LTvmVqFQMGHCBKpUqcLRo0f5/fff6dq1KwMGDFBWZnmbKbbDi9atWxMUFFRcw731PEuTUyPtmfqF8hUKvFdP2gBRPgHa7zp6EREYjxtHav/+iJo0KW1xXgsjIyNat25N69atmTJlCmPGjGHhwoWMGTMmX2WzatUqVq9ezcKFC6lXrx4mJibMmTOHZ880fEe08LoPbUtLS3x9ffH19WXGjBm4u7uzcuVK1q5d+1rjFSd79uwhJSWF9u3bq7TLZDLOnj1L06ZNAahQoYLGJLcvX76kYsXs0BkHBwcg+9zR1dW1UHL4+/sTGxvL/PnzsbW1xdDQkC5duqg51OQ1F8rlcv73v/8pzZG5ydkp6Tp2bopqfjQzM1Pz9oyLi0Mmk6nt4HKIiopi/fr1nDx5Uulx6+LiQnh4OOvXr2fVqlWEhYXxyy+/EBUVpTTnurm5ERISwrZt29Q8eN82iu3JGh0dna/dvyzy4FUWw/8JUWnLcG0K4tLPGl8qvHyJUVAQku++Q6ThwawoX54En8pQwPnN24ijoyNZWVmkpaUhkUiQSCRq3/Xw8HC8vb3x9fUFspXT/fv3qZQr4bKm+/Li6urKzp07i+R1J5VKMTc3V8ubd+HCBezs7IDs3Jw3b95UylsQusieH8HBwQwfPpzBgwertM+ePZvg4GClUqtVqxZXrlxR6SOTybh+/TqffvopAA0aNKBu3bqsXLmSHj16qJ2rJSQk5HuudvbsWRYuXKhUrrGxsSrOHvnh6urKvn37sLGxwcDAoNjGLqr50cPDgyVLlvDXX38pwy1CQkIwNDTEzc1N4z0pKSkAavOmp6enDLPI6SPOExsqFovfiZqZOpsfIyIiNP6cOHGC2bNn8+233yrt9e8D847eUmuTN2xRCpKUMgoFBnv3UsHDA8ONG9UUmkJPD7mNDfLatd96hRYfH8/HH3/Mzp07uX79OtHR0ezfv5+VK1fi5eWl3C3Y2toSHh7O33//rQxOrlWrFmFhYYSHh3P37l0mTZrEo0dMm5L4AAAgAElEQVSPVMa3tbUlIiKChw8fEhcXp/EBMXToUJKTkxk0aBCXLl3iwYMH7NmzJ1+vs82bNxMYGMiJEyeIiori1q1bfPHFF9y8eZNOnTqp9F2yZAkhISHcunWL0aNHI5FI6NVLt/Rstra2pKWlERISQlxcnPLBt379eppo2ZFfv36dy5cvM3DgQOrVq6fy4+Pjw/79+0lMzHYeCggIYOvWrWzYsIH79+9z9epVxo4dS0JCAoMGDQKyzWpr1qwhOjqa9u3bK3cUN27cYMWKFXTr1i1fWRwcHNi1axe3b9/m0qVLDBkyRKeFw7Bhw3j16hWDBw/m4sWLREdHExoaytixY5Wyv87YRTU/tmnTBicnJ0aOHMmVK1cIDQ1l1qxZDBgwQPldjYiIoEmTJkRERADZZ5H29vZMmDCBiIgIoqKiWLVqFSEhIXTu3BnIVpaVK1cmICCAa9eucf/+fWbOnKmc87cdnXdq7dq102inzfF67NKlS4HnDmWF2wmZ2KWor8IUVd+vAHRRdDTGEyZg8PvvGq/LK1dGYWUF+axu3zbKly9PkyZN+Pbbb3nw4AEZGRlYWFjQq1cvFZPL559/zrhx42jYsCHp6ek8ffqUSZMm8fDhQ3r37o2RkRF9+/ald+/eKmdWOWcXTZs2JTU1VW1XAtlmxCNHjjBr1iw+/vhjRCIR9erVY/ny5RplbtSoEefOnSMwMJCnT59ibGyMg4MD3377rVrA8hdffMH06dO5f/8+devWZefOnfl65uXF09OTIUOGMHToUOLj45kyZQrTpk0jLi6Oe/fUK07ksGXLFhwcHHB2dla71r59e+RyOT/99BODBg1SKtjVq1czZ84cjI2NcXNz48iRIyoOKu7u7oSGhrJ06VICAwOVQd2NGjXSGp+1evVqxo0bR6tWrahevTpTp07VKWOKhYUFx44dY/bs2fTs2ZP09HSsra1p3bo1hv8mB3jdsYuCnp4eO3fuZOLEiXh7e2NkZESvXr1UzKQpKSncu3dPuQgxMDBg9+7dfPnll/j6+pKcnEzNmjVZs2aNMnevqakpP/30E0FBQXTp0oWsrCzq1KnDtm3b8t0Bvk2IEhISdDLi/67hwZVTHsDOzu61U2Rt3LiRlStXEhMTQ926dVmwYAHNmzfX2PfgwYNs3ryZq1evkp6ejqOjIxMmTKBjx46v9d66cO/ePRXvrqhXWbQ+FIvH0yscubpIpW/SpuOgp7pOkCVcJ+3SRJW2cl4HEem9nQGdBaGcD5mMCo0aIX6oHlAuq1mTv3/8kYoaaqCVRdLS0t7qelknT57k448/5s8//1RxXS8p3vb5eNMI86GOrnPy8uVLFRO+Lui0U8vMzEQqlWJqaqq0yRcHe/fuZerUqSxdupSmTZuyceNGevfuzdmzZ7HJkzoJ4PTp03z44YfMmDGDypUrs2vXLvr168fPP/+cryIsbr67nUxChvo6IMu5sZpCU2Qlqym0MoOeHmmzZlEuV6yWwsCA9HHjSA8MRFGEbBYCAgICr4tOZ2pisRhvb2+OHTtWrG++Zs0a+vbty8CBA3F0dGTx4sWYm5uzadMmjf0XLVrE+PHjcXd3x97enqlTp+Lm5sbhw28uU8eLjOxzEJ+YM3mu5IlNy0ol5XR/9QH0jMuMM0lmjx5ktmkDQFaLFiSdPk369OlgbFzKkgkICLyv6LRT09PTw8bGhrQ09awYr0tGRgaRkZFqwZdt2rQpVFLSpKQkrVkEipPETDnb7mXbpgfG5PFayuMgkRVzAmQpamMY2PRAJHqHlJpCgejhQxSadugiEWlLl5IZHk7mJ5/Aaxb1EyhZPvjgg/eyKr3A+4nOjiJ+fn6sX7+eAQMGFBgQqAv5xVNUq1ZNazR8bjZs2MDff/+tdiCeF20H2bqQc/+RWD0g+2A4WWxIefl/5VJeGJnwJNf7VEi4Q96ItXTD2vwtawpFlOdNYRQdTY0FCzB68IDru3cj+3fxoDafTZrA/fuq9xoZKQ/R3weKc8FXFhDmQxVhPtTRZU5evXqlUR9oy2JTqDg1IyMj3Nzc6N69O3Z2dmoHfSKRiBEjRhRmSDWPyhxvyoI4cOAAs2bN4rvvvsPW1lZrX13S+ORHjmNEyF9pfHE3f2+mcgM/o3al/5xlMv6sQmaeNIfSxl9SxbDkD+qLTGoqhkuXYrhiBaLMTADq//ADqatXqznO5MfLly/fm8NxwRFAFWE+VBHmQx1d56RixYoa/Su0obNSmzZtmvL3H374QWOfwii1/HKUPX/+PN9o+BwOHDjAyJEj+fbbb0vU8zEHhUJB91+1u+cqjLSfIxnYD0T8Dig0/ZAQjAID0fs3/U8Okq1byejbFwr42wgICAiUJjorteIuoyCRSJSpV3IHTIaEhNClS5d879u3bx/+/v6sXbs230ShxU1c+tsfRV9URDExGE2fjmTPHo3XM9u2RW5pCf/u3AQEBATeRrQqtR07dtC8eXNq1KhRJBNefgQEBDBixAjc3d3x9PRk06ZNPH36VJlOJ2fXt27dOgB++uknRowYQVBQEM2bN1emoZFIJMVyzpcf086p56OTiPIP71PIs8h8pFk5vHXI5Ug2b8Zo9mxEGmowyc3NSVu4kMxu3bIdQd6R80ABAYH3E61KLSAggHXr1lGjRo0SefMePXoQHx/P4sWLiYmJwcnJiV27dinPyPJmuN60aRNZWVlMmzZNxRzaokWLEnXrvxKnujtpLnqOgSz/OKzMqC2gyCoxeYoL8bVrGI8fj/7Fi2rXFCIRGcOGkTZjBhQy+FFAQECgtNCq1IpS5kFXhg0bxrBhwzRey6uo3mQ8Wm4eJ6kmcv02PUxrf9kL9Tx9Ir23KO9hUhJGCxciWbsWkYYktTIXF1KXL0fm7l4KwpVtFixYwMGDBwkPDy9tUXSiU6dO1KtXT5l+Ku9rAYG3DZ0TGr+vXHklJjVPhevqmRpqhBnmchRRqCsKvWpvJuNJgWRlYdKmDYarV6spNEX58qTOm0dSSMh7q9D8/f2RSqXKH3t7e3x8fLh7926hxnn48CFSqVRZKTqHMWPGvJHFWUpKCnPmzKFhw4aYm5tjb29P+/bt2ZPPmamubN26VVm5G7LLlqxataqo4qqQk8vR2dlZY9JnqVTKgQMH1Nr9/f3VwnuioqIYPXo09evXx8zMDBcXFwYMGFCoWNiywOPHj/Hx8cHS0hJ7e3smT56stSwOQExMDH5+ftSpUwdLS0tatGjBrl27VPq4uLio/L9IpVK+/PLLEvwkBVOgo4gu7vVlmUMxqlMkUsipckG1OGjG//7LdK5QKJAnq2ZnN3Sdi9joLfEa1Ncno29fjPN88TI7dSJ10SIUuUrDv6+0atVKeY77zz//MGvWLPr161cszlImJiZFHkMXxo8fz7lz51i4cCFOTk68ePGCiIgIXrx4UaRxS/LsOoft27fj7e3N9evX+f333/noo49ea5zLly/TtWtX6tSpw5IlS6hbty7Jycn8+uuvTJ48mT/++KPYZC5KqaCSRiaT4ePjQ+XKlTly5AgvXrzA398fhUKhdcc9cuRIXrx4wfbt26latSqHDh1ixIgRWFlZ0aLFfxVJJk+ezNBc6fJ0TZJdUhS4UwsICMDCwkKnH0tLyzch8xvlQB6l5p4YpdZHXiPbiUaRlUzaxTGQKygbQGRQcOHQN0lGQACyevUAkFtbk7x9OynbtgkK7V8MDQ0xNzfH3NwcNzc3Ro0axd27d0lNTQXy34Xl3kHkFLBs3bo1UqlUWQZmwYIFNGvWTHlPzu5i7dq1ODk5UaNGDUaNGqXMqg5w/PhxOnToQI0aNbCzs6NHjx7cuXNH62c4evQogYGBeHt7U6NGDdzc3Bg6dCjDhw9X9unUqRPjx49nypQp1KhRgxo1ajBz5kytNbM6deqkrFjQqVMnHj9+zMyZM5Wr9OJg69at+Pr64uPjQ3Bw8GuNoVAoGDVqFDVq1ODYsWN06NCBmjVr4uzsTGBgoMadXg6XLl2ie/fu2NvbY2Njg7e3t9qCRiqVsmHDBvr164elpSVz5swB4Pbt2/Tp0wdra2tq1arF0KFDVcKWdBm7uDlx4gS3bt1i3bp1uLm50bp1a2bPns2WLVt4pcE5LIfz588zbNgwGjdujJ2dHWPGjMHKyopLly6p9KtQoYLy/8Xc3PyNLdzyo8Cdmru7e7EmMX6XOPM0Xa1tnHUa5PqbZlUSkSjahzxsPWQlq/XPppSsvKmpmvMwGhiQumwZBocPkzZlCryhL6HJwFZv5H1ySPohtMhjJCYmsnfvXurVq4dxIXJanjhxgjZt2vDTTz/h7OysdRUfHh6Oubk5+/fv56+//mLQoEHUqlWLwMBAILug58iRI3F2diY1NZUlS5bg6+vLuXPn8h3X3Nyc48eP07VrV61Zznfv3s0nn3zCb7/9xo0bNxg7dizm5uaMHj26wM+4detWWrZsyaeffqqyUtfEggULWLRoUYHpus6cOUN8fDzt2rXDycmJJUuW8Pz5c6pWrVqgPLm5evUqt27dYsOGDWoFMQGtCjgxMREfHx8WLlyISCRiw4YN9O7dm0uXLqlUOVi0aBGzZs1Slnp5+vQpHTt2pH///gQFBZGZmUlQUBADBgzgxIkTiMVincfOOydFqZB9/vx5HB0dsc61aG3bti3p6elERkby4YcfaryvadOm7N+/n44dOyKVSjl69ChxcXF4eXmp9Fu1ahXLli3DysqKbt268dlnn5XqrrVApTZ48OACJ7Sscj5W3ebsUFF1yl556iNPj85/EP3yiMtrz3hS7PxbhVr/1CmS/vgDNKSrkjVtiuzfisMCqhw/flxZSTg5ORlra2u1s4SCyHlAValSRaUWmCYqVKjAsmXL0NfXx9HRkW7duvHHH38olVreeMw1a9ZgY2NDRESEyq4vN8uXL8fPzw8HBwfq1auHp6cnHTt2pHXr1ir9zM3N+eqrrxCJRNSpU4f79+/zzTff6KTUKleujFgsVq7UtWFqaqpTWNCWLVvo0aMHBgYG2NnZ4e7uzo4dO9RyxBbEgwcPgOyimIUl70P7q6++4uDBgxw/flzlzK579+4MGDBA+XrevHk4Ozsze/ZsZdu6deuws7Pj8uXLuLu76zx2bopaITs2NlYtoUV+yS9ys3nzZoYOHYq9vT36+voYGhqyceNGGjRooOwzYsQIGjRoQJUqVbh06RJffvklDx8+LPZz1sJQqDRZ7xuajDB1KqkWvJRVNQLyD0g2cluASO8N5UBUKDDYtw+jadMQ/xvDZ7hiBemTJ7+Z9y8jNG/enBUrVgDw4sULNm7cSI8ePTh+/LjKare4cHR0RF//v3/F6tWrczFXmEVUVBTz5s3j4sWLyorZcrlcLeQlNy1atCAyMpILFy5w7tw5wsLC6N69O4MGDVIpONq4cWOVc3MPDw/mzZvHq1evlNWTiwM/Pz/8/Py09nn16hUHDx7k4MGDyjZfX1+++eabQiu1onhuP3v2jHnz5nHy5EmePXuGTCYjNTVVbb4bNmyo8vrKlSucOXNGuSDKTVRUFO7u7jqPnZucCtlFIT/fCG0+E3PnziUuLo4DBw5QpUoVDh8+jL+/P4cPH8bFxQVAZfHj7OxMhQoVGDx4MLNnz37tGptFRVBqhWB0fRMkBSXY1yuHuGJdxOWtkdh9ikjyZmK88qtCbbh0KZk9eyJ3cHgjcpQFypUrp/IQcXNzw9bWlu+//54ZM2YgFmebk3M/ODOLkGnFIE9lcJFIpDK2r68vFhYWLF++HAsLC/T19fH09CzQe83AwIDmzZvTvHlzxo8fz+LFi5k3bx7jx48vsdjTorBnzx5SUlJo3769SrtMJuPs2bM0/deyUKFCBV6+VPdAfvnypVIRO/z7fb97967yfFNX/P39iY2NZf78+dja2mJoaEiXLl3U5juvQ4RcLud///ufSuVpQFkpuzBj56ao5kczMzM1b8/8EsrnEBUVxfr16zl58qRSgbm4uBAeHs769evz3Ym5/+s1/eDBA0GpvQsY6HA0Zuy57s16OmZkYLhqFYaLFyPSkPVabmmJ6C0pO1IcZ1ylgUgkQiwWKx1Fcs53nj59quxz7do1lXtyzhRkGuIAC0N8fDx37txh8eLFyrOPyMhIsrIKH9zv+G8l8uTk/85+IyIiVJKIX7hwAQsLC513aRKJpMifMYfg4GCGDx+uzCiUw+zZswkODlYqtVq1anHlyhWVPjKZjOvXr/Ppp58C0KBBA+rWrcvKlSvp0aOH2rlaQkJCvudqZ8+eZeHChUrlGhsbq8xepA1XV1f27duHjY2NykIld/Le1xm7qOZHDw8PlixZwl9//aXcRYaEhGBoaIibm5vGe3IclfLOm56enlZHopz/g4LM0SWJ1sf0ixcv3tvztHcBvdOnMfngA4yCgtQUmsLAgLRJk0g6c+a9jTl7XdLT04mJiSEmJoY7d+4wefJkkpKS8Pb2BrLNQU2aNGHFihXcunWLCxcuMGPGDJUxqlWrhrGxMb///juxsbEadxa6kFNxfsuWLTx48IBTp04RGBioYq7URKdOndi8eTORkZE8fPiQX3/9laCgIGrXrq1UbpCtmKdOncq9e/c4cOAAK1euZNSoUTrLZ2trS3h4OH///Tdxcfkn/V6/fj1NmjTJ9/r169e5fPkyAwcOpF69eio/Pj4+7N+/n8TE7LIXAQEBbN26lQ0bNnD//n2uXr3K2LFjSUhIYNCgQUD2QmTNmjVER0fTvn17fvnlF6Kiorhx4wYrVqxQyTebFwcHB3bt2sXt27e5dOkSQ4YM0cnxYdiwYbx69YrBgwdz8eJFoqOjCQ0NZeLEiUrZX2fsHPOjth9tSq1NmzY4OTkxcuRIrly5QmhoKLNmzWLAgAHKxUtERARNmjQhIiICyD6LtLe3Z8KECURERBAVFcWqVasICQmhc+fOQLYDypo1a7h69SrR0dHs27ePiRMn0qFDh0Jn1i9OhODrQmLw60+lLQKi+HiMAwIw6dQJPQ2u3UIV6qIRGhqKo6Mjjo6OtGvXjkuXLvH999/zwQcfKPusXr0ayH5gTJo0SU2p6evrs2jRIoKDg6lbty59+/Z9LVnEYjGbNm3ixo0bNGvWjEmTJjF9+vQCa9W1bduWnTt30qNHDzw8PJgwYQLNmjVj3759Kqvv3r17I5fLadu2LZ999hn9+/cvlFL7/PPPefLkCQ0bNlSa/DQRFxenta7hli1bcHBwwNnZWe1a+/btkcvl/PRT9v9er169WLNmDdu2baN169b06tWL2NhYjhw5orJDcHd3JzQ0lDp16hAYGIiHhwc+Pj5ERERojc9avXo1ycnJtGrViiFDhtCvX78Cy1sBWFhYcOzYMcRiMT179qRp06ZMnDgRiUSi/Hu97thFQU9Pj507d1KuXDm8vb0ZPHgwnTt3VjGTpqSkcO/ePeUOzcDAgN27d1O1alV8fX1p0aIFP/74I2vWrKFDhw5A9i593759dO7cmaZNmzJ//nwGDBjAd999V6KfpyBECQkJJZ8L6x1l2dVE5kT8F8cx3sWExatUPdGe9a2A3OC/8xTj5sElZ35UKDDYvh2jmTMRx8erXZZXqULa3LklWoW6MPXUtLmSlyXe1XpZJZXy6l2dj5JCmA91dJ2T13mOCGdqhUQhEiNS/GdTVujpo837sdjIzKR8jx7o52Nbz+jXj7Q5c1CU0uGsgICAwNuAYH4sJLkVGgBGbyhRsYEBMg07JJmjI0lHjpC6erWg0AQEBN57hJ1aIbB5WriktsVN2qxZGPz8M+LYWBRGRqRPnkz66NHwluacE3i7Ka2qFwICJYmg1HRFoeCz3ZPUm7MS35wMUilp8+dj8OOPpC5ZguI9TV8mICAgkB+CUtORJokPlL9nmIvJrCYiyd0A5NoDYAuFXI7k++/RP3GClOBgjc4emT17ktmzZ4k5gggICAi8ywhKTUfsU7MDJFNrinn1YfGb+/JWoTbYuZNMX1/1joIyExAQEMgXwVFERyY/OgRAup2WPFkGlRAZFtJZIykJoxkzMGnVSqnQAIxmzEBUxNpXAgICAu8bglLTgV6xZ3H9t/CnIl+dJsLIZSYiUUHJIf9D/8gRKjRtqrEKtSg1Fb3IyNeUWEBAQOD9RDA/FoCRLIMfb2Yn75SVgwwrVaWlX/0jJLX9ClUIVPTkCcZTpmCQj/eZUIVaQEBA4PUQdmoFcPHi58rfX36gfpamZ+6lu0LLykKyZg0VPD01KjShCrVAWSI0NBSpVKosDJr3tYBASSAotXxQKBQsuRhH3dR/lG2ZZnmdNEToVdCtpIteRAQmrVtjPH06omTVCtkKPT3Sx4wh8exZsjp2LKroAkXA399frVjjL7/8goWFBUFBQaUk1ZsnLCyMjz/+mJo1a2JhYYGbmxt+fn4kJSW99pjNmzfnzp07yrRHW7ZsKXLew6dPn2JmZkaDBg3UaqhlZWUhlUr5+eef1e7z8/NTy8f54MEDRo0aRf369TEzM8PFxYWBAwdy/vz5Isn4rvHo0SP69OmDhYUFDg4OTJ06tcDSSk+fPsXPz486depgaWlJy5Yt2bNnj/J6VlYWPj4+ODs7Y25ujqurKyNGjOCff/7RMurrISi1fLj3Mgt9WfYfUlYOklz1QKyq1AzrTUYkyT87NgAZGRhNnEj5du3Qy1OeBCCrSROSQkNJCwoCE5Nik1+gePjxxx8ZMGAAs2bNYubMmaUtzhvhxo0b9O7dG1dXVw4fPkx4eDjLli3DxMSkSHXjJBIJ5ubmWgtTFpZt27bx8ccfIxaLCQ0Nfe1xLl68iJeXF/fv32fp0qWcO3eO7du34+LiwtSpU4tNXqDAOnilSVZWFr179yYtLY1ffvmF9evXs3fvXmbNmqX1vuHDh3P//n127NihrP82fPhwlTpurVq14vvvv+fChQvKCgsDBw4s9s8gKLV8eJSU7biRVVFEXFdDkt0M1PromXuptalhYID44UNEeVaRiooVSV22jORjx5D/W4RP4O1i7dq1fPbZZ6xcuRJ/f3+tfb29vZk0aRJTp06lRo0aODg4sH79etLS0hg/fjy2trY4Ozuze/dulfuePHnCoEGDqFGjBnZ2dvj4+BAVFaW8/ueff+Lr60vt2rWxsrLCy8uL3377TWWMevXqsWzZMsaMGYONjQ3169dXVhHIYePGjTRq1AgzMzMcHBzo2bNnvnWxTpw4gZmZGXPnzqVevXrY2dnRpk0bli1bpixxkmNKPHbsGC1atMDc3JzWrVur1TnLTW7zY2hoKJ999hmvXr1CKpUilUoLnVhZoVCwdetWfH196dOnD8HBwYW6Pwe5XM6oUaOoVasWv/zyC97e3tSsWRMXFxcmTpzI3r1787334sWLdOvWDXt7e2xtbenQoYOyfAtkK4nq1auzadMmPvnkEywtLZk/fz4AN2/epFevXlhbW1OrVi2GDx9ObGyszmOXBL/99hv37t1j3bp1uLq60rZtW7744gs2b96sdZd+4cIF/Pz8cHd3x87OjrFjx1K9enWlvPr6+vj7+9O4cWNsbW3x8PBg7NixXLhwoUgLJU0IjiIFkGYnRiHRsLLUNwF0WHGKRKQuXox+06bKmmcZvXqRNm8eilIspFcaJJ/wfqPvV77NL69979y5c1mzZg3BwcFqlZjz48cff2TMmDGcOHGCn3/+mSlTpvDbb7/Rrl07QkND2bp1K2PGjMHLywszMzOSkpLo3LkzLVu25PDhw0gkEpYvX07Xrl05d+4cxsbGJCYm0r59e2bOnImRkRF79uyhb9++nD17VqXUy6pVq5g+fTrjx4/n6NGjTJ8+nWbNmuHu7s7FixeZOnUq3377LR4eHiQkJBAWFpbv5zAzMyM2NpZTp07RsmVLrZ951qxZLFy4EHNzc+bPn4+vry9nzpwpMAN78+bNmTt3Ll999RUXLlwAwORfS8XcuXP5+uuvtdZnAzh58iRJSUm0bt0aBwcHmjVrRnx8fKErLkdGRnL37l02b96srGqem/yKiQIkJSXxySefsGjRIiC7blyvXr24fPmyyn0LFixg1qxZLFiwAJFIxN9//02nTp0YPHgw8+fPJz09naCgIPr168exY8cQiUQ6j513Tnw1xbfmYvLkyYwdO1bjtQsXLuDk5ISFhYWyrW3btqSlpXH16lWaN2+u8T5PT0/27dtH+/btqVSpEj///DMvXrzAy0vzwj8+Pp49e/bg6empVvm9qAhKTQtOksckN9Q84Qa2vXQ2oyjs7EifPBmD4GDSli4lq02b4hRToJgJCQnh2LFj7Ny5U2eFBuDs7MzkyZMB+Oyzz/j6668xNDRkxIgRAEyZMoUVK1Zw/vx5OnfuzJ49ezAwMGDVqlXK79LKlSuxt7fnt99+o0uXLri5ualUJ54yZQpHjx7l4MGDjB8/Xtn+0UcfMWzYMCC7iOa6desICwvD3d2dx48fY2Jigre3NyYmJtja2tKgQYN8P0evXr04ceIEnTt3plq1ari7u/Phhx/i4+ODqampSt8pU6bQunVrAL755hvq16/PgQMHlMU680MikSgLVOatkmxqakqdOnW03g/ZlbJ79uyJvr4+9vb2uLq6snPnzgJ31Xn5888/AXR6z7y0atVK5fWSJUvYv38/v//+Oz179lS29+rVi/79+ytfz5kzh4YNG6qY9dauXYuDgwNXrlzBzc1N57Fz07hx4wKrZGtT+jExMZiZmam0VatWDZFIpLKLzMsPP/zAkCFDqFmzJvr6+hgZGfH9999Tv359lX7Tp09n8+bNpKSk4OnpyY4dO7TK+joI5sd8qPbyd/bafKXWrmfaBONmPyCxU10N6Z05g+HChfmOlz56NElnzggK7R3AycmJmjVrsmjRIjVPvZMnT2JlZaX8yW2ayv0PLBKJqFq1KvXq1VO2GRoaUrFiRZ4/fw5k7xAePHiAtbW1crwaNWqQmJhIdHQ0kL0TmFR0ZK0AAB1vSURBVDFjBh4eHtja2mJlZcW1a9d48uSJilx5i2taWFjw7NkzIHulbWFhgaurK35+fuzYsUOrKUlPT49169Zx8+ZNgoKCsLKyYvny5TRp0oS7d1WTeueuZl2xYkXq1q2r1qew+Pv7Ex4errVPQkIChw4dUtmV+Pj4vJYJMq+DSWGIjY1l7NixuLu7Y2tri7W1NfHx8Wp/n4YNG6q8joyMVPsu5Sw0cv72uo6dG12qZGvbeQL5Lta1LeKDgoJITEzkwIEDnDhxglGjRuHn58eNGzdU+gUGBhIWFsaOHTuQy+X4+/sXaf41IezUNKCQZ1IzdoPGa/qWHREb/7eyFMXHYzRzJpJt2wDIatkSmSaTjZBJ/52hevXq7Nixgy5dutCtWzf279+vfBDkXQnnXtXq66v+O4lEIjXTikgkUp5lyeVy3Nzc2LBB/buWs5r+/PPPCQsLY86cOdjb21OuXDmGDx+u5myg6b1z3qdixYqcPHmSU6dOERoaytKlS5k7dy4nTpxQ2yXlxtLSEl9fX3x9fZkxYwaNGjVi1apVrFq1Kt973hS7du0iLS2Ntm3bqrTLZDIuXrxI48aN0dfXp1y5crx69Urt/pcvXyrPB2vVqgXA3bt31XYWBeHn58fLly9ZsGABNjY2GBoa0rlzZ7W/T7lyqiWq5HI53t7ezJ49W23MnO+UrmPnpqjmR3NzcyLzJH149uwZCoWCatU0Fz++d+8e3333HeHh4Tg5OQHQoEEDTp8+zcaNG/n666+VfU1NTTE1NcXa2pp69erh6urKhQsX8PDw0CpzYRCUmiayktBTpKk1Gz0QIW797+TnU4XaODCQpJMn4d/y7QL/UZQzrjeNpaUlP//8M126dKFLly7s37+fKlWqKFfCuUlLU/+u6IKrqysHDx6katWqSlNcXs6ePUvfvn3p0qULACkpKURHR6vsAHVBX1+fVq1a0apVK6ZOnUqtWrX49ddfVUxi2qhcuTJmZmYk5wlHuXjxIjY2NgAkJiZy584dNVf5/DAwMMjXWaUggoOD8ff3V5N/1qxZBAcH07hxYwAcHByIjIxUkSkrK4sbN24wePBgANzc3KhduzYrVqyga9euaudqCQkJ+e5uzp49y/Lly/nf//4HZLu2x8TEFCi/q6srR44cwdbWVm1BUpSxi2p+bNKkCcuXL+fp06dUr14dyDbHGxkZ5WuyTklJAbJ3+LnR09PT+vfN2aGlp6drlbewCOZHDaRkqv8hKp7MoOJFMSKRHuK7dynfuTPlAgJUFBqA3t276J848aZEFShBqlevzs8//0xmZiYff/xxgY4LhcXHx4fKlSvTt29fzpw5Q3R0NKdOnWLatGlKE5SDgwOHDh3iypUrXL9+XeMurSAOHz7Mt99+y9WrV3n06BG7d+8mJSUFR0dHjf03btzIhAkTCAkJITo6mps3bzJz5kzu3LlDp06dVPp+9dVXhIaGcuvWLQICAihXrhzdunXTSS5bW1uSkpL4448/iIuLIzU1Fcg+W2rWrFm+90VGRnLt2jUGDhxIvXr1VH769OnD3r17lco3ICCA4OBgNm7cyJ9//smVK1cYM2YMiYmJDBgwAACxWMyaNWu4f/8+3t7eHDt2jKioKG7cuMHy5cvzPb+C7L/Pzp07uXPnDhEREQwZMgRDHRa0fn5+xMXFMXToUCIiIoiOjiYkJIQxY8Yo5+F1xi6q+fGjjz6idu3ajBgxgqtXrxISEsKXX37J4MGDlY4858+fp0mTJsodnZOTEzVq1GD8+PFcunSJqKgoVqxYwcmTJ5Xfl7Nnz/Ldd99x7do1Hj16xMmTJxk+fDg1a9Ys1l0aCEpNI8lZqjZecaoC4wdyyJJhOHcuJi1aoH/6tNp9OVWoszp0eFOiCpQwZmZmHDqUncz6448/Vp5TFQcmJiYcPXoUa2trBgwYgIeHBwEBASQlJSkDlBcuXIhUKsXb2xsfHx+aN29e6IeAVCrl0KFDdO3aFQ8PD9auXcuaNWvyHadx48YkJiYyfvx4mjZtSqdOnTh79izr169Xe8B/8cUXfP7553h5efHo0SN+/PFHjI2NdZKrefPmDBw4kMGDB+Pg4KAMQ4iLi9N6LhccHIyjoyN169ZVu+bt7U1GRobyrNPX15fly5ezdetWWrVqRe/evYmPj+fo0aMq5jQPDw9CQ0Oxt7dn3LhxeHh44OPjw+XLl5Xeh5r45ptvePnyJR9++CHDhg1j8ODBWFlZFfjZraysOHbsGDKZjB49etC0aVMmTZqEsbGx0mT9umMXBX19fXbt2oVEIqF9+/YMHTqU7t27q5hJU1JSuHfvnlL5SiQS9uzZg1QqxcfHhxYtWrBr1y7Wrl2r3GUaGRmxd+9eunTpQpMmTZgwYQINGjTgyJEjOi0CCoMoISGheE/pCsnGjRtZuXIlMTEx1K1blwULFuTrNgpw6tQppk+fzu3bt6levTpjx45lyJAhxSrTs+d/Ue7qUOVrcaqCaqufI772F6IkdVPT+1SF+t69e9SuXbvAfi9fvlQ+mMs6aWlpBbqwlzVCQ0Pp1q0b0dHRaiv/93E+tCHMhzq6zsnrPEdKdae2d+9epk6dyoQJEwgLC8PDw4PevXvz+PFjjf2jo6Pp06cPHh4ehIWFERgYyOTJkzlw4ECxyiVOT/3v9xcZVFp9H73wPzUqtMx27Ug8e5b0wMAyr9AEBAQE3nZKVamtWbOGvn37MnDgQBwdHVm8eDHm5uZs2rRJY//NmzdTvXp1Fi9ejKOjIwMHDuSTTz5Ry55QLMgVlPvlKWZjrmAcrn6WIjc3J2XzZlJ270ZhZ1f87y8gICAgUGhKTallZGQQGRlJmzxxW23atFHJF5ab8+fPq/Vv27Ytly9fLvZUK8gVlD8WizhFtc6ZQiQiffhwEs+fJ7N7d6EStcB7SatWrbR6BQoIlBalptTi4uKQyWRqsQ/VqlXLN3I9NjZWY/+srKxi9UzTl5Qn5UUlYnzqo8ils2QuLiQfP07a4sXwnpwXCQgICLxLlHqcWt4odYVCoTVyXVN/Te25uXfvXuEFazQfGoHk/gJMjx7l75EjienTB/T14XXGK0PoMp9GRkbF7tX0NvO6sWplFWE+VBHmQx1d5uTVq1caNznanNVKTamZmpqip6enJvDz58/zjVzPSbSat7++vr7WgEJdvPXy48Ho0RjNmUNFa2s0h8e+XxTG+/F98fgSvNtUEeZDFWE+1NF1TipWrKgM7teVUjM/SiQS3NzcCAkJUWkPCQnB09NT4z05sSR5+zds2LDYMz3nIKtQQahC/Rro6+uTnJxc7HndBAQEyj4KhYLk5OR8s61oo1TNjwEBAYwYMQJ3d3c8PT3ZtGkTT58+Vaavycluvm7dOgAGDx7Mhg0bmDp1KoMHD1YW8tu4cWOpfQYBzZQvX5709HSNeffKGq9evco3zdX7iDAfqgjzoY4uc/K6RxilqtR69OhBfHw8ixcvJiYmBicnJ3bt2qUs8Z43G7WdnR27du3i888/Z9OmTVSvXp1FixbRtWvX0hBfoAAMDQ3fi3O12NjYQptIyjLCfKgizIc6JTknpe4oMmzYMGUdqLwcPnxYra1ly5ZaCxwKCAgICLy/CLkfBQQEBATKDIJSExAQEBAoMwhKTUBAQECgzFDqWfoFBAQEBASKC2GnJiAgICBQZhCUmoCAgIBAmUFQagICAgICZQZBqQkICAgIlBkEpSYgICAgUGZ475Xaxo0badCgAebm5nh5eXHmzBmt/U+dOoWXlxfm5ua4urrmW6X7XaUw83Hw4EG6d++Og4MD1tbWtG3bliNHjrxBaUuewn4/cggPD8fU1JRmzZqVsIRvnsLOSUZGBvPmzaNBgwaYmZnh7OzMt99++4akLXkKOx+7d++mZcuWWFhYUKdOHfz8/IiJiXlD0pYsp0+fxtfXFycnJ6RSKdu2bSvwnhs3btCxY0eqV6+Ok5MTixYtKlIi9Pdaqe3du5epU6cyYcIEwsLC8PDwoHfv3jx+/Fhj/+joaPr06YOHhwdhYWEEBgYyefLk/7d351E1p38Ax98p+1JTKmS5FUZk0CTKKFOTmRZrxn4sMWGSiRkUfpkmpElMI5EljGzNUbJVR9mT7dgGp7EPgzIKKRJuvz+ce4+rW+pyb4vndc49Z+a5z/d7P8/n5vvc5/t9vt+HhIQEDUeuHuXNR1paGvb29sTGxnLo0CGcnZ0ZOXJkmQ/8lV158yHz6NEjJk6ciIODg4Yi1RxVcjJu3DhSU1MJDw/n5MmTrFu3jg4dOmgwavUpbz6OHTvGhAkTGDZsGOnp6WzcuJGMjAy+++47DUeuHvn5+bRv356FCxdSt27dd9bPzc1lwIABGBkZsW/fPhYuXMjSpUuJiIhQOYaP+j41JycnOnTowO+//y4vs7Kyol+/fsydO7dY/blz57Jz505Onz4tL/Px8SEjI4O9e/dqJGZ1Km8+lHF0dMTW1pb58+erK0yNUTUfI0eOxNLSkqKiInbs2EF6eromwtWI8uZk3759jBkzhjNnzmBgYKDJUDWivPlYunQpUVFRXLhwQV4WExPDzJkzuXPnjkZi1hQTExN+/fVXRowYUWKdNWvW8PPPP3P58mV5JxgaGkp0dDSXLl0qdfHnkny0I7XCwkLOnj2Lo6OjQrmjoyPHjx9Xus2JEyeK1XdycuLMmTO8ePFCbbFqgir5UCYvLw89Pb0PHZ7GqZqP1atXc//+faZPn67uEDVOlZzs3r2bLl26sGzZMtq3b4+VlRUzZswgLy9PEyGrlSr56NatG1lZWSQmJlJUVER2djZxcXE4OztrIuRK58SJE9ja2iqM6pycnLh37x7//POPSvv8aDu17OxsXr16VWyVbUNDQ6XLh8Pr5RKU1X/58iXZ2dlqi1UTVMnH21atWsXdu3cZMmSIOkLUKFXycfHiRUJCQli5ciXa2tqaCFOjVMnJzZs3OXbsGBcuXOCPP/4gNDSU1NRUvv/+e02ErFaq5MPGxobVq1fj5eWFoaEh5ubmFBUVsXz5ck2EXOmUdEyVvaeKj7ZTk3l7eFtUVFTqkFdZfWXlVVV58yGTkJBAQEAAK1eulK+HVx2UNR/Pnz9n3LhxBAUFIZFINBRdxSjP34hUKkVLS4tVq1ZhbW2Nk5MToaGh7NixQ+WDVmVTnnxkZGTg5+fH9OnTOXDgANu2bSMrKwtfX19NhFopfehjaoWvp1ZRDAwM0NbWLvYP68GDB8V+OcgYGRkpra+jo4O+vr7aYtUEVfIhk5CQwMSJE1mxYgWurq7qDFNjypuPzMxMMjIy8Pb2xtvbG3h9QC8qKsLAwIA///yz2GmqqkaVvxFjY2OaNm2Krq6uvKxt27bA60WAjYyM1BewmqmSj8WLF2NlZcWUKVMAsLS0pF69eri4uPC///2P5s2bqz3uyqSkYyrwzuNOST7akVqtWrXo3Lkz+/fvVyjfv38/3bp1U7qNjY0NBw4cKFa/S5cu1KxZU12haoQq+QCIj49nwoQJREZGVqsVyMubj2bNmnH06FEOHz4sf3l6emJmZsbhw4exsbHRVOhqo8rfSPfu3cnMzFS4hnbt2jWAKr8atCr5ePbsWbFT07L/f59p7FWVjY0N6enpFBQUyMv2799P06ZNadWqlUr71Pbz8/v5A8VX5TRs2JDg4GCaNGlCnTp1CA0N5ejRo0RERKCrq8uECRPYtWsXffr0AcDU1JTffvuN//77jxYtWrBnzx7CwsKYN28e7dq1q+DWvL/y5mPbtm14eXkRGBhI7969yc/PJz8/nxcvXpRpOm9lV558aGtrY2hoqPA6ffo0165dw9/fn1q1alV0cz6I8v6NtG7dmo0bN3L27FnatWvHtWvXmD59Oj169Ch1VlxVUd58PHv2jKVLl2JgYIC+vr78dKSxsTE//PBDBbfm/eXl5ZGRkUFWVhYbNmygffv2NGrUiMLCQnR1dQkMDGTx4sUMGzYMAHNzc9auXctff/1FmzZtSE9PJyAgAF9f31J/TJfmoz39CDBw4EBycnIIDQ0lKysLCwsLYmNj5deE/v33X4X6EomE2NhYZs2aRXR0NE2aNCEkJKTajFDKm4/o6GhevnyJv78//v7+8vIePXqwe/dujcauDuXNx8egvDlp0KAB27dvZ8aMGTg6OqKnp4ebm1uZbxGp7MqbjxEjRpCXl8eqVauYM2cOjRo1omfPngQGBlZE+B/cmTNn5B04QHBwMMHBwQwbNozly5eTmZnJjRs35O/r6uoSHx/PTz/9xJdffomenh7e3t5MnjxZ5Rg+6vvUBEEQhOrlo72mJgiCIFQ/olMTBEEQqg3RqQmCIAjVhujUBEEQhGpDdGqCIAhCtSE6NUEQBKHaEJ2aUK3NmzevWi558rbr16+jp6fH1q1by1T/m2++qTb3VwrCm0SnJlQqGzduRE9PT+lr6tSpFR1emRw4cEAhbn19fdq2bYunp6f8EVGakJaWRnBwMLm5uRr7zHdRlps2bdowZswYrly5ovJ+K2NbhYrxUT9RRKi8/Pz8MDU1VShr3bp1BUWjmgkTJmBlZUVhYSHnz59n/fr1HDp0iPT0dJUf1loSU1NTMjMzFR7HdfToUUJCQhg1ahSNGjVSqL9jx44KXVnizdxcuHCB9evXc/jwYY4dO6ZSbkprq/BxEZ2aUCk5OTnRtWvXig7jvdjZ2Smc4pNIJMyePZstW7bg4+PzQT9LS0uLOnXqlLl+RT+L8u3cmJmZMXPmTLZu3fpej0gSBHH6UaiSdu3axeDBg7GwsMDQ0JCOHTsSGBhIYWHhO7c9c+YMHh4emJub06RJEzp16sTEiRN59uyZvE5RURErVqzAzs4OY2NjzMzM8PLy4t69eyrHbG9vD7xeOFMmJycHX19fPv30U4yMjLCxsWH58uXFnti+f/9+XFxcaNWqFSYmJlhbWyusrv32NbV58+Yxf/58ADp06CA/3Zeeng4oXlN7/vw5LVu2VLpwp7L31JEbOzu7YrkBOHLkCKNHj8bS0hIjIyPatWvHtGnTePz4sbzOu9oKkJqaiqurKyYmJjRr1oy+ffty8uRJleMVKi8xUhMqpdzc3GKrievr68tPmW3YsIFatWrh5eWFrq4ux48fJzw8nLt37xIVFVXifrOysujfvz9GRkb4+vqiq6vL7du3SUxM5OnTp/LVBaZMmcLmzZsZOnQo48ePJzMzk5UrV3LixAkOHjyosD5YWcke5PrJJ58AUFBQgLu7O5cvX8bT05M2bdqQlJSEv78/d+/eJSgoCHi9ovaQIUOwtLTEz8+PunXrcuPGDVJTU0v8rH79+nHlyhUSEhIICQlBT08PgDZt2hSrW7t2bdzc3Ni1axdLliyhdu3a8vf27t1Lbm4uHh4e8jJ15ObWrVsA8jhl4uPjyc3NZfTo0RgaGspX0M7IyGDPnj1lauuWLVuYNGkSvXr1Ys6cObx69YqYmBjc3d1JSkqiS5cu5Y5XqLxEpyZUSm8eRGWuXbsmn8m4du1a6tWrJ3/P09MTiURCaGgogYGBNGnSROl+jx07xuPHj9m5cyefffaZvHz27Nny/05LS2PDhg1ERUUxZMgQebmbmxuOjo6sWbOGadOmvbMNT548ITs7m8LCQs6dO8fs2bOpUaMGffv2BV6vcnDp0iUiIyMZPnw4AOPHj2f48OEsW7aMcePGIZFI2LdvH4WFhcTFxSkc9Et7snvHjh2xtLQkISEBd3d3TExMSo110KBBbN68mZSUFNzc3OTlcXFxGBgY4ODgoJbcvHjxggsXLshz8/aMzKCgIIXvGaBLly54e3tz6tQprK2tS23rkydPmDFjBiNHjmTp0qXy8jFjxtC9e3eCgoKIi4t7Z7xC1SFOPwqVUkhICNu3b1d4vTkBQHagk0qlPH78mOzsbOzs7JBKpZw/f77E/cr2kZSUxIsXL5TWkX2Wk5MT2dnZ8lfz5s2RSCQcOnSoTG2YPHky5ubmWFhYMHToULS0tFi/fr28M01OTsbIyIihQ4fKt9HS0sLHxwepVMrevXsVYt69ezdSqbRMn11eDg4ONG7cmPj4eHnZ06dPSU5Opl+/fujovP79+6Fz065dOwYNGkRBQQFr166lY8eOCvVk33NRUZF89G5rawvA2bNn3/k5+/btIzc3l2+//VYh3ufPn2Nvb09aWpracipUDDFSEyolKyurUieKXLx4kblz55KWlqZwLQxQuN7yNgcHB1xcXFiwYAERERHY2dnh6uqKh4cH9evXB+Dq1avk5uaWONuyrBMyZsyYgZ2dHTVr1sTExIQWLVoorHp869YtzM3NqVFD8belbMFZ2Sm5QYMGsWHDBry9vQkICMDe3h5XV1cGDBgg72zel46ODn379mXr1q08ffqUevXqkZSURH5+PgMHDpTX+9C5ycvLY8eOHWzfvl3pys+3bt0iICCAlJQUhdWzofTv+c14AfnoWJnc3Nxipz2Fqkt0akKV8+jRI/r06UPDhg0JCAhAIpFQt25dbt++LR/llKRGjRps3ryZU6dOkZSUxIEDB5gyZQphYWGkpqbSuHFjpFIphoaGrFq1Suk+ZJ3fu3To0IFevXqVu31vH9zr169PcnIyR44cISUlhdTUVOLj44mMjCQxMbFcsx5L4+HhQXR0NMnJyQwYMIBt27bRtGlT+SQOQC25cXd359mzZ/j4+NCtWzeaNm0KwKtXrxg4cCAPHz7kxx9/pG3bttSvX5/CwkIGDx5cphGWrE5UVBTGxsbvFbNQNYhOTahyDh48SE5ODps2baJ79+7yctnpurKwtrbG2tqaOXPmkJiYyLBhw4iJicHX1xdTU1OOHDmCjY1Nses5H1LLli3JyMhAKpUqjNYuX74sf19GW1sbBwcHHBwcCAoKIioqipkzZ7Jnzx6FkdSbynsfmp2dHSYmJmzbtg0nJydSU1MZO3asQmzqyk1gYCBdu3Zl0aJFhIWFAXD+/HmuXr3KypUrGTx4sLzu33//XWz7ktoqu9fR0NBQpR8YQtUjrqkJVY7sIPvmiEYqlRIZGfnObR8+fFhsJNSpUyfg9QgQYODAgbx69YqQkJBi2xcVFZGTk6Ny7G/6+uuvycrKIjY2VmH/ERERaGlp4ezsDKD0896OWRlZp1NanTdpaWnRv39/UlJS2LJlCwUFBcUm7KgrN2ZmZvTp04eYmBiysrIA5d8zQERERLHtS2qrs7MzjRo1IjQ0VOntHg8ePFApXqHyEiM1ocqxtbVFT08PLy8vvLy80NHRISEhgfz8/HduGxMTw7p163Bzc8PU1JSnT5+yceNGdHR05DPv7O3tGT9+POHh4Zw/fx5HR0fq1avHzZs32bVrF56enh/k5umxY8cSExODj48PZ8+exdzcnOTkZFJSUpg8eTISiQSA4OBgjh8/Tu/evWnZsiU5OTmsWbOGBg0a0Lt37xL3L5uqHhgYyIABA6hVqxa9evUq9VmYHh4eLFu2jKCgIFq1aoW1tbXC++rMjY+PD9u3bycyMpLAwEAsLCyQSCT4+/tz+/ZtdHV12bt3r9L74Upr65IlS/Dy8uKLL75g0KBBGBsbc+fOHQ4dOoSurm6Zn5cpVA2iUxOqnMaNGxMbG8ucOXMIDg6mQYMG9OvXj1GjRtGzZ89St+3Zsyfnzp0jPj6e+/fv07BhQzp16kRYWJjC/UqLFi2ic+fOrF27lgULFqCtrY2JiQlfffUVLi4uH6QddevWZefOnfzyyy/ExcXx8OFDJBIJCxYsYNKkSfJ67u7u3L17l02bNvHgwQP09fWxsbFh5syZNG/evMT929raMmvWLNavX09KSgpSqZTExET57EFlrKysMDMz4/r164wfP15pHXXl5vPPP8fW1pbo6GimTp0qv5ncz8+P8PBwdHR0cHZ2Jjw8HAsLizK31cPDg2bNmrFkyRKWLVtGQUEBxsbGdO3alVGjRqkcr1A5aT169Kj4lCNBEARBqILENTVBEASh2hCdmiAIglBtiE5NEARBqDZEpyYIgiBUG6JTEwRBEKoN0akJgiAI1Ybo1ARBEIRqQ3RqgiAIQrUhOjVBEASh2hCdmiAIglBt/B9Ri+bL9VZX1gAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_roc_curves_for_singlemodel([static_models[1], butina_models[1], kmeans_models[1]], \n",
+    "                                [static_xtest, butina_xtest, kmeans_xtest], \n",
+    "                                [static_ytest, butina_ytest, kmeans_ytest], \n",
+    "                                ['Static Split','Butina Split ','K-means Split'],\n",
+    "                                'ROC Curve Plot for SVM');\n",
+    "df_results_SVM"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "#### 5.3 Visualization of cluster and molecule distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of clusters: 1710 from 4493 molecules at distance cut-off 0.10\n",
+      "Number of molecules in largest cluster: 52\n",
+      "Similarity between two random points in same cluster: 0.91\n",
+      "Similarity between tfwo random points in different cluster: 0.64\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot the size of the clusters - save plot\n",
+    "fig, ax = plt.subplots(figsize=(15, 4))\n",
+    "ax.set_xlabel(\"Cluster index\")\n",
+    "ax.set_ylabel(\"# molecules\")\n",
+    "ax.bar(range(1, len(clusters) + 1), [len(c) for c in clusters])\n",
+    "ax.set_title(f\"Threshold: {cut_off:3.1f}\")\n",
+    "\n",
+    "print(f\"Number of clusters: {len(clusters)} from {len(compound_df)} molecules at distance cut-off {cut_off:.2f}\")\n",
+    "print(\"Number of molecules in largest cluster:\", len(clusters[0]))\n",
+    "print(f\"Similarity between two random points in same cluster: {DataStructs.TanimotoSimilarity(df_fingerprints[clusters[0][0]], df_fingerprints[clusters[0][1]]):.2f}\")\n",
+    "print(f\"Similarity between tfwo random points in different cluster: {DataStructs.TanimotoSimilarity(df_fingerprints[clusters[0][0]], df_fingerprints[clusters[1][0]]):.2f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "Distrubution of the clusters is flat and the molecules are quite homogenuous distributed, in contrast to the clusters created with k-means."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of clusters: 31 from 4493 molecules.\n",
+      "Number of molecules in largest cluster: 3484\n",
+      "Similarity between two random points in same cluster: 0.74\n",
+      "Similarity between two random points in different cluster: 0.30\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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WrFy5Ur1799Yrr7yi7du36+LFi3Jzc1NgYKCh82ndurXefvttLViwQLt371atWrXUsWNHJSYm6ttvvy0W7MeNGycXFxd99NFHSklJ0dWrV9W0aVONHDlSkydPtlkdv3Xr1lq/fr2WL1+ujRs3Wtcc+POf/ywnJ6cK/0xCQ0P1/fff69ChQ9q5c6fy8/Pl5uamoKAgTZw4USEhIYb3VZI2bdpo6tSpOnjwoPbs2aOzZ8+qTp068vLy0tixYxURESE/P79i7zt27Jhee+01m20nT57UyZMnra8J9gBQs5lyc3Mt1V0EAAAAAAAoH+6xBwAAAADAjhHsAQAAAACwYwR7AAAAAADsGMEeAAAAAAA7RrAHAAAAAMCOEewBAAAAALBjBHsAAAAAAOwYwb6apKenV3cJsBOMFRjBOIFRjBUYxViBEYwTGMVYqVwEewAAAAAA7BjBHgAAAAAAO0awBwAAAADAjlVbsF+7dq26desmLy8veXl56b777tOuXbus7ZGRkXJ2drb56dOnj80+Ll++rBkzZsjHx0eenp4aOXKkTp8+bdPn1KlTCg8Pl6enp3x8fDRz5kxduXKlSs4RAAAAAIDKVru6Duzp6akFCxaoVatWunbtml577TWNHj1ae/fu1R133CFJ6tWrl1avXm19T926dW32ER0drR07dmj9+vVycXHRnDlzFB4ern379snBwUGFhYUKDw+Xi4uLduzYoXPnzikyMlIWi0WxsbFVer4AAAAAAFSGagv2AwcOtHk9d+5crV+/XkeOHLEG+3r16snd3b3E9+fl5WnDhg1auXKlQkJCJEmrV69WQECA9u7dq9DQUO3Zs0fHjx/XsWPH1Lx5c0nSggULNGXKFM2dO1dNmjSpxDMEAAAAAKDy1Yh77AsLC7V161ZduHBBQUFB1u2HDh1S69at1blzZ02ZMkU//fSTte3o0aO6evWqevfubd3WvHlz+fn5KTk5WZKUkpIiPz8/a6iXpNDQUF2+fFlHjx6tgjMDAAAAAKByVduMvSR9/vnnCgsL06VLl9SwYUNt3LhR/v7+kqQ+ffpo0KBBatGihU6ePKlFixZp8ODB2rt3r+rVq6esrCw5ODjI1dXVZp9ms1lZWVmSpKysLJnNZpt2V1dXOTg4WPuUpiqes8izHGEUYwVGME5gFGMFRjFWYATjBEYxVm6Nr69vqW3VGux9fX31wQcfKC8vT4mJiYqMjNT27dvVvn17DR8+3NrP399fgYGBCggI0K5duzR48OBS92mxWGQymayvf/vv3ypt+29rq0zp6em3fAznl0/fvFM55I5pVin7RflUxFjB7x/jBEYxVmAUYwVGME5gFGOlclXrpfh169aVj4+POnbsqPnz5ysgIECrVq0qsW/Tpk3l6empb775RpLk5uamwsJC5eTk2PTLzs62ztK7ubkVm5nPyclRYWFhsZl8AAAAAADsUY24x77ItWvXSn0UXU5Ojs6cOWNdTC8wMFB16tRRUlKStc/p06d14sQJBQcHS5KCgoJ04sQJm0fgJSUlqV69egoMDKzEMwEAAAAAoGpU26X4f/vb3xQWFqZmzZqpoKBACQkJ2r9/v9544w0VFBRo8eLFGjx4sNzd3XXy5EktXLhQZrNZ999/vyTJyclJjzzyiObNmyez2Wx93J2/v7969eolSerdu7fatWuniRMnatGiRTp37pzmzZunRx99lBXxAQAAAAC/C9UW7DMzMxUREaGsrCw1adJE/v7+SkhIUGhoqC5evKi0tDS9/vrrysvLk7u7u7p3766XX35ZjRs3tu7jmWeekYODg8aMGaNLly6pR48eevHFF+Xg4CBJcnBw0JYtWzR9+nT169dP9evX14gRI7Ro0aLqOm0AAAAAACpUtQX7uLi4UtscHR21bdu2m+6jfv36io2NVWxsbKl9vLy8tGXLlnLVCAAAAABATVej7rEHAAAAAABlQ7AHAAAAAMCOEewBAAAAALBjBHsAAAAAAOwYwR4AAAAAADtGsAcAAAAAwI4R7AEAAAAAsGMEewAAAAAA7BjBHgAAAAAAO0awBwAAAADAjhHsAQAAAACwYwR7AAAAAADsGMEeAAAAAAA7RrAHAAAAAMCOEewBAAAAALBjBHsAAAAAAOwYwR4AAAAAADtGsAcAAAAAwI4R7AEAAAAAsGMEewAAAAAA7BjBHgAAAAAAO1ZtwX7t2rXq1q2bvLy85OXlpfvuu0+7du2ytlssFsXExKht27by8PDQwIEDdfz4cZt95ObmKiIiQt7e3vL29lZERIRyc3Nt+nz++ecaMGCAPDw81K5dOy1ZskQWi6VKzhEAAAAAgMpWbcHe09NTCxYs0L59+5SUlKQePXpo9OjR+uyzzyRJy5cv18qVK7VkyRLt2bNHZrNZQ4cO1fnz5637GDdunFJTUxUfH6+EhASlpqZqwoQJ1vb8/HwNHTpUbm5u2rNnjxYvXqwVK1bohRdeqPLzBQAAAACgMtSurgMPHDjQ5vXcuXO1fv16HTlyRP7+/oqLi9PUqVM1ZMgQSVJcXJx8fX2VkJCgMWPG6MSJE9q9e7d27typ4OBgSdJzzz2n/v37Kz09Xb6+voqPj9fFixcVFxcnR0dHtW/fXl9++aVWrVqlyZMny2QyVfl5AwAAAABQkWrEPfaFhYXaunWrLly4oKCgIGVkZCgzM1O9e/e29nF0dFS3bt2UnJwsSUpJSVGjRo2soV6SunbtqoYNG9r0ufvuu+Xo6GjtExoaqjNnzigjI6OKzg4AAAAAgMpTbTP20q/3v4eFhenSpUtq2LChNm7cKH9/f2swN5vNNv3NZrPOnDkjScrKypKrq6vNrLvJZNJtt92mrKwsax9PT89i+yhqa9myZam1paen3/L53cytH6NBhdRxvao4d5QNnwmMYJzAKMYKjGKswAjGCYxirNwaX1/fUtuqNdj7+vrqgw8+UF5enhITExUZGant27db26+/VN5isRQL8te7WZ+ihfNudhn+jX5pFaHodoFbsv90xRRznco+d5RNhYwV/O4xTmAUYwVGMVZgBOMERjFWKle1Xopft25d+fj4qGPHjpo/f74CAgK0atUqubu7S5J15r1Idna2dcbdzc1N2dnZNivcWywW5eTk2PQpaR9S8asBAAAAAACwRzXiHvsi165d05UrV9SiRQu5u7srKSnJ2nbp0iUdOnTIek99UFCQCgoKlJKSYu2TkpKiCxcu2PQ5dOiQLl26ZO2TlJSkpk2bqkWLFlV0VgAAAAAAVJ5qC/Z/+9vfdPDgQWVkZOjzzz/XggULtH//fj344IMymUyKjIzUsmXLlJiYqLS0NEVFRalhw4YaMWKEJMnPz099+vTRtGnTdOTIEaWkpGjatGnq27ev9RKPESNGyNHRUVFRUUpLS1NiYqKWLVumqKgoVsQHAAAAAPwuVNs99pmZmYqIiFBWVpaaNGkif39/JSQkKDQ0VJL0+OOP6+LFi5oxY4Zyc3PVuXNnbdu2TY0bN7buY+3atZo1a5aGDRsmSerfv7+effZZa7uTk5PefPNNTZ8+XSEhIXJ2dtakSZM0efLkqj1ZAAAAAAAqSbUF+7i4uBu2m0wmRUdHKzo6utQ+Li4uWrNmzQ334+/vr3feeadcNQIAAAAAUNPVqHvsAQAAAABA2RDsAQAAAACwYwR7AAAAAADsGMEeAAAAAAA7RrAHAAAAAMCOEewBAAAAALBjBHsAAAAAAOwYwR4AAAAAADtGsAcAAAAAwI4R7AEAAAAAsGMEewAAAAAA7BjBHgAAAAAAO0awBwAAAADAjhHsAQAAAACwYwR7AAAAAADsGMEeAAAAAAA7RrAHAAAAAMCOGQ72Bw4c0IsvvmizLT4+Xl26dFHr1q01a9YsXbt2rcILBAAAAAAApTMc7JcsWaLk5GTr6y+//FJRUVGqVauWOnbsqLVr1xYL/gAAAAAAoHIZDvZffPGFOnfubH39xhtvyNHRUbt371Z8fLzCw8O1cePGSikSAAAAAACUzHCwz8/Pl7Ozs/X1+++/r5CQEDVp0kSSdPfdd+vkyZMVXyEAAAAAACiV4WDv7u6uEydOSJLOnDmj1NRU9e7d29qen58vBwcHwwdeunSpQkJC5OXlpVatWik8PFxpaWk2fSIjI+Xs7Gzz06dPH5s+ly9f1owZM+Tj4yNPT0+NHDlSp0+ftulz6tQphYeHy9PTUz4+Ppo5c6auXLliuFYAAAAAAGqq2kY7Dho0SGvXrtXly5f18ccfq169eurfv7+1/bPPPlPLli0NH3j//v0aO3asOnXqJIvFomeeeUYPPPCAkpOT5eLiYu3Xq1cvrV692vq6bt26NvuJjo7Wjh07tH79erm4uGjOnDkKDw/Xvn375ODgoMLCQoWHh8vFxUU7duzQuXPnFBkZKYvFotjYWMP1AgAAAABQExkO9tHR0crKytIbb7yhxo0b64UXXpCbm5ukX2fr3377bY0fP97wgbdt22bzevXq1fL29tbhw4dtvjCoV6+e3N3dS9xHXl6eNmzYoJUrVyokJMS6n4CAAO3du1ehoaHas2ePjh8/rmPHjql58+aSpAULFmjKlCmaO3eu9VYCAAAAAADskeFg37BhQ61Zs6bEtkaNGiktLU0NGjQodyEFBQW6du2azX38knTo0CG1bt1aTk5OuueeezR37lyZzWZJ0tGjR3X16lWbWwKaN28uPz8/JScnKzQ0VCkpKfLz87OGekkKDQ3V5cuXdfToUfXo0aPcNQMAAAAAUN0MB/vfKiwsVF5enpo0aaLatWurVq1acnJyuqVCZs+erYCAAAUFBVm39enTR4MGDVKLFi108uRJLVq0SIMHD9bevXtVr149ZWVlycHBQa6urjb7MpvNysrKkiRlZWVZvwgo4urqKgcHB2ufkqSnp9/S+Rhx68co/xcpN1IV546y4TOBEYwTGMVYgVGMFRjBOIFRjJVb4+vrW2pbmYL9xx9/rIULF+rQoUO6evWq3nzzTfXs2VM5OTmKjIzUpEmT1LNnzzIX+NRTT+nw4cPauXOnzQJ8w4cPt/7b399fgYGBCggI0K5duzR48OBS92exWGQymayvf/vv3yptu3TjX1pFSE9Pv/Vj7D998z7lUNnnjrKpkLGC3z3GCYxirMAoxgqMYJzAKMZK5TK8Kn5KSooGDBigb7/9ViNHjpTFYrG2ubq6qqCgQBs2bChzAdHR0dq6dasSExNvuvhe06ZN5enpqW+++UaS5ObmpsLCQuXk5Nj0y87Ots7Su7m5FZuZz8nJUWFhYbGZfAAAAAAA7I3hYP/3v/9drVq1UnJysubNm1esvXv37vrwww/LdPBZs2YpISFBiYmJatOmzU375+Tk6MyZM9bF9AIDA1WnTh0lJSVZ+5w+fVonTpxQcHCwJCkoKEgnTpyweQReUlKS6tWrp8DAwDLVCwAAAABATWM42H/88cd6+OGHVb9+/RIvYW/WrJkyMzMNH3j69OnavHmz1q1bJ2dnZ2VmZiozM1MFBQWSfl1M7+mnn1ZKSooyMjL0wQcfaOTIkTKbzbr//vslSU5OTnrkkUc0b9487d27V59++qkmTJggf39/9erVS5LUu3dvtWvXThMnTtSnn36qvXv3at68eXr00UdZER8AAAAAYPcM32Nfq1Yt1apV+vcAmZmZcnR0NHzgdevWSZKGDBlis33WrFmKjo6Wg4OD0tLS9PrrrysvL0/u7u7q3r27Xn75ZTVu3Nja/5lnnpGDg4PGjBmjS5cuqUePHnrxxRet9+o7ODhoy5Ytmj59uvr166f69etrxIgRWrRokeFaAQAAAACoqQwH+8DAQO3cuVMTJkwo1nblyhXFx8fbrGh/M7m5uTdsd3R0LPas+5LUr19fsbGxio2NLbWPl5eXtmzZYrg2AAAAAADsheFL8Z944gn973//0+TJk3Xs2DFJ0o8//qjdu3dr8ODB+vbbb/Xkk09WWqEAAAAAAKA4wzP2ISEhWr16tWbMmKHNmzdLkiIjI2WxWOTk5KR169bprrvuqrRCAQAAAABAcWV6jv2IESM0YMAAJSUl6euvv9a1a9d0++23KzQ0VI0aNaqsGgEAAAAAQCnKFOwlqUGDBho4cGBl1AIAAAAAAMrI8KZANmkAACAASURBVD32AAAAAACg5il1xt7FxaXE59XfiMlkUk5Ozi0XBQAAAAAAjCk12M+cObPMwR4AAAAAAFStUoN9dHR0VdYBAAAAAADKgXvsAQAAAACwY4ZXxX/ttdcM9Rs1alS5iwEAAAAAAGVjONhHRUWV2vbbe/EJ9gAAAAAAVB3Dwf7TTz8ttu3atWvKyMjQ2rVr9cMPPyguLq5CiwMAAAAAADdmONh7e3uXuL1ly5bq2bOnhg0bpvXr1+vZZ5+tsOIAAAAAAMCNVdjief3799e2bdsqancAAAAAAMCACgv2WVlZunjxYkXtDgAAAAAAGGD4UvxTp06VuD0vL08ffPCBVq5cqXvvvbfCCgMAAAAAADdnONh36NDBZvX737JYLOratauWLl1aYYUBAAAAAICbMxzsX3jhhWLB3mQyydnZWT4+PvLz86vw4gAAAAAAwI0ZDvajR4+uzDoAAAAAAEA5GF4878cff9TBgwdLbT948KAyMzMrpCgAAAAAAGCM4WA/d+5c/f3vfy+1/R//+IfmzZtn+MBLly5VSEiIvLy81KpVK4WHhystLc2mj8ViUUxMjNq2bSsPDw8NHDhQx48ft+mTm5uriIgIeXt7y9vbWxEREcrNzbXp8/nnn2vAgAHy8PBQu3bttGTJElksFsO1AgAAAABQUxkO9gcOHNB9991XanufPn104MABwwfev3+/xo4dq127dikxMVG1a9fWAw88oHPnzln7LF++XCtXrtSSJUu0Z88emc1mDR06VOfPn7f2GTdunFJTUxUfH6+EhASlpqZqwoQJ1vb8/HwNHTpUbm5u2rNnjxYvXqwVK1bohRdeMFwrAAAAAAA1leF77HNycuTi4lJqu7Ozs3766SfDB962bZvN69WrV8vb21uHDx9W//79ZbFYFBcXp6lTp2rIkCGSpLi4OPn6+iohIUFjxozRiRMntHv3bu3cuVPBwcGSpOeee079+/dXenq6fH19FR8fr4sXLyouLk6Ojo5q3769vvzyS61atUqTJ08udaV/AAAAAADsgeEZ+6ZNm+qTTz4ptf3jjz+W2WwudyEFBQW6du2anJ2dJUkZGRnKzMxU7969rX0cHR3VrVs3JScnS5JSUlLUqFEja6iXpK5du6phw4Y2fe6++245Ojpa+4SGhurMmTPKyMgod70AAAAAANQEhoP9oEGDtHnzZm3durVY25tvvqnXXntNgwYNKnchs2fPVkBAgIKCgiTJuhDf9V8WmM1mZWVlSZKysrLk6upqM+tuMpl022232fQpaR9FbQAAAAAA2DPDl+LPmDFDSUlJGj9+vP71r3+pXbt2MplMSktL0xdffKG2bdtq9uzZ5Sriqaee0uHDh7Vz5045ODjYtF1/qbzFYikW5K93sz5FC+fd6DL89PR04ydQTrd+jAYVUsf1quLcUTZ8JjCCcQKjGCswirECIxgnMIqxcmt8fX1LbTMc7Js0aaJ3331Xy5cv19tvv60dO3ZIkm6//XbNnDlTU6ZMUYMGZQ+a0dHR2rZtm95++221bNnSut3d3V3Sr7PqzZs3t27Pzs62zri7ubkpOzvbJshbLBbl5OTY9Ll+Zj47O1tS8asBfutGv7SKULQGwC3Zf7piirlOZZ87yqZCxgp+9xgnMIqxAqMYKzCCcQKjGCuVy/Cl+JLUoEEDRUdH6+DBgzpz5ozOnDmjgwcPavbs2eUK9bNmzVJCQoISExPVpk0bm7YWLVrI3d1dSUlJ1m2XLl3SoUOHrPfUBwUFqaCgQCkpKdY+KSkpunDhgk2fQ4cO6dKlS9Y+SUlJatq0qVq0aFHmmgEAAAAAqEnKFOyLfP/99zp69KgKCgrKfeDp06dr8+bNWrdunZydnZWZmanMzEzrPk0mkyIjI7Vs2TIlJiYqLS1NUVFRatiwoUaMGCFJ8vPzU58+fTRt2jQdOXJEKSkpmjZtmvr27Wv9NmjEiBFydHRUVFSU0tLSlJiYqGXLlikqKooV8QEAAAAAdq9MwX779u3q1KmTOnTooN69e+ujjz6S9Ouj8Lp166a3337b8L7WrVun8+fPa8iQIfLz87P+rFixwtrn8ccfV1RUlGbMmKGQkBD9+OOP2rZtmxo3bmzts3btWt1xxx0aNmyYhg8frjvuuEOrV6+2tjs5OenNN9/UmTNnFBISohkzZmjSpEmaPHlyWU4dAAAAAIAayfA99rt27dKjjz6qLl26KDw8XIsXL7a2ubq6qnnz5tq8ebPhlfFzc3Nv2sdkMik6OlrR0dGl9nFxcdGaNWtuuB9/f3+98847huoCAAAAAMCeGJ6xf/bZZxUcHKx3331X48ePL9Z+11136dixYxVaHAAAAAAAuDHDwT4tLU3Dhg0rtd3d3d262jwAAAAAAKgahoN93bp1dfny5VLbT506pSZNmlRIUQAAAAAAwBjDwb5r16568803S2zLz8/Xpk2b1L179worDAAAAAAA3JzhYD979mx9/vnneuCBB6wL0aWmpuqll15Sz549lZ+fr5kzZ1ZaoQAAAAAAoDjDwb5jx45KSEjQ6dOnrY+Kmzdvnp588kk5ODgoISFBfn5+lVYoAAAAAAAozvDj7iTp3nvv1ZEjR3Ts2DF9/fXXunbtmm6//XYFBgbKZDJVVo0AAAAAAKAUZQr2RQICAhQQEFDRtQAAAAAAgDIqNdifOnWqXDv08vIqdzEAAAAAAKBsSg32HTp0KNfl9WfPnr2lggAAAAAAgHGlBvsXXniB++YBAAAAAKjhSg32o0ePrso6AAAAAABAORh+3N31zp8/r/Pnz1dkLQAAAAAAoIzKFOxPnjypCRMmyMfHRy1atFCLFi3k4+OjiRMn6uTJk5VVIwAAAAAAKIXhx92lp6erb9++ysvLU69eveTn5yeLxaL09HTFx8frvffe065du9S6devKrBcAAAAAAPyG4WC/YMECWSwWJSUlqUOHDjZtx44d05AhQ7RgwQJt2LChwosEAAAAAAAlM3wp/v79+zVhwoRioV6SAgICNH78eH3wwQcVWhwAAAAAALgxw8H+ypUratKkSantTk5OunLlSoUUBQAAAAAAjDEc7Nu3b68tW7bo4sWLxdouX76sLVu2qH379hVaHAAAAAAAuDHD99g/8cQTevjhhxUSEqKxY8fK19dXkvTll1/qpZdeUnp6ujZu3FhphQIAAAAAgOIMB/sBAwZozZo1evrppzVz5kyZTCZJksVikbu7u9asWaP+/ftXWqEAAAAAAKC4Mj3HfsSIEfrss8/03nvvad26dVq3bp3ee+89ffbZZxo+fHiZD37gwAGNHDlS7dq1k7OzszZt2mTTHhkZKWdnZ5ufPn362PS5fPmyZsyYIR8fH3l6emrkyJE6ffq0TZ9Tp04pPDxcnp6e8vHx0cyZM1kPAAAAAADwu2B4xt76htq11aVLF3Xp0uWWD37hwgW1b99eo0aN0sSJE0vs06tXL61evdr6um7dujbt0dHR2rFjh9avXy8XFxfNmTNH4eHh2rdvnxwcHFRYWKjw8HC5uLhox44dOnfunCIjI2WxWBQbG3vL5wAAAAAAQHUqc7A/e/asMjIylJubK4vFUqy9d+/ehvcVFhamsLAwSVJUVFSJferVqyd3d/cS2/Ly8rRhwwatXLlSISEhkqTVq1crICBAe/fuVWhoqPbs2aPjx4/r2LFjat68uSRpwYIFmjJliubOnXvDlf4BAAAAAKjpDAf7rKwsPfHEE3rnnXdKDPQWi0Umk0lnz56t0AIPHTqk1q1by8nJSffcc4/mzp0rs9ksSTp69KiuXr1q82VC8+bN5efnp+TkZIWGhiolJUV+fn7WUC9JoaGhunz5so4ePaoePXpUaL0AAAAAAFQlw8E+KipKe/fu1ZgxY9S5c+cqmenu06ePBg0apBYtWujkyZNatGiRBg8erL1796pevXrKysqSg4ODXF1dbd5nNpuVlZUl6dcvJIq+CCji6uoqBwcHax8AAAAAAOyV4WB/4MAB/fWvf9X8+fMrsx4bv12Qz9/fX4GBgQoICNCuXbs0ePDgUt9XdPVAkd/++7dK2y5J6enp5ai4bG79GA0qpI7rVcW5o2z4TGAE4wRGMVZgFGMFRjBOYBRj5dYUPXK+JIaDvdlsloeHR4UUVF5NmzaVp6envvnmG0mSm5ubCgsLlZOTo9tuu83aLzs7W926dbP2SU5OttlPTk6OCgsLi83k/9aNfmkVIT09/daPsf/0zfuUQ2WfO8qmQsYKfvcYJzCKsQKjGCswgnECoxgrlcvw4+4iIiK0ZcsW/fLLL5VZzw3l5OTozJkz1sX0AgMDVadOHSUlJVn7nD59WidOnFBwcLAkKSgoSCdOnLB5BF5SUpLq1aunwMDAqj0BAAAAAAAqmOEZ+8mTJ+vq1au6++679eCDD8rT01MODg7F+o0aNcrwwQsKCqyz79euXdP333+v1NRUubi4yMXFRYsXL9bgwYPl7u6ukydPauHChTKbzbr//vslSU5OTnrkkUc0b948mc1m6+Pu/P391atXL0m/rtLfrl07TZw4UYsWLdK5c+c0b948Pfroo6yIDwAAAACwe4aD/cmTJ7V161Z99dVXiomJKbGPyWQqU7D/5JNPNGjQIOvrmJgYxcTEaNSoUVq6dKnS0tL0+uuvKy8vT+7u7urevbtefvllNW7c2PqeZ555Rg4ODhozZowuXbqkHj166MUXX7R+6eDg4KAtW7Zo+vTp6tevn+rXr68RI0Zo0aJFhusEAAAAAKCmKtOM/ddff63o6Gh16dKlQma7u3fvrtzc3FLbt23bdtN91K9fX7GxsYqNjS21j5eXl7Zs2VKuGgEAAAAAqMkMB/sPP/xQU6dO1cyZMyuzHgAAAAAAUAaGF8/z8PBQo0aNKrMWAAAAAABQRoaD/dSpU/Xqq68qPz+/MusBAAAAAABlYPhS/HPnzql+/frq1KmThgwZombNmhVbFd9kMmnKlCkVXiQAAAAAACiZ4WD/t7/9zfrvl156qcQ+BHsAAAAAAKqW4WD/6aefVmYdAAAAAACgHAwHe29v78qsAwAAAAAAlIPhxfMAAAAAAEDNQ7AHAAAAAMCOEewBAAAAALBjBHsAAAAAAOwYwR4AAAAAADtGsAcAAAAAwI4ZDvb5+fkaNGgQz7MHAAAAAKAGMRzsf/nlF+3fv1+5ubmSCPoAAAAAANQEtW/U2KFDB3Xp0kWdOnVSq1atJEkmk0lS8aAPAAAAAACq3g2D/eTJk/XRRx/plVde0ddffy2TyaQ5c+YoLCxMAQEBkv4v6AMAAAAAgKp3w2AfERFh/fd3332njh076vbbb9f+/fu1YsUKmUwmzZ49W/fee6+Cg4MVFBQkLy+vSi8aAAAAAAD86ob32H/66acqLCyUJDVp0kSSNHbsWO3atUuffPKJLBaL2rVrp6+++kpPPPGE7rzzzsqvGAAAAAAAWN1wxr5Xr15ydHTUnXfeqXbt2slkMqmgoECS5OjoKEl69NFH1bNnT1ksFn3xxReVXzEAAAAAALC6YbBPS0vThx9+qI8//lhHjhyRxWLRI488Ih8fH3Xq1Ekmk0n5+fmSfr3Xvl27dlVSNAAAAAAA+NUNL8Vv2rSpBg0apPnz5+vf//63JOkf//iHHnvsMZ09e1YWi0WPPfaY/P399f/+3//TypUry3TwAwcOaOTIkWrXrp2cnZ21adMmm3aLxaKYmBi1bdtWHh4eGjhwoI4fP27TJzc3VxEREfL29pa3t7ciIiKKrdT/+eefa8CAAfLw8FC7du20ZMkSWSyWMtUKAAAAAEBNZPg59kWr37dv315//etftXr1aknSs88+q+nTp6t+/fp6+eWXy3TwCxcuqH379lq8eLH10v7fWr58uVauXKklS5Zoz549MpvNGjp0qM6fP2/tM27cOKWmpio+Pl4JCQlKTU3VhAkTrO35+fkaOnSo3NzctGfPHi1evFgrVqzQCy+8UKZaAQAAAACoiW54Kb5Nx9q1dc8998jZ2VnS/wV9X19f9ezZU2PGjCnzwcPCwhQWFiZJioqKsmmzWCyKi4vT1KlTNWTIEElSXFycfH19lZCQoDFjxujEiRPavXu3du7cqeDgYEnSc889p/79+ys9PV2+vr6Kj4/XxYsXFRcXJ0dHR7Vv315ffvmlVq1apcmTJ/O4PgAAAACAXTM8Y9+kSRNt377duvL99UG/omVkZCgzM1O9e/e2bnN0dFS3bt2UnJwsSUpJSVGjRo2soV6SunbtqoYNG9r0ufvuu22uCAgNDdWZM2eUkZFRKbUDAAAAAFBVDM/YX68o6FeWzMxMSZLZbLbZbjabdebMGUlSVlaWXF1dbWbdTSaTbrvtNmVlZVn7eHp6FttHUVvLli0r6xQAAAAAAKh05Q72VeX6S+UtFkuxIH+9m/UpWjjvRpfhp6enl6vesrj1YzSokDquVxXnjrLhM4ERjBMYxViBUYwVGME4gVGMlVvj6+tbaluNDfbu7u6Sfp1Vb968uXV7dna2dcbdzc1N2dnZNkHeYrEoJyfHpk/R7P1v9yEVvxrgt270S6sIRWsA3JL9pyummOtU9rmjbCpkrOB3j3ECoxgrMIqxAiMYJzCKsVK5DN9jX9VatGghd3d3JSUlWbddunRJhw4dst5THxQUpIKCAqWkpFj7pKSk6MKFCzZ9Dh06pEuXLln7JCUlqWnTpmrRokUVnQ0AAAAAAJWjWoN9QUGBUlNTlZqaqmvXrun7779XamqqTp06JZPJpMjISC1btkyJiYlKS0tTVFSUGjZsqBEjRkiS/Pz81KdPH02bNk1HjhxRSkqKpk2bpr59+1q/DRoxYoQcHR0VFRWltLQ0JSYmatmyZYqKimJFfAAAAACA3avWS/E/+eQTDRo0yPo6JiZGMTExGjVqlOLi4vT444/r4sWLmjFjhnJzc9W5c2dt27ZNjRs3tr5n7dq1mjVrloYNGyZJ6t+/v5599llru5OTk958801Nnz5dISEhcnZ21qRJkzR58uSqO1EAAAAAACpJtQb77t27Kzc3t9R2k8mk6OhoRUdHl9rHxcVFa9asueFx/P399c4775S7TgAAAAAAaqoae489AAAAAAC4OYI9AAAAAAB2jGAPAAAAAIAdI9gDAAAAAGDHCPYAAAAAANgxgj0AAAAAAHaMYA8AAAAAgB0j2AMAAAAAYMcI9gAAAAAA2DGCPQAAAAAAdoxgDwAAAACAHSPYAwAAAABgxwj2AAAAAADYMYI9AAAAAAB2jGAPAAAAAIAdI9gDAAAAAGDHCPYAAAAAANgxgj0AAAAAAHaMYA8AAAAAgB0j2AMAAAAAYMcI9gAAAAAA2LEaHexjYmLk7Oxs89OmTRtru8ViUUxMjNq2bSsPDw8NHDhQx48ft9lHbm6uIiIi5O3tLW9vb0VERCg3N7eqTwUAAAAAgEpRo4O9JPn6+urEiRPWn4MHD1rbli9frpUrV2rJkiXas2ePzGazhg4dqvPnz1v7jBs3TqmpqYqPj1dCQoJSU1M1YcKE6jgVAAAAAAAqXO3qLuBmateuLXd392LbLRaL4uLiNHXqVA0ZMkSSFBcXJ19fXyUkJGjMmDE6ceKEdu/erZ07dyo4OFiS9Nxzz6l///5KT0+Xr69vlZ4LAAAAAAAVrcbP2H/33Xdq166dOnTooL/85S/67rvvJEkZGRnKzMxU7969rX0dHR3VrVs3JScnS5JSUlLUqFEja6iXpK5du6phw4bWPgAAAAAA2LMaPWPfpUsXrVq1Sr6+vsrOzlZsbKzCwsJ0+PBhZWZmSpLMZrPNe8xms86cOSNJysrKkqurq0wmk7XdZDLptttuU1ZW1g2PnZ6eXsFnUxnHaFAhdVyvKs4dZcNnAiMYJzCKsQKjGCswgnECoxgrt+ZGV5zX6GB/33332bzu0qWLAgMDtXnzZt11112SZBPapV8v0b8+yF/v+j4lqezL9CvkVoD9pyummOtwi0LNwm0jMIJxAqMYKzCKsQIjGCcwirFSuWr8pfi/1ahRI7Vt21bffPON9b7762fes7OzrbP4bm5uys7OlsVisbZbLBbl5OQUm+kHAAAAAMAe1egZ++tdunRJ6enp6t69u1q0aCF3d3clJSWpU6dO1vZDhw5p4cKFkqSgoCAVFBQoJSXFep99SkqKLly4YHPfPQAAAABUNOeXK+cKW0nKHdOs0vYN+1Ojg/3TTz+tfv36qXnz5tZ77H/++WeNGjVKJpNJkZGR+te//iVfX1+1bt1a//znP9WwYUONGDFCkuTn56c+ffpo2rRpWr58uSwWi6ZNm6a+fftyGQgAAAAA4HehRgf7H374QePGjVNOTo5uu+02denSRe+99568vb0lSY8//rguXryoGTNmKDc3V507d9a2bdvUuHFj6z7Wrl2rWbNmadiwYZKk/v3769lnn62W8wEAAAAAoKLV6GD/0ksv3bDdZDIpOjpa0dHRpfZxcXHRmjVrKro0AAAAAABqBLtaPA8AAAAAANgi2AMAAAAAYMcI9gAAAAAA2DGCPQAAAAAAdoxgDwAAAACAHSPYAwAAAABgxwj2AAAAAADYMYI9AAAAAAB2jGAPAAAAAIAdI9gDAAAAAGDHCPYAAAAAANgxgj0AAAAAAHasdnUXAAAAgN8f55dPV9q+c8c0q7R9A4A9YsYeAAAAAAA7RrAHAAAAAMCOEewBAAAAALBjBHsAAAAAAOwYwR4AAAAAADtGsAcAAAAAwI7xuDsAAFBj8cg0AABujhl7AAAAAADs2B8q2K9bt04dOnSQu7u7evbsqYMHD1Z3SQAAAAAA3JI/zKX427Zt0+zZs/Wvf/1LXbt21bp16/Tggw/q8OHD8vLyqu7yAAAAYEcq6zYRbhEBUB5/mGC/cuVKPfTQQ3rsscckSbGxsXr//ff10ksvaf78+dVcHQDg94T/ww9UPf57B+CPzJSbm2up7iIq25UrV9S0aVOtX79eDzzwgHX79OnTlZaWph07dlRjdQAAAAAAlN8f4h77nJwcFRYWymw222w3m83KysqqpqoAAAAAALh1f4hgX8RkMtm8tlgsxbYBAAAAAGBP/hDB3tXVVQ4ODsVm57Ozs4vN4gMAAAAAYE/+EMG+bt26CgwMVFJSks32pKQkBQcHV1NVAAAAAADcuj/MqviTJk3ShAkT1LlzZwUHB+ull17Sjz/+qDFjxlR3aQAAAAAAlNsfYsZekoYNG6aYmBjFxsaqe/fuOnz4sN544w15e3tXeS3r1q1Thw4d5O7urp49e+rgwYNVXgNqrpiYGDk7O9v8tGnTprrLQg1w4MABjRw5Uu3atZOzs7M2bdpk026xWBQTE6O2bdvKw8NDAwcO1PHjx6upWlSnm42VyMjIYn9n+vTpU03VorosXbpUISEh8vLyUqtWrRQeHq60tDSbPvxdgZFxwt8USNLatWvVrVs3eXl5ycvLS/fdd5927dplbefvSeX6wwR7SRo3bpyOHTumrKws7du3T/fcc0+V17Bt2zbNnj1bTz75pP73v/8pKChIDz74oE6dOlXltaDm8vX11YkTJ6w/fPkDSbpw4YLat2+vxYsXy9HRsVj78uXLtXLlSi1ZskR79uyR2WzW0KFDdf78+WqoFtXpZmNFknr16mXzdyY+Pr6Kq0R1279/v8aOHatdu3YpMTFRtWvX1gMPPKBz585Z+/B3BUbGicTfFEienp5asGCB9u3bp6SkJPXo0UOjR4/WZ599Jom/J5XtD/Ec+5okNDRU/v7+ev75563bOnXqpCFDhmj+/2/vzoOqqvs4jr8BIRcQXAoRRFRUEGlQiEhyyQVzHKxEUUMnl8zIRGxwENFEcUTFPUbcJs3SzAEXtMGlCYXJpalxKSdNMZdMUVFUUETgPn843KcraE8qXHj4vGYYOL9zfvd8z53ffIfvOb9zzowZZoxMqouEhATS0tI4ePCguUORaszZ2Zn58+cTFhYGPDwL7uHhwdixY4mKigLg3r17tG3blvj4eN12VIs9Olbg4dW1Gzdu8M0335gxMqlu8vPzcXV1ZcOGDfTr1095RSr06DgB5RR5PDc3N2bMmMHIkSOVTypZrbpib25FRUUcPXqUnj17mrT37NmTw4cPmykqqY7OnTuHp6cnL7/8MqNHj+bcuXPmDkmqufPnz5OTk2OSX+rVq0eXLl2UX6RCBw8exN3dHV9fXyIiIrh27Zq5QxIzy8/Pp7S0FAcHB0B5RSr26Dgpo5wif1dSUkJqaioFBQX4+/srn1SBWvPwvOogNzeXkpKScq/Ye/HFF8u9ik9qLz8/P5YvX07btm25fv06iYmJBAUFcejQIRo3bmzu8KSaysnJAagwv1y+fNkcIUk11rt3b4KDg2nZsiUXLlxg9uzZDBgwgH379vHCCy+YOzwxkylTpuDt7Y2/vz+gvCIVe3ScgHKK/NeJEycICgqisLCQBg0a8NVXX+Hl5WUs3pVPKo8KezOwsLAwWTYYDOXapPbq06ePybKfnx8+Pj5s3LiRjz/+2ExRSU2h/CL/i5CQEOPfXl5e+Pj44O3tze7duxkwYIAZIxNzmTp1KocOHWLXrl1YWVmZrFNekTKPGyfKKVKmbdu2ZGVlcevWLdLS0ggPD2fnzp3G9conlUdT8atQkyZNsLKyKnd1/vr16+XOXomUsbW1xcPDg7Nnz5o7FKnGHB0dAZRf5Kk4OTnRvHlz5ZlaKiYmhtTUVNLS0nBzczO2K6/I3z1unFREOaX2srGxoXXr1nTq1IkZM2bg7e3N8uXLlU+qgAr7KmRjY4OPjw8ZGRkm7RkZGbz66qtmikqqu8LCQk6fPm1MiCIVadmyJY6Ojib5pbCwkIMHDyq/yD/Kzc3l8uXLyjO1UHR0NCkpKaSlpZV7taryipR50jipiHKKlCktLaWoqEj5pApYTZkyJc7cQdQmdnZ2JCQk0KxZM+rWrUtiYiIHDhwgKSkJbk5/hQAACtFJREFUe3t7c4cn1cC0adOwsbGhtLSUM2fOMHnyZM6ePcvixYs1Rmq5/Px8Tp48SU5ODl9++SUdOnSgYcOGFBUVYW9vT0lJCYsXL8bd3Z2SkhJiY2PJyclhyZIlusexlnnSWLGysmLWrFnY2tpSXFzML7/8woQJEygpKSExMVFjpRaJiopi06ZNrFu3DhcXFwoKCigoKAAeXoywsLBQXpF/HCf5+fnKKQJAXFyc8X/YS5cukZyczObNm4mLi6NNmzbKJ5VMr7szgzVr1rB06VJycnLw9PRkzpw5BAYGmjssqSZGjx7NgQMHyM3NpWnTpvj5+REbG4uHh4e5QxMzy8rKIjg4uFz7sGHDSE5OxmAwMHfuXNatW0deXh6+vr4sWLCADh06mCFaMacnjZVFixYRFhbG8ePHuXXrFo6OjnTt2pXY2FhcXFzMEK2Yy6NPNS8THR1NTEwMgPKK/OM4uXfvnnKKAA9fe5iVlcXVq1dp2LAhXl5eRERE0KtXL0D5pLKpsBcRERERERGpwXSPvYiIiIiIiEgNpsJeREREREREpAZTYS8iIiIiIiJSg6mwFxEREREREanBVNiLiIiIiIiI1GAq7EVERERERERqMBX2IiIiNUx4eDje3t7mDuO5On/+PA4ODmzYsOG5fm7//v3p37//c/1MERGR6kaFvYiISDVx7do14uLiCAgIoHnz5jg5OdGlSxfi4uK4cuVKlcWxa9cuEhISqmx/IiIi8mzqmDsAERERgSNHjjB48GDu3LlDSEgIY8eOxdLSkhMnTvDFF1+wY8cOfv755yqJZffu3axdu5aYmJgq2R+Aq6srV65cwdrausr2KSIi8v9Chb2IiIiZ5eXlERYWhoWFBfv27cPT09Nk/fTp01myZImZont+7t69S/369StcZ2FhQd26das4IhERkf8PmoovIiJiZuvWreOvv/5i9uzZ5Yp6AHt7e2bMmPHY/k+6P93b25vw8HDjcnFxMYmJifj6+tKsWTNat25NUFAQ27dvBx7ev7927VoAHBwcjD/nz583fkZqaiq9evXCyckJV1dXhgwZwsmTJ032Gx4ejqOjIxcuXODdd9/F1dWVwYMH/6tjSEhIwMHBgezsbCZNmkSrVq1wdnbmvffe48aNGyb9DQYDS5cupWPHjjRr1ow+ffpw+PDhCvdVVFTE/Pnz8fPz46WXXqJdu3ZMmjSJvLw84zb79++nUaNGzJw506Tvd999h4ODA3Pnzn3ssYiIiFQ1XbEXERExs/T0dOrWrcs777xT6fuaO3cuCxcuZMSIEfj6+lJQUMDx48f56aefeOuttxg1ahSXLl0iMzOTlStXGvs1bdoUgCVLlhAXF0dwcDBDhw6loKCANWvW0LdvX/bv34+bm5uxT2lpKQMHDqRz587MnDkTKyurp4p5zJgxODo6EhsbS3Z2NqtWrcLa2po1a9YYt5k3bx5z586lR48eREREkJ2dzZAhQ3BwcMDZ2dm4ncFgYPjw4WRmZjJixAi8vLz4448/WL16NUePHmXPnj1YW1vTvXt3PvjgA5YtW0a/fv3w9/cnLy+PCRMm4OPjQ1RU1FMdi4iISGVQYS8iImJmp06dwt3dHRsbm0rf1+7duwkKCmLZsmUVrvf396dNmzZkZmYyZMgQk3UXL15k9uzZREdHm9x/P3ToUPz9/VmwYAFJSUnG9gcPHhAUFMScOXOeKeZ27dqxatUq47LBYGD16tUsXLgQe3t7cnNzWbRoET169GDLli1YWj6ckOjp6UlkZKRJYZ+SksLevXvZvn073bp1M7YHBgYSGhpKamoqQ4cOBSAuLo7vv/+e8PBwsrKyiIqK4ubNm2zdupU6dfQvlIiIVB+aii8iImJmd+7cwc7Orkr2ZWdnx2+//caZM2f+dd8dO3ZQXFxMSEgIubm5xh9ra2v8/PzIzMws1+f9999/5pjHjBljshwYGEhJSQl//vknABkZGRQVFTFu3DhjUQ8QFhaGvb29Sd+tW7fi7u6Ol5eXyTH4+vpia2trcgz16tVjxYoVnDt3jgEDBpCSksK0adPw8PB45mMSERF5nnS6WURExMzs7Oy4c+dOlewrJiaG4cOH4+fnh4eHBz179mTQoEF07tz5H/tmZ2cDD6/qV+TRB+NZWlri6ur6zDG3aNHCZNnBwQGAmzdvAg9nEgC0bdvWZDtra2tatmxp0padnc3p06dp06ZNhfu6fv26ybKvry/h4eEkJSUREBDA+PHjn/5AREREKokKexERETNr3749x44do6io6Kmm41tYWDx2XWlpqcly165dOXbsGOnp6WRkZLBp0yaSk5OZPn06n3zyyRP3U/ZZKSkpFU5F//vVcnhYWD+PKeuPuzffYDCY/K7oeyhbV6a0tBQPD4/HPvyucePGJssPHjwwXsW/ePEit2/fLjcLQERExNxU2IuIiJhZv379OHz4MNu2bSM0NPRf92/UqBEAt27dMmm/f/8+V65cKbe9g4MDw4YNY9iwYdy7d49BgwYxb948Jk6ciJWV1WNPFLRq1QoAFxeXajUdvWxWwO+//25yJf7BgwdcuHCBjh07GttatWrF0aNH6datW7kTERWZN28ex48fJz4+nvj4eKKjo1mxYsXzPwgREZFnoHvsRUREzGzkyJE0b96cadOmcerUqXLrb9++zaxZsx7b387OjqZNm5KVlWXS/vnnn1NSUmLS9uhr4urVq0f79u25f/8+d+/eBf47pf7vr38DGDBgAHXq1CEhIaHcTAAoP429qrzxxhvY2NiwcuVKk7g2bNhQ7mTHwIEDuXr1qsnD+MoUFxebHPORI0dYsmQJo0ePZsKECcTExLBp0ya+/fbbyjsYERGRp6Ar9iIiImZW9v72wYMH0717d+M975aWlpw4cYLU1FQaN27Mp59++tjPGDlyJAsWLOCjjz7ilVde4ciRI+zfv58mTZqYbOfv70+XLl3o3LkzjRs35tdff2X9+vX07dvX+AC/Tp06ATB58mR69+5NnTp1ePPNN3Fzc2PmzJnExsbSu3dvgoODadSoERcvXmTPnj34+fmxePHiyvuiHqNJkyZMnDiRxMREBg4cSP/+/cnOzubrr782ef0eQGhoKDt27GDKlCn88MMPBAYGYmFhwdmzZ0lLS2P27NmEhIRQWFjIhx9+iIuLi/GkSkREBOnp6URGRhIQEFDuuxURETEXFfYiIiLVQKdOnTh48CBJSUns2rWL1NRUDAYDrVu3ZtSoUYwbN+6J/aOiorhx4wZbtmxh27ZtvP7662zfvp3g4GCT7cLDw0lPTyczM5PCwkKcnZ2JjIwkMjLSuM3bb7/Njz/+yNatW0lJScFgMHDs2DEaNGjA+PHjcXd357PPPmPRokUUFxfj5OREQEAAI0aMqJTv5n8xdepU6tevz5o1a5g+fTodO3Zk8+bN5WY6WFpasn79elauXMnGjRvZu3cvNjY2tGjRgtDQUF577TUA4uPjOX36NDt37sTW1hZ4eK9/cnIyXbt2ZdKkSaxfv77Kj1NERKQiFnl5eYZ/3kxEREREREREqiPdYy8iIiIiIiJSg6mwFxEREREREanBVNiLiIiIiIiI1GAq7EVERERERERqMBX2IiIiIiIiIjWYCnsRERERERGRGkyFvYiIiIiIiEgNpsJeREREREREpAZTYS8iIiIiIiJSg6mwFxEREREREanB/gNuMFcy0dTquwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1080x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot the size of the clusters - save plot\n",
+    "fig, ax = plt.subplots(figsize=(15, 4))\n",
+    "ax.set_xlabel(\"Cluster index\")\n",
+    "ax.set_ylabel(\"# molecules\")\n",
+    "ax.bar(range(1, len(features) + 1), [len(f) for f in features])\n",
+    "ax.set_title(f\"Number of clusters: {num_clusters}\")\n",
+    "\n",
+    "print(f\"Number of clusters: {len(features)} from {len(compound_df)} molecules.\")\n",
+    "print(\"Number of molecules in largest cluster:\", len(features[0]))\n",
+    "print(f\"Similarity between two random points in same cluster: {DataStructs.TanimotoSimilarity(df_fingerprints[features[0][0]], df_fingerprints[features[0][1]]):.2f}\")\n",
+    "print(f\"Similarity between two random points in different cluster: {DataStructs.TanimotoSimilarity(df_fingerprints[features[0][0]], df_fingerprints[features[1][0]]):.2f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "K-means tend to create one large cluster for this data. The number of clusters is lower and the size of the largest cluster is twice as large compared to butina. Accordingly, the similarity between the molecules within a cluster is lower with 74% compared to butina with 91% and difference between two random molecules from the clusters as well (30% vs. 64%)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Ten molecules from largest cluster:\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=1000x400 at 0x7F78C42AAEB8>"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(\"Ten molecules from largest cluster:\")\n",
+    "# Draw molecules\n",
+    "Draw.MolsToGridImage(\n",
+    "    [Chem.MolFromSmiles(compound_df.smiles[i]) for i in clusters[0][:10]],\n",
+    "    legends=[compound_df.molecule_chembl_id[i] for i in clusters[0][:10]],\n",
+    "    molsPerRow=5,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Ten molecules from largest cluster:\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=1000x400 at 0x7F78BFA56828>"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(\"Ten molecules from largest cluster:\")\n",
+    "# Draw molecules\n",
+    "Draw.MolsToGridImage(\n",
+    "    [Chem.MolFromSmiles(compound_df.smiles[i]) for i in features[0][:10]],\n",
+    "    legends=[compound_df.molecule_chembl_id[i] for i in features[0][:10]],\n",
+    "    molsPerRow=5,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
+   "source": [
+    "The similarity between the molecules within a cluster is lower in case of K-means. Since for both clutser methods, the largest cluster was used as training set, it is to be expected that the mocules in K-means cover a wider chemical space and thus lead to a better accuracy."
+   ]
+  }
+ ],
+ "metadata": {
+  "celltoolbar": "Slideshow",
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
+  },
+  "toc-autonumbering": true
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}