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Organisation of the scripts

The fig_script folder contains all scripts used to plot the figures in the paper. The checking_script folder contains all scripts used for data analysis but not shown in the results.

Main results

background_trapping.py - Generates data to introduce the trapping mechanism.

binding_kinetics_comparison.py - Calibrates the ionic conductance of the CS model from the SD model for a dofetilide-like drug and a verapamil-like drug, then compare the APD90s at steady state.

AP_simulation.py - Simulates action potentials of the ORd-SD model and the ORd-CS model at transient phase.

protocol_dependence.py - Compares the Hill curve of the SD model for drugs with different protocols and the APD90 of the ORd-CS model when the ionic conductance is scaled with the Hill curves.

SA_param_space.py - Explore the parameter space of drug-related parameters (Vhalf, Kmax and Ku) and compute the APD90 differences between the ORd-SD model and the ORd-CS model for a given virtual drug.

SA_curve.py - Compute the APD90 differences between the ORd-SD model and the ORd-CS model for the parameter space around the boundary surface where the APD90s are similar.

SA_drugs.py - Compute the APD90 differences between the two AP models for all synthetic drugs.

combine_APD.py - Combine all simulated data of the parameter space with essential information for easy loading when plotting figures. (Requires SA_param_space.py to be run first.)

Supplementary materials

supp_comparison_drugs.py - Compare the APD90 of the ORd-SD model and the ORd-CS model for each synthetic drug and generate the Hill curves of the drug for different protocols.

supp_SA_parameter.py - Compute the RMSD between APD90s of the ORd-SD model and the ORd-CS model when the Hill coefficient of each synthetic drug changes.