diff --git a/README.md b/README.md index f3f8dfb..9bc7940 100644 --- a/README.md +++ b/README.md @@ -12,6 +12,8 @@ First you need to clone this repository. Replace **[install_folder]** with the p The navigate into your install folder using *cd* and run the installation code. BindCraft requires a CUDA-compatible Nvidia graphics card to run. In the *cuda* setting, please specify the CUDA version compatible with your graphics card, for example '11.8'. If unsure, leave blank but it's possible that the installation might select the wrong version, which will lead to errors. In *pkg_manager* specify whether you are using 'mamba' or 'conda', if left blank it will use 'conda' by default. +Note: This install script will install PyRosetta, which requires a license for commercial purposes. + `bash install_bindcraft.sh --cuda '12.4' --pkg_manager 'conda'` ## Google Colab @@ -39,16 +41,16 @@ number_of_final_designs -> how many designs that pass all filters to aim for, ``` Then run the binder design script: -`sbatch ./bindcraft.slurm --settings './settings_target/PDL1.json' --filters './settings_filters/default_filters.json' --advanced './settings_advanced/4stage_multimer.json'` +`sbatch ./bindcraft.slurm --settings './settings_target/PDL1.json' --filters './settings_filters/default_filters.json' --advanced './settings_advanced/default_4stage_multimer.json'` -The *settings* flag should point to your target .json which you set above. The *filters* flag points to the json where the design filters are specified (default is ./filters/default_filters.json). The *advanced* flag points to your advanced settings (default is ./advanced_settings/4stage_multimer.json). If you leave out the filters and advanced settings flags it will automatically point to the defaults. +The *settings* flag should point to your target .json which you set above. The *filters* flag points to the json where the design filters are specified (default is ./filters/default_filters.json). The *advanced* flag points to your advanced settings (default is ./advanced_settings/default_4stage_multimer.json). If you leave out the filters and advanced settings flags it will automatically point to the defaults. Alternatively, if your machine does not support SLURM, you can run the code directly by activating the environment in conda and running the python code: ``` conda activate BindCraft cd /path/to/bindcraft/folder/ -python -u ./bindcraft.py --settings './settings_target/PDL1.json' --filters './settings_filters/default_filters.json' --advanced './settings_advanced/4stage_multimer.json' +python -u ./bindcraft.py --settings './settings_target/PDL1.json' --filters './settings_filters/default_filters.json' --advanced './settings_advanced/default_4stage_multimer.json' ``` **We recommend to generate at least a 100 final designs passing all filters, then order the top 5-20 for experimental characterisation.** If high affinity binders are required, it is better to screen more, as the ipTM metric used for ranking is not a good predictor for affinity, but has been shown to be a good binary predictor of binding. diff --git a/bindcraft.py b/bindcraft.py index 0c0b6a4..2c4405c 100644 --- a/bindcraft.py +++ b/bindcraft.py @@ -15,7 +15,7 @@ help='Path to the basic settings.json file. Required.') parser.add_argument('--filters', '-f', type=str, default='./settings_filters/default_filters.json', help='Path to the filters.json file used to filter design. If not provided, default will be used.') -parser.add_argument('--advanced', '-a', type=str, default='./settings_advanced/4stage_multimer.json', +parser.add_argument('--advanced', '-a', type=str, default='./settings_advanced/default_4stage_multimer.json', help='Path to the advanced.json file with additional design settings. If not provided, default will be used.') args = parser.parse_args() @@ -33,11 +33,9 @@ ### load AF2 model settings design_models, prediction_models, multimer_validation = load_af2_models(advanced_settings["use_multimer_design"]) -### set package settings +### perform checks on advanced_settings bindcraft_folder = os.path.dirname(os.path.realpath(__file__)) -advanced_settings["af_params_dir"] = bindcraft_folder -advanced_settings["dssp_path"] = os.path.join(bindcraft_folder, 'functions/dssp') -advanced_settings["dalphaball_path"] = os.path.join(bindcraft_folder, 'functions/DAlphaBall.gcc') +advanced_settings = perform_advanced_settings_check(advanced_settings, bindcraft_folder) ### generate directories, design path names can be found within the function design_paths = generate_directories(target_settings["design_path"]) @@ -66,7 +64,6 @@ script_start_time = time.time() trajectory_n = 1 accepted_designs = 0 -rejected_designs = 0 ### start design loop while True: @@ -170,44 +167,47 @@ ### MPNN redesign of starting binder mpnn_trajectories = mpnn_gen_sequence(trajectory_pdb, binder_chain, trajectory_interface_residues, advanced_settings) + existing_mpnn_sequences = set(pd.read_csv(mpnn_csv, usecols=['Sequence'])['Sequence'].values) + + # create set of MPNN sequences with allowed amino acid composition + restricted_AAs = set(aa.strip().upper() for aa in advanced_settings["omit_AAs"].split(',')) if advanced_settings["force_reject_AA"] else set() + + mpnn_sequences = sorted({ + mpnn_trajectories['seq'][n][-length:]: { + 'seq': mpnn_trajectories['seq'][n][-length:], + 'score': mpnn_trajectories['score'][n], + 'seqid': mpnn_trajectories['seqid'][n] + } for n in range(advanced_settings["num_seqs"]) + if (not restricted_AAs or not any(aa in mpnn_trajectories['seq'][n][-length:].upper() for aa in restricted_AAs)) + and mpnn_trajectories['seq'][n][-length:] not in existing_mpnn_sequences + }.values(), key=lambda x: x['score']) + + del existing_mpnn_sequences + + # check whether any sequences are left after amino acid rejection and duplication check, and if yes proceed with prediction + if mpnn_sequences: + # add optimisation for increasing recycles if trajectory is beta sheeted + if advanced_settings["optimise_beta"] and float(trajectory_beta) > 15: + advanced_settings["num_recycles_validation"] = advanced_settings["optimise_beta_recycles_valid"] + + ### Compile prediction models once for faster prediction of MPNN sequences + clear_mem() + # compile complex prediction model + complex_prediction_model = mk_afdesign_model(protocol="binder", num_recycles=advanced_settings["num_recycles_validation"], data_dir=advanced_settings["af_params_dir"], + use_multimer=multimer_validation) + complex_prediction_model.prep_inputs(pdb_filename=target_settings["starting_pdb"], chain=target_settings["chains"], binder_len=length, rm_target_seq=advanced_settings["rm_template_seq_predict"], + rm_target_sc=advanced_settings["rm_template_sc_predict"]) + + # compile binder monomer prediction model + binder_prediction_model = mk_afdesign_model(protocol="hallucination", use_templates=False, initial_guess=False, + use_initial_atom_pos=False, num_recycles=advanced_settings["num_recycles_validation"], + data_dir=advanced_settings["af_params_dir"], use_multimer=multimer_validation) + binder_prediction_model.prep_inputs(length=length) + + # iterate over designed sequences + for mpnn_sequence in mpnn_sequences: + mpnn_time = time.time() - # whether to hard reject sequences with excluded amino acids - if advanced_settings["force_reject_AA"]: - restricted_AAs = set(advanced_settings["omit_AAs"].split(',')) - mpnn_sequences = [{'seq': mpnn_trajectories['seq'][n][-length:], 'score': mpnn_trajectories['score'][n], 'seqid': mpnn_trajectories['seqid'][n]} - for n in range(advanced_settings["num_seqs"]) - if not any(restricted_AA in mpnn_trajectories['seq'][n] for restricted_AA in restricted_AAs)] - else: - mpnn_sequences = [{'seq': mpnn_trajectories['seq'][n][-length:], 'score': mpnn_trajectories['score'][n], 'seqid': mpnn_trajectories['seqid'][n]} - for n in range(advanced_settings["num_seqs"])] - - # sort MPNN sequences by lowest MPNN score - mpnn_sequences.sort(key=lambda x: x['score']) - - # add optimisation for increasing recycles if trajectory is beta sheeted - if advanced_settings["optimise_beta"] and float(trajectory_beta) > 15: - advanced_settings["num_recycles_validation"] = advanced_settings["optimise_beta_recycles_valid"] - - ### Compile prediction models once for faster prediction of MPNN sequences - clear_mem() - # compile complex prediction model - complex_prediction_model = mk_afdesign_model(protocol="binder", num_recycles=advanced_settings["num_recycles_validation"], data_dir=advanced_settings["af_params_dir"], - use_multimer=multimer_validation) - complex_prediction_model.prep_inputs(pdb_filename=target_settings["starting_pdb"], chain=target_settings["chains"], binder_len=length, rm_target_seq=advanced_settings["rm_template_seq_predict"], - rm_target_sc=advanced_settings["rm_template_sc_predict"]) - - # compile binder monomer prediction model - binder_prediction_model = mk_afdesign_model(protocol="hallucination", use_templates=False, initial_guess=False, - use_initial_atom_pos=False, num_recycles=advanced_settings["num_recycles_validation"], - data_dir=advanced_settings["af_params_dir"], use_multimer=multimer_validation) - binder_prediction_model.prep_inputs(length=length) - - # iterate over designed sequences - for mpnn_sequence in mpnn_sequences: - mpnn_time = time.time() - - # compile sequences dictionary with scores and remove duplicate sequences - if mpnn_sequence['seq'] not in [v['seq'] for v in mpnn_dict.values()]: # generate mpnn design name numbering mpnn_design_name = design_name + "_mpnn" + str(mpnn_n) mpnn_score = round(mpnn_sequence['score'],2) @@ -230,6 +230,7 @@ # if AF2 filters are not passed then skip the scoring if not pass_af2_filters: print(f"Base AF2 filters not passed for {mpnn_design_name}, skipping interface scoring") + mpnn_n += 1 continue # calculate statistics for each model individually @@ -415,14 +416,17 @@ # if enough mpnn sequences of the same trajectory pass filters then stop if accepted_mpnn >= advanced_settings["max_mpnn_sequences"]: break + + if accepted_mpnn >= 1: + print("Found "+str(accepted_mpnn)+" MPNN designs passing filters") + print("") else: - print("Skipping duplicate sequence") + print("No accepted MPNN designs found for this trajectory.") + print("") - if accepted_mpnn >= 1: - print("Found "+str(accepted_mpnn)+" MPNN designs passing filters") else: - print("No accepted MPNN designs found for this trajectory.") - rejected_designs += 1 + print('Duplicate MPNN designs sampled with different trajectory, skipping current trajectory optimisation') + print("") # save space by removing unrelaxed design trajectory PDB if advanced_settings["remove_unrelaxed_trajectory"]: @@ -447,4 +451,4 @@ ### Script finished elapsed_time = time.time() - script_start_time elapsed_text = f"{'%d hours, %d minutes, %d seconds' % (int(elapsed_time // 3600), int((elapsed_time % 3600) // 60), int(elapsed_time % 60))}" -print("Finished all designs. Script execution for "+str(trajectory_n)+" trajectories took: "+elapsed_text) +print("Finished all designs. Script execution for "+str(trajectory_n)+" trajectories took: "+elapsed_text) \ No newline at end of file diff --git a/bindcraft.slurm b/bindcraft.slurm index 669aa41..739a3b1 100644 --- a/bindcraft.slurm +++ b/bindcraft.slurm @@ -10,7 +10,9 @@ #SBATCH --output=bindcraft_%A.log # Initialise environment and modules -conda activate BindCraft +CONDA_BASE=$(conda info --base) +source ${CONDA_BASE}/bin/activate ${CONDA_BASE}/envs/BindCraft +export LD_LIBRARY_PATH=${CONDA_BASE}/lib # alternatively you can source the environment directly #source /path/to/mambaforge/bin/activate /path/to/mambaforge/envs/BindCraft diff --git a/functions/biopython_utils.py b/functions/biopython_utils.py index e25a8cb..a0a4bd4 100644 --- a/functions/biopython_utils.py +++ b/functions/biopython_utils.py @@ -233,4 +233,4 @@ def calculate_percentages(total, helix, sheet): sheet_percentage = round((sheet / total) * 100,2) if total > 0 else 0 loop_percentage = round(((total - helix - sheet) / total) * 100,2) if total > 0 else 0 - return helix_percentage, sheet_percentage, loop_percentage + return helix_percentage, sheet_percentage, loop_percentage \ No newline at end of file diff --git a/functions/colabdesign_utils.py b/functions/colabdesign_utils.py index e925c28..7884538 100644 --- a/functions/colabdesign_utils.py +++ b/functions/colabdesign_utils.py @@ -357,7 +357,7 @@ def mpnn_gen_sequence(trajectory_pdb, binder_chain, trajectory_interface_residue mpnn_model.prep_inputs(pdb_filename=trajectory_pdb, chain=design_chains, fix_pos=fixed_positions, rm_aa=advanced_settings["omit_AAs"]) # sample MPNN sequences in parallel - mpnn_sequences = mpnn_model.sample_parallel(temperature=advanced_settings["sampling_temp"], num=advanced_settings["num_seqs"], batch=advanced_settings["sample_seq_parallel"]) + mpnn_sequences = mpnn_model.sample(temperature=advanced_settings["sampling_temp"], num=advanced_settings["num_seqs"], batch=advanced_settings["num_seqs"]) return mpnn_sequences @@ -474,4 +474,4 @@ def plot_trajectory(af_model, design_name, design_paths): plt.savefig(os.path.join(design_paths["Trajectory/Plots"], design_name+"_"+metric+".png"), dpi=150) # Close the figure - plt.close() + plt.close() \ No newline at end of file diff --git a/functions/generic_utils.py b/functions/generic_utils.py index 8d3776e..17c213f 100644 --- a/functions/generic_utils.py +++ b/functions/generic_utils.py @@ -225,10 +225,35 @@ def perform_input_check(args): # Set a random advanced json settings file if not provided if not args.advanced: - args.advanced = os.path.join(binder_script_path, 'settings_advanced', '4stage_multimer.json') + args.advanced = os.path.join(binder_script_path, 'settings_advanced', 'default_4stage_multimer.json') return args.settings, args.filters, args.advanced +# check specific advanced settings +def perform_advanced_settings_check(advanced_settings, bindcraft_folder): + # set paths to model weights and executables + if bindcraft_folder == "colab": + advanced_settings["af_params_dir"] = '/content/bindcraft/params/' + advanced_settings["dssp_path"] = '/content/bindcraft/functions/dssp' + advanced_settings["dalphaball_path"] = '/content/bindcraft/functions/DAlphaBall.gcc' + else: + # Set paths individually if they are not already set + if not advanced_settings["af_params_dir"]: + advanced_settings["af_params_dir"] = bindcraft_folder + if not advanced_settings["dssp_path"]: + advanced_settings["dssp_path"] = os.path.join(bindcraft_folder, 'functions', 'dssp') + if not advanced_settings["dalphaball_path"]: + advanced_settings["dalphaball_path"] = os.path.join(bindcraft_folder, 'functions', 'DAlphaBall.gcc') + + # check formatting of omit_AAs setting + omit_aas = advanced_settings["omit_AAs"] + if advanced_settings["omit_AAs"] in [None, False, '']: + advanced_settings["omit_AAs"] = None + elif isinstance(advanced_settings["omit_AAs"], str): + advanced_settings["omit_AAs"] = advanced_settings["omit_AAs"].strip() + + return advanced_settings + # Load settings from JSONs def load_json_settings(settings_json, filters_json, advanced_json): # load settings from json files diff --git a/functions/pyrosetta_utils.py b/functions/pyrosetta_utils.py index e5e08a0..4d6c8a2 100644 --- a/functions/pyrosetta_utils.py +++ b/functions/pyrosetta_utils.py @@ -99,9 +99,11 @@ def score_interface(pdb_file, binder_chain="B"): interface_binder_fraction = 0 # calculate surface hydrophobicity + binder_pose = {pose.pdb_info().chain(pose.conformation().chain_begin(i)): p for i, p in zip(range(1, pose.num_chains()+1), pose.split_by_chain())}[binder_chain] + layer_sel = pr.rosetta.core.select.residue_selector.LayerSelector() layer_sel.set_layers(pick_core = False, pick_boundary = False, pick_surface = True) - surface_res = layer_sel.apply(pose) + surface_res = layer_sel.apply(binder_pose) exp_apol_count = 0 total_count = 0 @@ -109,7 +111,7 @@ def score_interface(pdb_file, binder_chain="B"): # count apolar and aromatic residues at the surface for i in range(1, len(surface_res) + 1): if surface_res[i] == True: - res = pose.residue(i) + res = binder_pose.residue(i) # count apolar and aromatic residues as hydrophobic if res.is_apolar() == True or res.name() == 'PHE' or res.name() == 'TRP' or res.name() == 'TYR': diff --git a/install_bindcraft.sh b/install_bindcraft.sh index 1f9c71c..89bc7de 100644 --- a/install_bindcraft.sh +++ b/install_bindcraft.sh @@ -29,65 +29,103 @@ while true; do break ;; *) - echo "Invalid option $1" >&2 + echo -e "Invalid option $1" >&2 exit 1 ;; esac done # Example usage of the parsed variables -echo "Package manager: $pkg_manager" -echo "CUDA version (if provided): $cuda" +echo -e "Package manager: $pkg_manager" +echo -e "CUDA: $cuda" ############################################################################################################ ############################################################################################################ ################## initialisation SECONDS=0 -# set paths +# set paths needed for installation and check for conda installation install_dir=$(pwd) +CONDA_BASE=$(conda info --base 2>/dev/null) || { echo -e "Error: conda is not installed or cannot be initialised."; exit 1; } +echo -e "Conda is installed at: $CONDA_BASE" -### BindCraft install -printf "Installing BindCraft environment\n" -$pkg_manager create --name BindCraft python=3.10 -y -CONDA_BASE=$(conda info --base) -source ${CONDA_BASE}/bin/activate ${CONDA_BASE}/envs/BindCraft -printf "BindCraft environment activated at ${CONDA_BASE}/envs/BindCraft" +### BindCraft install begin, create base environment +echo -e "Installing BindCraft environment\n" +$pkg_manager create --name BindCraft python=3.10 -y || { echo -e "Error: Failed to create BindCraft conda environment"; exit 1; } +conda env list | grep -w 'BindCraft' >/dev/null 2>&1 || { echo -e "Error: Conda environment 'BindCraft' does not exist after creation."; exit 1; } -# install required packages +# Load newly created BindCraft environment +echo -e "Loading BindCraft environment\n" +source ${CONDA_BASE}/bin/activate ${CONDA_BASE}/envs/BindCraft || { echo -e "Error: Failed to activate the BindCraft environment."; exit 1; } +[ "$CONDA_DEFAULT_ENV" = "BindCraft" ] || { echo -e "Error: The BindCraft environment is not active."; exit 1; } +echo -e "BindCraft environment activated at ${CONDA_BASE}/envs/BindCraft" + +# install required conda packages +echo -e "Instaling conda requirements\n" if [ -n "$cuda" ]; then - CONDA_OVERRIDE_CUDA="$cuda" $pkg_manager install pip pandas matplotlib numpy"<2.0.0" biopython scipy pdbfixer seaborn tqdm jupyter ffmpeg pyrosetta fsspec py3dmol chex dm-haiku dm-tree joblib ml-collections immutabledict optax jaxlib=*=*cuda* jax cuda-nvcc cudnn -c conda-forge -c anaconda -c nvidia --channel https://conda.graylab.jhu.edu -y + CONDA_OVERRIDE_CUDA="$cuda" $pkg_manager install pip pandas matplotlib numpy"<2.0.0" biopython scipy pdbfixer seaborn libgfortran5 tqdm jupyter ffmpeg pyrosetta fsspec py3dmol chex dm-haiku flax"<0.10.0" dm-tree joblib ml-collections immutabledict optax jaxlib=*=*cuda* jax cuda-nvcc cudnn -c conda-forge -c nvidia --channel https://conda.graylab.jhu.edu -y || { echo -e "Error: Failed to install conda packages."; exit 1; } else - $pkg_manager install pip pandas matplotlib numpy"<2.0.0" biopython scipy pdbfixer seaborn tqdm jupyter ffmpeg pyrosetta fsspec py3dmol chex dm-haiku dm-tree joblib ml-collections immutabledict optax jaxlib jax cuda-nvcc cudnn -c conda-forge -c anaconda -c nvidia --channel https://conda.graylab.jhu.edu -y + $pkg_manager install pip pandas matplotlib numpy"<2.0.0" biopython scipy pdbfixer seaborn libgfortran5 tqdm jupyter ffmpeg pyrosetta fsspec py3dmol chex dm-haiku flax"<0.10.0" dm-tree joblib ml-collections immutabledict optax jaxlib jax cuda-nvcc cudnn -c conda-forge -c nvidia --channel https://conda.graylab.jhu.edu -y || { echo -e "Error: Failed to install conda packages."; exit 1; } +fi + +# make sure all required packages were installed +required_packages=(pip pandas libgfortran5 matplotlib numpy biopython scipy pdbfixer seaborn tqdm jupyter ffmpeg pyrosetta fsspec py3dmol chex dm-haiku dm-tree joblib ml-collections immutabledict optax jaxlib jax cuda-nvcc cudnn) +missing_packages=() + +# Check each package +for pkg in "${required_packages[@]}"; do + conda list "$pkg" | grep -w "$pkg" >/dev/null 2>&1 || missing_packages+=("$pkg") +done + +# If any packages are missing, output error and exit +if [ ${#missing_packages[@]} -ne 0 ]; then + echo -e "Error: The following packages are missing from the environment:" + for pkg in "${missing_packages[@]}"; do + echo -e " - $pkg" + done + exit 1 fi # install ColabDesign -pip3 install git+https://github.com/sokrypton/ColabDesign.git --no-deps +echo -e "Installing ColabDesign\n" +pip3 install git+https://github.com/sokrypton/ColabDesign.git --no-deps || { echo -e "Error: Failed to install ColabDesign"; exit 1; } +python -c "import colabdesign" >/dev/null 2>&1 || { echo -e "Error: colabdesign module not found after installation"; exit 1; } + +# AlphaFold2 weights +echo -e "Downloading AlphaFold2 model weights \n" +params_dir="${install_dir}/params" +params_file="${params_dir}/alphafold_params_2022-12-06.tar" + +# download AF2 weights +mkdir -p "${params_dir}" || { echo -e "Error: Failed to create weights directory"; exit 1; } +wget -O "${params_file}" "https://storage.googleapis.com/alphafold/alphafold_params_2022-12-06.tar" || { echo -e "Error: Failed to download AlphaFold2 weights"; exit 1; } +[ -s "${params_file}" ] || { echo -e "Error: Could not locate downloaded AlphaFold2 weights"; exit 1; } -# Download AlphaFold2 weights -mkdir -p ${install_dir}/params/ -cd ${install_dir}/params/ -wget -P ${install_dir}/params/ https://storage.googleapis.com/alphafold/alphafold_params_2022-12-06.tar -tar -xvf ${install_dir}/params/alphafold_params_2022-12-06.tar +# extract AF2 weights +tar tf "${params_file}" >/dev/null 2>&1 || { echo -e "Error: Corrupt AlphaFold2 weights download"; exit 1; } +tar -xvf "${params_file}" -C "${params_dir}" || { echo -e "Error: Failed to extract AlphaFold2weights"; exit 1; } +[ -f "${params_dir}/params_model_5_ptm.npz" ] || { echo -e "Error: Could not locate extracted AlphaFold2 weights"; exit 1; } +rm "${params_file}" || { echo -e "Warning: Failed to remove AlphaFold2 weights archive"; } # chmod executables -chmod +x ${install_dir}/functions/dssp -chmod +x ${install_dir}/functions/DAlphaBall.gcc +echo -e "Changing permissions for executables\n" +chmod +x "${install_dir}/functions/dssp" || { echo -e "Error: Failed to chmod dssp"; exit 1; } +chmod +x "${install_dir}/functions/DAlphaBall.gcc" || { echo -e "Error: Failed to chmod DAlphaBall.gcc"; exit 1; } # finish conda deactivate -printf "BindCraft environment installed\n" +echo -e "BindCraft environment set up\n" ############################################################################################################ ############################################################################################################ ################## cleanup -printf "Cleaning up ${pkg_manager} temporary files to save space\n" +echo -e "Cleaning up ${pkg_manager} temporary files to save space\n" $pkg_manager clean -a -y -printf "$pkg_manager cleaned up\n" +echo -e "$pkg_manager cleaned up\n" ################## finish script t=$SECONDS -printf "Finished setting up BindCraft environment\n" -printf "Activate environment using command: \"$pkg_manager activate BindCraft\"" -printf "\n" -printf "Installation took $(($t / 3600)) hours, $((($t / 60) % 60)) minutes and $(($t % 60)) seconds." +echo -e "Successfully finished BindCraft installation!\n" +echo -e "Activate environment using command: \"$pkg_manager activate BindCraft\"" +echo -e "\n" +echo -e "Installation took $(($t / 3600)) hours, $((($t / 60) % 60)) minutes and $(($t % 60)) seconds." \ No newline at end of file diff --git a/notebooks/BindCraft.ipynb b/notebooks/BindCraft.ipynb index 050d91b..de9a206 100644 --- a/notebooks/BindCraft.ipynb +++ b/notebooks/BindCraft.ipynb @@ -1,24 +1,10 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [], - "gpuType": "A100", - "machine_shape": "hm" - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - }, - "accelerator": "GPU" - }, "cells": [ { "cell_type": "markdown", + "metadata": { + "id": "MTagjooX0XC1" + }, "source": [ "# BindCraft: Protein binder design\n", "\n", @@ -27,51 +13,25 @@ "Simple binder design pipeline using AlphaFold2 backpropagation, MPNN, and PyRosetta. Select your target and let the script do the rest of the work and finish once you have enough designs to order!\n", "\n", "The designs will be saved on your Google Drive under BindCraft/[design_name]/ and you can continue running the design pipeline if the session times out and it will continue adding new designs." - ], - "metadata": { - "id": "MTagjooX0XC1" - } + ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { - "id": "7fMzl8JiyaXm", - "colab": { - "base_uri": "https://localhost:8080/" - }, - "outputId": "23c75b17-7485-488c-d7df-ffd8f4ad0d5c", - "cellView": "form" + "cellView": "form", + "id": "7fMzl8JiyaXm" }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Installing required BindCraft components\n", - "Pulling BindCraft code from Github\n", - "Cloning into '/content/bindcraft'...\n", - "remote: Enumerating objects: 71, done.\u001b[K\n", - "remote: Counting objects: 100% (71/71), done.\u001b[K\n", - "remote: Compressing objects: 100% (66/66), done.\u001b[K\n", - "remote: Total 71 (delta 26), reused 0 (delta 0), pack-reused 0 (from 0)\u001b[K\n", - "Receiving objects: 100% (71/71), 1.24 MiB | 14.15 MiB/s, done.\n", - "Resolving deltas: 100% (26/26), done.\n", - "Installing ColabDesign\n", - "Installing PyRosetta\n", - "BindCraft installation is finished, ready to run!\n", - "CPU times: user 1.86 s, sys: 244 ms, total: 2.11 s\n", - "Wall time: 2min 10s\n" - ] - } - ], + "outputs": [], "source": [ "#@title Installation\n", "%%time\n", "import os, time, gc, io\n", "import contextlib\n", - "from datetime import datetime\n", "import json\n", + "from datetime import datetime\n", + "from ipywidgets import HTML, VBox\n", + "from IPython.display import display\n", "\n", "if not os.path.isfile(\"bindcraft/params/done.txt\"):\n", " print(\"Installing required BindCraft components\")\n", @@ -109,6 +69,12 @@ }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "01IH64-ycCQY" + }, + "outputs": [], "source": [ "#@title Mount your Google Drive to save design results\n", "from google.colab import drive\n", @@ -119,30 +85,16 @@ "bindcraft_google_drive = '/content/drive/My Drive/BindCraft/'\n", "os.makedirs(bindcraft_google_drive, exist_ok=True)\n", "print(\"BindCraft folder successfully created in your drive!\")" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "cellView": "form", - "id": "01IH64-ycCQY", - "outputId": "316a7640-73d7-4bda-c0cc-d324a4fac271" - }, - "execution_count": 2, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Mounted at /content/drive\n", - "Google drive mounted at: 2024-09-29 19:15:57\n", - "BindCraft folder successfully created in your drive!\n" - ] - } ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "RbL-S_t2hicj" + }, + "outputs": [], "source": [ "#@title Binder design settings\n", "# @markdown ---\n", @@ -167,143 +119,135 @@ "# @markdown How many binder designs passing filters do you require?\n", "number_of_final_designs = 100 # @param {\"type\":\"integer\",\"placeholder\":\"100\"}\n", "# @markdown ---\n", + "# @markdown Enter path on your Google drive (/content/drive/MyDrive/BindCraft/[binder_name].json) to previous target settings to continue design campaign. If left empty, it will use the settings above and generate a new settings json in your design output folder.\n", + "load_previous_target_settings = \"\" # @param {\"type\":\"string\",\"placeholder\":\"\"}\n", + "# @markdown ---\n", "\n", - "lengths = [int(x.strip()) for x in lengths.split(',') if len(lengths.split(',')) == 2]\n", - "\n", - "if len(lengths) != 2:\n", - " raise ValueError(\"Incorrect specification of binder lengths.\")\n", + "if load_previous_target_settings:\n", + " target_settings_path = load_previous_target_settings\n", + "else:\n", + " lengths = [int(x.strip()) for x in lengths.split(',') if len(lengths.split(',')) == 2]\n", "\n", + " if len(lengths) != 2:\n", + " raise ValueError(\"Incorrect specification of binder lengths.\")\n", "\n", - "settings = {\n", - " \"design_path\": design_path,\n", - " \"binder_name\": binder_name,\n", - " \"starting_pdb\": starting_pdb,\n", - " \"chains\": chains,\n", - " \"target_hotspot_residues\": target_hotspot_residues,\n", - " \"lengths\": lengths,\n", - " \"number_of_final_designs\": number_of_final_designs\n", - "}\n", + " settings = {\n", + " \"design_path\": design_path,\n", + " \"binder_name\": binder_name,\n", + " \"starting_pdb\": starting_pdb,\n", + " \"chains\": chains,\n", + " \"target_hotspot_residues\": target_hotspot_residues,\n", + " \"lengths\": lengths,\n", + " \"number_of_final_designs\": number_of_final_designs\n", + " }\n", "\n", - "target_settings_path = \"/content/bindcraft/settings_target/\"+binder_name+\".json\"\n", + " target_settings_path = os.path.join(design_path, binder_name+\".json\")\n", "\n", - "with open(target_settings_path, 'w') as f:\n", - " json.dump(settings, f, indent=4)\n", + " with open(target_settings_path, 'w') as f:\n", + " json.dump(settings, f, indent=4)\n", "\n", "currenttime = datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n", "print(f\"Binder design settings updated at: {currenttime}\")\n", "print(f\"New .json file with target settings has been generated in: {target_settings_path}\")" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "cellView": "form", - "id": "RbL-S_t2hicj", - "outputId": "fb73d721-9fd0-484a-93ef-bd2e537c6d41" - }, - "execution_count": 3, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Binder design settings updated at: 2024-09-29 19:15:57\n", - "New .json file with target settings has been generated in: /content/bindcraft/settings_target/PDL1.json\n" - ] - } ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "qcEjqCIlhire" + }, + "outputs": [], "source": [ "#@title Advanced settings\n", "# @markdown ---\n", "# @markdown Which binder design protocol to run? Default is recommended. \"Beta-sheet\" promotes the design of more beta sheeted proteins, but requires more sampling. \"Peptide\" is optimised for helical peptide binders.\n", - "advanced_option = \"Default\" # @param [\"Default\",\"Beta-sheet\",\"Peptide\"]\n", + "design_protocol = \"Default\" # @param [\"Default\",\"Beta-sheet\",\"Peptide\"]\n", + "# @markdown What interface design method to use?. \"AlphaFold2\" is the default, interface is generated by AlphaFold2. \"MPNN\" uses soluble MPNN to optimise the interface, but majority of residues still originate from AlphaFold2.\n", + "interface_protocol = \"AlphaFold2\" # @param [\"AlphaFold2\",\"MPNN\"]\n", + "# @markdown What target template protocol to use? \"Default\" allows for limited amount flexibility. \"Masked\" allows for greater target flexibility on both sidechain and backbone level, but might result in reduced experimental success rates.\n", + "template_protocol = \"Default\" # @param [\"Default\",\"Masked\"]\n", "# @markdown ---\n", "\n", - "if advanced_option == \"Default\":\n", - " advanced_settings_path = \"/content/bindcraft/settings_advanced/4stage_multimer.json\"\n", - "elif advanced_option == \"Beta-sheet\":\n", - " advanced_settings_path = \"/content/bindcraft/settings_advanced/4stage_multimer_betasheet.json\"\n", - "elif advanced_option == \"Peptide\":\n", - " advanced_settings_path = \"/content/bindcraft/settings_advanced/4stage_multimer_peptides.json\"\n", + "if design_protocol == \"Default\":\n", + " design_protocol_tag = \"default_4stage_multimer\"\n", + "elif design_protocol == \"Beta-sheet\":\n", + " design_protocol_tag = \"betasheet_4stage_multimer\"\n", + "elif design_protocol == \"Peptide\":\n", + " design_protocol_tag = \"peptide_3stage_multimer\"\n", + "else:\n", + " raise ValueError(f\"Unsupported design protocol\")\n", + "\n", + "if interface_protocol == \"AlphaFold2\":\n", + " interface_protocol_tag = \"\"\n", + "elif interface_protocol == \"MPNN\":\n", + " interface_protocol_tag = \"_mpnn\"\n", + "else:\n", + " raise ValueError(f\"Unsupported interface protocol\")\n", + "\n", + "if template_protocol == \"Default\":\n", + " template_protocol_tag = \"\"\n", + "elif template_protocol == \"Masked\":\n", + " template_protocol_tag = \"_flexible\"\n", "else:\n", - " raise ValueError(f\"Unsupported protocol\")\n", + " raise ValueError(f\"Unsupported template protocol\")\n", + "\n", + "advanced_settings_path = \"/content/bindcraft/settings_advanced/\" + design_protocol_tag + interface_protocol_tag + template_protocol_tag + \".json\"\n", "\n", "currenttime = datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n", "print(f\"Advanced design settings updated at: {currenttime}\")" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "cellView": "form", - "id": "qcEjqCIlhire", - "outputId": "0efd5e2a-5253-4a63-c83c-b32f76ed6dd3" - }, - "execution_count": 4, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Advanced design settings updated at: 2024-09-29 19:15:57\n" - ] - } ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "r-OpCVe4hi5Q" + }, + "outputs": [], "source": [ "#@title Filters\n", "# @markdown ---\n", - "# @markdown Which filters for designs to use? \"Default\" are recommended, \"Peptide\" are for the design of peptide binders, \"None\" is for benchmarking.\n", - "filter_option = \"Default\" # @param [\"Default\",\"Peptide\", \"None\"]\n", + "# @markdown Which filters for designs to use? \"Default\" are recommended, \"Peptide\" are for the design of peptide binders, \"Relaxed\" are more permissive but may result in fewer experimental successes, \"Peptide_Relaxed\" are more permissive filters for non-helical peptides, \"None\" is for benchmarking.\n", + "filter_option = \"Peptide\" # @param [\"Default\", \"Peptide\", \"Relaxed\", \"Peptide_Relaxed\", \"None\"]\n", "# @markdown ---\n", "\n", "if filter_option == \"Default\":\n", " filter_settings_path = \"/content/bindcraft/settings_filters/default_filters.json\"\n", + "elif filter_option == \"Peptide\":\n", + " filter_settings_path = \"/content/bindcraft/settings_filters/peptide_filters.json\"\n", + "elif filter_option == \"Relaxed\":\n", + " filter_settings_path = \"/content/bindcraft/settings_filters/relaxed_filters.json\"\n", + "elif filter_option == \"Peptide_Relaxed\":\n", + " filter_settings_path = \"/content/bindcraft/settings_filters/peptide_relaxed_filters.json\"\n", "elif filter_option == \"None\":\n", " filter_settings_path = \"/content/bindcraft/settings_filters/no_filters.json\"\n", - "elif filter_option == \"Peptide\":\n", - " filter_settings_path = \"/content/bindcraft/settings_filters/filters_peptides.json\"\n", "else:\n", " raise ValueError(f\"Unsupported filter type\")\n", "\n", "currenttime = datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n", "print(f\"Filter settings updated at: {currenttime}\")" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "cellView": "form", - "id": "r-OpCVe4hi5Q", - "outputId": "ef188d03-45f4-42bf-b25f-a8b4e65bf040" - }, - "execution_count": 5, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Filter settings updated at: 2024-09-29 19:15:57\n" - ] - } ] }, { "cell_type": "markdown", - "source": [ - "# Everything is set, BindCraft is ready to run!" - ], "metadata": { "id": "BR3gtmcChtvX" - } + }, + "source": [ + "# Everything is set, BindCraft is ready to run!" + ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "LgRFO3EKAnM5" + }, + "outputs": [], "source": [ "# @title Import functions and settings\n", "from bindcraft.functions import *\n", @@ -325,14 +269,13 @@ "filters_file = os.path.basename(filters_path).split('.')[0]\n", "advanced_file = os.path.basename(advanced_path).split('.')[0]\n", "\n", - "### set package settings\n", - "advanced_settings[\"af_params_dir\"] = '/content/bindcraft/params/'\n", - "advanced_settings[\"dssp_path\"] = '/content/bindcraft/functions/dssp'\n", - "advanced_settings[\"dalphaball_path\"] = '/content/bindcraft/functions/DAlphaBall.gcc'\n", - "\n", "### load AF2 model settings\n", "design_models, prediction_models, multimer_validation = load_af2_models(advanced_settings[\"use_multimer_design\"])\n", "\n", + "### perform checks on advanced_settings\n", + "bindcraft_folder = \"colab\"\n", + "advanced_settings = perform_advanced_settings_check(advanced_settings, bindcraft_folder)\n", + "\n", "### generate directories, design path names can be found within the function\n", "design_paths = generate_directories(target_settings[\"design_path\"])\n", "\n", @@ -351,30 +294,16 @@ "\n", "currenttime = datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n", "print(f\"Loaded design functions and settings at: {currenttime}\")" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "LgRFO3EKAnM5", - "outputId": "ff84bc8e-abd8-4894-e1c1-80e8045d72eb", - "cellView": "form" - }, - "execution_count": 6, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Available GPUs:\n", - "NVIDIA A100-SXM4-40GB1: gpu\n", - "Loaded design functions and settings at: 2024-09-29 19:15:59\n" - ] - } ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "1sOAn_xyEZKo" + }, + "outputs": [], "source": [ "#@title Initialise PyRosetta\n", "\n", @@ -383,46 +312,32 @@ "####################################\n", "### initialise PyRosetta\n", "pr.init(f'-ignore_unrecognized_res -ignore_zero_occupancy -mute all -holes:dalphaball {advanced_settings[\"dalphaball_path\"]} -corrections::beta_nov16 true -relax:default_repeats 1')" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "cellView": "form", - "id": "1sOAn_xyEZKo", - "outputId": "6d599721-fe67-4605-884c-1c87b2b9e02c" - }, - "execution_count": 7, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "┌──────────────────────────────────────────────────────────────────────────────┐\n", - "│ PyRosetta-4 │\n", - "│ Created in JHU by Sergey Lyskov and PyRosetta Team │\n", - "│ (C) Copyright Rosetta Commons Member Institutions │\n", - "│ │\n", - "│ NOTE: USE OF PyRosetta FOR COMMERCIAL PURPOSES REQUIRE PURCHASE OF A LICENSE │\n", - "│ See LICENSE.PyRosetta.md or email license@uw.edu for details │\n", - "└──────────────────────────────────────────────────────────────────────────────┘\n", - "PyRosetta-4 2024 [Rosetta PyRosetta4.Release.python310.ubuntu.cxx11thread.serialization 2024.38+release.200d5f9a7d8cdd7afdd078f156da6b5a7d97543f 2024-09-11T17:31:36] retrieved from: http://www.pyrosetta.org\n" - ] - } ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "ZH2hVVrpzn-o" + }, + "outputs": [], "source": [ "#@title Run BindCraft!\n", "####################################\n", "###################### BindCraft Run\n", "####################################\n", + "# Colab-specific: live displays\n", + "num_sampled_trajectories = len(pd.read_csv(trajectory_csv))\n", + "num_accepted_designs = len(pd.read_csv(final_csv))\n", + "sampled_trajectories_label = HTML(value=f\"

Sampled Trajectories: {num_sampled_trajectories}

\")\n", + "accepted_designs_label = HTML(value=f\"

Accepted Designs: {num_accepted_designs}

\")\n", + "display(VBox([sampled_trajectories_label, accepted_designs_label]))\n", + "\n", "# initialise counters\n", "script_start_time = time.time()\n", "trajectory_n = 1\n", "accepted_designs = 0\n", - "rejected_designs = 0\n", "\n", "### start design loop\n", "while True:\n", @@ -526,44 +441,47 @@ "\n", " ### MPNN redesign of starting binder\n", " mpnn_trajectories = mpnn_gen_sequence(trajectory_pdb, binder_chain, trajectory_interface_residues, advanced_settings)\n", + " existing_mpnn_sequences = set(pd.read_csv(mpnn_csv, usecols=['Sequence'])['Sequence'].values)\n", + "\n", + " # create set of MPNN sequences with allowed amino acid composition\n", + " restricted_AAs = set(aa.strip().upper() for aa in advanced_settings[\"omit_AAs\"].split(',')) if advanced_settings[\"force_reject_AA\"] else set()\n", + "\n", + " mpnn_sequences = sorted({\n", + " mpnn_trajectories['seq'][n][-length:]: {\n", + " 'seq': mpnn_trajectories['seq'][n][-length:],\n", + " 'score': mpnn_trajectories['score'][n],\n", + " 'seqid': mpnn_trajectories['seqid'][n]\n", + " } for n in range(advanced_settings[\"num_seqs\"])\n", + " if (not restricted_AAs or not any(aa in mpnn_trajectories['seq'][n][-length:].upper() for aa in restricted_AAs))\n", + " and mpnn_trajectories['seq'][n][-length:] not in existing_mpnn_sequences\n", + " }.values(), key=lambda x: x['score'])\n", + "\n", + " del existing_mpnn_sequences\n", + "\n", + " # check whether any sequences are left after amino acid rejection and duplication check, and if yes proceed with prediction\n", + " if mpnn_sequences:\n", + " # add optimisation for increasing recycles if trajectory is beta sheeted\n", + " if advanced_settings[\"optimise_beta\"] and float(trajectory_beta) > 15:\n", + " advanced_settings[\"num_recycles_validation\"] = advanced_settings[\"optimise_beta_recycles_valid\"]\n", + "\n", + " ### Compile prediction models once for faster prediction of MPNN sequences\n", + " clear_mem()\n", + " # compile complex prediction model\n", + " complex_prediction_model = mk_afdesign_model(protocol=\"binder\", num_recycles=advanced_settings[\"num_recycles_validation\"], data_dir=advanced_settings[\"af_params_dir\"],\n", + " use_multimer=multimer_validation)\n", + " complex_prediction_model.prep_inputs(pdb_filename=target_settings[\"starting_pdb\"], chain=target_settings[\"chains\"], binder_len=length, rm_target_seq=advanced_settings[\"rm_template_seq_predict\"],\n", + " rm_target_sc=advanced_settings[\"rm_template_sc_predict\"])\n", + "\n", + " # compile binder monomer prediction model\n", + " binder_prediction_model = mk_afdesign_model(protocol=\"hallucination\", use_templates=False, initial_guess=False,\n", + " use_initial_atom_pos=False, num_recycles=advanced_settings[\"num_recycles_validation\"],\n", + " data_dir=advanced_settings[\"af_params_dir\"], use_multimer=multimer_validation)\n", + " binder_prediction_model.prep_inputs(length=length)\n", + "\n", + " # iterate over designed sequences\n", + " for mpnn_sequence in mpnn_sequences:\n", + " mpnn_time = time.time()\n", "\n", - " # whether to hard reject sequences with excluded amino acids\n", - " if advanced_settings[\"force_reject_AA\"]:\n", - " restricted_AAs = set(advanced_settings[\"omit_AAs\"].split(','))\n", - " mpnn_sequences = [{'seq': mpnn_trajectories['seq'][n][-length:], 'score': mpnn_trajectories['score'][n], 'seqid': mpnn_trajectories['seqid'][n]}\n", - " for n in range(advanced_settings[\"num_seqs\"])\n", - " if not any(restricted_AA in mpnn_trajectories['seq'][n] for restricted_AA in restricted_AAs)]\n", - " else:\n", - " mpnn_sequences = [{'seq': mpnn_trajectories['seq'][n][-length:], 'score': mpnn_trajectories['score'][n], 'seqid': mpnn_trajectories['seqid'][n]}\n", - " for n in range(advanced_settings[\"num_seqs\"])]\n", - "\n", - " # sort MPNN sequences by lowest MPNN score\n", - " mpnn_sequences.sort(key=lambda x: x['score'])\n", - "\n", - " # add optimisation for increasing recycles if trajectory is beta sheeted\n", - " if advanced_settings[\"optimise_beta\"] and float(trajectory_beta) > 15:\n", - " advanced_settings[\"num_recycles_validation\"] = advanced_settings[\"optimise_beta_recycles_valid\"]\n", - "\n", - " ### Compile prediction models once for faster prediction of MPNN sequences\n", - " clear_mem()\n", - " # compile complex prediction model\n", - " complex_prediction_model = mk_afdesign_model(protocol=\"binder\", num_recycles=advanced_settings[\"num_recycles_validation\"], data_dir=advanced_settings[\"af_params_dir\"],\n", - " use_multimer=multimer_validation)\n", - " complex_prediction_model.prep_inputs(pdb_filename=target_settings[\"starting_pdb\"], chain=target_settings[\"chains\"], binder_len=length, rm_target_seq=advanced_settings[\"rm_template_seq_predict\"],\n", - " rm_target_sc=advanced_settings[\"rm_template_sc_predict\"])\n", - "\n", - " # compile binder monomer prediction model\n", - " binder_prediction_model = mk_afdesign_model(protocol=\"hallucination\", use_templates=False, initial_guess=False,\n", - " use_initial_atom_pos=False, num_recycles=advanced_settings[\"num_recycles_validation\"],\n", - " data_dir=advanced_settings[\"af_params_dir\"], use_multimer=multimer_validation)\n", - " binder_prediction_model.prep_inputs(length=length)\n", - "\n", - " # iterate over designed sequences\n", - " for mpnn_sequence in mpnn_sequences:\n", - " mpnn_time = time.time()\n", - "\n", - " # compile sequences dictionary with scores and remove duplicate sequences\n", - " if mpnn_sequence['seq'] not in [v['seq'] for v in mpnn_dict.values()]:\n", " # generate mpnn design name numbering\n", " mpnn_design_name = design_name + \"_mpnn\" + str(mpnn_n)\n", " mpnn_score = round(mpnn_sequence['score'],2)\n", @@ -586,6 +504,7 @@ " # if AF2 filters are not passed then skip the scoring\n", " if not pass_af2_filters:\n", " print(f\"Base AF2 filters not passed for {mpnn_design_name}, skipping interface scoring\")\n", + " mpnn_n += 1\n", " continue\n", "\n", " # calculate statistics for each model individually\n", @@ -608,7 +527,7 @@ " rmsd_site = unaligned_rmsd(trajectory_pdb, mpnn_design_pdb, binder_chain, binder_chain)\n", "\n", " # calculate RMSD of target compared to input PDB\n", - " target_rmsd = unaligned_rmsd(target_settings[\"starting_pdb\"], mpnn_design_pdb, target_settings[\"chains\"], 'A')\n", + " target_rmsd = target_pdb_rmsd(mpnn_design_pdb, target_settings[\"starting_pdb\"], target_settings[\"chains\"])\n", "\n", " # add the additional statistics to the mpnn_complex_statistics dictionary\n", " mpnn_complex_statistics[model_num+1].update({\n", @@ -732,9 +651,10 @@ " insert_data(final_csv, final_data)\n", "\n", " # copy animation from accepted trajectory\n", - " accepted_animation = os.path.join(design_paths[\"Accepted/Animation\"], f\"{design_name}.html\")\n", - " if not os.path.exists(accepted_animation):\n", - " shutil.copy(os.path.join(design_paths[\"Trajectory/Animation\"], f\"{design_name}.html\"), accepted_animation)\n", + " if advanced_settings[\"save_design_animations\"]:\n", + " accepted_animation = os.path.join(design_paths[\"Accepted/Animation\"], f\"{design_name}.html\")\n", + " if not os.path.exists(accepted_animation):\n", + " shutil.copy(os.path.join(design_paths[\"Trajectory/Animation\"], f\"{design_name}.html\"), accepted_animation)\n", "\n", " # copy plots of accepted trajectory\n", " plot_files = os.listdir(design_paths[\"Trajectory/Plots\"])\n", @@ -770,14 +690,14 @@ " # if enough mpnn sequences of the same trajectory pass filters then stop\n", " if accepted_mpnn >= advanced_settings[\"max_mpnn_sequences\"]:\n", " break\n", + "\n", + " if accepted_mpnn >= 1:\n", + " print(\"Found \"+str(accepted_mpnn)+\" MPNN designs passing filters\")\n", " else:\n", - " print(\"Skipping duplicate sequence\")\n", + " print(\"No accepted MPNN designs found for this trajectory.\")\n", "\n", - " if accepted_mpnn >= 1:\n", - " print(\"Found \"+str(accepted_mpnn)+\" MPNN designs passing filters\")\n", " else:\n", - " print(\"No accepted MPNN designs found for this trajectory.\")\n", - " rejected_designs += 1\n", + " print('Duplicate MPNN designs sampled with different trajectory, skipping current trajectory optimisation')\n", "\n", " # save space by removing unrelaxed design trajectory PDB\n", " if advanced_settings[\"remove_unrelaxed_trajectory\"]:\n", @@ -799,896 +719,33 @@ " # increase trajectory number\n", " trajectory_n += 1\n", "\n", + " # Colab-specific: update counters\n", + " num_sampled_trajectories = len(pd.read_csv(trajectory_csv))\n", + " num_accepted_designs = len(pd.read_csv(final_csv))\n", + " sampled_trajectories_label.value = f\"Sampled trajectories: {num_sampled_trajectories}\"\n", + " accepted_designs_label.value = f\"Accepted designs: {num_accepted_designs}\"\n", + "\n", "### Script finished\n", "elapsed_time = time.time() - script_start_time\n", "elapsed_text = f\"{'%d hours, %d minutes, %d seconds' % (int(elapsed_time // 3600), int((elapsed_time % 3600) // 60), int(elapsed_time % 60))}\"\n", "print(\"Finished all designs. Script execution for \"+str(trajectory_n)+\" trajectories took: \"+elapsed_text)" - ], - "metadata": { - "id": "ZH2hVVrpzn-o", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 1000 - }, - "cellView": "form", - "outputId": "e1e5984c-cdae-421c-eb88-b40b9a17d0c3" - }, - "execution_count": 8, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Starting trajectory: PDL1_l70_s228294\n", - "Stage 1: Test Logits\n", - "1 models [4] recycles 1 hard 0 soft 0.02 temp 1 loss 10.47 helix 1.19 pae 0.76 i_pae 0.80 con 4.80 i_con 4.26 plddt 0.33 ptm 0.59 i_ptm 0.12 rg 4.25\n", - "2 models [0] recycles 1 hard 0 soft 0.04 temp 1 loss 9.77 helix 1.01 pae 0.69 i_pae 0.74 con 4.25 i_con 4.24 plddt 0.36 ptm 0.59 i_ptm 0.15 rg 3.75\n", - "3 models [3] recycles 1 hard 0 soft 0.05 temp 1 loss 9.06 helix 0.83 pae 0.63 i_pae 0.73 con 3.88 i_con 4.21 plddt 0.44 ptm 0.60 i_ptm 0.15 rg 2.65\n", - "4 models [1] recycles 1 hard 0 soft 0.07 temp 1 loss 8.94 helix 1.10 pae 0.65 i_pae 0.72 con 4.01 i_con 4.21 plddt 0.42 ptm 0.60 i_ptm 0.15 rg 2.07\n", - "5 models [3] recycles 1 hard 0 soft 0.09 temp 1 loss 8.07 helix 0.90 pae 0.58 i_pae 0.66 con 3.75 i_con 3.94 plddt 0.44 ptm 0.62 i_ptm 0.21 rg 0.83\n", - "6 models [2] recycles 1 hard 0 soft 0.11 temp 1 loss 7.69 helix 0.83 pae 0.48 i_pae 0.52 con 3.62 i_con 3.50 plddt 0.55 ptm 0.67 i_ptm 0.47 rg 1.67\n", - "7 models [1] recycles 1 hard 0 soft 0.13 temp 1 loss 7.46 helix 0.84 pae 0.43 i_pae 0.46 con 3.51 i_con 3.44 plddt 0.58 ptm 0.71 i_ptm 0.51 rg 1.61\n", - "8 models [3] recycles 1 hard 0 soft 0.14 temp 1 loss 6.82 helix 0.86 pae 0.36 i_pae 0.40 con 3.17 i_con 3.17 plddt 0.64 ptm 0.73 i_ptm 0.56 rg 1.62\n", - "9 models [3] recycles 1 hard 0 soft 0.16 temp 1 loss 6.85 helix 0.88 pae 0.36 i_pae 0.41 con 3.10 i_con 3.27 plddt 0.65 ptm 0.73 i_ptm 0.50 rg 1.68\n", - "10 models [2] recycles 1 hard 0 soft 0.18 temp 1 loss 6.56 helix 0.92 pae 0.34 i_pae 0.39 con 2.87 i_con 3.21 plddt 0.70 ptm 0.73 i_ptm 0.50 rg 1.75\n", - "11 models [1] recycles 1 hard 0 soft 0.20 temp 1 loss 6.27 helix 0.98 pae 0.33 i_pae 0.39 con 2.61 i_con 3.24 plddt 0.70 ptm 0.73 i_ptm 0.49 rg 1.62\n", - "12 models [3] recycles 1 hard 0 soft 0.22 temp 1 loss 6.46 helix 1.10 pae 0.35 i_pae 0.42 con 2.69 i_con 3.29 plddt 0.68 ptm 0.72 i_ptm 0.47 rg 1.88\n", - "13 models [2] recycles 1 hard 0 soft 0.23 temp 1 loss 6.40 helix 0.94 pae 0.34 i_pae 0.43 con 2.62 i_con 3.31 plddt 0.72 ptm 0.70 i_ptm 0.44 rg 1.73\n", - "14 models [3] recycles 1 hard 0 soft 0.25 temp 1 loss 5.45 helix 1.01 pae 0.24 i_pae 0.29 con 2.19 i_con 2.80 plddt 0.81 ptm 0.79 i_ptm 0.64 rg 2.01\n", - "15 models [1] recycles 1 hard 0 soft 0.27 temp 1 loss 5.30 helix 0.93 pae 0.21 i_pae 0.23 con 2.35 i_con 2.53 plddt 0.82 ptm 0.83 i_ptm 0.74 rg 1.87\n", - "16 models [0] recycles 1 hard 0 soft 0.29 temp 1 loss 4.91 helix 0.99 pae 0.19 i_pae 0.22 con 2.05 i_con 2.48 plddt 0.84 ptm 0.83 i_ptm 0.73 rg 1.84\n", - "17 models [3] recycles 1 hard 0 soft 0.31 temp 1 loss 6.96 helix 0.86 pae 0.41 i_pae 0.49 con 3.00 i_con 3.45 plddt 0.62 ptm 0.67 i_ptm 0.35 rg 1.61\n", - "18 models [0] recycles 1 hard 0 soft 0.32 temp 1 loss 5.07 helix 1.07 pae 0.18 i_pae 0.21 con 2.21 i_con 2.44 plddt 0.83 ptm 0.84 i_ptm 0.74 rg 2.04\n", - "19 models [3] recycles 1 hard 0 soft 0.34 temp 1 loss 5.53 helix 0.91 pae 0.23 i_pae 0.29 con 2.23 i_con 2.82 plddt 0.82 ptm 0.78 i_ptm 0.63 rg 2.02\n", - "20 models [1] recycles 1 hard 0 soft 0.36 temp 1 loss 6.92 helix 0.66 pae 0.22 i_pae 0.24 con 2.65 i_con 2.78 plddt 0.83 ptm 0.83 i_ptm 0.74 rg 5.15\n", - "21 models [2] recycles 1 hard 0 soft 0.38 temp 1 loss 7.75 helix 0.68 pae 0.29 i_pae 0.33 con 2.96 i_con 3.28 plddt 0.77 ptm 0.76 i_ptm 0.59 rg 5.09\n", - "22 models [1] recycles 1 hard 0 soft 0.40 temp 1 loss 6.72 helix 0.70 pae 0.20 i_pae 0.23 con 2.36 i_con 2.94 plddt 0.86 ptm 0.82 i_ptm 0.72 rg 5.01\n", - "23 models [2] recycles 1 hard 0 soft 0.41 temp 1 loss 5.02 helix 0.85 pae 0.18 i_pae 0.21 con 2.30 i_con 2.30 plddt 0.84 ptm 0.84 i_ptm 0.76 rg 1.86\n", - "24 models [0] recycles 1 hard 0 soft 0.43 temp 1 loss 6.40 helix 0.65 pae 0.19 i_pae 0.23 con 2.05 i_con 2.96 plddt 0.88 ptm 0.81 i_ptm 0.70 rg 4.87\n", - "25 models [1] recycles 1 hard 0 soft 0.45 temp 1 loss 6.22 helix 0.70 pae 0.18 i_pae 0.21 con 2.06 i_con 2.79 plddt 0.89 ptm 0.84 i_ptm 0.76 rg 4.89\n", - "26 models [0] recycles 1 hard 0 soft 0.47 temp 1 loss 6.32 helix 0.66 pae 0.18 i_pae 0.21 con 2.11 i_con 2.79 plddt 0.88 ptm 0.83 i_ptm 0.76 rg 4.99\n", - "27 models [4] recycles 1 hard 0 soft 0.49 temp 1 loss 6.32 helix 0.61 pae 0.18 i_pae 0.22 con 1.97 i_con 2.91 plddt 0.90 ptm 0.82 i_ptm 0.73 rg 5.00\n", - "28 models [2] recycles 1 hard 0 soft 0.50 temp 1 loss 5.96 helix 0.62 pae 0.17 i_pae 0.19 con 1.91 i_con 2.64 plddt 0.92 ptm 0.85 i_ptm 0.79 rg 4.98\n", - "29 models [4] recycles 1 hard 0 soft 0.52 temp 1 loss 7.00 helix 0.66 pae 0.28 i_pae 0.38 con 2.01 i_con 3.52 plddt 0.83 ptm 0.69 i_ptm 0.46 rg 4.89\n", - "30 models [2] recycles 1 hard 0 soft 0.54 temp 1 loss 6.96 helix 0.59 pae 0.27 i_pae 0.36 con 2.05 i_con 3.44 plddt 0.84 ptm 0.72 i_ptm 0.49 rg 4.89\n", - "31 models [3] recycles 1 hard 0 soft 0.56 temp 1 loss 8.00 helix 0.62 pae 0.48 i_pae 0.70 con 1.94 i_con 4.50 plddt 0.78 ptm 0.59 i_ptm 0.12 rg 4.71\n", - "32 models [3] recycles 1 hard 0 soft 0.58 temp 1 loss 7.67 helix 0.69 pae 0.45 i_pae 0.65 con 1.88 i_con 4.27 plddt 0.78 ptm 0.59 i_ptm 0.15 rg 4.74\n", - "33 models [1] recycles 1 hard 0 soft 0.59 temp 1 loss 6.09 helix 0.71 pae 0.17 i_pae 0.21 con 1.89 i_con 2.84 plddt 0.89 ptm 0.82 i_ptm 0.73 rg 4.87\n", - "34 models [1] recycles 1 hard 0 soft 0.61 temp 1 loss 5.74 helix 0.74 pae 0.15 i_pae 0.18 con 1.78 i_con 2.60 plddt 0.92 ptm 0.85 i_ptm 0.80 rg 4.96\n", - "35 models [0] recycles 1 hard 0 soft 0.63 temp 1 loss 5.90 helix 0.69 pae 0.17 i_pae 0.20 con 1.87 i_con 2.66 plddt 0.91 ptm 0.84 i_ptm 0.77 rg 4.92\n", - "36 models [4] recycles 1 hard 0 soft 0.65 temp 1 loss 6.20 helix 0.65 pae 0.18 i_pae 0.23 con 1.90 i_con 2.87 plddt 0.90 ptm 0.80 i_ptm 0.72 rg 5.00\n", - "37 models [2] recycles 1 hard 0 soft 0.67 temp 1 loss 6.04 helix 0.67 pae 0.18 i_pae 0.22 con 1.90 i_con 2.73 plddt 0.91 ptm 0.82 i_ptm 0.75 rg 5.01\n", - "38 models [1] recycles 1 hard 0 soft 0.68 temp 1 loss 5.76 helix 0.74 pae 0.16 i_pae 0.19 con 1.80 i_con 2.57 plddt 0.92 ptm 0.83 i_ptm 0.80 rg 5.02\n", - "39 models [3] recycles 1 hard 0 soft 0.70 temp 1 loss 5.55 helix 0.75 pae 0.16 i_pae 0.18 con 1.75 i_con 2.41 plddt 0.93 ptm 0.86 i_ptm 0.82 rg 5.05\n", - "40 models [2] recycles 1 hard 0 soft 0.72 temp 1 loss 5.73 helix 0.76 pae 0.17 i_pae 0.19 con 1.81 i_con 2.51 plddt 0.92 ptm 0.83 i_ptm 0.79 rg 5.14\n", - "41 models [0] recycles 1 hard 0 soft 0.74 temp 1 loss 5.64 helix 0.87 pae 0.18 i_pae 0.20 con 1.88 i_con 2.39 plddt 0.90 ptm 0.85 i_ptm 0.81 rg 5.04\n", - "42 models [1] recycles 1 hard 0 soft 0.76 temp 1 loss 5.70 helix 0.78 pae 0.16 i_pae 0.19 con 1.78 i_con 2.57 plddt 0.92 ptm 0.84 i_ptm 0.80 rg 4.97\n", - "43 models [2] recycles 1 hard 0 soft 0.77 temp 1 loss 5.62 helix 0.83 pae 0.18 i_pae 0.21 con 1.76 i_con 2.50 plddt 0.91 ptm 0.83 i_ptm 0.80 rg 5.00\n", - "44 models [0] recycles 1 hard 0 soft 0.79 temp 1 loss 5.86 helix 0.76 pae 0.17 i_pae 0.20 con 1.71 i_con 2.77 plddt 0.90 ptm 0.83 i_ptm 0.76 rg 4.97\n", - "45 models [3] recycles 1 hard 0 soft 0.81 temp 1 loss 5.46 helix 0.77 pae 0.16 i_pae 0.19 con 1.71 i_con 2.38 plddt 0.92 ptm 0.85 i_ptm 0.81 rg 5.03\n", - "46 models [1] recycles 1 hard 0 soft 0.83 temp 1 loss 7.37 helix 0.59 pae 0.34 i_pae 0.46 con 2.14 i_con 3.81 plddt 0.78 ptm 0.66 i_ptm 0.36 rg 4.55\n", - "47 models [4] recycles 1 hard 0 soft 0.85 temp 1 loss 5.63 helix 0.81 pae 0.17 i_pae 0.20 con 1.75 i_con 2.54 plddt 0.92 ptm 0.83 i_ptm 0.79 rg 4.91\n", - "48 models [0] recycles 1 hard 0 soft 0.86 temp 1 loss 5.40 helix 0.86 pae 0.16 i_pae 0.18 con 1.65 i_con 2.49 plddt 0.92 ptm 0.85 i_ptm 0.80 rg 4.74\n", - "49 models [1] recycles 1 hard 0 soft 0.88 temp 1 loss 5.96 helix 0.81 pae 0.19 i_pae 0.25 con 1.71 i_con 2.97 plddt 0.89 ptm 0.79 i_ptm 0.66 rg 4.66\n", - "50 models [0] recycles 1 hard 0 soft 0.90 temp 1 loss 5.45 helix 0.80 pae 0.15 i_pae 0.18 con 1.63 i_con 2.52 plddt 0.92 ptm 0.85 i_ptm 0.80 rg 4.79\n", - "Initial trajectory pLDDT good, continuing: 0.84\n", - "Stage 1: Additional Logits Optimisation\n", - "51 models [0] recycles 1 hard 0 soft 0.04 temp 1 loss 8.28 helix 0.85 pae 0.39 i_pae 0.40 con 3.45 i_con 3.39 plddt 0.65 ptm 0.74 i_ptm 0.60 rg 4.82\n", - "52 models [1] recycles 1 hard 0 soft 0.08 temp 1 loss 6.96 helix 0.74 pae 0.26 i_pae 0.30 con 2.43 i_con 3.09 plddt 0.79 ptm 0.78 i_ptm 0.61 rg 4.94\n", - "53 models [0] recycles 1 hard 0 soft 0.12 temp 1 loss 5.34 helix 0.88 pae 0.16 i_pae 0.18 con 1.74 i_con 2.32 plddt 0.92 ptm 0.87 i_ptm 0.83 rg 4.85\n", - "54 models [3] recycles 1 hard 0 soft 0.16 temp 1 loss 5.23 helix 0.83 pae 0.15 i_pae 0.18 con 1.59 i_con 2.35 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 4.82\n", - "55 models [1] recycles 1 hard 0 soft 0.20 temp 1 loss 5.09 helix 0.82 pae 0.15 i_pae 0.18 con 1.59 i_con 2.23 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 4.73\n", - "56 models [0] recycles 1 hard 0 soft 0.24 temp 1 loss 5.21 helix 0.93 pae 0.19 i_pae 0.21 con 1.74 i_con 2.14 plddt 0.89 ptm 0.86 i_ptm 0.84 rg 4.95\n", - "57 models [1] recycles 1 hard 0 soft 0.28 temp 1 loss 5.09 helix 0.92 pae 0.17 i_pae 0.19 con 1.68 i_con 2.14 plddt 0.92 ptm 0.86 i_ptm 0.83 rg 4.80\n", - "58 models [4] recycles 1 hard 0 soft 0.32 temp 1 loss 5.12 helix 0.89 pae 0.17 i_pae 0.19 con 1.63 i_con 2.21 plddt 0.92 ptm 0.86 i_ptm 0.83 rg 4.83\n", - "59 models [0] recycles 1 hard 0 soft 0.36 temp 1 loss 4.95 helix 0.96 pae 0.18 i_pae 0.19 con 1.65 i_con 2.04 plddt 0.91 ptm 0.87 i_ptm 0.84 rg 4.79\n", - "60 models [0] recycles 1 hard 0 soft 0.40 temp 1 loss 4.95 helix 0.94 pae 0.14 i_pae 0.16 con 1.54 i_con 2.15 plddt 0.93 ptm 0.88 i_ptm 0.86 rg 4.84\n", - "61 models [3] recycles 1 hard 0 soft 0.44 temp 1 loss 4.92 helix 0.94 pae 0.14 i_pae 0.17 con 1.50 i_con 2.14 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 4.93\n", - "62 models [0] recycles 1 hard 0 soft 0.48 temp 1 loss 4.97 helix 0.99 pae 0.14 i_pae 0.16 con 1.58 i_con 2.14 plddt 0.93 ptm 0.88 i_ptm 0.85 rg 4.89\n", - "63 models [2] recycles 1 hard 0 soft 0.52 temp 1 loss 5.01 helix 1.01 pae 0.15 i_pae 0.17 con 1.55 i_con 2.17 plddt 0.94 ptm 0.86 i_ptm 0.83 rg 4.99\n", - "64 models [0] recycles 1 hard 0 soft 0.56 temp 1 loss 5.12 helix 0.89 pae 0.15 i_pae 0.18 con 1.61 i_con 2.22 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.86\n", - "65 models [3] recycles 1 hard 0 soft 0.60 temp 1 loss 5.01 helix 0.97 pae 0.16 i_pae 0.18 con 1.63 i_con 2.11 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 4.87\n", - "66 models [2] recycles 1 hard 0 soft 0.64 temp 1 loss 5.27 helix 0.85 pae 0.16 i_pae 0.19 con 1.66 i_con 2.28 plddt 0.93 ptm 0.84 i_ptm 0.80 rg 4.95\n", - "67 models [2] recycles 1 hard 0 soft 0.68 temp 1 loss 5.17 helix 0.93 pae 0.14 i_pae 0.17 con 1.59 i_con 2.25 plddt 0.94 ptm 0.87 i_ptm 0.83 rg 5.04\n", - "68 models [0] recycles 1 hard 0 soft 0.72 temp 1 loss 5.64 helix 0.94 pae 0.18 i_pae 0.22 con 1.72 i_con 2.66 plddt 0.89 ptm 0.82 i_ptm 0.72 rg 4.77\n", - "69 models [3] recycles 1 hard 0 soft 0.76 temp 1 loss 5.07 helix 0.96 pae 0.15 i_pae 0.18 con 1.61 i_con 2.17 plddt 0.93 ptm 0.86 i_ptm 0.82 rg 4.95\n", - "70 models [1] recycles 1 hard 0 soft 0.80 temp 1 loss 5.16 helix 0.90 pae 0.15 i_pae 0.18 con 1.61 i_con 2.27 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.83\n", - "71 models [1] recycles 1 hard 0 soft 0.84 temp 1 loss 5.23 helix 0.84 pae 0.16 i_pae 0.18 con 1.69 i_con 2.26 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.76\n", - "72 models [4] recycles 1 hard 0 soft 0.88 temp 1 loss 5.24 helix 0.86 pae 0.16 i_pae 0.19 con 1.66 i_con 2.30 plddt 0.92 ptm 0.85 i_ptm 0.81 rg 4.78\n", - "73 models [0] recycles 1 hard 0 soft 0.92 temp 1 loss 5.21 helix 0.82 pae 0.17 i_pae 0.19 con 1.72 i_con 2.18 plddt 0.91 ptm 0.87 i_ptm 0.82 rg 4.85\n", - "74 models [3] recycles 1 hard 0 soft 0.96 temp 1 loss 5.22 helix 0.87 pae 0.18 i_pae 0.20 con 1.71 i_con 2.20 plddt 0.91 ptm 0.85 i_ptm 0.83 rg 4.88\n", - "75 models [2] recycles 1 hard 0 soft 1 temp 1 loss 7.69 helix 0.66 pae 0.48 i_pae 0.68 con 1.96 i_con 4.24 plddt 0.74 ptm 0.58 i_ptm 0.15 rg 4.54\n", - "Optimised logit trajectory pLDDT: 0.94\n", - "Stage 2: Softmax Optimisation\n", - "76 models [2] recycles 1 hard 0 soft 1 temp 0.96 loss 5.33 helix 0.82 pae 0.17 i_pae 0.20 con 1.73 i_con 2.27 plddt 0.91 ptm 0.85 i_ptm 0.81 rg 4.90\n", - "77 models [4] recycles 1 hard 0 soft 1 temp 0.91 loss 5.31 helix 0.81 pae 0.18 i_pae 0.20 con 1.73 i_con 2.26 plddt 0.91 ptm 0.85 i_ptm 0.82 rg 4.84\n", - "78 models [0] recycles 1 hard 0 soft 1 temp 0.87 loss 5.44 helix 1.01 pae 0.22 i_pae 0.23 con 1.91 i_con 2.24 plddt 0.87 ptm 0.85 i_ptm 0.83 rg 4.87\n", - "79 models [0] recycles 1 hard 0 soft 1 temp 0.83 loss 5.27 helix 0.89 pae 0.19 i_pae 0.20 con 1.74 i_con 2.24 plddt 0.90 ptm 0.85 i_ptm 0.82 rg 4.78\n", - "80 models [3] recycles 1 hard 0 soft 1 temp 0.79 loss 5.16 helix 0.86 pae 0.17 i_pae 0.19 con 1.63 i_con 2.21 plddt 0.92 ptm 0.86 i_ptm 0.83 rg 4.92\n", - "81 models [0] recycles 1 hard 0 soft 1 temp 0.75 loss 5.13 helix 0.87 pae 0.16 i_pae 0.18 con 1.63 i_con 2.21 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.82\n", - "82 models [2] recycles 1 hard 0 soft 1 temp 0.72 loss 5.46 helix 0.86 pae 0.17 i_pae 0.20 con 1.65 i_con 2.49 plddt 0.92 ptm 0.84 i_ptm 0.78 rg 4.90\n", - "83 models [4] recycles 1 hard 0 soft 1 temp 0.68 loss 5.28 helix 0.86 pae 0.17 i_pae 0.19 con 1.65 i_con 2.31 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.90\n", - "84 models [2] recycles 1 hard 0 soft 1 temp 0.64 loss 5.19 helix 0.90 pae 0.16 i_pae 0.19 con 1.64 i_con 2.26 plddt 0.92 ptm 0.85 i_ptm 0.81 rg 4.87\n", - "85 models [0] recycles 1 hard 0 soft 1 temp 0.61 loss 5.10 helix 0.94 pae 0.15 i_pae 0.17 con 1.62 i_con 2.20 plddt 0.93 ptm 0.87 i_ptm 0.82 rg 4.90\n", - "86 models [3] recycles 1 hard 0 soft 1 temp 0.58 loss 5.09 helix 0.92 pae 0.16 i_pae 0.18 con 1.59 i_con 2.21 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 4.90\n", - "87 models [0] recycles 1 hard 0 soft 1 temp 0.54 loss 5.20 helix 0.90 pae 0.14 i_pae 0.17 con 1.62 i_con 2.29 plddt 0.93 ptm 0.87 i_ptm 0.82 rg 4.90\n", - "88 models [3] recycles 1 hard 0 soft 1 temp 0.51 loss 5.14 helix 0.88 pae 0.16 i_pae 0.19 con 1.61 i_con 2.24 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.86\n", - "89 models [3] recycles 1 hard 0 soft 1 temp 0.48 loss 5.10 helix 0.86 pae 0.15 i_pae 0.18 con 1.51 i_con 2.29 plddt 0.94 ptm 0.85 i_ptm 0.84 rg 4.88\n", - "90 models [4] recycles 1 hard 0 soft 1 temp 0.45 loss 5.25 helix 0.78 pae 0.16 i_pae 0.19 con 1.65 i_con 2.28 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.88\n", - "91 models [0] recycles 1 hard 0 soft 1 temp 0.42 loss 5.03 helix 0.92 pae 0.15 i_pae 0.17 con 1.54 i_con 2.23 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 4.79\n", - "92 models [1] recycles 1 hard 0 soft 1 temp 0.39 loss 7.07 helix 0.87 pae 0.41 i_pae 0.59 con 1.67 i_con 3.94 plddt 0.79 ptm 0.61 i_ptm 0.22 rg 4.79\n", - "93 models [4] recycles 1 hard 0 soft 1 temp 0.37 loss 5.23 helix 0.87 pae 0.15 i_pae 0.18 con 1.56 i_con 2.39 plddt 0.94 ptm 0.86 i_ptm 0.83 rg 4.83\n", - "94 models [0] recycles 1 hard 0 soft 1 temp 0.34 loss 5.10 helix 0.86 pae 0.14 i_pae 0.17 con 1.52 i_con 2.33 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 4.75\n", - "95 models [0] recycles 1 hard 0 soft 1 temp 0.32 loss 5.29 helix 0.96 pae 0.17 i_pae 0.20 con 1.75 i_con 2.25 plddt 0.90 ptm 0.85 i_ptm 0.80 rg 4.88\n", - "96 models [3] recycles 1 hard 0 soft 1 temp 0.29 loss 5.11 helix 0.92 pae 0.16 i_pae 0.19 con 1.57 i_con 2.23 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 4.94\n", - "97 models [0] recycles 1 hard 0 soft 1 temp 0.27 loss 5.30 helix 0.90 pae 0.18 i_pae 0.20 con 1.76 i_con 2.26 plddt 0.90 ptm 0.85 i_ptm 0.80 rg 4.81\n", - "98 models [3] recycles 1 hard 0 soft 1 temp 0.25 loss 4.99 helix 0.94 pae 0.16 i_pae 0.19 con 1.58 i_con 2.14 plddt 0.93 ptm 0.87 i_ptm 0.84 rg 4.83\n", - "99 models [1] recycles 1 hard 0 soft 1 temp 0.23 loss 5.15 helix 0.88 pae 0.17 i_pae 0.19 con 1.68 i_con 2.21 plddt 0.91 ptm 0.85 i_ptm 0.82 rg 4.72\n", - "100 models [1] recycles 1 hard 0 soft 1 temp 0.21 loss 5.37 helix 0.90 pae 0.18 i_pae 0.20 con 1.81 i_con 2.25 plddt 0.90 ptm 0.85 i_ptm 0.80 rg 4.89\n", - "101 models [2] recycles 1 hard 0 soft 1 temp 0.19 loss 8.54 helix 0.60 pae 0.58 i_pae 0.77 con 2.51 i_con 4.53 plddt 0.66 ptm 0.58 i_ptm 0.10 rg 4.32\n", - "102 models [1] recycles 1 hard 0 soft 1 temp 0.17 loss 5.07 helix 0.82 pae 0.15 i_pae 0.17 con 1.59 i_con 2.19 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 4.80\n", - "103 models [2] recycles 1 hard 0 soft 1 temp 0.15 loss 7.06 helix 0.61 pae 0.37 i_pae 0.46 con 2.10 i_con 3.49 plddt 0.78 ptm 0.69 i_ptm 0.42 rg 4.71\n", - "104 models [2] recycles 1 hard 0 soft 1 temp 0.14 loss 5.16 helix 0.91 pae 0.17 i_pae 0.20 con 1.72 i_con 2.14 plddt 0.92 ptm 0.85 i_ptm 0.81 rg 4.89\n", - "105 models [3] recycles 1 hard 0 soft 1 temp 0.12 loss 4.99 helix 1.01 pae 0.16 i_pae 0.19 con 1.60 i_con 2.10 plddt 0.93 ptm 0.86 i_ptm 0.82 rg 4.95\n", - "106 models [2] recycles 1 hard 0 soft 1 temp 0.11 loss 5.24 helix 0.82 pae 0.16 i_pae 0.19 con 1.63 i_con 2.29 plddt 0.93 ptm 0.85 i_ptm 0.80 rg 4.90\n", - "107 models [2] recycles 1 hard 0 soft 1 temp 0.09 loss 6.43 helix 0.80 pae 0.25 i_pae 0.33 con 1.81 i_con 3.24 plddt 0.85 ptm 0.73 i_ptm 0.52 rg 4.84\n", - "108 models [1] recycles 1 hard 0 soft 1 temp 0.08 loss 5.22 helix 0.88 pae 0.17 i_pae 0.19 con 1.69 i_con 2.22 plddt 0.91 ptm 0.85 i_ptm 0.81 rg 4.90\n", - "109 models [1] recycles 1 hard 0 soft 1 temp 0.07 loss 5.27 helix 0.86 pae 0.15 i_pae 0.18 con 1.62 i_con 2.37 plddt 0.93 ptm 0.86 i_ptm 0.81 rg 4.81\n", - "110 models [0] recycles 1 hard 0 soft 1 temp 0.06 loss 5.08 helix 0.95 pae 0.15 i_pae 0.18 con 1.65 i_con 2.14 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.91\n", - "111 models [1] recycles 1 hard 0 soft 1 temp 0.05 loss 5.27 helix 0.87 pae 0.15 i_pae 0.18 con 1.61 i_con 2.37 plddt 0.92 ptm 0.86 i_ptm 0.81 rg 4.85\n", - "112 models [2] recycles 1 hard 0 soft 1 temp 0.04 loss 8.01 helix 0.74 pae 0.54 i_pae 0.79 con 1.80 i_con 4.73 plddt 0.82 ptm 0.58 i_ptm 0.09 rg 4.48\n", - "113 models [4] recycles 1 hard 0 soft 1 temp 0.03 loss 5.95 helix 0.81 pae 0.19 i_pae 0.24 con 1.74 i_con 2.87 plddt 0.90 ptm 0.81 i_ptm 0.72 rg 4.87\n", - "114 models [2] recycles 1 hard 0 soft 1 temp 0.03 loss 7.69 helix 0.82 pae 0.49 i_pae 0.71 con 1.81 i_con 4.41 plddt 0.78 ptm 0.60 i_ptm 0.15 rg 4.61\n", - "115 models [4] recycles 1 hard 0 soft 1 temp 0.02 loss 8.56 helix 0.72 pae 0.52 i_pae 0.72 con 2.57 i_con 4.56 plddt 0.70 ptm 0.59 i_ptm 0.14 rg 4.34\n", - "116 models [4] recycles 1 hard 0 soft 1 temp 0.02 loss 7.53 helix 0.81 pae 0.44 i_pae 0.63 con 1.94 i_con 4.14 plddt 0.76 ptm 0.60 i_ptm 0.18 rg 4.63\n", - "117 models [0] recycles 1 hard 0 soft 1 temp 0.01 loss 5.18 helix 1.00 pae 0.15 i_pae 0.18 con 1.67 i_con 2.23 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.91\n", - "118 models [2] recycles 1 hard 0 soft 1 temp 0.01 loss 8.05 helix 0.82 pae 0.51 i_pae 0.74 con 1.93 i_con 4.65 plddt 0.80 ptm 0.58 i_ptm 0.13 rg 4.59\n", - "119 models [2] recycles 1 hard 0 soft 1 temp 0.01 loss 9.05 helix 0.80 pae 0.70 i_pae 0.81 con 4.11 i_con 4.42 plddt 0.43 ptm 0.58 i_ptm 0.10 rg 0.97\n", - "120 models [2] recycles 1 hard 0 soft 1 temp 0.01 loss 9.51 helix 0.86 pae 0.69 i_pae 0.79 con 4.02 i_con 4.39 plddt 0.47 ptm 0.57 i_ptm 0.10 rg 3.02\n", - "Softmax trajectory pLDDT good, continuing: 0.93\n", - "Stage 3: One-hot Optimisation\n", - "121 models [1] recycles 1 hard 1 soft 1 temp 0.01 loss 5.01 helix 0.95 pae 0.15 i_pae 0.17 con 1.62 i_con 2.09 plddt 0.92 ptm 0.87 i_ptm 0.83 rg 4.98\n", - "122 models [2] recycles 1 hard 1 soft 1 temp 0.01 loss 7.93 helix 0.77 pae 0.49 i_pae 0.72 con 1.74 i_con 4.67 plddt 0.80 ptm 0.59 i_ptm 0.13 rg 4.73\n", - "123 models [3] recycles 1 hard 1 soft 1 temp 0.01 loss 5.06 helix 0.94 pae 0.14 i_pae 0.17 con 1.50 i_con 2.25 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 5.02\n", - "124 models [1] recycles 1 hard 1 soft 1 temp 0.01 loss 5.03 helix 0.89 pae 0.15 i_pae 0.17 con 1.56 i_con 2.19 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 4.88\n", - "125 models [1] recycles 1 hard 1 soft 1 temp 0.01 loss 5.03 helix 0.89 pae 0.15 i_pae 0.17 con 1.56 i_con 2.19 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 4.88\n", - "One-hot trajectory pLDDT good, continuing: 0.92\n", - "Stage 4: PSSM Semigreedy Optimisation\n", - "Running semigreedy optimization...\n", - "126 models [2] recycles 1 hard 1 soft 0 temp 1 loss 5.24 helix 0.89 pae 0.15 i_pae 0.18 con 1.61 i_con 2.31 plddt 0.92 ptm 0.86 i_ptm 0.81 rg 4.97\n", - "127 models [2] recycles 1 hard 1 soft 0 temp 1 loss 5.28 helix 0.86 pae 0.15 i_pae 0.17 con 1.66 i_con 2.30 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 4.93\n", - "128 models [3] recycles 1 hard 1 soft 0 temp 1 loss 5.07 helix 0.89 pae 0.14 i_pae 0.17 con 1.53 i_con 2.23 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 4.97\n", - "129 models [3] recycles 1 hard 1 soft 0 temp 1 loss 5.11 helix 0.90 pae 0.14 i_pae 0.17 con 1.53 i_con 2.27 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 4.98\n", - "130 models [0] recycles 1 hard 1 soft 0 temp 1 loss 5.16 helix 0.86 pae 0.15 i_pae 0.17 con 1.60 i_con 2.24 plddt 0.92 ptm 0.88 i_ptm 0.83 rg 4.96\n", - "131 models [4] recycles 1 hard 1 soft 0 temp 1 loss 5.31 helix 0.79 pae 0.16 i_pae 0.19 con 1.64 i_con 2.33 plddt 0.92 ptm 0.85 i_ptm 0.82 rg 4.91\n", - "132 models [4] recycles 1 hard 1 soft 0 temp 1 loss 5.31 helix 0.79 pae 0.16 i_pae 0.19 con 1.64 i_con 2.34 plddt 0.92 ptm 0.85 i_ptm 0.82 rg 4.90\n", - "133 models [3] recycles 1 hard 1 soft 0 temp 1 loss 5.15 helix 0.87 pae 0.15 i_pae 0.17 con 1.54 i_con 2.29 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 4.99\n", - "134 models [0] recycles 1 hard 1 soft 0 temp 1 loss 5.13 helix 0.85 pae 0.14 i_pae 0.16 con 1.60 i_con 2.21 plddt 0.92 ptm 0.88 i_ptm 0.83 rg 4.94\n", - "135 models [3] recycles 1 hard 1 soft 0 temp 1 loss 5.15 helix 0.85 pae 0.15 i_pae 0.17 con 1.56 i_con 2.26 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 4.98\n", - "136 models [0] recycles 1 hard 1 soft 0 temp 1 loss 5.15 helix 0.83 pae 0.15 i_pae 0.16 con 1.61 i_con 2.22 plddt 0.92 ptm 0.88 i_ptm 0.83 rg 4.93\n", - "137 models [1] recycles 1 hard 1 soft 0 temp 1 loss 5.11 helix 0.80 pae 0.15 i_pae 0.17 con 1.55 i_con 2.25 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 4.87\n", - "138 models [3] recycles 1 hard 1 soft 0 temp 1 loss 5.19 helix 0.79 pae 0.15 i_pae 0.18 con 1.58 i_con 2.26 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 4.99\n", - "139 models [4] recycles 1 hard 1 soft 0 temp 1 loss 5.67 helix 0.66 pae 0.17 i_pae 0.20 con 1.75 i_con 2.51 plddt 0.90 ptm 0.85 i_ptm 0.80 rg 5.00\n", - "140 models [3] recycles 1 hard 1 soft 0 temp 1 loss 5.32 helix 0.70 pae 0.16 i_pae 0.19 con 1.59 i_con 2.33 plddt 0.92 ptm 0.86 i_ptm 0.82 rg 5.02\n", - "Trajectory successful, final pLDDT: 0.94\n", - "Starting trajectory took: 0 hours, 4 minutes, 21 seconds\n", - "\n", - "Fixing interface residues: B22,B25,B26,B28,B29,B30,B32,B33,B34,B36,B37,B44,B48,B51,B52,B55,B56,B58,B59,B62\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l70_s228294_mpnn1, skipping interface scoring\n", - "No accepted MPNN designs found for this trajectory.\n", - "Design and validation of trajectory PDL1_l70_s228294 took: 0 hours, 0 minutes, 55 seconds\n", - "Starting trajectory: PDL1_l118_s893196\n", - "Stage 1: Test Logits\n", - "1 models [1] recycles 1 hard 0 soft 0.02 temp 1 loss 12.59 helix 1.58 pae 0.85 i_pae 0.88 con 4.63 i_con 4.90 plddt 0.29 ptm 0.49 i_ptm 0.09 rg 9.98\n", - "2 models [3] recycles 1 hard 0 soft 0.04 temp 1 loss 11.17 helix 0.79 pae 0.75 i_pae 0.83 con 4.29 i_con 4.63 plddt 0.39 ptm 0.49 i_ptm 0.11 rg 6.68\n", - "3 models [0] recycles 1 hard 0 soft 0.05 temp 1 loss 9.46 helix 0.77 pae 0.72 i_pae 0.80 con 4.06 i_con 4.56 plddt 0.35 ptm 0.49 i_ptm 0.12 rg 1.97\n", - "4 models [1] recycles 1 hard 0 soft 0.07 temp 1 loss 8.59 helix 0.82 pae 0.67 i_pae 0.79 con 3.77 i_con 4.52 plddt 0.39 ptm 0.50 i_ptm 0.13 rg 0.31\n", - "5 models [1] recycles 1 hard 0 soft 0.09 temp 1 loss 9.07 helix 0.88 pae 0.67 i_pae 0.78 con 3.83 i_con 4.66 plddt 0.41 ptm 0.50 i_ptm 0.14 rg 1.32\n", - "6 models [2] recycles 1 hard 0 soft 0.11 temp 1 loss 8.99 helix 0.85 pae 0.69 i_pae 0.80 con 3.83 i_con 4.56 plddt 0.40 ptm 0.49 i_ptm 0.13 rg 1.34\n", - "7 models [0] recycles 1 hard 0 soft 0.13 temp 1 loss 8.20 helix 0.85 pae 0.60 i_pae 0.71 con 3.61 i_con 4.38 plddt 0.45 ptm 0.53 i_ptm 0.19 rg 0.17\n", - "8 models [0] recycles 1 hard 0 soft 0.14 temp 1 loss 8.17 helix 0.80 pae 0.59 i_pae 0.73 con 3.50 i_con 4.42 plddt 0.49 ptm 0.52 i_ptm 0.17 rg 0.28\n", - "9 models [1] recycles 1 hard 0 soft 0.16 temp 1 loss 7.88 helix 0.86 pae 0.60 i_pae 0.77 con 3.16 i_con 4.46 plddt 0.52 ptm 0.51 i_ptm 0.15 rg 0.36\n", - "10 models [3] recycles 1 hard 0 soft 0.18 temp 1 loss 7.47 helix 0.83 pae 0.54 i_pae 0.74 con 2.93 i_con 4.48 plddt 0.57 ptm 0.51 i_ptm 0.15 rg -0.23\n", - "11 models [1] recycles 1 hard 0 soft 0.20 temp 1 loss 7.43 helix 0.86 pae 0.47 i_pae 0.64 con 2.71 i_con 4.41 plddt 0.66 ptm 0.55 i_ptm 0.23 rg 0.82\n", - "12 models [2] recycles 1 hard 0 soft 0.22 temp 1 loss 7.15 helix 1.06 pae 0.45 i_pae 0.64 con 2.33 i_con 4.50 plddt 0.73 ptm 0.53 i_ptm 0.20 rg 1.07\n", - "13 models [4] recycles 1 hard 0 soft 0.23 temp 1 loss 7.06 helix 1.02 pae 0.46 i_pae 0.67 con 2.42 i_con 4.55 plddt 0.69 ptm 0.52 i_ptm 0.18 rg 0.23\n", - "14 models [4] recycles 1 hard 0 soft 0.25 temp 1 loss 6.56 helix 1.17 pae 0.41 i_pae 0.66 con 2.12 i_con 4.45 plddt 0.78 ptm 0.54 i_ptm 0.22 rg 0.17\n", - "15 models [2] recycles 1 hard 0 soft 0.27 temp 1 loss 7.59 helix 0.94 pae 0.59 i_pae 0.77 con 3.01 i_con 4.51 plddt 0.54 ptm 0.50 i_ptm 0.14 rg -0.14\n", - "16 models [4] recycles 1 hard 0 soft 0.29 temp 1 loss 6.93 helix 1.05 pae 0.39 i_pae 0.58 con 2.45 i_con 4.45 plddt 0.74 ptm 0.57 i_ptm 0.27 rg 0.20\n", - "17 models [2] recycles 1 hard 0 soft 0.31 temp 1 loss 5.67 helix 1.36 pae 0.21 i_pae 0.31 con 1.85 i_con 3.99 plddt 0.89 ptm 0.72 i_ptm 0.59 rg 0.29\n", - "18 models [3] recycles 1 hard 0 soft 0.32 temp 1 loss 5.82 helix 1.33 pae 0.23 i_pae 0.30 con 1.92 i_con 4.02 plddt 0.85 ptm 0.73 i_ptm 0.60 rg 0.41\n", - "19 models [4] recycles 1 hard 0 soft 0.34 temp 1 loss 5.33 helix 1.47 pae 0.18 i_pae 0.24 con 1.89 i_con 3.68 plddt 0.88 ptm 0.80 i_ptm 0.74 rg 0.27\n", - "20 models [1] recycles 1 hard 0 soft 0.36 temp 1 loss 7.80 helix 0.90 pae 0.60 i_pae 0.77 con 3.07 i_con 4.55 plddt 0.55 ptm 0.50 i_ptm 0.14 rg 0.15\n", - "21 models [2] recycles 1 hard 0 soft 0.38 temp 1 loss 7.48 helix 0.97 pae 0.56 i_pae 0.76 con 2.91 i_con 4.61 plddt 0.60 ptm 0.50 i_ptm 0.14 rg -0.42\n", - "22 models [3] recycles 1 hard 0 soft 0.40 temp 1 loss 6.73 helix 1.15 pae 0.49 i_pae 0.71 con 2.32 i_con 4.43 plddt 0.69 ptm 0.52 i_ptm 0.17 rg -0.09\n", - "23 models [4] recycles 1 hard 0 soft 0.41 temp 1 loss 7.10 helix 1.12 pae 0.53 i_pae 0.76 con 2.58 i_con 4.54 plddt 0.65 ptm 0.50 i_ptm 0.14 rg -0.18\n", - "24 models [2] recycles 1 hard 0 soft 0.43 temp 1 loss 6.52 helix 1.22 pae 0.42 i_pae 0.62 con 2.15 i_con 4.49 plddt 0.75 ptm 0.54 i_ptm 0.21 rg -0.16\n", - "25 models [1] recycles 1 hard 0 soft 0.45 temp 1 loss 8.25 helix 0.95 pae 0.66 i_pae 0.77 con 3.71 i_con 4.53 plddt 0.42 ptm 0.51 i_ptm 0.14 rg -0.46\n", - "26 models [0] recycles 1 hard 0 soft 0.47 temp 1 loss 6.92 helix 1.16 pae 0.48 i_pae 0.67 con 2.50 i_con 4.46 plddt 0.65 ptm 0.53 i_ptm 0.19 rg -0.09\n", - "27 models [1] recycles 1 hard 0 soft 0.49 temp 1 loss 6.58 helix 1.30 pae 0.45 i_pae 0.69 con 1.96 i_con 4.48 plddt 0.78 ptm 0.51 i_ptm 0.16 rg 0.72\n", - "28 models [4] recycles 1 hard 0 soft 0.50 temp 1 loss 6.32 helix 1.31 pae 0.41 i_pae 0.68 con 1.86 i_con 4.52 plddt 0.81 ptm 0.52 i_ptm 0.17 rg 0.15\n", - "29 models [4] recycles 1 hard 0 soft 0.52 temp 1 loss 6.16 helix 1.33 pae 0.37 i_pae 0.62 con 1.83 i_con 4.44 plddt 0.82 ptm 0.54 i_ptm 0.20 rg 0.09\n", - "30 models [4] recycles 1 hard 0 soft 0.54 temp 1 loss 5.00 helix 1.48 pae 0.17 i_pae 0.23 con 1.70 i_con 3.58 plddt 0.90 ptm 0.82 i_ptm 0.77 rg 0.18\n", - "31 models [1] recycles 1 hard 0 soft 0.56 temp 1 loss 6.83 helix 1.11 pae 0.51 i_pae 0.72 con 2.42 i_con 4.53 plddt 0.66 ptm 0.52 i_ptm 0.16 rg -0.45\n", - "32 models [1] recycles 1 hard 0 soft 0.58 temp 1 loss 7.90 helix 0.96 pae 0.61 i_pae 0.75 con 3.41 i_con 4.51 plddt 0.49 ptm 0.51 i_ptm 0.15 rg -0.47\n", - "33 models [1] recycles 1 hard 0 soft 0.59 temp 1 loss 7.94 helix 1.07 pae 0.60 i_pae 0.73 con 3.39 i_con 4.48 plddt 0.50 ptm 0.52 i_ptm 0.16 rg -0.07\n", - "34 models [3] recycles 1 hard 0 soft 0.61 temp 1 loss 6.84 helix 1.11 pae 0.44 i_pae 0.65 con 2.41 i_con 4.45 plddt 0.71 ptm 0.53 i_ptm 0.20 rg 0.03\n", - "35 models [1] recycles 1 hard 0 soft 0.63 temp 1 loss 6.45 helix 1.24 pae 0.43 i_pae 0.66 con 2.12 i_con 4.40 plddt 0.77 ptm 0.52 i_ptm 0.19 rg 0.01\n", - "36 models [3] recycles 1 hard 0 soft 0.65 temp 1 loss 5.97 helix 1.24 pae 0.29 i_pae 0.45 con 1.84 i_con 4.24 plddt 0.85 ptm 0.62 i_ptm 0.37 rg 0.20\n", - "37 models [1] recycles 1 hard 0 soft 0.67 temp 1 loss 5.66 helix 1.28 pae 0.26 i_pae 0.40 con 1.77 i_con 4.04 plddt 0.86 ptm 0.67 i_ptm 0.47 rg 0.16\n", - "38 models [2] recycles 1 hard 0 soft 0.68 temp 1 loss 5.69 helix 1.26 pae 0.29 i_pae 0.44 con 1.76 i_con 4.08 plddt 0.86 ptm 0.63 i_ptm 0.38 rg 0.07\n", - "39 models [3] recycles 1 hard 0 soft 0.70 temp 1 loss 7.50 helix 0.91 pae 0.55 i_pae 0.75 con 3.02 i_con 4.50 plddt 0.55 ptm 0.51 i_ptm 0.14 rg -0.45\n", - "40 models [0] recycles 1 hard 0 soft 0.72 temp 1 loss 7.49 helix 0.94 pae 0.52 i_pae 0.65 con 3.22 i_con 4.27 plddt 0.53 ptm 0.56 i_ptm 0.25 rg -0.25\n", - "41 models [2] recycles 1 hard 0 soft 0.74 temp 1 loss 5.30 helix 1.40 pae 0.22 i_pae 0.31 con 1.78 i_con 3.75 plddt 0.87 ptm 0.71 i_ptm 0.58 rg 0.14\n", - "42 models [1] recycles 1 hard 0 soft 0.76 temp 1 loss 5.46 helix 1.30 pae 0.22 i_pae 0.30 con 1.74 i_con 3.89 plddt 0.87 ptm 0.73 i_ptm 0.60 rg 0.23\n", - "43 models [0] recycles 1 hard 0 soft 0.77 temp 1 loss 5.33 helix 1.38 pae 0.18 i_pae 0.25 con 1.72 i_con 3.85 plddt 0.89 ptm 0.77 i_ptm 0.68 rg 0.17\n", - "44 models [0] recycles 1 hard 0 soft 0.79 temp 1 loss 6.46 helix 1.11 pae 0.37 i_pae 0.59 con 1.98 i_con 4.31 plddt 0.80 ptm 0.56 i_ptm 0.25 rg 0.77\n", - "45 models [1] recycles 1 hard 0 soft 0.81 temp 1 loss 6.39 helix 1.12 pae 0.39 i_pae 0.61 con 2.02 i_con 4.42 plddt 0.78 ptm 0.54 i_ptm 0.21 rg 0.03\n", - "46 models [2] recycles 1 hard 0 soft 0.83 temp 1 loss 4.97 helix 1.31 pae 0.18 i_pae 0.25 con 1.74 i_con 3.46 plddt 0.90 ptm 0.80 i_ptm 0.72 rg 0.16\n", - "47 models [1] recycles 1 hard 0 soft 0.85 temp 1 loss 5.28 helix 1.27 pae 0.19 i_pae 0.26 con 1.81 i_con 3.68 plddt 0.87 ptm 0.77 i_ptm 0.65 rg 0.14\n", - "48 models [4] recycles 1 hard 0 soft 0.86 temp 1 loss 9.56 helix 0.76 pae 0.73 i_pae 0.86 con 3.78 i_con 4.76 plddt 0.44 ptm 0.48 i_ptm 0.09 rg 2.58\n", - "49 models [4] recycles 1 hard 0 soft 0.88 temp 1 loss 5.74 helix 1.10 pae 0.29 i_pae 0.42 con 1.99 i_con 3.85 plddt 0.82 ptm 0.65 i_ptm 0.45 rg 0.08\n", - "50 models [0] recycles 1 hard 0 soft 0.90 temp 1 loss 7.52 helix 0.80 pae 0.50 i_pae 0.69 con 3.03 i_con 4.44 plddt 0.59 ptm 0.53 i_ptm 0.19 rg -0.20\n", - "Initial trajectory pLDDT good, continuing: 0.9\n", - "Stage 1: Additional Logits Optimisation\n", - "51 models [1] recycles 1 hard 0 soft 0.04 temp 1 loss 4.97 helix 1.39 pae 0.16 i_pae 0.22 con 1.69 i_con 3.57 plddt 0.90 ptm 0.82 i_ptm 0.75 rg 0.08\n", - "52 models [2] recycles 1 hard 0 soft 0.08 temp 1 loss 9.45 helix 1.12 pae 0.79 i_pae 0.86 con 4.18 i_con 4.57 plddt 0.32 ptm 0.47 i_ptm 0.09 rg 1.74\n", - "53 models [1] recycles 1 hard 0 soft 0.12 temp 1 loss 5.18 helix 1.24 pae 0.18 i_pae 0.23 con 1.89 i_con 3.49 plddt 0.87 ptm 0.80 i_ptm 0.73 rg 0.16\n", - "54 models [2] recycles 1 hard 0 soft 0.16 temp 1 loss 6.21 helix 1.27 pae 0.35 i_pae 0.53 con 2.01 i_con 4.29 plddt 0.80 ptm 0.58 i_ptm 0.32 rg 0.13\n", - "55 models [3] recycles 1 hard 0 soft 0.20 temp 1 loss 9.42 helix 1.02 pae 0.74 i_pae 0.78 con 4.19 i_con 4.31 plddt 0.31 ptm 0.51 i_ptm 0.13 rg 2.45\n", - "56 models [3] recycles 1 hard 0 soft 0.24 temp 1 loss 6.74 helix 1.14 pae 0.42 i_pae 0.64 con 2.30 i_con 4.48 plddt 0.74 ptm 0.53 i_ptm 0.18 rg 0.04\n", - "57 models [0] recycles 1 hard 0 soft 0.28 temp 1 loss 6.17 helix 1.29 pae 0.33 i_pae 0.43 con 2.26 i_con 3.98 plddt 0.75 ptm 0.65 i_ptm 0.46 rg 0.33\n", - "58 models [1] recycles 1 hard 0 soft 0.32 temp 1 loss 5.85 helix 1.30 pae 0.28 i_pae 0.35 con 2.05 i_con 3.87 plddt 0.79 ptm 0.69 i_ptm 0.55 rg 0.46\n", - "59 models [3] recycles 1 hard 0 soft 0.36 temp 1 loss 6.46 helix 1.10 pae 0.38 i_pae 0.58 con 2.14 i_con 4.34 plddt 0.77 ptm 0.56 i_ptm 0.24 rg 0.11\n", - "60 models [2] recycles 1 hard 0 soft 0.40 temp 1 loss 6.50 helix 1.16 pae 0.40 i_pae 0.60 con 2.10 i_con 4.44 plddt 0.78 ptm 0.54 i_ptm 0.25 rg 0.11\n", - "61 models [3] recycles 1 hard 0 soft 0.44 temp 1 loss 6.30 helix 1.19 pae 0.37 i_pae 0.56 con 2.05 i_con 4.29 plddt 0.78 ptm 0.57 i_ptm 0.27 rg 0.20\n", - "62 models [3] recycles 1 hard 0 soft 0.48 temp 1 loss 6.00 helix 1.33 pae 0.36 i_pae 0.53 con 1.91 i_con 4.16 plddt 0.79 ptm 0.57 i_ptm 0.28 rg 0.24\n", - "63 models [4] recycles 1 hard 0 soft 0.52 temp 1 loss 6.19 helix 1.17 pae 0.38 i_pae 0.56 con 2.02 i_con 4.20 plddt 0.77 ptm 0.57 i_ptm 0.28 rg 0.16\n", - "64 models [0] recycles 1 hard 0 soft 0.56 temp 1 loss 5.93 helix 1.21 pae 0.30 i_pae 0.42 con 1.95 i_con 4.09 plddt 0.81 ptm 0.64 i_ptm 0.44 rg 0.15\n", - "65 models [1] recycles 1 hard 0 soft 0.60 temp 1 loss 5.38 helix 1.24 pae 0.25 i_pae 0.35 con 1.83 i_con 3.72 plddt 0.85 ptm 0.71 i_ptm 0.55 rg 0.12\n", - "66 models [3] recycles 1 hard 0 soft 0.64 temp 1 loss 5.56 helix 1.35 pae 0.27 i_pae 0.42 con 1.73 i_con 4.00 plddt 0.86 ptm 0.65 i_ptm 0.42 rg 0.14\n", - "67 models [0] recycles 1 hard 0 soft 0.68 temp 1 loss 5.85 helix 1.30 pae 0.32 i_pae 0.52 con 1.87 i_con 4.15 plddt 0.82 ptm 0.59 i_ptm 0.32 rg -0.03\n", - "68 models [1] recycles 1 hard 0 soft 0.72 temp 1 loss 5.71 helix 1.35 pae 0.32 i_pae 0.54 con 1.68 i_con 4.16 plddt 0.85 ptm 0.58 i_ptm 0.26 rg 0.13\n", - "69 models [2] recycles 1 hard 0 soft 0.76 temp 1 loss 5.39 helix 1.26 pae 0.22 i_pae 0.31 con 1.90 i_con 3.66 plddt 0.86 ptm 0.72 i_ptm 0.61 rg 0.18\n", - "70 models [1] recycles 1 hard 0 soft 0.80 temp 1 loss 5.77 helix 1.30 pae 0.32 i_pae 0.48 con 1.86 i_con 4.01 plddt 0.81 ptm 0.61 i_ptm 0.35 rg 0.19\n", - "71 models [3] recycles 1 hard 0 soft 0.84 temp 1 loss 5.90 helix 1.19 pae 0.29 i_pae 0.44 con 1.98 i_con 4.01 plddt 0.82 ptm 0.63 i_ptm 0.38 rg 0.21\n", - "72 models [3] recycles 1 hard 0 soft 0.88 temp 1 loss 5.89 helix 1.22 pae 0.31 i_pae 0.49 con 1.88 i_con 4.12 plddt 0.82 ptm 0.60 i_ptm 0.32 rg 0.12\n", - "73 models [0] recycles 1 hard 0 soft 0.92 temp 1 loss 5.56 helix 1.33 pae 0.27 i_pae 0.43 con 1.77 i_con 3.95 plddt 0.84 ptm 0.63 i_ptm 0.41 rg 0.15\n", - "74 models [0] recycles 1 hard 0 soft 0.96 temp 1 loss 7.63 helix 0.86 pae 0.52 i_pae 0.72 con 3.04 i_con 4.48 plddt 0.57 ptm 0.51 i_ptm 0.17 rg 0.01\n", - "75 models [0] recycles 1 hard 0 soft 1 temp 1 loss 6.18 helix 1.09 pae 0.34 i_pae 0.48 con 2.26 i_con 3.95 plddt 0.75 ptm 0.61 i_ptm 0.37 rg 0.21\n", - "Optimised logit trajectory pLDDT: 0.9\n", - "Stage 2: Softmax Optimisation\n", - "76 models [3] recycles 1 hard 0 soft 1 temp 0.96 loss 6.13 helix 1.12 pae 0.34 i_pae 0.52 con 2.02 i_con 4.16 plddt 0.79 ptm 0.58 i_ptm 0.29 rg 0.14\n", - "77 models [3] recycles 1 hard 0 soft 1 temp 0.91 loss 5.60 helix 1.23 pae 0.27 i_pae 0.40 con 1.86 i_con 3.87 plddt 0.83 ptm 0.65 i_ptm 0.43 rg 0.15\n", - "78 models [0] recycles 1 hard 0 soft 1 temp 0.87 loss 5.08 helix 1.31 pae 0.19 i_pae 0.26 con 1.82 i_con 3.48 plddt 0.87 ptm 0.77 i_ptm 0.66 rg 0.16\n", - "79 models [0] recycles 1 hard 0 soft 1 temp 0.83 loss 5.71 helix 1.14 pae 0.25 i_pae 0.33 con 2.14 i_con 3.67 plddt 0.79 ptm 0.71 i_ptm 0.53 rg 0.17\n", - "80 models [0] recycles 1 hard 0 soft 1 temp 0.79 loss 5.48 helix 1.19 pae 0.25 i_pae 0.35 con 1.82 i_con 3.77 plddt 0.84 ptm 0.68 i_ptm 0.48 rg 0.22\n", - "81 models [0] recycles 1 hard 0 soft 1 temp 0.75 loss 5.43 helix 1.21 pae 0.22 i_pae 0.31 con 1.91 i_con 3.68 plddt 0.85 ptm 0.72 i_ptm 0.59 rg 0.18\n", - "82 models [0] recycles 1 hard 0 soft 1 temp 0.72 loss 4.65 helix 1.47 pae 0.15 i_pae 0.20 con 1.61 i_con 3.32 plddt 0.91 ptm 0.84 i_ptm 0.79 rg 0.18\n", - "83 models [2] recycles 1 hard 0 soft 1 temp 0.68 loss 5.03 helix 1.39 pae 0.18 i_pae 0.25 con 1.69 i_con 3.55 plddt 0.90 ptm 0.78 i_ptm 0.69 rg 0.29\n", - "84 models [0] recycles 1 hard 0 soft 1 temp 0.64 loss 4.83 helix 1.43 pae 0.17 i_pae 0.24 con 1.66 i_con 3.41 plddt 0.89 ptm 0.79 i_ptm 0.70 rg 0.24\n", - "85 models [3] recycles 1 hard 0 soft 1 temp 0.61 loss 5.73 helix 1.17 pae 0.26 i_pae 0.38 con 1.87 i_con 3.96 plddt 0.85 ptm 0.67 i_ptm 0.47 rg 0.24\n", - "86 models [2] recycles 1 hard 0 soft 1 temp 0.58 loss 5.48 helix 1.28 pae 0.24 i_pae 0.36 con 1.79 i_con 3.84 plddt 0.87 ptm 0.68 i_ptm 0.49 rg 0.21\n", - "87 models [0] recycles 1 hard 0 soft 1 temp 0.54 loss 5.24 helix 1.33 pae 0.21 i_pae 0.31 con 1.77 i_con 3.68 plddt 0.87 ptm 0.72 i_ptm 0.55 rg 0.14\n", - "88 models [0] recycles 1 hard 0 soft 1 temp 0.51 loss 4.82 helix 1.34 pae 0.18 i_pae 0.26 con 1.64 i_con 3.41 plddt 0.89 ptm 0.77 i_ptm 0.66 rg 0.14\n", - "89 models [4] recycles 1 hard 0 soft 1 temp 0.48 loss 5.20 helix 1.21 pae 0.20 i_pae 0.28 con 1.78 i_con 3.57 plddt 0.87 ptm 0.75 i_ptm 0.62 rg 0.25\n", - "90 models [4] recycles 1 hard 0 soft 1 temp 0.45 loss 5.32 helix 1.24 pae 0.20 i_pae 0.26 con 2.09 i_con 3.41 plddt 0.84 ptm 0.78 i_ptm 0.69 rg 0.18\n", - "91 models [0] recycles 1 hard 0 soft 1 temp 0.42 loss 4.67 helix 1.38 pae 0.17 i_pae 0.21 con 1.79 i_con 3.14 plddt 0.88 ptm 0.83 i_ptm 0.77 rg 0.16\n", - "92 models [1] recycles 1 hard 0 soft 1 temp 0.39 loss 4.84 helix 1.47 pae 0.16 i_pae 0.22 con 1.70 i_con 3.42 plddt 0.89 ptm 0.80 i_ptm 0.72 rg 0.17\n", - "93 models [3] recycles 1 hard 0 soft 1 temp 0.37 loss 4.73 helix 1.47 pae 0.17 i_pae 0.22 con 1.76 i_con 3.26 plddt 0.89 ptm 0.82 i_ptm 0.76 rg 0.13\n", - "94 models [2] recycles 1 hard 0 soft 1 temp 0.34 loss 4.57 helix 1.58 pae 0.15 i_pae 0.21 con 1.61 i_con 3.28 plddt 0.92 ptm 0.82 i_ptm 0.77 rg 0.17\n", - "95 models [1] recycles 1 hard 0 soft 1 temp 0.32 loss 4.57 helix 1.58 pae 0.15 i_pae 0.20 con 1.61 i_con 3.29 plddt 0.91 ptm 0.82 i_ptm 0.76 rg 0.16\n", - "96 models [0] recycles 1 hard 0 soft 1 temp 0.29 loss 4.49 helix 1.56 pae 0.16 i_pae 0.22 con 1.53 i_con 3.29 plddt 0.91 ptm 0.81 i_ptm 0.73 rg 0.10\n", - "97 models [1] recycles 1 hard 0 soft 1 temp 0.27 loss 4.53 helix 1.66 pae 0.16 i_pae 0.22 con 1.49 i_con 3.40 plddt 0.91 ptm 0.80 i_ptm 0.71 rg 0.10\n", - "98 models [1] recycles 1 hard 0 soft 1 temp 0.25 loss 4.48 helix 1.62 pae 0.14 i_pae 0.19 con 1.61 i_con 3.23 plddt 0.91 ptm 0.84 i_ptm 0.79 rg 0.11\n", - "99 models [4] recycles 1 hard 0 soft 1 temp 0.23 loss 5.03 helix 1.34 pae 0.19 i_pae 0.26 con 1.76 i_con 3.52 plddt 0.87 ptm 0.77 i_ptm 0.65 rg 0.07\n", - "100 models [2] recycles 1 hard 0 soft 1 temp 0.21 loss 4.52 helix 1.61 pae 0.14 i_pae 0.19 con 1.59 i_con 3.27 plddt 0.92 ptm 0.83 i_ptm 0.78 rg 0.17\n", - "101 models [1] recycles 1 hard 0 soft 1 temp 0.19 loss 4.29 helix 1.62 pae 0.14 i_pae 0.19 con 1.50 i_con 3.15 plddt 0.92 ptm 0.85 i_ptm 0.81 rg 0.11\n", - "102 models [1] recycles 1 hard 0 soft 1 temp 0.17 loss 4.36 helix 1.63 pae 0.14 i_pae 0.19 con 1.51 i_con 3.23 plddt 0.92 ptm 0.85 i_ptm 0.80 rg 0.09\n", - "103 models [1] recycles 1 hard 0 soft 1 temp 0.15 loss 4.42 helix 1.66 pae 0.15 i_pae 0.20 con 1.59 i_con 3.21 plddt 0.91 ptm 0.83 i_ptm 0.78 rg 0.04\n", - "104 models [2] recycles 1 hard 0 soft 1 temp 0.14 loss 4.43 helix 1.52 pae 0.15 i_pae 0.20 con 1.70 i_con 3.06 plddt 0.91 ptm 0.85 i_ptm 0.82 rg 0.09\n", - "105 models [3] recycles 1 hard 0 soft 1 temp 0.12 loss 4.36 helix 1.60 pae 0.15 i_pae 0.19 con 1.69 i_con 3.02 plddt 0.91 ptm 0.86 i_ptm 0.82 rg 0.09\n", - "106 models [2] recycles 1 hard 0 soft 1 temp 0.11 loss 4.71 helix 1.55 pae 0.17 i_pae 0.25 con 1.68 i_con 3.36 plddt 0.90 ptm 0.78 i_ptm 0.68 rg 0.05\n", - "107 models [0] recycles 1 hard 0 soft 1 temp 0.09 loss 4.92 helix 1.35 pae 0.19 i_pae 0.24 con 1.75 i_con 3.42 plddt 0.87 ptm 0.78 i_ptm 0.68 rg 0.09\n", - "108 models [4] recycles 1 hard 0 soft 1 temp 0.08 loss 6.06 helix 1.27 pae 0.34 i_pae 0.53 con 2.12 i_con 4.10 plddt 0.78 ptm 0.58 i_ptm 0.29 rg -0.08\n", - "109 models [1] recycles 1 hard 0 soft 1 temp 0.07 loss 4.94 helix 1.57 pae 0.20 i_pae 0.29 con 1.73 i_con 3.53 plddt 0.86 ptm 0.72 i_ptm 0.56 rg 0.02\n", - "110 models [2] recycles 1 hard 0 soft 1 temp 0.06 loss 6.06 helix 1.23 pae 0.37 i_pae 0.59 con 1.98 i_con 4.20 plddt 0.80 ptm 0.56 i_ptm 0.25 rg -0.06\n", - "111 models [0] recycles 1 hard 0 soft 1 temp 0.05 loss 5.57 helix 1.26 pae 0.29 i_pae 0.43 con 2.02 i_con 3.73 plddt 0.80 ptm 0.64 i_ptm 0.41 rg -0.04\n", - "112 models [1] recycles 1 hard 0 soft 1 temp 0.04 loss 6.63 helix 1.05 pae 0.37 i_pae 0.49 con 2.75 i_con 3.90 plddt 0.68 ptm 0.63 i_ptm 0.39 rg 0.12\n", - "113 models [3] recycles 1 hard 0 soft 1 temp 0.03 loss 4.52 helix 1.51 pae 0.17 i_pae 0.23 con 1.72 i_con 3.12 plddt 0.89 ptm 0.82 i_ptm 0.75 rg 0.07\n", - "114 models [3] recycles 1 hard 0 soft 1 temp 0.03 loss 4.41 helix 1.63 pae 0.16 i_pae 0.21 con 1.64 i_con 3.13 plddt 0.91 ptm 0.83 i_ptm 0.78 rg 0.09\n", - "115 models [0] recycles 1 hard 0 soft 1 temp 0.02 loss 4.38 helix 1.55 pae 0.14 i_pae 0.18 con 1.66 i_con 3.07 plddt 0.91 ptm 0.86 i_ptm 0.81 rg 0.06\n", - "116 models [1] recycles 1 hard 0 soft 1 temp 0.02 loss 8.16 helix 0.95 pae 0.60 i_pae 0.70 con 3.59 i_con 4.35 plddt 0.48 ptm 0.54 i_ptm 0.20 rg 0.32\n", - "117 models [3] recycles 1 hard 0 soft 1 temp 0.01 loss 4.65 helix 1.50 pae 0.17 i_pae 0.23 con 1.70 i_con 3.26 plddt 0.89 ptm 0.81 i_ptm 0.74 rg 0.09\n", - "118 models [0] recycles 1 hard 0 soft 1 temp 0.01 loss 4.66 helix 1.48 pae 0.18 i_pae 0.24 con 1.70 i_con 3.26 plddt 0.88 ptm 0.80 i_ptm 0.71 rg 0.09\n", - "119 models [3] recycles 1 hard 0 soft 1 temp 0.01 loss 4.64 helix 1.48 pae 0.17 i_pae 0.21 con 1.73 i_con 3.22 plddt 0.89 ptm 0.84 i_ptm 0.79 rg 0.10\n", - "120 models [4] recycles 1 hard 0 soft 1 temp 0.01 loss 5.30 helix 1.24 pae 0.25 i_pae 0.36 con 1.94 i_con 3.57 plddt 0.82 ptm 0.69 i_ptm 0.51 rg -0.04\n", - "Softmax trajectory pLDDT good, continuing: 0.92\n", - "Stage 3: One-hot Optimisation\n", - "121 models [3] recycles 1 hard 1 soft 1 temp 0.01 loss 4.43 helix 1.61 pae 0.15 i_pae 0.19 con 1.65 i_con 3.11 plddt 0.90 ptm 0.85 i_ptm 0.80 rg 0.15\n", - "122 models [3] recycles 1 hard 1 soft 1 temp 0.01 loss 4.33 helix 1.64 pae 0.14 i_pae 0.19 con 1.61 i_con 3.08 plddt 0.91 ptm 0.86 i_ptm 0.83 rg 0.13\n", - "123 models [4] recycles 1 hard 1 soft 1 temp 0.01 loss 4.73 helix 1.47 pae 0.18 i_pae 0.25 con 1.82 i_con 3.20 plddt 0.85 ptm 0.79 i_ptm 0.72 rg 0.07\n", - "124 models [0] recycles 1 hard 1 soft 1 temp 0.01 loss 4.22 helix 1.67 pae 0.14 i_pae 0.18 con 1.55 i_con 3.03 plddt 0.91 ptm 0.88 i_ptm 0.84 rg 0.15\n", - "125 models [2] recycles 1 hard 1 soft 1 temp 0.01 loss 4.80 helix 1.47 pae 0.19 i_pae 0.27 con 1.73 i_con 3.34 plddt 0.87 ptm 0.76 i_ptm 0.65 rg 0.11\n", - "One-hot trajectory pLDDT good, continuing: 0.91\n", - "Stage 4: PSSM Semigreedy Optimisation\n", - "Running semigreedy optimization...\n", - "126 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.69 helix 1.47 pae 0.18 i_pae 0.23 con 1.70 i_con 3.26 plddt 0.88 ptm 0.80 i_ptm 0.73 rg 0.16\n", - "127 models [4] recycles 1 hard 1 soft 0 temp 1 loss 4.52 helix 1.50 pae 0.16 i_pae 0.21 con 1.72 i_con 3.09 plddt 0.88 ptm 0.83 i_ptm 0.79 rg 0.15\n", - "128 models [1] recycles 1 hard 1 soft 0 temp 1 loss 4.38 helix 1.62 pae 0.15 i_pae 0.20 con 1.55 i_con 3.17 plddt 0.90 ptm 0.84 i_ptm 0.78 rg 0.15\n", - "129 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.99 helix 1.41 pae 0.21 i_pae 0.30 con 1.75 i_con 3.47 plddt 0.86 ptm 0.73 i_ptm 0.58 rg 0.13\n", - "130 models [3] recycles 1 hard 1 soft 0 temp 1 loss 4.39 helix 1.62 pae 0.14 i_pae 0.19 con 1.58 i_con 3.15 plddt 0.91 ptm 0.85 i_ptm 0.81 rg 0.18\n", - "131 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.48 helix 1.49 pae 0.16 i_pae 0.20 con 1.63 i_con 3.16 plddt 0.89 ptm 0.84 i_ptm 0.78 rg 0.14\n", - "132 models [4] recycles 1 hard 1 soft 0 temp 1 loss 5.17 helix 1.35 pae 0.23 i_pae 0.32 con 1.91 i_con 3.45 plddt 0.81 ptm 0.71 i_ptm 0.56 rg 0.13\n", - "133 models [3] recycles 1 hard 1 soft 0 temp 1 loss 4.36 helix 1.64 pae 0.15 i_pae 0.19 con 1.63 i_con 3.08 plddt 0.91 ptm 0.85 i_ptm 0.81 rg 0.15\n", - "134 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.72 helix 1.46 pae 0.19 i_pae 0.26 con 1.73 i_con 3.25 plddt 0.87 ptm 0.76 i_ptm 0.66 rg 0.15\n", - "135 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.89 helix 1.42 pae 0.21 i_pae 0.28 con 1.77 i_con 3.32 plddt 0.86 ptm 0.74 i_ptm 0.63 rg 0.25\n", - "136 models [1] recycles 1 hard 1 soft 0 temp 1 loss 4.47 helix 1.56 pae 0.16 i_pae 0.21 con 1.60 i_con 3.18 plddt 0.89 ptm 0.82 i_ptm 0.75 rg 0.17\n", - "137 models [2] recycles 1 hard 1 soft 0 temp 1 loss 5.38 helix 1.34 pae 0.27 i_pae 0.39 con 1.85 i_con 3.65 plddt 0.82 ptm 0.66 i_ptm 0.45 rg 0.28\n", - "138 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.80 helix 1.44 pae 0.19 i_pae 0.26 con 1.75 i_con 3.27 plddt 0.87 ptm 0.77 i_ptm 0.67 rg 0.25\n", - "139 models [3] recycles 1 hard 1 soft 0 temp 1 loss 4.45 helix 1.56 pae 0.15 i_pae 0.20 con 1.65 i_con 3.10 plddt 0.90 ptm 0.84 i_ptm 0.80 rg 0.21\n", - "140 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.50 helix 1.50 pae 0.16 i_pae 0.21 con 1.63 i_con 3.16 plddt 0.89 ptm 0.83 i_ptm 0.77 rg 0.17\n", - "Trajectory successful, final pLDDT: 0.91\n", - "Starting trajectory took: 0 hours, 6 minutes, 7 seconds\n", - "\n", - "Fixing interface residues: B1,B2,B3,B4,B5,B8,B9,B10,B12,B13,B16,B17,B20,B21,B24,B100,B101,B103,B104,B105,B107,B108,B111,B115\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l118_s893196_mpnn1, skipping interface scoring\n", - "No accepted MPNN designs found for this trajectory.\n", - "Design and validation of trajectory PDL1_l118_s893196 took: 0 hours, 1 minutes, 26 seconds\n", - "Starting trajectory: PDL1_l145_s718363\n", - "Stage 1: Test Logits\n", - "1 models [1] recycles 1 hard 0 soft 0.02 temp 1 loss 12.41 helix 1.60 pae 0.87 i_pae 0.91 con 4.60 i_con 4.90 plddt 0.28 ptm 0.43 i_ptm 0.07 rg 9.41\n", - "2 models [0] recycles 1 hard 0 soft 0.04 temp 1 loss 12.76 helix 0.93 pae 0.79 i_pae 0.87 con 4.42 i_con 4.96 plddt 0.44 ptm 0.44 i_ptm 0.10 rg 10.53\n", - "3 models [2] recycles 1 hard 0 soft 0.05 temp 1 loss 9.95 helix 0.73 pae 0.69 i_pae 0.83 con 3.90 i_con 4.76 plddt 0.46 ptm 0.45 i_ptm 0.11 rg 3.52\n", - "4 models [0] recycles 1 hard 0 soft 0.07 temp 1 loss 9.80 helix 0.68 pae 0.65 i_pae 0.83 con 3.64 i_con 4.91 plddt 0.50 ptm 0.46 i_ptm 0.12 rg 3.37\n", - "5 models [0] recycles 1 hard 0 soft 0.09 temp 1 loss 8.93 helix 0.67 pae 0.56 i_pae 0.76 con 3.04 i_con 4.63 plddt 0.59 ptm 0.48 i_ptm 0.16 rg 3.60\n", - "6 models [4] recycles 1 hard 0 soft 0.11 temp 1 loss 8.59 helix 0.60 pae 0.51 i_pae 0.70 con 2.88 i_con 4.43 plddt 0.61 ptm 0.51 i_ptm 0.21 rg 3.70\n", - "7 models [2] recycles 1 hard 0 soft 0.13 temp 1 loss 8.23 helix 0.57 pae 0.47 i_pae 0.65 con 2.78 i_con 4.34 plddt 0.65 ptm 0.53 i_ptm 0.27 rg 3.20\n", - "8 models [1] recycles 1 hard 0 soft 0.14 temp 1 loss 7.62 helix 0.63 pae 0.38 i_pae 0.48 con 2.74 i_con 3.87 plddt 0.69 ptm 0.63 i_ptm 0.44 rg 3.13\n", - "9 models [0] recycles 1 hard 0 soft 0.16 temp 1 loss 6.22 helix 0.71 pae 0.25 i_pae 0.29 con 2.27 i_con 3.07 plddt 0.79 ptm 0.77 i_ptm 0.71 rg 3.11\n", - "10 models [4] recycles 1 hard 0 soft 0.18 temp 1 loss 9.43 helix 0.54 pae 0.62 i_pae 0.75 con 3.64 i_con 4.58 plddt 0.49 ptm 0.48 i_ptm 0.16 rg 3.20\n", - "11 models [2] recycles 1 hard 0 soft 0.20 temp 1 loss 7.30 helix 0.65 pae 0.40 i_pae 0.51 con 2.60 i_con 3.73 plddt 0.68 ptm 0.62 i_ptm 0.47 rg 3.01\n", - "12 models [3] recycles 1 hard 0 soft 0.22 temp 1 loss 6.33 helix 0.68 pae 0.29 i_pae 0.32 con 2.38 i_con 3.03 plddt 0.76 ptm 0.77 i_ptm 0.73 rg 3.11\n", - "13 models [0] recycles 1 hard 0 soft 0.23 temp 1 loss 5.99 helix 0.69 pae 0.24 i_pae 0.28 con 2.12 i_con 2.95 plddt 0.81 ptm 0.80 i_ptm 0.77 rg 3.22\n", - "14 models [3] recycles 1 hard 0 soft 0.25 temp 1 loss 5.65 helix 0.66 pae 0.23 i_pae 0.26 con 1.97 i_con 2.79 plddt 0.84 ptm 0.83 i_ptm 0.81 rg 3.15\n", - "15 models [1] recycles 1 hard 0 soft 0.27 temp 1 loss 6.19 helix 0.70 pae 0.27 i_pae 0.39 con 1.86 i_con 3.42 plddt 0.83 ptm 0.74 i_ptm 0.56 rg 3.11\n", - "16 models [3] recycles 1 hard 0 soft 0.29 temp 1 loss 6.58 helix 0.67 pae 0.29 i_pae 0.37 con 2.25 i_con 3.32 plddt 0.78 ptm 0.70 i_ptm 0.57 rg 3.38\n", - "17 models [4] recycles 1 hard 0 soft 0.31 temp 1 loss 6.37 helix 0.64 pae 0.26 i_pae 0.32 con 2.20 i_con 3.14 plddt 0.80 ptm 0.75 i_ptm 0.67 rg 3.47\n", - "18 models [4] recycles 1 hard 0 soft 0.32 temp 1 loss 6.27 helix 0.63 pae 0.25 i_pae 0.34 con 1.97 i_con 3.29 plddt 0.83 ptm 0.75 i_ptm 0.62 rg 3.42\n", - "19 models [2] recycles 1 hard 0 soft 0.34 temp 1 loss 9.56 helix 0.58 pae 0.66 i_pae 0.84 con 3.53 i_con 4.88 plddt 0.49 ptm 0.43 i_ptm 0.10 rg 2.90\n", - "20 models [3] recycles 1 hard 0 soft 0.36 temp 1 loss 6.27 helix 0.69 pae 0.25 i_pae 0.30 con 2.32 i_con 2.98 plddt 0.79 ptm 0.78 i_ptm 0.73 rg 3.37\n", - "21 models [3] recycles 1 hard 0 soft 0.38 temp 1 loss 6.87 helix 0.71 pae 0.30 i_pae 0.35 con 2.61 i_con 3.25 plddt 0.72 ptm 0.72 i_ptm 0.62 rg 3.41\n", - "22 models [4] recycles 1 hard 0 soft 0.40 temp 1 loss 6.14 helix 0.70 pae 0.24 i_pae 0.29 con 2.18 i_con 3.00 plddt 0.81 ptm 0.79 i_ptm 0.72 rg 3.39\n", - "23 models [4] recycles 1 hard 0 soft 0.41 temp 1 loss 5.96 helix 0.67 pae 0.22 i_pae 0.26 con 2.05 i_con 2.95 plddt 0.84 ptm 0.79 i_ptm 0.74 rg 3.39\n", - "24 models [1] recycles 1 hard 0 soft 0.43 temp 1 loss 5.85 helix 0.77 pae 0.21 i_pae 0.28 con 1.88 i_con 3.06 plddt 0.86 ptm 0.80 i_ptm 0.71 rg 3.35\n", - "25 models [1] recycles 1 hard 0 soft 0.45 temp 1 loss 5.64 helix 0.80 pae 0.20 i_pae 0.25 con 1.79 i_con 2.97 plddt 0.87 ptm 0.83 i_ptm 0.77 rg 3.31\n", - "26 models [3] recycles 1 hard 0 soft 0.47 temp 1 loss 6.03 helix 0.74 pae 0.21 i_pae 0.28 con 1.98 i_con 3.13 plddt 0.85 ptm 0.79 i_ptm 0.70 rg 3.33\n", - "27 models [4] recycles 1 hard 0 soft 0.49 temp 1 loss 5.96 helix 0.74 pae 0.21 i_pae 0.29 con 1.89 i_con 3.13 plddt 0.86 ptm 0.80 i_ptm 0.71 rg 3.41\n", - "28 models [2] recycles 1 hard 0 soft 0.50 temp 1 loss 5.84 helix 0.75 pae 0.22 i_pae 0.29 con 1.90 i_con 3.01 plddt 0.86 ptm 0.80 i_ptm 0.72 rg 3.36\n", - "29 models [1] recycles 1 hard 0 soft 0.52 temp 1 loss 5.31 helix 0.76 pae 0.19 i_pae 0.22 con 1.88 i_con 2.54 plddt 0.87 ptm 0.86 i_ptm 0.83 rg 3.32\n", - "30 models [0] recycles 1 hard 0 soft 0.54 temp 1 loss 5.25 helix 0.80 pae 0.18 i_pae 0.23 con 1.77 i_con 2.61 plddt 0.89 ptm 0.85 i_ptm 0.80 rg 3.32\n", - "31 models [1] recycles 1 hard 0 soft 0.56 temp 1 loss 5.16 helix 0.89 pae 0.17 i_pae 0.21 con 1.74 i_con 2.53 plddt 0.90 ptm 0.86 i_ptm 0.83 rg 3.50\n", - "32 models [4] recycles 1 hard 0 soft 0.58 temp 1 loss 5.35 helix 0.79 pae 0.18 i_pae 0.23 con 1.81 i_con 2.66 plddt 0.89 ptm 0.84 i_ptm 0.80 rg 3.32\n", - "33 models [3] recycles 1 hard 0 soft 0.59 temp 1 loss 7.46 helix 0.73 pae 0.39 i_pae 0.65 con 2.13 i_con 4.37 plddt 0.77 ptm 0.54 i_ptm 0.20 rg 2.99\n", - "34 models [2] recycles 1 hard 0 soft 0.61 temp 1 loss 5.74 helix 0.74 pae 0.20 i_pae 0.26 con 2.00 i_con 2.79 plddt 0.87 ptm 0.80 i_ptm 0.74 rg 3.47\n", - "35 models [4] recycles 1 hard 0 soft 0.63 temp 1 loss 5.14 helix 0.87 pae 0.17 i_pae 0.21 con 1.75 i_con 2.53 plddt 0.90 ptm 0.84 i_ptm 0.80 rg 3.38\n", - "36 models [1] recycles 1 hard 0 soft 0.65 temp 1 loss 4.72 helix 0.99 pae 0.15 i_pae 0.18 con 1.55 i_con 2.36 plddt 0.92 ptm 0.88 i_ptm 0.85 rg 3.37\n", - "37 models [3] recycles 1 hard 0 soft 0.67 temp 1 loss 5.21 helix 0.96 pae 0.18 i_pae 0.22 con 1.80 i_con 2.58 plddt 0.88 ptm 0.84 i_ptm 0.79 rg 3.36\n", - "38 models [2] recycles 1 hard 0 soft 0.68 temp 1 loss 5.50 helix 0.99 pae 0.19 i_pae 0.28 con 1.69 i_con 2.98 plddt 0.90 ptm 0.79 i_ptm 0.67 rg 3.33\n", - "39 models [4] recycles 1 hard 0 soft 0.70 temp 1 loss 5.25 helix 0.88 pae 0.18 i_pae 0.22 con 1.87 i_con 2.54 plddt 0.88 ptm 0.85 i_ptm 0.80 rg 3.34\n", - "40 models [1] recycles 1 hard 0 soft 0.72 temp 1 loss 9.47 helix 0.68 pae 0.64 i_pae 0.81 con 3.52 i_con 4.81 plddt 0.52 ptm 0.46 i_ptm 0.13 rg 3.03\n", - "41 models [0] recycles 1 hard 0 soft 0.74 temp 1 loss 5.23 helix 0.77 pae 0.18 i_pae 0.21 con 1.87 i_con 2.53 plddt 0.87 ptm 0.85 i_ptm 0.82 rg 3.19\n", - "42 models [4] recycles 1 hard 0 soft 0.76 temp 1 loss 6.60 helix 0.74 pae 0.28 i_pae 0.43 con 2.07 i_con 3.61 plddt 0.79 ptm 0.66 i_ptm 0.45 rg 3.14\n", - "43 models [2] recycles 1 hard 0 soft 0.77 temp 1 loss 5.17 helix 0.82 pae 0.18 i_pae 0.23 con 1.79 i_con 2.56 plddt 0.89 ptm 0.85 i_ptm 0.80 rg 3.18\n", - "44 models [2] recycles 1 hard 0 soft 0.79 temp 1 loss 5.38 helix 0.77 pae 0.19 i_pae 0.25 con 1.79 i_con 2.75 plddt 0.88 ptm 0.83 i_ptm 0.77 rg 3.17\n", - "45 models [1] recycles 1 hard 0 soft 0.81 temp 1 loss 5.19 helix 0.82 pae 0.18 i_pae 0.22 con 1.78 i_con 2.58 plddt 0.87 ptm 0.84 i_ptm 0.80 rg 3.19\n", - "46 models [2] recycles 1 hard 0 soft 0.83 temp 1 loss 5.36 helix 0.79 pae 0.20 i_pae 0.24 con 1.85 i_con 2.67 plddt 0.86 ptm 0.84 i_ptm 0.79 rg 3.19\n", - "47 models [3] recycles 1 hard 0 soft 0.85 temp 1 loss 5.18 helix 0.86 pae 0.18 i_pae 0.22 con 1.80 i_con 2.57 plddt 0.87 ptm 0.85 i_ptm 0.80 rg 3.17\n", - "48 models [0] recycles 1 hard 0 soft 0.86 temp 1 loss 5.07 helix 0.88 pae 0.16 i_pae 0.20 con 1.66 i_con 2.63 plddt 0.90 ptm 0.86 i_ptm 0.81 rg 3.14\n", - "49 models [2] recycles 1 hard 0 soft 0.88 temp 1 loss 5.10 helix 0.84 pae 0.18 i_pae 0.23 con 1.69 i_con 2.60 plddt 0.89 ptm 0.85 i_ptm 0.79 rg 3.19\n", - "50 models [0] recycles 1 hard 0 soft 0.90 temp 1 loss 5.27 helix 0.87 pae 0.18 i_pae 0.22 con 1.87 i_con 2.62 plddt 0.85 ptm 0.84 i_ptm 0.78 rg 3.10\n", - "Initial trajectory pLDDT good, continuing: 0.92\n", - "Stage 1: Additional Logits Optimisation\n", - "51 models [3] recycles 1 hard 0 soft 0.04 temp 1 loss 8.08 helix 2.82 pae 0.83 i_pae 0.88 con 4.20 i_con 4.47 plddt 0.18 ptm 0.16 i_ptm 0.15 rg -0.93\n", - "52 models [4] recycles 1 hard 0 soft 0.08 temp 1 loss 12.39 helix 2.27 pae 0.93 i_pae 0.97 con 4.57 i_con 5.12 plddt 0.17 ptm 0.29 i_ptm 0.06 rg 9.29\n", - "53 models [0] recycles 1 hard 0 soft 0.12 temp 1 loss 4.97 helix 0.89 pae 0.16 i_pae 0.20 con 1.74 i_con 2.44 plddt 0.89 ptm 0.86 i_ptm 0.83 rg 3.16\n", - "54 models [0] recycles 1 hard 0 soft 0.16 temp 1 loss 9.69 helix 0.75 pae 0.69 i_pae 0.84 con 3.69 i_con 4.95 plddt 0.47 ptm 0.45 i_ptm 0.10 rg 2.72\n", - "55 models [4] recycles 1 hard 0 soft 0.20 temp 1 loss 9.97 helix 1.29 pae 0.81 i_pae 0.85 con 4.32 i_con 4.58 plddt 0.25 ptm 0.41 i_ptm 0.10 rg 3.09\n", - "56 models [2] recycles 1 hard 0 soft 0.24 temp 1 loss 9.35 helix 0.92 pae 0.70 i_pae 0.83 con 3.58 i_con 4.77 plddt 0.44 ptm 0.44 i_ptm 0.12 rg 2.73\n", - "57 models [1] recycles 1 hard 0 soft 0.28 temp 1 loss 4.87 helix 1.01 pae 0.16 i_pae 0.21 con 1.66 i_con 2.45 plddt 0.90 ptm 0.86 i_ptm 0.82 rg 3.21\n", - "58 models [2] recycles 1 hard 0 soft 0.32 temp 1 loss 5.42 helix 0.86 pae 0.20 i_pae 0.24 con 2.01 i_con 2.57 plddt 0.86 ptm 0.83 i_ptm 0.79 rg 3.20\n", - "59 models [0] recycles 1 hard 0 soft 0.36 temp 1 loss 5.12 helix 0.89 pae 0.17 i_pae 0.21 con 1.78 i_con 2.54 plddt 0.89 ptm 0.84 i_ptm 0.79 rg 3.23\n", - "60 models [4] recycles 1 hard 0 soft 0.40 temp 1 loss 5.05 helix 0.92 pae 0.16 i_pae 0.21 con 1.79 i_con 2.45 plddt 0.90 ptm 0.85 i_ptm 0.81 rg 3.27\n", - "61 models [4] recycles 1 hard 0 soft 0.44 temp 1 loss 5.08 helix 0.81 pae 0.17 i_pae 0.20 con 1.85 i_con 2.43 plddt 0.89 ptm 0.86 i_ptm 0.83 rg 3.12\n", - "62 models [2] recycles 1 hard 0 soft 0.48 temp 1 loss 7.16 helix 2.93 pae 0.78 i_pae 0.80 con 4.14 i_con 3.69 plddt 0.23 ptm 0.21 i_ptm 0.18 rg -0.99\n", - "63 models [1] recycles 1 hard 0 soft 0.52 temp 1 loss 4.75 helix 0.98 pae 0.16 i_pae 0.20 con 1.69 i_con 2.32 plddt 0.90 ptm 0.86 i_ptm 0.84 rg 3.09\n", - "64 models [4] recycles 1 hard 0 soft 0.56 temp 1 loss 4.44 helix 1.01 pae 0.14 i_pae 0.18 con 1.50 i_con 2.24 plddt 0.94 ptm 0.88 i_ptm 0.86 rg 3.06\n", - "65 models [4] recycles 1 hard 0 soft 0.60 temp 1 loss 6.07 helix 0.83 pae 0.24 i_pae 0.36 con 1.90 i_con 3.30 plddt 0.83 ptm 0.71 i_ptm 0.53 rg 3.13\n", - "66 models [0] recycles 1 hard 0 soft 0.64 temp 1 loss 4.45 helix 1.08 pae 0.14 i_pae 0.18 con 1.53 i_con 2.22 plddt 0.93 ptm 0.88 i_ptm 0.85 rg 3.14\n", - "67 models [0] recycles 1 hard 0 soft 0.68 temp 1 loss 4.54 helix 1.05 pae 0.15 i_pae 0.19 con 1.54 i_con 2.29 plddt 0.92 ptm 0.87 i_ptm 0.83 rg 3.10\n", - "68 models [3] recycles 1 hard 0 soft 0.72 temp 1 loss 4.17 helix 1.19 pae 0.13 i_pae 0.17 con 1.45 i_con 2.04 plddt 0.94 ptm 0.90 i_ptm 0.88 rg 3.18\n", - "69 models [1] recycles 1 hard 0 soft 0.76 temp 1 loss 4.21 helix 1.09 pae 0.13 i_pae 0.17 con 1.44 i_con 2.09 plddt 0.94 ptm 0.89 i_ptm 0.87 rg 3.09\n", - "70 models [3] recycles 1 hard 0 soft 0.80 temp 1 loss 4.74 helix 1.06 pae 0.15 i_pae 0.20 con 1.52 i_con 2.49 plddt 0.93 ptm 0.85 i_ptm 0.79 rg 3.20\n", - "71 models [2] recycles 1 hard 0 soft 0.84 temp 1 loss 4.37 helix 1.10 pae 0.14 i_pae 0.18 con 1.46 i_con 2.18 plddt 0.94 ptm 0.89 i_ptm 0.85 rg 3.20\n", - "72 models [3] recycles 1 hard 0 soft 0.88 temp 1 loss 4.73 helix 1.03 pae 0.16 i_pae 0.19 con 1.67 i_con 2.29 plddt 0.90 ptm 0.88 i_ptm 0.86 rg 3.26\n", - "73 models [3] recycles 1 hard 0 soft 0.92 temp 1 loss 6.27 helix 0.88 pae 0.27 i_pae 0.39 con 2.15 i_con 3.34 plddt 0.77 ptm 0.66 i_ptm 0.50 rg 2.83\n", - "74 models [1] recycles 1 hard 0 soft 0.96 temp 1 loss 9.37 helix 0.65 pae 0.62 i_pae 0.72 con 3.55 i_con 4.50 plddt 0.53 ptm 0.50 i_ptm 0.25 rg 3.72\n", - "75 models [4] recycles 1 hard 0 soft 1 temp 1 loss 5.71 helix 0.78 pae 0.21 i_pae 0.28 con 1.97 i_con 2.88 plddt 0.84 ptm 0.78 i_ptm 0.71 rg 3.16\n", - "Optimised logit trajectory pLDDT: 0.94\n", - "Stage 2: Softmax Optimisation\n", - "76 models [1] recycles 1 hard 0 soft 1 temp 0.96 loss 5.44 helix 0.93 pae 0.20 i_pae 0.24 con 1.97 i_con 2.70 plddt 0.84 ptm 0.81 i_ptm 0.78 rg 3.08\n", - "77 models [4] recycles 1 hard 0 soft 1 temp 0.91 loss 5.03 helix 0.91 pae 0.17 i_pae 0.23 con 1.65 i_con 2.59 plddt 0.90 ptm 0.84 i_ptm 0.77 rg 3.18\n", - "78 models [3] recycles 1 hard 0 soft 1 temp 0.87 loss 4.78 helix 0.90 pae 0.16 i_pae 0.20 con 1.65 i_con 2.35 plddt 0.90 ptm 0.87 i_ptm 0.83 rg 3.15\n", - "79 models [2] recycles 1 hard 0 soft 1 temp 0.83 loss 6.31 helix 0.73 pae 0.26 i_pae 0.31 con 2.29 i_con 3.03 plddt 0.78 ptm 0.76 i_ptm 0.73 rg 3.45\n", - "80 models [2] recycles 1 hard 0 soft 1 temp 0.79 loss 4.73 helix 0.93 pae 0.15 i_pae 0.20 con 1.59 i_con 2.36 plddt 0.92 ptm 0.88 i_ptm 0.84 rg 3.17\n", - "81 models [4] recycles 1 hard 0 soft 1 temp 0.75 loss 5.91 helix 0.76 pae 0.23 i_pae 0.26 con 2.18 i_con 2.74 plddt 0.81 ptm 0.81 i_ptm 0.79 rg 3.56\n", - "82 models [0] recycles 1 hard 0 soft 1 temp 0.72 loss 5.78 helix 0.89 pae 0.22 i_pae 0.26 con 2.10 i_con 2.72 plddt 0.82 ptm 0.81 i_ptm 0.79 rg 3.60\n", - "83 models [1] recycles 1 hard 0 soft 1 temp 0.68 loss 4.74 helix 0.97 pae 0.16 i_pae 0.21 con 1.65 i_con 2.32 plddt 0.90 ptm 0.85 i_ptm 0.81 rg 3.20\n", - "84 models [2] recycles 1 hard 0 soft 1 temp 0.64 loss 4.48 helix 1.09 pae 0.15 i_pae 0.19 con 1.51 i_con 2.26 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 3.17\n", - "85 models [1] recycles 1 hard 0 soft 1 temp 0.61 loss 4.37 helix 1.11 pae 0.14 i_pae 0.18 con 1.47 i_con 2.19 plddt 0.93 ptm 0.87 i_ptm 0.84 rg 3.17\n", - "86 models [2] recycles 1 hard 0 soft 1 temp 0.58 loss 4.91 helix 1.04 pae 0.16 i_pae 0.22 con 1.64 i_con 2.53 plddt 0.91 ptm 0.84 i_ptm 0.78 rg 3.15\n", - "87 models [2] recycles 1 hard 0 soft 1 temp 0.54 loss 4.65 helix 1.02 pae 0.15 i_pae 0.19 con 1.66 i_con 2.25 plddt 0.92 ptm 0.87 i_ptm 0.85 rg 3.19\n", - "88 models [0] recycles 1 hard 0 soft 1 temp 0.51 loss 4.48 helix 1.15 pae 0.15 i_pae 0.19 con 1.55 i_con 2.25 plddt 0.92 ptm 0.86 i_ptm 0.83 rg 3.13\n", - "89 models [0] recycles 1 hard 0 soft 1 temp 0.48 loss 4.88 helix 1.09 pae 0.17 i_pae 0.20 con 1.80 i_con 2.34 plddt 0.89 ptm 0.86 i_ptm 0.83 rg 3.22\n", - "90 models [4] recycles 1 hard 0 soft 1 temp 0.45 loss 4.65 helix 1.09 pae 0.15 i_pae 0.20 con 1.66 i_con 2.26 plddt 0.91 ptm 0.87 i_ptm 0.84 rg 3.17\n", - "91 models [3] recycles 1 hard 0 soft 1 temp 0.42 loss 4.36 helix 1.20 pae 0.14 i_pae 0.17 con 1.51 i_con 2.16 plddt 0.93 ptm 0.89 i_ptm 0.86 rg 3.21\n", - "92 models [1] recycles 1 hard 0 soft 1 temp 0.39 loss 4.43 helix 1.16 pae 0.14 i_pae 0.18 con 1.55 i_con 2.18 plddt 0.92 ptm 0.88 i_ptm 0.85 rg 3.19\n", - "93 models [2] recycles 1 hard 0 soft 1 temp 0.37 loss 4.40 helix 1.15 pae 0.14 i_pae 0.18 con 1.51 i_con 2.18 plddt 0.94 ptm 0.88 i_ptm 0.86 rg 3.26\n", - "94 models [2] recycles 1 hard 0 soft 1 temp 0.34 loss 4.95 helix 1.01 pae 0.17 i_pae 0.21 con 1.81 i_con 2.38 plddt 0.90 ptm 0.85 i_ptm 0.81 rg 3.16\n", - "95 models [1] recycles 1 hard 0 soft 1 temp 0.32 loss 4.17 helix 1.15 pae 0.13 i_pae 0.17 con 1.42 i_con 2.08 plddt 0.94 ptm 0.89 i_ptm 0.86 rg 3.12\n", - "96 models [2] recycles 1 hard 0 soft 1 temp 0.29 loss 4.46 helix 1.06 pae 0.14 i_pae 0.18 con 1.54 i_con 2.17 plddt 0.94 ptm 0.88 i_ptm 0.86 rg 3.27\n", - "97 models [4] recycles 1 hard 0 soft 1 temp 0.27 loss 5.21 helix 1.00 pae 0.17 i_pae 0.22 con 1.87 i_con 2.54 plddt 0.88 ptm 0.85 i_ptm 0.80 rg 3.28\n", - "98 models [4] recycles 1 hard 0 soft 1 temp 0.25 loss 4.42 helix 1.08 pae 0.14 i_pae 0.18 con 1.53 i_con 2.16 plddt 0.93 ptm 0.89 i_ptm 0.87 rg 3.21\n", - "99 models [0] recycles 1 hard 0 soft 1 temp 0.23 loss 4.55 helix 1.02 pae 0.14 i_pae 0.18 con 1.60 i_con 2.22 plddt 0.92 ptm 0.88 i_ptm 0.85 rg 3.15\n", - "100 models [0] recycles 1 hard 0 soft 1 temp 0.21 loss 4.29 helix 1.13 pae 0.14 i_pae 0.18 con 1.44 i_con 2.16 plddt 0.93 ptm 0.87 i_ptm 0.84 rg 3.16\n", - "101 models [2] recycles 1 hard 0 soft 1 temp 0.19 loss 4.32 helix 1.26 pae 0.14 i_pae 0.19 con 1.47 i_con 2.18 plddt 0.94 ptm 0.88 i_ptm 0.86 rg 3.20\n", - "102 models [2] recycles 1 hard 0 soft 1 temp 0.17 loss 4.48 helix 1.16 pae 0.14 i_pae 0.19 con 1.54 i_con 2.27 plddt 0.93 ptm 0.87 i_ptm 0.84 rg 3.09\n", - "103 models [0] recycles 1 hard 0 soft 1 temp 0.15 loss 4.45 helix 1.27 pae 0.14 i_pae 0.19 con 1.50 i_con 2.28 plddt 0.93 ptm 0.86 i_ptm 0.83 rg 3.18\n", - "104 models [3] recycles 1 hard 0 soft 1 temp 0.14 loss 4.76 helix 1.18 pae 0.16 i_pae 0.22 con 1.48 i_con 2.56 plddt 0.92 ptm 0.83 i_ptm 0.76 rg 3.21\n", - "105 models [2] recycles 1 hard 0 soft 1 temp 0.12 loss 4.51 helix 1.13 pae 0.14 i_pae 0.19 con 1.50 i_con 2.32 plddt 0.94 ptm 0.86 i_ptm 0.84 rg 3.12\n", - "106 models [2] recycles 1 hard 0 soft 1 temp 0.11 loss 4.47 helix 1.09 pae 0.14 i_pae 0.19 con 1.51 i_con 2.25 plddt 0.93 ptm 0.87 i_ptm 0.84 rg 3.13\n", - "107 models [4] recycles 1 hard 0 soft 1 temp 0.09 loss 4.56 helix 1.17 pae 0.15 i_pae 0.20 con 1.52 i_con 2.32 plddt 0.93 ptm 0.86 i_ptm 0.82 rg 3.23\n", - "108 models [0] recycles 1 hard 0 soft 1 temp 0.08 loss 4.43 helix 1.13 pae 0.14 i_pae 0.19 con 1.48 i_con 2.26 plddt 0.93 ptm 0.87 i_ptm 0.84 rg 3.11\n", - "109 models [0] recycles 1 hard 0 soft 1 temp 0.07 loss 9.23 helix 0.79 pae 0.63 i_pae 0.82 con 3.06 i_con 5.08 plddt 0.53 ptm 0.45 i_ptm 0.12 rg 3.01\n", - "110 models [4] recycles 1 hard 0 soft 1 temp 0.06 loss 4.92 helix 1.13 pae 0.16 i_pae 0.22 con 1.59 i_con 2.60 plddt 0.91 ptm 0.82 i_ptm 0.76 rg 3.19\n", - "111 models [4] recycles 1 hard 0 soft 1 temp 0.05 loss 5.25 helix 1.02 pae 0.18 i_pae 0.25 con 1.67 i_con 2.79 plddt 0.89 ptm 0.78 i_ptm 0.69 rg 3.23\n", - "112 models [4] recycles 1 hard 0 soft 1 temp 0.04 loss 4.76 helix 1.11 pae 0.16 i_pae 0.21 con 1.63 i_con 2.41 plddt 0.91 ptm 0.84 i_ptm 0.81 rg 3.15\n", - "113 models [3] recycles 1 hard 0 soft 1 temp 0.03 loss 5.77 helix 0.97 pae 0.22 i_pae 0.32 con 1.87 i_con 3.11 plddt 0.85 ptm 0.71 i_ptm 0.59 rg 3.09\n", - "114 models [4] recycles 1 hard 0 soft 1 temp 0.03 loss 5.00 helix 1.01 pae 0.16 i_pae 0.21 con 1.79 i_con 2.44 plddt 0.89 ptm 0.85 i_ptm 0.81 rg 3.24\n", - "115 models [1] recycles 1 hard 0 soft 1 temp 0.02 loss 4.43 helix 1.25 pae 0.14 i_pae 0.18 con 1.48 i_con 2.30 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 3.14\n", - "116 models [1] recycles 1 hard 0 soft 1 temp 0.02 loss 4.30 helix 1.14 pae 0.14 i_pae 0.18 con 1.49 i_con 2.12 plddt 0.93 ptm 0.88 i_ptm 0.86 rg 3.16\n", - "117 models [1] recycles 1 hard 0 soft 1 temp 0.01 loss 4.95 helix 1.08 pae 0.16 i_pae 0.21 con 1.73 i_con 2.50 plddt 0.89 ptm 0.83 i_ptm 0.78 rg 3.15\n", - "118 models [1] recycles 1 hard 0 soft 1 temp 0.01 loss 6.71 helix 0.83 pae 0.29 i_pae 0.43 con 2.24 i_con 3.63 plddt 0.78 ptm 0.64 i_ptm 0.45 rg 2.92\n", - "119 models [4] recycles 1 hard 0 soft 1 temp 0.01 loss 4.99 helix 1.03 pae 0.16 i_pae 0.22 con 1.70 i_con 2.52 plddt 0.90 ptm 0.83 i_ptm 0.79 rg 3.21\n", - "120 models [2] recycles 1 hard 0 soft 1 temp 0.01 loss 4.83 helix 1.07 pae 0.16 i_pae 0.21 con 1.68 i_con 2.43 plddt 0.91 ptm 0.84 i_ptm 0.81 rg 3.14\n", - "Softmax trajectory pLDDT good, continuing: 0.94\n", - "Stage 3: One-hot Optimisation\n", - "121 models [0] recycles 1 hard 1 soft 1 temp 0.01 loss 4.41 helix 1.17 pae 0.14 i_pae 0.18 con 1.48 i_con 2.22 plddt 0.92 ptm 0.87 i_ptm 0.84 rg 3.21\n", - "122 models [4] recycles 1 hard 1 soft 1 temp 0.01 loss 4.68 helix 1.12 pae 0.14 i_pae 0.19 con 1.56 i_con 2.38 plddt 0.92 ptm 0.85 i_ptm 0.82 rg 3.28\n", - "123 models [1] recycles 1 hard 1 soft 1 temp 0.01 loss 4.06 helix 1.21 pae 0.13 i_pae 0.17 con 1.38 i_con 2.00 plddt 0.94 ptm 0.90 i_ptm 0.88 rg 3.17\n", - "124 models [3] recycles 1 hard 1 soft 1 temp 0.01 loss 4.15 helix 1.30 pae 0.13 i_pae 0.17 con 1.36 i_con 2.10 plddt 0.94 ptm 0.89 i_ptm 0.87 rg 3.32\n", - "125 models [0] recycles 1 hard 1 soft 1 temp 0.01 loss 4.41 helix 1.17 pae 0.14 i_pae 0.18 con 1.48 i_con 2.22 plddt 0.92 ptm 0.87 i_ptm 0.84 rg 3.21\n", - "One-hot trajectory pLDDT good, continuing: 0.94\n", - "Stage 4: PSSM Semigreedy Optimisation\n", - "Running semigreedy optimization...\n", - "126 models [4] recycles 1 hard 1 soft 0 temp 1 loss 4.37 helix 1.17 pae 0.14 i_pae 0.18 con 1.49 i_con 2.16 plddt 0.92 ptm 0.88 i_ptm 0.86 rg 3.28\n", - "127 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.36 helix 1.24 pae 0.14 i_pae 0.18 con 1.46 i_con 2.20 plddt 0.93 ptm 0.87 i_ptm 0.84 rg 3.27\n", - "128 models [4] recycles 1 hard 1 soft 0 temp 1 loss 4.40 helix 1.19 pae 0.14 i_pae 0.18 con 1.49 i_con 2.19 plddt 0.92 ptm 0.88 i_ptm 0.86 rg 3.31\n", - "129 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.34 helix 1.24 pae 0.14 i_pae 0.18 con 1.46 i_con 2.19 plddt 0.92 ptm 0.88 i_ptm 0.85 rg 3.26\n", - "130 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.81 helix 1.15 pae 0.16 i_pae 0.21 con 1.56 i_con 2.49 plddt 0.91 ptm 0.85 i_ptm 0.80 rg 3.33\n", - "131 models [1] recycles 1 hard 1 soft 0 temp 1 loss 4.04 helix 1.26 pae 0.13 i_pae 0.17 con 1.37 i_con 2.01 plddt 0.94 ptm 0.89 i_ptm 0.88 rg 3.19\n", - "132 models [3] recycles 1 hard 1 soft 0 temp 1 loss 4.23 helix 1.30 pae 0.14 i_pae 0.18 con 1.37 i_con 2.19 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 3.29\n", - "133 models [1] recycles 1 hard 1 soft 0 temp 1 loss 4.02 helix 1.29 pae 0.13 i_pae 0.17 con 1.35 i_con 2.01 plddt 0.94 ptm 0.89 i_ptm 0.88 rg 3.21\n", - "134 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.47 helix 1.19 pae 0.14 i_pae 0.19 con 1.48 i_con 2.28 plddt 0.93 ptm 0.87 i_ptm 0.83 rg 3.27\n", - "135 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.12 helix 1.26 pae 0.13 i_pae 0.17 con 1.38 i_con 2.06 plddt 0.94 ptm 0.89 i_ptm 0.87 rg 3.24\n", - "136 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.38 helix 1.21 pae 0.14 i_pae 0.18 con 1.47 i_con 2.20 plddt 0.93 ptm 0.88 i_ptm 0.85 rg 3.29\n", - "137 models [3] recycles 1 hard 1 soft 0 temp 1 loss 4.06 helix 1.35 pae 0.13 i_pae 0.17 con 1.34 i_con 2.08 plddt 0.94 ptm 0.89 i_ptm 0.88 rg 3.21\n", - "138 models [1] recycles 1 hard 1 soft 0 temp 1 loss 4.03 helix 1.28 pae 0.13 i_pae 0.17 con 1.34 i_con 2.03 plddt 0.94 ptm 0.89 i_ptm 0.88 rg 3.18\n", - "139 models [4] recycles 1 hard 1 soft 0 temp 1 loss 4.07 helix 1.30 pae 0.13 i_pae 0.17 con 1.36 i_con 2.04 plddt 0.94 ptm 0.89 i_ptm 0.88 rg 3.23\n", - "140 models [4] recycles 1 hard 1 soft 0 temp 1 loss 4.06 helix 1.30 pae 0.13 i_pae 0.17 con 1.36 i_con 2.04 plddt 0.94 ptm 0.89 i_ptm 0.88 rg 3.22\n", - "Trajectory successful, final pLDDT: 0.94\n", - "Starting trajectory took: 0 hours, 7 minutes, 43 seconds\n", - "\n", - "Fixing interface residues: B14,B15,B18,B19,B21,B22,B25,B26,B29,B30,B32,B33,B34,B36,B37,B100,B104,B108,B111,B112,B115,B116,B118,B119,B122\n", - "Base AF2 filters not passed for PDL1_l145_s718363_mpnn1, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l145_s718363_mpnn1, skipping interface scoring\n", - "PDL1_l145_s718363_mpnn1 passed all filters\n", - "Base AF2 filters not passed for PDL1_l145_s718363_mpnn2, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l145_s718363_mpnn2, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l145_s718363_mpnn2, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l145_s718363_mpnn2, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l145_s718363_mpnn2, skipping interface scoring\n", - "Unmet filter conditions for PDL1_l145_s718363_mpnn2\n", - "PDL1_l145_s718363_mpnn3 passed all filters\n", - "Found 2 MPNN designs passing filters\n", - "Design and validation of trajectory PDL1_l145_s718363 took: 0 hours, 8 minutes, 50 seconds\n", - "Starting trajectory: PDL1_l92_s843319\n", - "Stage 1: Test Logits\n", - "1 models [3] recycles 1 hard 0 soft 0.02 temp 1 loss 11.82 helix 1.63 pae 0.83 i_pae 0.87 con 4.69 i_con 4.36 plddt 0.27 ptm 0.53 i_ptm 0.08 rg 9.08\n", - "2 models [2] recycles 1 hard 0 soft 0.04 temp 1 loss 15.16 helix 1.58 pae 0.79 i_pae 0.82 con 4.80 i_con 4.53 plddt 0.39 ptm 0.54 i_ptm 0.16 rg 19.34\n", - "3 models [4] recycles 1 hard 0 soft 0.05 temp 1 loss 12.39 helix 1.47 pae 0.74 i_pae 0.76 con 4.58 i_con 4.29 plddt 0.40 ptm 0.56 i_ptm 0.21 rg 11.65\n", - "4 models [2] recycles 1 hard 0 soft 0.07 temp 1 loss 9.44 helix 0.89 pae 0.66 i_pae 0.72 con 4.12 i_con 4.26 plddt 0.41 ptm 0.55 i_ptm 0.17 rg 2.96\n", - "5 models [0] recycles 1 hard 0 soft 0.09 temp 1 loss 8.57 helix 0.72 pae 0.58 i_pae 0.67 con 3.72 i_con 4.24 plddt 0.47 ptm 0.58 i_ptm 0.20 rg 1.45\n", - "6 models [1] recycles 1 hard 0 soft 0.11 temp 1 loss 8.48 helix 0.71 pae 0.54 i_pae 0.68 con 3.41 i_con 4.21 plddt 0.54 ptm 0.56 i_ptm 0.19 rg 2.35\n", - "7 models [4] recycles 1 hard 0 soft 0.13 temp 1 loss 8.50 helix 0.75 pae 0.59 i_pae 0.71 con 3.60 i_con 4.19 plddt 0.49 ptm 0.55 i_ptm 0.16 rg 1.78\n", - "8 models [2] recycles 1 hard 0 soft 0.14 temp 1 loss 7.75 helix 0.75 pae 0.45 i_pae 0.55 con 3.09 i_con 3.75 plddt 0.63 ptm 0.61 i_ptm 0.34 rg 2.73\n", - "9 models [0] recycles 1 hard 0 soft 0.16 temp 1 loss 6.70 helix 0.81 pae 0.31 i_pae 0.35 con 2.78 i_con 3.11 plddt 0.71 ptm 0.75 i_ptm 0.64 rg 2.81\n", - "10 models [0] recycles 1 hard 0 soft 0.18 temp 1 loss 6.44 helix 0.95 pae 0.31 i_pae 0.36 con 2.46 i_con 3.16 plddt 0.74 ptm 0.73 i_ptm 0.55 rg 3.00\n", - "11 models [1] recycles 1 hard 0 soft 0.20 temp 1 loss 6.34 helix 0.96 pae 0.31 i_pae 0.35 con 2.38 i_con 3.10 plddt 0.75 ptm 0.74 i_ptm 0.58 rg 3.15\n", - "12 models [2] recycles 1 hard 0 soft 0.22 temp 1 loss 6.01 helix 0.76 pae 0.27 i_pae 0.34 con 2.25 i_con 3.00 plddt 0.81 ptm 0.72 i_ptm 0.56 rg 2.71\n", - "13 models [1] recycles 1 hard 0 soft 0.23 temp 1 loss 6.53 helix 0.88 pae 0.32 i_pae 0.44 con 2.29 i_con 3.45 plddt 0.77 ptm 0.66 i_ptm 0.39 rg 2.77\n", - "14 models [3] recycles 1 hard 0 soft 0.25 temp 1 loss 6.26 helix 0.78 pae 0.26 i_pae 0.31 con 2.49 i_con 2.97 plddt 0.79 ptm 0.76 i_ptm 0.60 rg 2.84\n", - "15 models [0] recycles 1 hard 0 soft 0.27 temp 1 loss 5.29 helix 1.10 pae 0.22 i_pae 0.25 con 2.03 i_con 2.54 plddt 0.83 ptm 0.81 i_ptm 0.71 rg 3.00\n", - "16 models [4] recycles 1 hard 0 soft 0.29 temp 1 loss 4.84 helix 0.99 pae 0.17 i_pae 0.22 con 1.70 i_con 2.43 plddt 0.91 ptm 0.81 i_ptm 0.75 rg 2.97\n", - "17 models [0] recycles 1 hard 0 soft 0.31 temp 1 loss 4.41 helix 1.12 pae 0.16 i_pae 0.19 con 1.67 i_con 2.08 plddt 0.91 ptm 0.85 i_ptm 0.81 rg 2.99\n", - "18 models [2] recycles 1 hard 0 soft 0.32 temp 1 loss 4.55 helix 1.01 pae 0.17 i_pae 0.21 con 1.53 i_con 2.29 plddt 0.92 ptm 0.82 i_ptm 0.76 rg 3.08\n", - "19 models [3] recycles 1 hard 0 soft 0.34 temp 1 loss 4.31 helix 1.07 pae 0.15 i_pae 0.19 con 1.61 i_con 2.00 plddt 0.93 ptm 0.85 i_ptm 0.83 rg 3.09\n", - "20 models [4] recycles 1 hard 0 soft 0.36 temp 1 loss 4.42 helix 1.04 pae 0.16 i_pae 0.21 con 1.47 i_con 2.24 plddt 0.93 ptm 0.83 i_ptm 0.77 rg 3.06\n", - "21 models [2] recycles 1 hard 0 soft 0.38 temp 1 loss 3.86 helix 1.05 pae 0.14 i_pae 0.17 con 1.39 i_con 1.79 plddt 0.95 ptm 0.87 i_ptm 0.85 rg 3.02\n", - "22 models [4] recycles 1 hard 0 soft 0.40 temp 1 loss 3.94 helix 1.11 pae 0.14 i_pae 0.18 con 1.38 i_con 1.90 plddt 0.95 ptm 0.86 i_ptm 0.84 rg 3.02\n", - "23 models [1] recycles 1 hard 0 soft 0.41 temp 1 loss 4.02 helix 1.18 pae 0.15 i_pae 0.18 con 1.43 i_con 1.96 plddt 0.93 ptm 0.85 i_ptm 0.81 rg 2.97\n", - "24 models [3] recycles 1 hard 0 soft 0.43 temp 1 loss 5.94 helix 1.12 pae 0.36 i_pae 0.57 con 1.41 i_con 3.75 plddt 0.82 ptm 0.57 i_ptm 0.22 rg 2.84\n", - "25 models [0] recycles 1 hard 0 soft 0.45 temp 1 loss 3.72 helix 1.21 pae 0.13 i_pae 0.17 con 1.36 i_con 1.75 plddt 0.94 ptm 0.87 i_ptm 0.85 rg 2.97\n", - "26 models [4] recycles 1 hard 0 soft 0.47 temp 1 loss 5.89 helix 1.10 pae 0.35 i_pae 0.57 con 1.40 i_con 3.72 plddt 0.85 ptm 0.57 i_ptm 0.24 rg 2.85\n", - "27 models [0] recycles 1 hard 0 soft 0.49 temp 1 loss 3.73 helix 1.23 pae 0.13 i_pae 0.17 con 1.33 i_con 1.79 plddt 0.94 ptm 0.86 i_ptm 0.84 rg 3.00\n", - "28 models [3] recycles 1 hard 0 soft 0.50 temp 1 loss 5.81 helix 1.18 pae 0.35 i_pae 0.55 con 1.39 i_con 3.69 plddt 0.85 ptm 0.58 i_ptm 0.23 rg 2.80\n", - "29 models [2] recycles 1 hard 0 soft 0.52 temp 1 loss 4.34 helix 1.18 pae 0.15 i_pae 0.19 con 1.37 i_con 2.34 plddt 0.94 ptm 0.84 i_ptm 0.78 rg 2.94\n", - "30 models [1] recycles 1 hard 0 soft 0.54 temp 1 loss 5.13 helix 1.45 pae 0.23 i_pae 0.29 con 1.60 i_con 2.83 plddt 0.86 ptm 0.74 i_ptm 0.63 rg 3.29\n", - "31 models [2] recycles 1 hard 0 soft 0.56 temp 1 loss 4.50 helix 1.16 pae 0.16 i_pae 0.21 con 1.38 i_con 2.46 plddt 0.94 ptm 0.83 i_ptm 0.75 rg 2.99\n", - "32 models [0] recycles 1 hard 0 soft 0.58 temp 1 loss 4.40 helix 1.21 pae 0.15 i_pae 0.20 con 1.40 i_con 2.37 plddt 0.93 ptm 0.82 i_ptm 0.75 rg 2.99\n", - "33 models [0] recycles 1 hard 0 soft 0.59 temp 1 loss 4.86 helix 1.20 pae 0.19 i_pae 0.26 con 1.42 i_con 2.81 plddt 0.91 ptm 0.76 i_ptm 0.62 rg 2.86\n", - "34 models [4] recycles 1 hard 0 soft 0.61 temp 1 loss 5.06 helix 1.10 pae 0.21 i_pae 0.31 con 1.45 i_con 2.92 plddt 0.90 ptm 0.73 i_ptm 0.57 rg 2.92\n", - "35 models [1] recycles 1 hard 0 soft 0.63 temp 1 loss 4.52 helix 1.20 pae 0.16 i_pae 0.21 con 1.38 i_con 2.50 plddt 0.92 ptm 0.81 i_ptm 0.72 rg 2.97\n", - "36 models [2] recycles 1 hard 0 soft 0.65 temp 1 loss 4.73 helix 1.09 pae 0.18 i_pae 0.25 con 1.43 i_con 2.62 plddt 0.92 ptm 0.78 i_ptm 0.68 rg 2.94\n", - "37 models [4] recycles 1 hard 0 soft 0.67 temp 1 loss 7.36 helix 0.76 pae 0.40 i_pae 0.57 con 2.62 i_con 3.86 plddt 0.70 ptm 0.61 i_ptm 0.28 rg 2.79\n", - "38 models [2] recycles 1 hard 0 soft 0.68 temp 1 loss 5.23 helix 1.12 pae 0.23 i_pae 0.33 con 1.46 i_con 3.07 plddt 0.90 ptm 0.69 i_ptm 0.52 rg 2.94\n", - "39 models [2] recycles 1 hard 0 soft 0.70 temp 1 loss 4.80 helix 1.11 pae 0.18 i_pae 0.24 con 1.45 i_con 2.66 plddt 0.92 ptm 0.78 i_ptm 0.67 rg 3.01\n", - "40 models [2] recycles 1 hard 0 soft 0.72 temp 1 loss 4.37 helix 1.13 pae 0.15 i_pae 0.20 con 1.42 i_con 2.29 plddt 0.94 ptm 0.82 i_ptm 0.77 rg 3.02\n", - "41 models [0] recycles 1 hard 0 soft 0.74 temp 1 loss 4.43 helix 1.19 pae 0.14 i_pae 0.18 con 1.44 i_con 2.34 plddt 0.93 ptm 0.84 i_ptm 0.78 rg 3.04\n", - "42 models [1] recycles 1 hard 0 soft 0.76 temp 1 loss 4.23 helix 1.19 pae 0.14 i_pae 0.19 con 1.47 i_con 2.12 plddt 0.93 ptm 0.84 i_ptm 0.80 rg 3.01\n", - "43 models [3] recycles 1 hard 0 soft 0.77 temp 1 loss 4.02 helix 1.18 pae 0.13 i_pae 0.17 con 1.38 i_con 1.98 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 3.09\n", - "44 models [1] recycles 1 hard 0 soft 0.79 temp 1 loss 4.03 helix 1.26 pae 0.14 i_pae 0.17 con 1.38 i_con 2.04 plddt 0.94 ptm 0.86 i_ptm 0.82 rg 3.01\n", - "45 models [2] recycles 1 hard 0 soft 0.81 temp 1 loss 4.10 helix 1.14 pae 0.14 i_pae 0.18 con 1.42 i_con 2.03 plddt 0.94 ptm 0.86 i_ptm 0.82 rg 3.04\n", - "46 models [1] recycles 1 hard 0 soft 0.83 temp 1 loss 3.98 helix 1.21 pae 0.14 i_pae 0.17 con 1.42 i_con 1.95 plddt 0.94 ptm 0.86 i_ptm 0.83 rg 2.96\n", - "47 models [1] recycles 1 hard 0 soft 0.85 temp 1 loss 5.93 helix 1.15 pae 0.33 i_pae 0.52 con 1.49 i_con 3.65 plddt 0.83 ptm 0.58 i_ptm 0.25 rg 2.95\n", - "48 models [4] recycles 1 hard 0 soft 0.86 temp 1 loss 4.66 helix 1.01 pae 0.16 i_pae 0.21 con 1.64 i_con 2.32 plddt 0.91 ptm 0.83 i_ptm 0.76 rg 3.01\n", - "49 models [0] recycles 1 hard 0 soft 0.88 temp 1 loss 4.08 helix 1.18 pae 0.13 i_pae 0.17 con 1.42 i_con 2.04 plddt 0.94 ptm 0.86 i_ptm 0.82 rg 2.95\n", - "50 models [4] recycles 1 hard 0 soft 0.90 temp 1 loss 4.64 helix 1.04 pae 0.16 i_pae 0.22 con 1.56 i_con 2.37 plddt 0.92 ptm 0.81 i_ptm 0.75 rg 3.06\n", - "Initial trajectory pLDDT good, continuing: 0.94\n", - "Stage 1: Additional Logits Optimisation\n", - "51 models [2] recycles 1 hard 0 soft 0.04 temp 1 loss 8.85 helix 0.82 pae 0.65 i_pae 0.79 con 3.69 i_con 4.45 plddt 0.48 ptm 0.52 i_ptm 0.11 rg 1.71\n", - "52 models [4] recycles 1 hard 0 soft 0.08 temp 1 loss 4.14 helix 1.13 pae 0.14 i_pae 0.18 con 1.38 i_con 2.09 plddt 0.95 ptm 0.86 i_ptm 0.82 rg 3.08\n", - "53 models [2] recycles 1 hard 0 soft 0.12 temp 1 loss 7.00 helix 0.93 pae 0.42 i_pae 0.64 con 1.97 i_con 4.15 plddt 0.78 ptm 0.56 i_ptm 0.18 rg 2.89\n", - "54 models [4] recycles 1 hard 0 soft 0.16 temp 1 loss 9.03 helix 0.86 pae 0.68 i_pae 0.76 con 4.31 i_con 4.26 plddt 0.38 ptm 0.54 i_ptm 0.13 rg 0.88\n", - "55 models [4] recycles 1 hard 0 soft 0.20 temp 1 loss 3.87 helix 1.20 pae 0.13 i_pae 0.17 con 1.29 i_con 1.94 plddt 0.95 ptm 0.88 i_ptm 0.85 rg 3.07\n", - "56 models [3] recycles 1 hard 0 soft 0.24 temp 1 loss 3.78 helix 1.21 pae 0.13 i_pae 0.16 con 1.29 i_con 1.88 plddt 0.95 ptm 0.88 i_ptm 0.85 rg 2.97\n", - "57 models [0] recycles 1 hard 0 soft 0.28 temp 1 loss 4.79 helix 1.27 pae 0.23 i_pae 0.27 con 1.65 i_con 2.52 plddt 0.85 ptm 0.79 i_ptm 0.71 rg 2.87\n", - "58 models [1] recycles 1 hard 0 soft 0.32 temp 1 loss 4.75 helix 1.25 pae 0.20 i_pae 0.30 con 1.36 i_con 2.76 plddt 0.90 ptm 0.74 i_ptm 0.60 rg 2.89\n", - "59 models [3] recycles 1 hard 0 soft 0.36 temp 1 loss 3.79 helix 1.31 pae 0.13 i_pae 0.16 con 1.30 i_con 1.90 plddt 0.95 ptm 0.88 i_ptm 0.85 rg 3.02\n", - "60 models [3] recycles 1 hard 0 soft 0.40 temp 1 loss 3.84 helix 1.27 pae 0.13 i_pae 0.17 con 1.28 i_con 1.96 plddt 0.95 ptm 0.87 i_ptm 0.84 rg 3.02\n", - "61 models [0] recycles 1 hard 0 soft 0.44 temp 1 loss 3.97 helix 1.26 pae 0.13 i_pae 0.17 con 1.31 i_con 2.06 plddt 0.94 ptm 0.86 i_ptm 0.83 rg 2.98\n", - "62 models [1] recycles 1 hard 0 soft 0.48 temp 1 loss 3.75 helix 1.37 pae 0.13 i_pae 0.16 con 1.29 i_con 1.89 plddt 0.95 ptm 0.87 i_ptm 0.85 rg 2.98\n", - "63 models [4] recycles 1 hard 0 soft 0.52 temp 1 loss 3.81 helix 1.24 pae 0.12 i_pae 0.16 con 1.28 i_con 1.92 plddt 0.95 ptm 0.88 i_ptm 0.86 rg 2.99\n", - "64 models [1] recycles 1 hard 0 soft 0.56 temp 1 loss 6.07 helix 1.28 pae 0.37 i_pae 0.59 con 1.33 i_con 3.96 plddt 0.86 ptm 0.56 i_ptm 0.22 rg 2.99\n", - "65 models [3] recycles 1 hard 0 soft 0.60 temp 1 loss 3.73 helix 1.28 pae 0.12 i_pae 0.16 con 1.27 i_con 1.85 plddt 0.96 ptm 0.88 i_ptm 0.86 rg 3.07\n", - "66 models [4] recycles 1 hard 0 soft 0.64 temp 1 loss 3.85 helix 1.25 pae 0.13 i_pae 0.17 con 1.30 i_con 1.95 plddt 0.95 ptm 0.87 i_ptm 0.84 rg 2.99\n", - "67 models [0] recycles 1 hard 0 soft 0.68 temp 1 loss 3.73 helix 1.42 pae 0.12 i_pae 0.16 con 1.32 i_con 1.86 plddt 0.95 ptm 0.88 i_ptm 0.85 rg 3.00\n", - "68 models [2] recycles 1 hard 0 soft 0.72 temp 1 loss 3.73 helix 1.34 pae 0.12 i_pae 0.16 con 1.28 i_con 1.89 plddt 0.96 ptm 0.88 i_ptm 0.84 rg 2.95\n", - "69 models [0] recycles 1 hard 0 soft 0.76 temp 1 loss 5.15 helix 1.24 pae 0.23 i_pae 0.26 con 1.81 i_con 2.64 plddt 0.84 ptm 0.80 i_ptm 0.70 rg 3.10\n", - "70 models [2] recycles 1 hard 0 soft 0.80 temp 1 loss 4.35 helix 1.30 pae 0.20 i_pae 0.21 con 1.67 i_con 1.95 plddt 0.89 ptm 0.86 i_ptm 0.85 rg 3.33\n", - "71 models [2] recycles 1 hard 0 soft 0.84 temp 1 loss 4.03 helix 1.18 pae 0.13 i_pae 0.18 con 1.41 i_con 1.98 plddt 0.95 ptm 0.86 i_ptm 0.83 rg 3.02\n", - "72 models [4] recycles 1 hard 0 soft 0.88 temp 1 loss 3.83 helix 1.20 pae 0.13 i_pae 0.17 con 1.36 i_con 1.83 plddt 0.95 ptm 0.87 i_ptm 0.85 rg 3.02\n", - "73 models [0] recycles 1 hard 0 soft 0.92 temp 1 loss 3.99 helix 1.22 pae 0.13 i_pae 0.16 con 1.45 i_con 1.94 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 2.97\n", - "74 models [2] recycles 1 hard 0 soft 0.96 temp 1 loss 5.13 helix 0.99 pae 0.19 i_pae 0.26 con 1.76 i_con 2.63 plddt 0.89 ptm 0.78 i_ptm 0.67 rg 3.00\n", - "75 models [4] recycles 1 hard 0 soft 1 temp 1 loss 5.14 helix 1.01 pae 0.19 i_pae 0.25 con 1.76 i_con 2.63 plddt 0.89 ptm 0.79 i_ptm 0.67 rg 3.09\n", - "Optimised logit trajectory pLDDT: 0.96\n", - "Stage 2: Softmax Optimisation\n", - "76 models [2] recycles 1 hard 0 soft 1 temp 0.96 loss 4.33 helix 1.17 pae 0.15 i_pae 0.19 con 1.54 i_con 2.13 plddt 0.93 ptm 0.85 i_ptm 0.80 rg 3.06\n", - "77 models [4] recycles 1 hard 0 soft 1 temp 0.91 loss 4.11 helix 1.09 pae 0.14 i_pae 0.17 con 1.46 i_con 1.97 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 3.06\n", - "78 models [4] recycles 1 hard 0 soft 1 temp 0.87 loss 4.03 helix 1.20 pae 0.14 i_pae 0.18 con 1.40 i_con 1.98 plddt 0.94 ptm 0.86 i_ptm 0.83 rg 3.09\n", - "79 models [4] recycles 1 hard 0 soft 1 temp 0.83 loss 3.96 helix 1.18 pae 0.13 i_pae 0.18 con 1.36 i_con 1.97 plddt 0.95 ptm 0.86 i_ptm 0.83 rg 3.02\n", - "80 models [1] recycles 1 hard 0 soft 1 temp 0.79 loss 4.02 helix 1.28 pae 0.13 i_pae 0.17 con 1.37 i_con 2.04 plddt 0.93 ptm 0.86 i_ptm 0.82 rg 3.01\n", - "81 models [0] recycles 1 hard 0 soft 1 temp 0.75 loss 3.80 helix 1.32 pae 0.13 i_pae 0.16 con 1.30 i_con 1.94 plddt 0.95 ptm 0.87 i_ptm 0.84 rg 2.92\n", - "82 models [1] recycles 1 hard 0 soft 1 temp 0.72 loss 4.05 helix 1.21 pae 0.14 i_pae 0.18 con 1.41 i_con 2.02 plddt 0.93 ptm 0.86 i_ptm 0.82 rg 2.99\n", - "83 models [2] recycles 1 hard 0 soft 1 temp 0.68 loss 3.97 helix 1.30 pae 0.13 i_pae 0.17 con 1.33 i_con 2.06 plddt 0.95 ptm 0.87 i_ptm 0.83 rg 2.97\n", - "84 models [2] recycles 1 hard 0 soft 1 temp 0.64 loss 4.33 helix 1.21 pae 0.14 i_pae 0.19 con 1.49 i_con 2.23 plddt 0.94 ptm 0.84 i_ptm 0.79 rg 2.94\n", - "85 models [0] recycles 1 hard 0 soft 1 temp 0.61 loss 3.77 helix 1.37 pae 0.12 i_pae 0.15 con 1.27 i_con 1.95 plddt 0.95 ptm 0.88 i_ptm 0.85 rg 2.97\n", - "86 models [3] recycles 1 hard 0 soft 1 temp 0.58 loss 3.94 helix 1.31 pae 0.13 i_pae 0.17 con 1.37 i_con 1.95 plddt 0.95 ptm 0.87 i_ptm 0.84 rg 3.08\n", - "87 models [4] recycles 1 hard 0 soft 1 temp 0.54 loss 4.26 helix 1.26 pae 0.14 i_pae 0.18 con 1.51 i_con 2.12 plddt 0.94 ptm 0.86 i_ptm 0.82 rg 3.05\n", - "88 models [0] recycles 1 hard 0 soft 1 temp 0.51 loss 3.99 helix 1.39 pae 0.13 i_pae 0.16 con 1.31 i_con 2.11 plddt 0.95 ptm 0.86 i_ptm 0.81 rg 3.02\n", - "89 models [0] recycles 1 hard 0 soft 1 temp 0.48 loss 3.68 helix 1.39 pae 0.12 i_pae 0.15 con 1.29 i_con 1.84 plddt 0.96 ptm 0.88 i_ptm 0.85 rg 2.97\n", - "90 models [0] recycles 1 hard 0 soft 1 temp 0.45 loss 3.68 helix 1.39 pae 0.12 i_pae 0.15 con 1.27 i_con 1.88 plddt 0.96 ptm 0.88 i_ptm 0.86 rg 2.91\n", - "91 models [2] recycles 1 hard 0 soft 1 temp 0.42 loss 5.05 helix 1.17 pae 0.21 i_pae 0.31 con 1.47 i_con 2.89 plddt 0.90 ptm 0.72 i_ptm 0.55 rg 2.97\n", - "92 models [1] recycles 1 hard 0 soft 1 temp 0.39 loss 3.79 helix 1.37 pae 0.13 i_pae 0.16 con 1.36 i_con 1.88 plddt 0.95 ptm 0.87 i_ptm 0.84 rg 2.95\n", - "93 models [2] recycles 1 hard 0 soft 1 temp 0.37 loss 3.89 helix 1.39 pae 0.13 i_pae 0.17 con 1.34 i_con 2.01 plddt 0.95 ptm 0.86 i_ptm 0.82 rg 2.92\n", - "94 models [4] recycles 1 hard 0 soft 1 temp 0.34 loss 3.73 helix 1.45 pae 0.13 i_pae 0.17 con 1.28 i_con 1.92 plddt 0.95 ptm 0.87 i_ptm 0.84 rg 2.95\n", - "95 models [3] recycles 1 hard 0 soft 1 temp 0.32 loss 3.81 helix 1.35 pae 0.13 i_pae 0.16 con 1.35 i_con 1.87 plddt 0.95 ptm 0.88 i_ptm 0.86 rg 3.06\n", - "96 models [4] recycles 1 hard 0 soft 1 temp 0.29 loss 4.05 helix 1.30 pae 0.13 i_pae 0.18 con 1.43 i_con 2.03 plddt 0.94 ptm 0.85 i_ptm 0.82 rg 3.00\n", - "97 models [3] recycles 1 hard 0 soft 1 temp 0.27 loss 3.59 helix 1.39 pae 0.12 i_pae 0.15 con 1.31 i_con 1.72 plddt 0.96 ptm 0.89 i_ptm 0.87 rg 2.98\n", - "98 models [0] recycles 1 hard 0 soft 1 temp 0.25 loss 3.62 helix 1.42 pae 0.12 i_pae 0.16 con 1.29 i_con 1.80 plddt 0.95 ptm 0.88 i_ptm 0.85 rg 2.91\n", - "99 models [2] recycles 1 hard 0 soft 1 temp 0.23 loss 5.81 helix 1.20 pae 0.33 i_pae 0.53 con 1.51 i_con 3.58 plddt 0.84 ptm 0.60 i_ptm 0.27 rg 2.83\n", - "100 models [4] recycles 1 hard 0 soft 1 temp 0.21 loss 4.56 helix 1.29 pae 0.17 i_pae 0.22 con 1.52 i_con 2.43 plddt 0.91 ptm 0.81 i_ptm 0.74 rg 2.97\n", - "101 models [4] recycles 1 hard 0 soft 1 temp 0.19 loss 4.00 helix 1.42 pae 0.14 i_pae 0.19 con 1.33 i_con 2.11 plddt 0.94 ptm 0.85 i_ptm 0.80 rg 2.98\n", - "102 models [4] recycles 1 hard 0 soft 1 temp 0.17 loss 3.84 helix 1.40 pae 0.14 i_pae 0.17 con 1.36 i_con 1.93 plddt 0.94 ptm 0.87 i_ptm 0.84 rg 2.93\n", - "103 models [4] recycles 1 hard 0 soft 1 temp 0.15 loss 3.82 helix 1.37 pae 0.13 i_pae 0.17 con 1.32 i_con 1.95 plddt 0.95 ptm 0.86 i_ptm 0.82 rg 2.93\n", - "104 models [4] recycles 1 hard 0 soft 1 temp 0.14 loss 3.63 helix 1.43 pae 0.12 i_pae 0.15 con 1.26 i_con 1.84 plddt 0.96 ptm 0.88 i_ptm 0.85 rg 2.94\n", - "105 models [3] recycles 1 hard 0 soft 1 temp 0.12 loss 3.61 helix 1.44 pae 0.12 i_pae 0.16 con 1.25 i_con 1.83 plddt 0.96 ptm 0.88 i_ptm 0.86 rg 2.97\n", - "106 models [0] recycles 1 hard 0 soft 1 temp 0.11 loss 3.75 helix 1.39 pae 0.12 i_pae 0.15 con 1.31 i_con 1.91 plddt 0.95 ptm 0.88 i_ptm 0.84 rg 2.91\n", - "107 models [4] recycles 1 hard 0 soft 1 temp 0.09 loss 3.71 helix 1.37 pae 0.13 i_pae 0.17 con 1.27 i_con 1.88 plddt 0.95 ptm 0.87 i_ptm 0.85 rg 2.96\n", - "108 models [2] recycles 1 hard 0 soft 1 temp 0.08 loss 3.80 helix 1.33 pae 0.13 i_pae 0.17 con 1.32 i_con 1.94 plddt 0.95 ptm 0.87 i_ptm 0.84 rg 2.90\n", - "109 models [3] recycles 1 hard 0 soft 1 temp 0.07 loss 3.59 helix 1.41 pae 0.12 i_pae 0.16 con 1.25 i_con 1.79 plddt 0.96 ptm 0.88 i_ptm 0.87 rg 2.97\n", - "110 models [3] recycles 1 hard 0 soft 1 temp 0.06 loss 3.64 helix 1.43 pae 0.12 i_pae 0.16 con 1.27 i_con 1.84 plddt 0.96 ptm 0.88 i_ptm 0.86 rg 2.97\n", - "111 models [0] recycles 1 hard 0 soft 1 temp 0.05 loss 3.54 helix 1.46 pae 0.12 i_pae 0.15 con 1.24 i_con 1.81 plddt 0.96 ptm 0.89 i_ptm 0.86 rg 2.86\n", - "112 models [4] recycles 1 hard 0 soft 1 temp 0.04 loss 3.69 helix 1.36 pae 0.12 i_pae 0.16 con 1.27 i_con 1.85 plddt 0.96 ptm 0.88 i_ptm 0.85 rg 3.00\n", - "113 models [0] recycles 1 hard 0 soft 1 temp 0.03 loss 3.59 helix 1.44 pae 0.12 i_pae 0.15 con 1.23 i_con 1.84 plddt 0.96 ptm 0.88 i_ptm 0.86 rg 2.89\n", - "114 models [0] recycles 1 hard 0 soft 1 temp 0.03 loss 3.57 helix 1.43 pae 0.12 i_pae 0.15 con 1.26 i_con 1.79 plddt 0.96 ptm 0.89 i_ptm 0.86 rg 2.93\n", - "115 models [0] recycles 1 hard 0 soft 1 temp 0.02 loss 3.47 helix 1.42 pae 0.12 i_pae 0.15 con 1.26 i_con 1.69 plddt 0.95 ptm 0.89 i_ptm 0.87 rg 2.90\n", - "116 models [4] recycles 1 hard 0 soft 1 temp 0.02 loss 4.30 helix 1.24 pae 0.15 i_pae 0.20 con 1.43 i_con 2.25 plddt 0.93 ptm 0.83 i_ptm 0.76 rg 2.99\n", - "117 models [1] recycles 1 hard 0 soft 1 temp 0.01 loss 3.47 helix 1.44 pae 0.12 i_pae 0.15 con 1.21 i_con 1.76 plddt 0.95 ptm 0.87 i_ptm 0.85 rg 2.86\n", - "118 models [3] recycles 1 hard 0 soft 1 temp 0.01 loss 3.59 helix 1.39 pae 0.12 i_pae 0.15 con 1.26 i_con 1.79 plddt 0.96 ptm 0.88 i_ptm 0.86 rg 2.92\n", - "119 models [2] recycles 1 hard 0 soft 1 temp 0.01 loss 4.57 helix 1.12 pae 0.15 i_pae 0.19 con 1.66 i_con 2.25 plddt 0.91 ptm 0.84 i_ptm 0.79 rg 3.00\n", - "120 models [4] recycles 1 hard 0 soft 1 temp 0.01 loss 4.18 helix 1.27 pae 0.14 i_pae 0.18 con 1.49 i_con 2.08 plddt 0.93 ptm 0.85 i_ptm 0.81 rg 3.00\n", - "Softmax trajectory pLDDT good, continuing: 0.95\n", - "Stage 3: One-hot Optimisation\n", - "121 models [0] recycles 1 hard 1 soft 1 temp 0.01 loss 3.54 helix 1.38 pae 0.12 i_pae 0.15 con 1.23 i_con 1.75 plddt 0.95 ptm 0.88 i_ptm 0.86 rg 2.98\n", - "122 models [0] recycles 1 hard 1 soft 1 temp 0.01 loss 3.47 helix 1.43 pae 0.11 i_pae 0.14 con 1.21 i_con 1.73 plddt 0.96 ptm 0.89 i_ptm 0.87 rg 2.95\n", - "123 models [1] recycles 1 hard 1 soft 1 temp 0.01 loss 5.00 helix 0.95 pae 0.17 i_pae 0.22 con 1.65 i_con 2.59 plddt 0.88 ptm 0.81 i_ptm 0.70 rg 3.10\n", - "124 models [1] recycles 1 hard 1 soft 1 temp 0.01 loss 5.05 helix 0.93 pae 0.17 i_pae 0.22 con 1.71 i_con 2.54 plddt 0.87 ptm 0.81 i_ptm 0.70 rg 3.18\n", - "125 models [3] recycles 1 hard 1 soft 1 temp 0.01 loss 5.21 helix 0.93 pae 0.19 i_pae 0.25 con 1.70 i_con 2.73 plddt 0.86 ptm 0.79 i_ptm 0.66 rg 3.08\n", - "One-hot trajectory pLDDT good, continuing: 0.96\n", - "Stage 4: PSSM Semigreedy Optimisation\n", - "Running semigreedy optimization...\n", - "126 models [0] recycles 1 hard 1 soft 0 temp 1 loss 3.50 helix 1.39 pae 0.12 i_pae 0.15 con 1.25 i_con 1.70 plddt 0.95 ptm 0.89 i_ptm 0.87 rg 2.97\n", - "127 models [1] recycles 1 hard 1 soft 0 temp 1 loss 3.52 helix 1.38 pae 0.12 i_pae 0.15 con 1.21 i_con 1.75 plddt 0.96 ptm 0.88 i_ptm 0.86 rg 3.01\n", - "128 models [2] recycles 1 hard 1 soft 0 temp 1 loss 3.75 helix 1.35 pae 0.12 i_pae 0.16 con 1.25 i_con 1.91 plddt 0.95 ptm 0.87 i_ptm 0.83 rg 3.04\n", - "129 models [4] recycles 1 hard 1 soft 0 temp 1 loss 3.69 helix 1.30 pae 0.12 i_pae 0.16 con 1.25 i_con 1.84 plddt 0.95 ptm 0.88 i_ptm 0.84 rg 3.05\n", - "130 models [0] recycles 1 hard 1 soft 0 temp 1 loss 3.68 helix 1.37 pae 0.12 i_pae 0.15 con 1.27 i_con 1.84 plddt 0.95 ptm 0.88 i_ptm 0.85 rg 3.00\n", - "131 models [3] recycles 1 hard 1 soft 0 temp 1 loss 3.70 helix 1.34 pae 0.12 i_pae 0.16 con 1.31 i_con 1.80 plddt 0.95 ptm 0.88 i_ptm 0.87 rg 3.05\n", - "132 models [3] recycles 1 hard 1 soft 0 temp 1 loss 3.67 helix 1.31 pae 0.12 i_pae 0.16 con 1.28 i_con 1.78 plddt 0.95 ptm 0.88 i_ptm 0.87 rg 3.05\n", - "133 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.15 helix 1.20 pae 0.13 i_pae 0.17 con 1.45 i_con 2.05 plddt 0.93 ptm 0.85 i_ptm 0.81 rg 3.08\n", - "134 models [2] recycles 1 hard 1 soft 0 temp 1 loss 5.92 helix 0.91 pae 0.24 i_pae 0.33 con 2.02 i_con 3.09 plddt 0.81 ptm 0.73 i_ptm 0.54 rg 3.03\n", - "135 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.56 helix 1.13 pae 0.14 i_pae 0.18 con 1.73 i_con 2.15 plddt 0.89 ptm 0.86 i_ptm 0.81 rg 3.09\n", - "136 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.40 helix 1.14 pae 0.16 i_pae 0.20 con 1.61 i_con 2.11 plddt 0.91 ptm 0.84 i_ptm 0.80 rg 3.07\n", - "137 models [2] recycles 1 hard 1 soft 0 temp 1 loss 5.63 helix 1.00 pae 0.26 i_pae 0.28 con 2.25 i_con 2.59 plddt 0.78 ptm 0.80 i_ptm 0.76 rg 3.06\n", - "138 models [2] recycles 1 hard 1 soft 0 temp 1 loss 5.38 helix 1.09 pae 0.27 i_pae 0.30 con 2.28 i_con 2.66 plddt 0.75 ptm 0.79 i_ptm 0.75 rg 1.95\n", - "139 models [4] recycles 1 hard 1 soft 0 temp 1 loss 5.26 helix 1.04 pae 0.25 i_pae 0.28 con 2.23 i_con 2.59 plddt 0.76 ptm 0.81 i_ptm 0.74 rg 1.94\n", - "140 models [3] recycles 1 hard 1 soft 0 temp 1 loss 8.54 helix 0.81 pae 0.59 i_pae 0.70 con 3.68 i_con 4.23 plddt 0.43 ptm 0.57 i_ptm 0.17 rg 1.54\n", - "Trajectory successful, final pLDDT: 0.95\n", - "Starting trajectory took: 0 hours, 5 minutes, 9 seconds\n", - "\n", - "Fixing interface residues: B4,B7,B8,B11,B12,B14,B15,B16,B18,B19,B22,B23,B25,B26,B29,B62,B63,B66,B67,B70,B71,B74,B77,B81\n", - "PDL1_l92_s843319_mpnn1 passed all filters\n", - "Base AF2 filters not passed for PDL1_l92_s843319_mpnn2, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l92_s843319_mpnn2, skipping interface scoring\n", - "Unmet filter conditions for PDL1_l92_s843319_mpnn2\n", - "Unmet filter conditions for PDL1_l92_s843319_mpnn3\n", - "Base AF2 filters not passed for PDL1_l92_s843319_mpnn4, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l92_s843319_mpnn4, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l92_s843319_mpnn4, skipping interface scoring\n", - "PDL1_l92_s843319_mpnn4 passed all filters\n", - "Found 2 MPNN designs passing filters\n", - "Design and validation of trajectory PDL1_l92_s843319 took: 0 hours, 8 minutes, 15 seconds\n", - "Starting trajectory: PDL1_l128_s89368\n", - "Stage 1: Test Logits\n", - "1 models [0] recycles 1 hard 0 soft 0.02 temp 1 loss 14.50 helix 1.76 pae 0.85 i_pae 0.89 con 4.88 i_con 4.93 plddt 0.33 ptm 0.46 i_ptm 0.10 rg 15.57\n", - "2 models [1] recycles 1 hard 0 soft 0.04 temp 1 loss 13.17 helix 1.40 pae 0.83 i_pae 0.87 con 4.72 i_con 4.95 plddt 0.35 ptm 0.46 i_ptm 0.09 rg 11.29\n", - "3 models [3] recycles 1 hard 0 soft 0.05 temp 1 loss 12.42 helix 1.44 pae 0.80 i_pae 0.85 con 4.40 i_con 4.59 plddt 0.32 ptm 0.48 i_ptm 0.11 rg 11.14\n", - "4 models [2] recycles 1 hard 0 soft 0.07 temp 1 loss 10.45 helix 1.31 pae 0.84 i_pae 0.87 con 4.51 i_con 4.57 plddt 0.28 ptm 0.46 i_ptm 0.10 rg 4.08\n", - "5 models [1] recycles 1 hard 0 soft 0.09 temp 1 loss 9.50 helix 1.32 pae 0.76 i_pae 0.83 con 4.13 i_con 4.66 plddt 0.35 ptm 0.47 i_ptm 0.11 rg 2.01\n", - "6 models [2] recycles 1 hard 0 soft 0.11 temp 1 loss 9.23 helix 0.86 pae 0.71 i_pae 0.81 con 3.90 i_con 4.63 plddt 0.41 ptm 0.47 i_ptm 0.12 rg 1.64\n", - "7 models [2] recycles 1 hard 0 soft 0.13 temp 1 loss 8.94 helix 0.89 pae 0.71 i_pae 0.84 con 3.84 i_con 4.76 plddt 0.42 ptm 0.46 i_ptm 0.11 rg 0.46\n", - "8 models [1] recycles 1 hard 0 soft 0.14 temp 1 loss 8.87 helix 1.03 pae 0.69 i_pae 0.81 con 3.76 i_con 4.70 plddt 0.43 ptm 0.48 i_ptm 0.13 rg 0.88\n", - "9 models [0] recycles 1 hard 0 soft 0.16 temp 1 loss 8.47 helix 0.94 pae 0.66 i_pae 0.78 con 3.67 i_con 4.60 plddt 0.43 ptm 0.49 i_ptm 0.14 rg 0.14\n", - "10 models [2] recycles 1 hard 0 soft 0.18 temp 1 loss 8.52 helix 0.99 pae 0.69 i_pae 0.84 con 3.73 i_con 4.74 plddt 0.42 ptm 0.47 i_ptm 0.11 rg -0.38\n", - "11 models [4] recycles 1 hard 0 soft 0.20 temp 1 loss 8.54 helix 1.00 pae 0.71 i_pae 0.83 con 3.88 i_con 4.63 plddt 0.37 ptm 0.47 i_ptm 0.11 rg -0.48\n", - "12 models [0] recycles 1 hard 0 soft 0.22 temp 1 loss 8.31 helix 0.95 pae 0.66 i_pae 0.79 con 3.71 i_con 4.61 plddt 0.43 ptm 0.49 i_ptm 0.13 rg -0.58\n", - "13 models [2] recycles 1 hard 0 soft 0.23 temp 1 loss 8.05 helix 0.91 pae 0.63 i_pae 0.79 con 3.40 i_con 4.61 plddt 0.47 ptm 0.48 i_ptm 0.14 rg -0.38\n", - "14 models [4] recycles 1 hard 0 soft 0.25 temp 1 loss 7.80 helix 0.93 pae 0.60 i_pae 0.71 con 3.43 i_con 4.39 plddt 0.48 ptm 0.53 i_ptm 0.25 rg -0.48\n", - "15 models [1] recycles 1 hard 0 soft 0.27 temp 1 loss 7.95 helix 1.04 pae 0.59 i_pae 0.73 con 3.31 i_con 4.50 plddt 0.53 ptm 0.52 i_ptm 0.19 rg 0.18\n", - "16 models [2] recycles 1 hard 0 soft 0.29 temp 1 loss 7.64 helix 1.00 pae 0.58 i_pae 0.73 con 3.14 i_con 4.42 plddt 0.52 ptm 0.51 i_ptm 0.18 rg -0.05\n", - "17 models [0] recycles 1 hard 0 soft 0.31 temp 1 loss 7.03 helix 1.08 pae 0.49 i_pae 0.62 con 2.79 i_con 4.15 plddt 0.62 ptm 0.57 i_ptm 0.30 rg 0.29\n", - "18 models [2] recycles 1 hard 0 soft 0.32 temp 1 loss 7.40 helix 1.09 pae 0.58 i_pae 0.77 con 2.88 i_con 4.43 plddt 0.60 ptm 0.49 i_ptm 0.17 rg 0.10\n", - "19 models [0] recycles 1 hard 0 soft 0.34 temp 1 loss 6.62 helix 0.97 pae 0.43 i_pae 0.54 con 2.76 i_con 3.90 plddt 0.65 ptm 0.62 i_ptm 0.44 rg -0.13\n", - "20 models [3] recycles 1 hard 0 soft 0.36 temp 1 loss 6.16 helix 1.20 pae 0.37 i_pae 0.40 con 2.50 i_con 3.58 plddt 0.72 ptm 0.74 i_ptm 0.68 rg 0.70\n", - "21 models [4] recycles 1 hard 0 soft 0.38 temp 1 loss 6.14 helix 1.01 pae 0.38 i_pae 0.45 con 2.59 i_con 3.65 plddt 0.68 ptm 0.68 i_ptm 0.56 rg -0.17\n", - "22 models [1] recycles 1 hard 0 soft 0.40 temp 1 loss 6.64 helix 0.95 pae 0.43 i_pae 0.47 con 3.06 i_con 3.67 plddt 0.60 ptm 0.69 i_ptm 0.60 rg -0.27\n", - "23 models [1] recycles 1 hard 0 soft 0.41 temp 1 loss 6.06 helix 0.98 pae 0.32 i_pae 0.35 con 2.62 i_con 3.51 plddt 0.72 ptm 0.78 i_ptm 0.79 rg 0.08\n", - "24 models [0] recycles 1 hard 0 soft 0.43 temp 1 loss 5.56 helix 1.12 pae 0.29 i_pae 0.32 con 2.41 i_con 3.33 plddt 0.75 ptm 0.79 i_ptm 0.78 rg -0.09\n", - "25 models [4] recycles 1 hard 0 soft 0.45 temp 1 loss 5.36 helix 1.09 pae 0.24 i_pae 0.29 con 2.17 i_con 3.36 plddt 0.81 ptm 0.82 i_ptm 0.81 rg 0.03\n", - "26 models [0] recycles 1 hard 0 soft 0.47 temp 1 loss 6.38 helix 0.95 pae 0.42 i_pae 0.57 con 2.57 i_con 3.91 plddt 0.69 ptm 0.61 i_ptm 0.37 rg -0.35\n", - "27 models [3] recycles 1 hard 0 soft 0.49 temp 1 loss 5.35 helix 1.16 pae 0.26 i_pae 0.28 con 2.21 i_con 3.32 plddt 0.80 ptm 0.83 i_ptm 0.84 rg 0.00\n", - "28 models [4] recycles 1 hard 0 soft 0.50 temp 1 loss 5.20 helix 1.14 pae 0.27 i_pae 0.30 con 2.16 i_con 3.24 plddt 0.78 ptm 0.82 i_ptm 0.82 rg -0.09\n", - "29 models [2] recycles 1 hard 0 soft 0.52 temp 1 loss 5.68 helix 1.16 pae 0.30 i_pae 0.35 con 2.27 i_con 3.56 plddt 0.76 ptm 0.76 i_ptm 0.74 rg 0.01\n", - "30 models [0] recycles 1 hard 0 soft 0.54 temp 1 loss 5.45 helix 1.14 pae 0.25 i_pae 0.28 con 2.21 i_con 3.46 plddt 0.79 ptm 0.81 i_ptm 0.78 rg -0.10\n", - "31 models [2] recycles 1 hard 0 soft 0.56 temp 1 loss 5.35 helix 1.26 pae 0.30 i_pae 0.33 con 2.20 i_con 3.33 plddt 0.78 ptm 0.78 i_ptm 0.79 rg 0.00\n", - "32 models [2] recycles 1 hard 0 soft 0.58 temp 1 loss 5.05 helix 1.28 pae 0.21 i_pae 0.25 con 1.93 i_con 3.42 plddt 0.86 ptm 0.84 i_ptm 0.82 rg -0.12\n", - "33 models [2] recycles 1 hard 0 soft 0.59 temp 1 loss 5.00 helix 1.24 pae 0.22 i_pae 0.26 con 1.97 i_con 3.31 plddt 0.83 ptm 0.84 i_ptm 0.83 rg -0.17\n", - "34 models [2] recycles 1 hard 0 soft 0.61 temp 1 loss 4.86 helix 1.24 pae 0.27 i_pae 0.30 con 2.06 i_con 3.05 plddt 0.81 ptm 0.81 i_ptm 0.83 rg -0.15\n", - "35 models [0] recycles 1 hard 0 soft 0.63 temp 1 loss 5.17 helix 1.10 pae 0.22 i_pae 0.25 con 2.06 i_con 3.29 plddt 0.83 ptm 0.83 i_ptm 0.81 rg 0.04\n", - "36 models [2] recycles 1 hard 0 soft 0.65 temp 1 loss 4.79 helix 1.28 pae 0.21 i_pae 0.25 con 1.90 i_con 3.19 plddt 0.85 ptm 0.85 i_ptm 0.84 rg -0.17\n", - "37 models [4] recycles 1 hard 0 soft 0.67 temp 1 loss 5.09 helix 1.20 pae 0.24 i_pae 0.28 con 2.08 i_con 3.28 plddt 0.81 ptm 0.82 i_ptm 0.81 rg -0.21\n", - "38 models [1] recycles 1 hard 0 soft 0.68 temp 1 loss 5.08 helix 1.19 pae 0.20 i_pae 0.24 con 1.95 i_con 3.38 plddt 0.85 ptm 0.84 i_ptm 0.83 rg -0.11\n", - "39 models [4] recycles 1 hard 0 soft 0.70 temp 1 loss 5.47 helix 1.10 pae 0.26 i_pae 0.30 con 2.35 i_con 3.35 plddt 0.77 ptm 0.80 i_ptm 0.79 rg -0.25\n", - "40 models [0] recycles 1 hard 0 soft 0.72 temp 1 loss 4.79 helix 1.37 pae 0.18 i_pae 0.22 con 1.72 i_con 3.40 plddt 0.89 ptm 0.86 i_ptm 0.83 rg -0.09\n", - "41 models [0] recycles 1 hard 0 soft 0.74 temp 1 loss 5.01 helix 1.24 pae 0.24 i_pae 0.26 con 2.02 i_con 3.24 plddt 0.81 ptm 0.83 i_ptm 0.82 rg -0.09\n", - "42 models [0] recycles 1 hard 0 soft 0.76 temp 1 loss 4.51 helix 1.39 pae 0.20 i_pae 0.23 con 1.80 i_con 3.05 plddt 0.86 ptm 0.85 i_ptm 0.84 rg -0.17\n", - "43 models [0] recycles 1 hard 0 soft 0.77 temp 1 loss 4.89 helix 1.31 pae 0.24 i_pae 0.29 con 1.88 i_con 3.32 plddt 0.81 ptm 0.79 i_ptm 0.75 rg -0.26\n", - "44 models [3] recycles 1 hard 0 soft 0.79 temp 1 loss 4.76 helix 1.33 pae 0.18 i_pae 0.22 con 1.79 i_con 3.31 plddt 0.88 ptm 0.86 i_ptm 0.83 rg -0.20\n", - "45 models [2] recycles 1 hard 0 soft 0.81 temp 1 loss 4.49 helix 1.37 pae 0.23 i_pae 0.26 con 1.82 i_con 2.99 plddt 0.84 ptm 0.84 i_ptm 0.85 rg -0.17\n", - "46 models [0] recycles 1 hard 0 soft 0.83 temp 1 loss 4.65 helix 1.33 pae 0.23 i_pae 0.26 con 1.92 i_con 3.02 plddt 0.82 ptm 0.83 i_ptm 0.84 rg -0.13\n", - "47 models [1] recycles 1 hard 0 soft 0.85 temp 1 loss 4.78 helix 1.40 pae 0.24 i_pae 0.27 con 2.01 i_con 3.07 plddt 0.82 ptm 0.82 i_ptm 0.84 rg -0.10\n", - "48 models [3] recycles 1 hard 0 soft 0.86 temp 1 loss 6.18 helix 1.01 pae 0.35 i_pae 0.40 con 2.61 i_con 3.70 plddt 0.69 ptm 0.70 i_ptm 0.59 rg -0.21\n", - "49 models [0] recycles 1 hard 0 soft 0.88 temp 1 loss 4.57 helix 1.34 pae 0.22 i_pae 0.25 con 1.89 i_con 2.95 plddt 0.83 ptm 0.84 i_ptm 0.85 rg -0.04\n", - "50 models [4] recycles 1 hard 0 soft 0.90 temp 1 loss 5.24 helix 1.14 pae 0.30 i_pae 0.32 con 2.35 i_con 3.04 plddt 0.74 ptm 0.79 i_ptm 0.82 rg 0.02\n", - "Initial trajectory pLDDT good, continuing: 0.84\n", - "Stage 1: Additional Logits Optimisation\n", - "51 models [1] recycles 1 hard 0 soft 0.04 temp 1 loss 5.54 helix 1.32 pae 0.27 i_pae 0.33 con 2.15 i_con 3.61 plddt 0.78 ptm 0.75 i_ptm 0.69 rg -0.03\n", - "52 models [1] recycles 1 hard 0 soft 0.08 temp 1 loss 4.65 helix 1.47 pae 0.21 i_pae 0.25 con 1.85 i_con 3.17 plddt 0.85 ptm 0.85 i_ptm 0.84 rg -0.21\n", - "53 models [2] recycles 1 hard 0 soft 0.12 temp 1 loss 4.51 helix 1.35 pae 0.18 i_pae 0.23 con 1.65 i_con 3.22 plddt 0.90 ptm 0.87 i_ptm 0.85 rg -0.23\n", - "54 models [2] recycles 1 hard 0 soft 0.16 temp 1 loss 9.29 helix 1.03 pae 0.75 i_pae 0.84 con 3.94 i_con 4.69 plddt 0.37 ptm 0.46 i_ptm 0.10 rg 1.60\n", - "55 models [2] recycles 1 hard 0 soft 0.20 temp 1 loss 4.47 helix 1.39 pae 0.21 i_pae 0.24 con 1.81 i_con 3.00 plddt 0.87 ptm 0.86 i_ptm 0.86 rg -0.16\n", - "56 models [4] recycles 1 hard 0 soft 0.24 temp 1 loss 4.18 helix 1.42 pae 0.16 i_pae 0.20 con 1.62 i_con 2.97 plddt 0.90 ptm 0.88 i_ptm 0.87 rg -0.29\n", - "57 models [0] recycles 1 hard 0 soft 0.28 temp 1 loss 5.09 helix 1.25 pae 0.27 i_pae 0.29 con 2.25 i_con 3.11 plddt 0.76 ptm 0.82 i_ptm 0.84 rg -0.18\n", - "58 models [4] recycles 1 hard 0 soft 0.32 temp 1 loss 4.06 helix 1.46 pae 0.15 i_pae 0.19 con 1.57 i_con 2.93 plddt 0.92 ptm 0.88 i_ptm 0.86 rg -0.33\n", - "59 models [2] recycles 1 hard 0 soft 0.36 temp 1 loss 4.04 helix 1.55 pae 0.14 i_pae 0.19 con 1.49 i_con 3.01 plddt 0.94 ptm 0.89 i_ptm 0.86 rg -0.30\n", - "60 models [1] recycles 1 hard 0 soft 0.40 temp 1 loss 4.08 helix 1.56 pae 0.13 i_pae 0.18 con 1.43 i_con 3.13 plddt 0.94 ptm 0.89 i_ptm 0.86 rg -0.33\n", - "61 models [1] recycles 1 hard 0 soft 0.44 temp 1 loss 4.05 helix 1.57 pae 0.13 i_pae 0.18 con 1.45 i_con 3.08 plddt 0.94 ptm 0.89 i_ptm 0.87 rg -0.30\n", - "62 models [2] recycles 1 hard 0 soft 0.48 temp 1 loss 4.02 helix 1.59 pae 0.13 i_pae 0.18 con 1.42 i_con 3.06 plddt 0.95 ptm 0.89 i_ptm 0.87 rg -0.23\n", - "63 models [2] recycles 1 hard 0 soft 0.52 temp 1 loss 4.38 helix 1.50 pae 0.15 i_pae 0.20 con 1.58 i_con 3.24 plddt 0.92 ptm 0.87 i_ptm 0.84 rg -0.26\n", - "64 models [4] recycles 1 hard 0 soft 0.56 temp 1 loss 4.02 helix 1.55 pae 0.14 i_pae 0.18 con 1.45 i_con 3.02 plddt 0.94 ptm 0.89 i_ptm 0.86 rg -0.25\n", - "65 models [3] recycles 1 hard 0 soft 0.60 temp 1 loss 4.06 helix 1.61 pae 0.13 i_pae 0.18 con 1.47 i_con 3.08 plddt 0.93 ptm 0.89 i_ptm 0.87 rg -0.28\n", - "66 models [3] recycles 1 hard 0 soft 0.64 temp 1 loss 4.19 helix 1.56 pae 0.14 i_pae 0.19 con 1.53 i_con 3.14 plddt 0.92 ptm 0.88 i_ptm 0.86 rg -0.33\n", - "67 models [4] recycles 1 hard 0 soft 0.68 temp 1 loss 4.18 helix 1.43 pae 0.15 i_pae 0.19 con 1.54 i_con 3.04 plddt 0.92 ptm 0.89 i_ptm 0.86 rg -0.24\n", - "68 models [1] recycles 1 hard 0 soft 0.72 temp 1 loss 5.50 helix 1.14 pae 0.34 i_pae 0.37 con 2.36 i_con 3.24 plddt 0.69 ptm 0.76 i_ptm 0.85 rg 0.12\n", - "69 models [4] recycles 1 hard 0 soft 0.76 temp 1 loss 4.03 helix 1.61 pae 0.13 i_pae 0.18 con 1.42 i_con 3.06 plddt 0.94 ptm 0.89 i_ptm 0.86 rg -0.20\n", - "70 models [4] recycles 1 hard 0 soft 0.80 temp 1 loss 4.72 helix 1.38 pae 0.19 i_pae 0.23 con 1.94 i_con 3.14 plddt 0.85 ptm 0.86 i_ptm 0.86 rg -0.22\n", - "71 models [1] recycles 1 hard 0 soft 0.84 temp 1 loss 4.88 helix 1.21 pae 0.19 i_pae 0.23 con 1.90 i_con 3.28 plddt 0.85 ptm 0.85 i_ptm 0.84 rg -0.19\n", - "72 models [4] recycles 1 hard 0 soft 0.88 temp 1 loss 4.61 helix 1.27 pae 0.17 i_pae 0.22 con 1.79 i_con 3.15 plddt 0.88 ptm 0.86 i_ptm 0.84 rg -0.22\n", - "73 models [3] recycles 1 hard 0 soft 0.92 temp 1 loss 4.45 helix 1.37 pae 0.17 i_pae 0.21 con 1.63 i_con 3.22 plddt 0.90 ptm 0.86 i_ptm 0.83 rg -0.32\n", - "74 models [4] recycles 1 hard 0 soft 0.96 temp 1 loss 5.66 helix 0.97 pae 0.33 i_pae 0.35 con 2.67 i_con 3.14 plddt 0.68 ptm 0.78 i_ptm 0.81 rg -0.25\n", - "75 models [4] recycles 1 hard 0 soft 1 temp 1 loss 4.74 helix 1.24 pae 0.17 i_pae 0.23 con 1.82 i_con 3.24 plddt 0.88 ptm 0.85 i_ptm 0.81 rg -0.20\n", - "Optimised logit trajectory pLDDT: 0.94\n", - "Stage 2: Softmax Optimisation\n", - "76 models [3] recycles 1 hard 0 soft 1 temp 0.96 loss 4.57 helix 1.29 pae 0.18 i_pae 0.22 con 1.73 i_con 3.20 plddt 0.88 ptm 0.86 i_ptm 0.83 rg -0.31\n", - "77 models [3] recycles 1 hard 0 soft 1 temp 0.91 loss 4.46 helix 1.36 pae 0.18 i_pae 0.22 con 1.69 i_con 3.14 plddt 0.89 ptm 0.85 i_ptm 0.83 rg -0.26\n", - "78 models [4] recycles 1 hard 0 soft 1 temp 0.87 loss 4.24 helix 1.45 pae 0.14 i_pae 0.19 con 1.53 i_con 3.14 plddt 0.93 ptm 0.87 i_ptm 0.84 rg -0.29\n", - "79 models [4] recycles 1 hard 0 soft 1 temp 0.83 loss 4.14 helix 1.54 pae 0.14 i_pae 0.19 con 1.54 i_con 3.05 plddt 0.93 ptm 0.86 i_ptm 0.83 rg -0.30\n", - "80 models [3] recycles 1 hard 0 soft 1 temp 0.79 loss 4.10 helix 1.54 pae 0.13 i_pae 0.18 con 1.45 i_con 3.12 plddt 0.94 ptm 0.88 i_ptm 0.86 rg -0.28\n", - "81 models [4] recycles 1 hard 0 soft 1 temp 0.75 loss 3.93 helix 1.55 pae 0.14 i_pae 0.18 con 1.47 i_con 2.94 plddt 0.94 ptm 0.88 i_ptm 0.86 rg -0.31\n", - "82 models [0] recycles 1 hard 0 soft 1 temp 0.72 loss 6.32 helix 1.29 pae 0.47 i_pae 0.84 con 1.72 i_con 4.80 plddt 0.83 ptm 0.50 i_ptm 0.11 rg -0.47\n", - "83 models [0] recycles 1 hard 0 soft 1 temp 0.68 loss 6.05 helix 1.33 pae 0.38 i_pae 0.68 con 1.58 i_con 4.69 plddt 0.87 ptm 0.56 i_ptm 0.22 rg -0.28\n", - "84 models [1] recycles 1 hard 0 soft 1 temp 0.64 loss 4.12 helix 1.49 pae 0.15 i_pae 0.20 con 1.56 i_con 3.00 plddt 0.91 ptm 0.87 i_ptm 0.84 rg -0.27\n", - "85 models [3] recycles 1 hard 0 soft 1 temp 0.61 loss 4.56 helix 1.36 pae 0.16 i_pae 0.22 con 1.71 i_con 3.24 plddt 0.89 ptm 0.85 i_ptm 0.81 rg -0.31\n", - "86 models [0] recycles 1 hard 0 soft 1 temp 0.58 loss 4.14 helix 1.46 pae 0.14 i_pae 0.19 con 1.46 i_con 3.11 plddt 0.93 ptm 0.86 i_ptm 0.82 rg -0.29\n", - "87 models [1] recycles 1 hard 0 soft 1 temp 0.54 loss 4.08 helix 1.62 pae 0.14 i_pae 0.20 con 1.43 i_con 3.14 plddt 0.93 ptm 0.86 i_ptm 0.81 rg -0.32\n", - "88 models [1] recycles 1 hard 0 soft 1 temp 0.51 loss 3.97 helix 1.66 pae 0.14 i_pae 0.19 con 1.40 i_con 3.08 plddt 0.94 ptm 0.87 i_ptm 0.83 rg -0.33\n", - "89 models [2] recycles 1 hard 0 soft 1 temp 0.48 loss 4.17 helix 1.46 pae 0.16 i_pae 0.21 con 1.47 i_con 3.12 plddt 0.92 ptm 0.87 i_ptm 0.83 rg -0.29\n", - "90 models [3] recycles 1 hard 0 soft 1 temp 0.45 loss 4.06 helix 1.61 pae 0.13 i_pae 0.18 con 1.45 i_con 3.08 plddt 0.94 ptm 0.88 i_ptm 0.86 rg -0.23\n", - "91 models [3] recycles 1 hard 0 soft 1 temp 0.42 loss 4.12 helix 1.60 pae 0.14 i_pae 0.19 con 1.43 i_con 3.16 plddt 0.94 ptm 0.87 i_ptm 0.84 rg -0.26\n", - "92 models [2] recycles 1 hard 0 soft 1 temp 0.39 loss 4.13 helix 1.61 pae 0.13 i_pae 0.18 con 1.43 i_con 3.18 plddt 0.94 ptm 0.88 i_ptm 0.86 rg -0.30\n", - "93 models [0] recycles 1 hard 0 soft 1 temp 0.37 loss 4.34 helix 1.43 pae 0.16 i_pae 0.21 con 1.51 i_con 3.24 plddt 0.91 ptm 0.84 i_ptm 0.78 rg -0.28\n", - "94 models [4] recycles 1 hard 0 soft 1 temp 0.34 loss 4.19 helix 1.42 pae 0.15 i_pae 0.20 con 1.65 i_con 2.97 plddt 0.91 ptm 0.87 i_ptm 0.85 rg -0.34\n", - "95 models [2] recycles 1 hard 0 soft 1 temp 0.32 loss 4.43 helix 1.44 pae 0.17 i_pae 0.22 con 1.75 i_con 3.10 plddt 0.89 ptm 0.86 i_ptm 0.83 rg -0.32\n", - "96 models [1] recycles 1 hard 0 soft 1 temp 0.29 loss 4.15 helix 1.47 pae 0.16 i_pae 0.20 con 1.54 i_con 3.03 plddt 0.91 ptm 0.87 i_ptm 0.86 rg -0.27\n", - "97 models [0] recycles 1 hard 0 soft 1 temp 0.27 loss 4.01 helix 1.47 pae 0.14 i_pae 0.18 con 1.47 i_con 3.00 plddt 0.93 ptm 0.88 i_ptm 0.86 rg -0.32\n", - "98 models [0] recycles 1 hard 0 soft 1 temp 0.25 loss 4.51 helix 1.45 pae 0.18 i_pae 0.22 con 1.80 i_con 3.13 plddt 0.87 ptm 0.86 i_ptm 0.85 rg -0.33\n", - "99 models [3] recycles 1 hard 0 soft 1 temp 0.23 loss 5.35 helix 1.27 pae 0.24 i_pae 0.28 con 2.35 i_con 3.33 plddt 0.77 ptm 0.81 i_ptm 0.81 rg -0.35\n", - "100 models [2] recycles 1 hard 0 soft 1 temp 0.21 loss 5.16 helix 1.32 pae 0.23 i_pae 0.28 con 2.18 i_con 3.30 plddt 0.79 ptm 0.81 i_ptm 0.80 rg -0.27\n", - "101 models [2] recycles 1 hard 0 soft 1 temp 0.19 loss 5.23 helix 1.15 pae 0.25 i_pae 0.29 con 2.30 i_con 3.21 plddt 0.78 ptm 0.81 i_ptm 0.82 rg -0.31\n", - "102 models [2] recycles 1 hard 0 soft 1 temp 0.17 loss 4.52 helix 1.40 pae 0.20 i_pae 0.24 con 1.89 i_con 3.02 plddt 0.84 ptm 0.85 i_ptm 0.85 rg -0.33\n", - "103 models [4] recycles 1 hard 0 soft 1 temp 0.15 loss 5.14 helix 1.25 pae 0.29 i_pae 0.32 con 2.40 i_con 3.02 plddt 0.73 ptm 0.80 i_ptm 0.83 rg -0.29\n", - "104 models [0] recycles 1 hard 0 soft 1 temp 0.14 loss 4.67 helix 1.36 pae 0.19 i_pae 0.23 con 1.96 i_con 3.06 plddt 0.84 ptm 0.86 i_ptm 0.84 rg -0.21\n", - "105 models [1] recycles 1 hard 0 soft 1 temp 0.12 loss 4.76 helix 1.34 pae 0.20 i_pae 0.24 con 2.00 i_con 3.11 plddt 0.84 ptm 0.85 i_ptm 0.85 rg -0.24\n", - "106 models [3] recycles 1 hard 0 soft 1 temp 0.11 loss 4.95 helix 1.28 pae 0.23 i_pae 0.26 con 2.14 i_con 3.12 plddt 0.81 ptm 0.83 i_ptm 0.85 rg -0.26\n", - "107 models [3] recycles 1 hard 0 soft 1 temp 0.09 loss 4.74 helix 1.40 pae 0.20 i_pae 0.24 con 1.96 i_con 3.18 plddt 0.84 ptm 0.85 i_ptm 0.85 rg -0.33\n", - "108 models [4] recycles 1 hard 0 soft 1 temp 0.08 loss 4.70 helix 1.31 pae 0.23 i_pae 0.27 con 2.10 i_con 2.93 plddt 0.80 ptm 0.83 i_ptm 0.83 rg -0.30\n", - "109 models [2] recycles 1 hard 0 soft 1 temp 0.07 loss 4.68 helix 1.33 pae 0.20 i_pae 0.25 con 1.94 i_con 3.09 plddt 0.84 ptm 0.84 i_ptm 0.83 rg -0.25\n", - "110 models [1] recycles 1 hard 0 soft 1 temp 0.06 loss 4.72 helix 1.35 pae 0.20 i_pae 0.24 con 1.95 i_con 3.10 plddt 0.83 ptm 0.85 i_ptm 0.85 rg -0.21\n", - "111 models [1] recycles 1 hard 0 soft 1 temp 0.05 loss 4.64 helix 1.40 pae 0.21 i_pae 0.24 con 1.94 i_con 3.06 plddt 0.83 ptm 0.85 i_ptm 0.85 rg -0.21\n", - "112 models [2] recycles 1 hard 0 soft 1 temp 0.04 loss 4.68 helix 1.41 pae 0.22 i_pae 0.26 con 1.99 i_con 3.07 plddt 0.83 ptm 0.83 i_ptm 0.83 rg -0.32\n", - "113 models [4] recycles 1 hard 0 soft 1 temp 0.03 loss 4.84 helix 1.35 pae 0.22 i_pae 0.26 con 2.12 i_con 3.08 plddt 0.80 ptm 0.83 i_ptm 0.83 rg -0.30\n", - "114 models [0] recycles 1 hard 0 soft 1 temp 0.03 loss 5.25 helix 1.33 pae 0.22 i_pae 0.28 con 2.06 i_con 3.51 plddt 0.81 ptm 0.78 i_ptm 0.72 rg -0.25\n", - "115 models [0] recycles 1 hard 0 soft 1 temp 0.02 loss 4.67 helix 1.44 pae 0.19 i_pae 0.23 con 1.93 i_con 3.11 plddt 0.84 ptm 0.86 i_ptm 0.84 rg -0.20\n", - "116 models [2] recycles 1 hard 0 soft 1 temp 0.02 loss 4.76 helix 1.38 pae 0.23 i_pae 0.27 con 2.04 i_con 3.05 plddt 0.81 ptm 0.83 i_ptm 0.84 rg -0.21\n", - "117 models [0] recycles 1 hard 0 soft 1 temp 0.01 loss 4.64 helix 1.40 pae 0.21 i_pae 0.24 con 1.98 i_con 3.01 plddt 0.83 ptm 0.85 i_ptm 0.85 rg -0.19\n", - "118 models [1] recycles 1 hard 0 soft 1 temp 0.01 loss 4.74 helix 1.36 pae 0.19 i_pae 0.22 con 1.89 i_con 3.21 plddt 0.85 ptm 0.86 i_ptm 0.85 rg -0.23\n", - "119 models [0] recycles 1 hard 0 soft 1 temp 0.01 loss 4.58 helix 1.48 pae 0.18 i_pae 0.22 con 1.82 i_con 3.13 plddt 0.86 ptm 0.86 i_ptm 0.86 rg -0.14\n", - "120 models [1] recycles 1 hard 0 soft 1 temp 0.01 loss 4.67 helix 1.42 pae 0.20 i_pae 0.24 con 1.88 i_con 3.14 plddt 0.84 ptm 0.84 i_ptm 0.83 rg -0.21\n", - "Softmax trajectory pLDDT good, continuing: 0.94\n", - "Stage 3: One-hot Optimisation\n", - "121 models [2] recycles 1 hard 1 soft 1 temp 0.01 loss 4.75 helix 1.32 pae 0.22 i_pae 0.26 con 2.05 i_con 2.99 plddt 0.80 ptm 0.84 i_ptm 0.85 rg -0.14\n", - "122 models [3] recycles 1 hard 1 soft 1 temp 0.01 loss 4.41 helix 1.51 pae 0.17 i_pae 0.21 con 1.71 i_con 3.10 plddt 0.86 ptm 0.87 i_ptm 0.86 rg -0.17\n", - "123 models [0] recycles 1 hard 1 soft 1 temp 0.01 loss 4.49 helix 1.49 pae 0.17 i_pae 0.21 con 1.75 i_con 3.13 plddt 0.85 ptm 0.87 i_ptm 0.86 rg -0.15\n", - "124 models [4] recycles 1 hard 1 soft 1 temp 0.01 loss 4.49 helix 1.41 pae 0.20 i_pae 0.23 con 1.88 i_con 2.95 plddt 0.82 ptm 0.86 i_ptm 0.86 rg -0.16\n", - "125 models [1] recycles 1 hard 1 soft 1 temp 0.01 loss 4.51 helix 1.48 pae 0.17 i_pae 0.21 con 1.78 i_con 3.12 plddt 0.85 ptm 0.87 i_ptm 0.86 rg -0.18\n", - "One-hot trajectory pLDDT good, continuing: 0.86\n", - "Stage 4: PSSM Semigreedy Optimisation\n", - "Running semigreedy optimization...\n", - "126 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.72 helix 1.33 pae 0.21 i_pae 0.25 con 2.02 i_con 3.02 plddt 0.81 ptm 0.85 i_ptm 0.85 rg -0.17\n", - "127 models [1] recycles 1 hard 1 soft 0 temp 1 loss 4.51 helix 1.46 pae 0.18 i_pae 0.21 con 1.79 i_con 3.10 plddt 0.84 ptm 0.87 i_ptm 0.86 rg -0.17\n", - "128 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.56 helix 1.41 pae 0.18 i_pae 0.22 con 1.84 i_con 3.05 plddt 0.83 ptm 0.86 i_ptm 0.84 rg -0.10\n", - "129 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.61 helix 1.38 pae 0.19 i_pae 0.23 con 1.89 i_con 3.05 plddt 0.82 ptm 0.86 i_ptm 0.84 rg -0.14\n", - "130 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.79 helix 1.29 pae 0.21 i_pae 0.25 con 2.01 i_con 3.05 plddt 0.81 ptm 0.85 i_ptm 0.85 rg -0.09\n", - "131 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.67 helix 1.32 pae 0.19 i_pae 0.23 con 1.88 i_con 3.09 plddt 0.84 ptm 0.86 i_ptm 0.85 rg -0.06\n", - "132 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.64 helix 1.43 pae 0.18 i_pae 0.22 con 1.83 i_con 3.17 plddt 0.84 ptm 0.86 i_ptm 0.84 rg -0.14\n", - "133 models [1] recycles 1 hard 1 soft 0 temp 1 loss 4.54 helix 1.43 pae 0.18 i_pae 0.21 con 1.80 i_con 3.10 plddt 0.85 ptm 0.87 i_ptm 0.85 rg -0.14\n", - "134 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.64 helix 1.42 pae 0.19 i_pae 0.22 con 1.89 i_con 3.10 plddt 0.83 ptm 0.86 i_ptm 0.85 rg -0.15\n", - "135 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.83 helix 1.28 pae 0.21 i_pae 0.24 con 1.98 i_con 3.12 plddt 0.82 ptm 0.85 i_ptm 0.84 rg -0.06\n", - "136 models [2] recycles 1 hard 1 soft 0 temp 1 loss 4.73 helix 1.30 pae 0.19 i_pae 0.23 con 1.90 i_con 3.10 plddt 0.84 ptm 0.86 i_ptm 0.84 rg -0.06\n", - "137 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.58 helix 1.41 pae 0.17 i_pae 0.21 con 1.76 i_con 3.15 plddt 0.86 ptm 0.87 i_ptm 0.84 rg -0.08\n", - "138 models [0] recycles 1 hard 1 soft 0 temp 1 loss 4.55 helix 1.44 pae 0.17 i_pae 0.21 con 1.74 i_con 3.16 plddt 0.86 ptm 0.87 i_ptm 0.85 rg -0.11\n", - "139 models [3] recycles 1 hard 1 soft 0 temp 1 loss 4.53 helix 1.54 pae 0.16 i_pae 0.20 con 1.68 i_con 3.25 plddt 0.88 ptm 0.87 i_ptm 0.84 rg -0.16\n", - "140 models [3] recycles 1 hard 1 soft 0 temp 1 loss 4.52 helix 1.50 pae 0.16 i_pae 0.20 con 1.69 i_con 3.22 plddt 0.88 ptm 0.87 i_ptm 0.84 rg -0.17\n", - "Trajectory successful, final pLDDT: 0.84\n", - "Starting trajectory took: 0 hours, 6 minutes, 52 seconds\n", - "\n", - "Fixing interface residues: B10,B13,B14,B15,B17,B18,B21,B22,B26,B29,B30,B33,B34,B36,B37,B40,B41,B43,B44\n", - "Unmet filter conditions for PDL1_l128_s89368_mpnn1\n", - "Unmet filter conditions for PDL1_l128_s89368_mpnn2\n", - "Unmet filter conditions for PDL1_l128_s89368_mpnn3\n", - "Base AF2 filters not passed for PDL1_l128_s89368_mpnn4, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l128_s89368_mpnn4, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l128_s89368_mpnn4, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l128_s89368_mpnn4, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l128_s89368_mpnn4, skipping interface scoring\n", - "Base AF2 filters not passed for PDL1_l128_s89368_mpnn4, skipping interface scoring\n" - ] - }, - { - "output_type": "error", - "ename": "KeyboardInterrupt", - "evalue": "", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 162\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 163\u001b[0m \u001b[0;31m### Predict mpnn redesigned binder complex using masked templates\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 164\u001b[0;31m mpnn_complex_statistics, pass_af2_filters = masked_binder_predict(complex_prediction_model,\n\u001b[0m\u001b[1;32m 165\u001b[0m \u001b[0mmpnn_sequence\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'seq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpnn_design_name\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 166\u001b[0m \u001b[0mtarget_settings\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"starting_pdb\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget_settings\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"chains\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/content/bindcraft/functions/colabdesign_utils.py\u001b[0m in \u001b[0;36mmasked_binder_predict\u001b[0;34m(prediction_model, binder_sequence, mpnn_design_name, target_pdb, chain, length, trajectory_pdb, prediction_models, advanced_settings, filters, design_paths, failure_csv, seed)\u001b[0m\n\u001b[1;32m 299\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mpass_af2_filters\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 300\u001b[0m \u001b[0mmpnn_relaxed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdesign_paths\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"MPNN/Relaxed\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34mf\"{mpnn_design_name}_model{model_num+1}.pdb\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 301\u001b[0;31m \u001b[0mpr_relax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomplex_pdb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpnn_relaxed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 302\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 303\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexists\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcomplex_pdb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/content/bindcraft/functions/pyrosetta_utils.py\u001b[0m in \u001b[0;36mpr_relax\u001b[0;34m(pdb_file, relaxed_pdb_path)\u001b[0m\n\u001b[1;32m 220\u001b[0m \u001b[0mfastrelax\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmin_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"lbfgs_armijo_nonmonotone\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 221\u001b[0m \u001b[0mfastrelax\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconstrain_relax_to_start_coords\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 222\u001b[0;31m \u001b[0mfastrelax\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpose\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 223\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 224\u001b[0m \u001b[0;31m# Align relaxed structure to original trajectory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } ] }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "id": "jdmYnBypaUHR" + } + }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "U5qKDGGabhZo" + }, + "outputs": [], "source": [ "#@title Consolidate & Rank Designs\n", "#@markdown ---\n", @@ -1724,453 +781,30 @@ "final_df.to_csv(final_csv, index=False)\n", "\n", "print(\"Designs ranked and final_designs_stats.csv generated\")" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "cellView": "form", - "id": "U5qKDGGabhZo", - "outputId": "b1cda50e-eeec-4b8d-9990-d551f7e52eec" - }, - "execution_count": 10, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Designs ranked and final_designs_stats.csv generated\n" - ] - } ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "ro9PQBE9zoIw" + }, + "outputs": [], "source": [ "#@title Top 20 Designs\n", "df = pd.read_csv(os.path.join(design_path, 'final_design_stats.csv'))\n", "df.head(20)" - ], - "metadata": { - "id": "ro9PQBE9zoIw", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 358 - }, - "cellView": "form", - "outputId": "d1fdad1d-7361-4e97-c1e1-b51939c15d3b" - }, - "execution_count": 12, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - " Rank Design Protocol Length Seed Helicity \\\n", - "0 1 PDL1_l145_s718363_mpnn3 4stage 145 718363 -0.3 \n", - "1 2 PDL1_l92_s843319_mpnn4 4stage 92 843319 -0.3 \n", - "2 3 PDL1_l92_s843319_mpnn1 4stage 92 843319 -0.3 \n", - "3 4 PDL1_l145_s718363_mpnn1 4stage 145 718363 -0.3 \n", - "\n", - " Target_Hotspot Sequence \\\n", - "0 NaN SELEEALKKYEEIHREFLKKINEATYALFRSAVYYEWAAEGKMSKE... \n", - "1 NaN SAMEEEEDRKHVVRMIEDIAEQNIHVARTDPRFSPAIQARLEEEMR... \n", - "2 NaN SMAELEEDRKHVVRMIEDIARQNIHVARTDPRFSPEIVEELEKRME... \n", - "3 NaN SRLEEAKEKYKELHREYLKKINEMTYNLFRSAVYKEWAAEGKMSEE... \n", - "\n", - " InterfaceResidues MPNN_score ... \\\n", - "0 B18,B21,B22,B25,B26,B29,B30,B32,B33,B36,B37,B4... 0.87 ... \n", - "1 B8,B11,B12,B14,B15,B18,B19,B22,B23,B26,B62,B63... 1.03 ... \n", - "2 B4,B7,B8,B11,B12,B14,B15,B18,B19,B21,B22,B23,B... 0.97 ... \n", - "3 B18,B21,B22,B25,B26,B29,B30,B32,B33,B36,B37,B4... 0.84 ... \n", - "\n", - " 1_Binder_RMSD 2_Binder_RMSD 3_Binder_RMSD 4_Binder_RMSD 5_Binder_RMSD \\\n", - "0 1.25 1.33 NaN NaN NaN \n", - "1 1.09 1.09 NaN NaN NaN \n", - "2 1.06 0.99 NaN NaN NaN \n", - "3 1.05 1.11 NaN NaN NaN \n", - "\n", - " DesignTime Notes TargetSettings Filters \\\n", - "0 0 hours, 2 minutes, 27 seconds NaN PDL1 default_filters \n", - "1 0 hours, 1 minutes, 47 seconds NaN PDL1 default_filters \n", - "2 0 hours, 2 minutes, 26 seconds NaN PDL1 default_filters \n", - "3 0 hours, 2 minutes, 47 seconds NaN PDL1 default_filters \n", - "\n", - " AdvancedSettings \n", - "0 4stage_multimer \n", - "1 4stage_multimer \n", - "2 4stage_multimer \n", - "3 4stage_multimer \n", - "\n", - "[4 rows x 232 columns]" - ], - "text/html": [ - "\n", - "
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RankDesignProtocolLengthSeedHelicityTarget_HotspotSequenceInterfaceResiduesMPNN_score...1_Binder_RMSD2_Binder_RMSD3_Binder_RMSD4_Binder_RMSD5_Binder_RMSDDesignTimeNotesTargetSettingsFiltersAdvancedSettings
01PDL1_l145_s718363_mpnn34stage145718363-0.3NaNSELEEALKKYEEIHREFLKKINEATYALFRSAVYYEWAAEGKMSKE...B18,B21,B22,B25,B26,B29,B30,B32,B33,B36,B37,B4...0.87...1.251.33NaNNaNNaN0 hours, 2 minutes, 27 secondsNaNPDL1default_filters4stage_multimer
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23PDL1_l92_s843319_mpnn14stage92843319-0.3NaNSMAELEEDRKHVVRMIEDIARQNIHVARTDPRFSPEIVEELEKRME...B4,B7,B8,B11,B12,B14,B15,B18,B19,B21,B22,B23,B...0.97...1.060.99NaNNaNNaN0 hours, 2 minutes, 26 secondsNaNPDL1default_filters4stage_multimer
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-0,0 +1,64 @@ +{ + "omit_AAs": "C", + "force_reject_AA": false, + "use_multimer_design": true, + "design_algorithm": "4stage", + "sample_models": true, + "rm_template_seq_design": false, + "rm_template_seq_predict": false, + "rm_template_sc_design": false, + "rm_template_sc_predict": false, + "soft_iterations": 75, + "temporary_iterations": 45, + "hard_iterations": 5, + "greedy_iterations": 15, + "greedy_percentage": 5, + "save_design_animations": true, + "save_design_trajectory_plots": true, + "weights_plddt": 0.1, + "weights_pae_intra": 0.4, + "weights_pae_inter": 0.1, + "weights_con_intra": 1.0, + "weights_con_inter": 1.0, + "intra_contact_distance": 14.0, + "inter_contact_distance": 20.0, + "intra_contact_number": 2, + "inter_contact_number": 1, + "weights_helicity": -0.3, + "random_helicity": false, + "use_i_ptm_loss": true, + "weights_iptm": 0.05, + "use_rg_loss": true, + "weights_rg": 0.3, + "use_termini_distance_loss": false, + "weights_termini_loss": 0.1, + "enable_mpnn": 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--- /dev/null +++ b/settings_advanced/default_4stage_multimer_mpnn_flexible.json @@ -0,0 +1,64 @@ +{ + "omit_AAs": "C", + "force_reject_AA": false, + "use_multimer_design": true, + "design_algorithm": "4stage", + "sample_models": true, + "rm_template_seq_design": true, + "rm_template_seq_predict": true, + "rm_template_sc_design": false, + "rm_template_sc_predict": false, + "soft_iterations": 75, + "temporary_iterations": 45, + "hard_iterations": 5, + "greedy_iterations": 15, + "greedy_percentage": 5, + "save_design_animations": true, + "save_design_trajectory_plots": true, + "weights_plddt": 0.1, + "weights_pae_intra": 0.4, + "weights_pae_inter": 0.1, + "weights_con_intra": 1.0, + "weights_con_inter": 1.0, + "intra_contact_distance": 14.0, + "inter_contact_distance": 20.0, + "intra_contact_number": 2, + "inter_contact_number": 1, + "weights_helicity": -0.3, + "random_helicity": false, + "use_i_ptm_loss": true, + "weights_iptm": 0.05, + "use_rg_loss": true, + "weights_rg": 0.3, + 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b/settings_advanced/peptide_3stage_multimer.json new file mode 100644 index 0000000..a38c8a7 --- /dev/null +++ b/settings_advanced/peptide_3stage_multimer.json @@ -0,0 +1,64 @@ +{ + "omit_AAs": "C", + "force_reject_AA": true, + "use_multimer_design": true, + "design_algorithm": "3stage", + "sample_models": true, + "rm_template_seq_design": false, + "rm_template_seq_predict": false, + "rm_template_sc_design": false, + "rm_template_sc_predict": false, + "soft_iterations": 75, + "temporary_iterations": 45, + "hard_iterations": 5, + "greedy_iterations": 15, + "greedy_percentage": 5, + "save_design_animations": true, + "save_design_trajectory_plots": true, + "weights_plddt": 0.1, + "weights_pae_intra": 0.4, + "weights_pae_inter": 0.2, + "weights_con_intra": 0.5, + "weights_con_inter": 0.5, + "intra_contact_distance": 14.0, + "inter_contact_distance": 20.0, + "intra_contact_number": 2, + "inter_contact_number": 1, + "weights_helicity": 0.95, + "random_helicity": false, + "use_i_ptm_loss": true, + "weights_iptm": 0.05, + "use_rg_loss": false, + "weights_rg": 0.3, + "use_termini_distance_loss": false, + "weights_termini_loss": 0.1, + "enable_mpnn": true, + "mpnn_fix_interface": true, + "num_seqs": 10, + "max_mpnn_sequences": 2, + "sampling_temp": 0.1, + "backbone_noise": 0.00, + "model_path": "v_48_020", + "mpnn_weights": "soluble", + "save_mpnn_fasta": false, + "num_recycles_design": 1, + "num_recycles_validation": 3, + "optimise_beta": false, + "optimise_beta_extra_soft": 0, + "optimise_beta_extra_temp": 0, + "optimise_beta_recycles_design": 3, + "optimise_beta_recycles_valid": 3, + "remove_unrelaxed_trajectory": true, + "remove_unrelaxed_complex": true, + "remove_binder_monomer": true, + "zip_animations": true, + "zip_plots": true, + "save_trajectory_pickle": false, + "max_trajectories": false, + "enable_rejection_check": true, + "acceptance_rate": 0.01, + "start_monitoring": 300, + "af_params_dir": "", + "dssp_path": "", + "dalphaball_path": "" +} diff --git a/settings_advanced/peptide_3stage_multimer_flexible.json b/settings_advanced/peptide_3stage_multimer_flexible.json new file mode 100644 index 0000000..eeac132 --- /dev/null +++ b/settings_advanced/peptide_3stage_multimer_flexible.json @@ -0,0 +1,64 @@ +{ + "omit_AAs": "C", + "force_reject_AA": true, + "use_multimer_design": true, + "design_algorithm": "3stage", + "sample_models": true, + "rm_template_seq_design": true, + "rm_template_seq_predict": true, + "rm_template_sc_design": false, + "rm_template_sc_predict": false, + "soft_iterations": 75, + "temporary_iterations": 45, + "hard_iterations": 5, + "greedy_iterations": 15, + "greedy_percentage": 5, + "save_design_animations": true, + "save_design_trajectory_plots": true, + "weights_plddt": 0.1, + "weights_pae_intra": 0.4, + "weights_pae_inter": 0.2, + "weights_con_intra": 0.5, + "weights_con_inter": 0.5, + "intra_contact_distance": 14.0, + "inter_contact_distance": 20.0, + "intra_contact_number": 2, + "inter_contact_number": 1, + "weights_helicity": 0.95, + "random_helicity": false, + "use_i_ptm_loss": true, + "weights_iptm": 0.05, + "use_rg_loss": false, + "weights_rg": 0.3, + "use_termini_distance_loss": false, + "weights_termini_loss": 0.1, + "enable_mpnn": true, + "mpnn_fix_interface": true, + "num_seqs": 10, + "max_mpnn_sequences": 2, + "sampling_temp": 0.1, + "backbone_noise": 0.00, + "model_path": "v_48_020", + "mpnn_weights": "soluble", + "save_mpnn_fasta": false, + "num_recycles_design": 1, + "num_recycles_validation": 3, + "optimise_beta": false, + "optimise_beta_extra_soft": 0, + "optimise_beta_extra_temp": 0, + "optimise_beta_recycles_design": 3, + "optimise_beta_recycles_valid": 3, + "remove_unrelaxed_trajectory": true, + "remove_unrelaxed_complex": true, + "remove_binder_monomer": true, + "zip_animations": true, + "zip_plots": true, + "save_trajectory_pickle": false, + "max_trajectories": false, + "enable_rejection_check": true, + "acceptance_rate": 0.01, + "start_monitoring": 300, + "af_params_dir": "", + "dssp_path": "", + "dalphaball_path": "" +} diff --git a/settings_advanced/peptide_3stage_multimer_mpnn.json b/settings_advanced/peptide_3stage_multimer_mpnn.json new file mode 100644 index 0000000..430ee57 --- /dev/null +++ b/settings_advanced/peptide_3stage_multimer_mpnn.json @@ -0,0 +1,64 @@ +{ + "omit_AAs": "C", + "force_reject_AA": true, + "use_multimer_design": true, + "design_algorithm": "3stage", + "sample_models": true, + "rm_template_seq_design": false, + "rm_template_seq_predict": false, + "rm_template_sc_design": false, + "rm_template_sc_predict": false, + "soft_iterations": 75, + "temporary_iterations": 45, + "hard_iterations": 5, + "greedy_iterations": 15, + "greedy_percentage": 5, + "save_design_animations": true, + "save_design_trajectory_plots": true, + "weights_plddt": 0.1, + "weights_pae_intra": 0.4, + "weights_pae_inter": 0.2, + "weights_con_intra": 0.5, + "weights_con_inter": 0.5, + "intra_contact_distance": 14.0, + "inter_contact_distance": 20.0, + "intra_contact_number": 2, + "inter_contact_number": 1, + "weights_helicity": 0.95, + "random_helicity": false, + "use_i_ptm_loss": true, + "weights_iptm": 0.05, + "use_rg_loss": false, + "weights_rg": 0.3, + "use_termini_distance_loss": false, + "weights_termini_loss": 0.1, + "enable_mpnn": true, + "mpnn_fix_interface": false, + "num_seqs": 50, + "max_mpnn_sequences": 2, + "sampling_temp": 0.1, + "backbone_noise": 0.00, + "model_path": "v_48_020", + "mpnn_weights": "soluble", + "save_mpnn_fasta": false, + "num_recycles_design": 1, + "num_recycles_validation": 3, + "optimise_beta": false, + "optimise_beta_extra_soft": 0, + "optimise_beta_extra_temp": 0, + "optimise_beta_recycles_design": 3, + "optimise_beta_recycles_valid": 3, + "remove_unrelaxed_trajectory": true, + "remove_unrelaxed_complex": true, + "remove_binder_monomer": true, + "zip_animations": true, + "zip_plots": true, + "save_trajectory_pickle": false, + "max_trajectories": false, + "enable_rejection_check": true, + "acceptance_rate": 0.01, + "start_monitoring": 300, + "af_params_dir": "", + "dssp_path": "", + "dalphaball_path": "" +} diff --git a/settings_advanced/peptide_3stage_multimer_mpnn_flexible.json b/settings_advanced/peptide_3stage_multimer_mpnn_flexible.json new file mode 100644 index 0000000..98dbafc --- /dev/null +++ b/settings_advanced/peptide_3stage_multimer_mpnn_flexible.json @@ -0,0 +1,64 @@ +{ + "omit_AAs": "C", + "force_reject_AA": true, + "use_multimer_design": true, + "design_algorithm": "3stage", + "sample_models": true, + "rm_template_seq_design": true, + "rm_template_seq_predict": true, + "rm_template_sc_design": false, + "rm_template_sc_predict": false, + "soft_iterations": 75, + "temporary_iterations": 45, + "hard_iterations": 5, + "greedy_iterations": 15, + "greedy_percentage": 5, + "save_design_animations": true, + "save_design_trajectory_plots": true, + "weights_plddt": 0.1, + "weights_pae_intra": 0.4, + "weights_pae_inter": 0.2, + "weights_con_intra": 0.5, + "weights_con_inter": 0.5, + "intra_contact_distance": 14.0, + "inter_contact_distance": 20.0, + "intra_contact_number": 2, + "inter_contact_number": 1, + "weights_helicity": 0.95, + "random_helicity": false, + "use_i_ptm_loss": true, + "weights_iptm": 0.05, + "use_rg_loss": false, + "weights_rg": 0.3, + "use_termini_distance_loss": false, + "weights_termini_loss": 0.1, + "enable_mpnn": true, + "mpnn_fix_interface": false, + "num_seqs": 50, + "max_mpnn_sequences": 2, + "sampling_temp": 0.1, + "backbone_noise": 0.00, + "model_path": "v_48_020", + "mpnn_weights": "soluble", + "save_mpnn_fasta": false, + "num_recycles_design": 1, + "num_recycles_validation": 3, + "optimise_beta": false, + "optimise_beta_extra_soft": 0, + "optimise_beta_extra_temp": 0, + "optimise_beta_recycles_design": 3, + "optimise_beta_recycles_valid": 3, + "remove_unrelaxed_trajectory": true, + "remove_unrelaxed_complex": true, + "remove_binder_monomer": true, + "zip_animations": true, + "zip_plots": true, + "save_trajectory_pickle": false, + "max_trajectories": false, + "enable_rejection_check": true, + "acceptance_rate": 0.01, + "start_monitoring": 300, + "af_params_dir": "", + "dssp_path": "", + "dalphaball_path": "" +} diff --git a/settings_filters/default_filters.json b/settings_filters/default_filters.json index 488a164..a4c571e 100644 --- a/settings_filters/default_filters.json +++ b/settings_filters/default_filters.json @@ -248,15 +248,15 @@ "higher": false }, "Average_Surface_Hydrophobicity": { - "threshold": null, + "threshold": 0.35, "higher": false }, "1_Surface_Hydrophobicity": { - "threshold": null, + "threshold": 0.35, "higher": false }, "2_Surface_Hydrophobicity": { - "threshold": null, + "threshold": 0.35, "higher": false }, "3_Surface_Hydrophobicity": { @@ -1339,4 +1339,4 @@ "threshold": 3.5, "higher": false } -} +} \ No newline at end of file diff --git a/settings_filters/peptide_filters.json b/settings_filters/peptide_filters.json new file mode 100644 index 0000000..69c043d --- /dev/null +++ b/settings_filters/peptide_filters.json @@ -0,0 +1,1342 @@ +{ + "MPNN_score": { + "threshold": null, + "higher": false + }, + "MPNN_seq_recovery": { + "threshold": null, + "higher": false + }, + "Average_pLDDT": { + "threshold": 0.8, + "higher": true + }, + "1_pLDDT": { + "threshold": 0.8, + "higher": true + }, + "2_pLDDT": { + "threshold": 0.8, + "higher": true + }, + "3_pLDDT": { + "threshold": null, + "higher": true + }, + "4_pLDDT": { + "threshold": null, + "higher": true + }, + "5_pLDDT": { + "threshold": null, + "higher": true + }, + "Average_pTM": { + "threshold": 0.55, + "higher": true + }, + "1_pTM": { + "threshold": 0.55, + "higher": true + }, + "2_pTM": { + "threshold": 0.55, + "higher": true + }, + "3_pTM": { + "threshold": null, + "higher": true + }, + "4_pTM": { + "threshold": null, + "higher": true + }, + "5_pTM": { + "threshold": null, + "higher": true + }, + "Average_i_pTM": { + "threshold": 0.4, + "higher": true + }, + "1_i_pTM": { + "threshold": 0.4, + "higher": true + }, + "2_i_pTM": { + "threshold": 0.4, + "higher": true + }, + "3_i_pTM": { + "threshold": null, + "higher": true + }, + "4_i_pTM": { + "threshold": null, + "higher": true + }, + "5_i_pTM": { + "threshold": null, + "higher": true + }, + "Average_pAE": { + "threshold": null, + "higher": false + }, + "1_pAE": { + "threshold": null, + "higher": false + }, + "2_pAE": { + "threshold": null, + "higher": false + }, + "3_pAE": { + "threshold": null, + "higher": false + }, + "4_pAE": { + "threshold": null, + "higher": false + }, + "5_pAE": { + "threshold": null, + "higher": false + }, + "Average_i_pAE": { + "threshold": 0.3, + "higher": false + }, + "1_i_pAE": { + "threshold": 0.3, + "higher": false + }, + "2_i_pAE": { + "threshold": 0.3, + "higher": false + }, + "3_i_pAE": { + "threshold": null, + "higher": false + }, + "4_i_pAE": { + "threshold": null, + "higher": false + }, + "5_i_pAE": { + "threshold": null, + "higher": false + }, + "Average_i_pLDDT": { + 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