In this work, we study the impact of including state-dependent drug binding in a mathematical ion channel model of the human Ether-à-go-go-Related Gene (hERG) channel. We compared the action potential predictions when modelling drug binding of hERG using a state-dependent model versus a conductance scaling model.

Source code associated with "Importance of modelling hERG binding in predicting drug-induced action potential prolongations for drug safety assessment" by Hui Jia Farm, Michael Clerx, Fergus Cooper, Liudmila Polonchuk, Ken Wang, David J. Gavaghan and Chon Lok Lei.

All scripts that generate the data and plot the figures are in the scripts folder.

Figures can be reproduced with the command:

make FigureX

where X is the figure number. The list of commands to reproduce the figures are provided below.

1. Figure1
   • to reproduce Figure 1 (background figure)
2. Figure2
   • to reproduce Figure 2 (method description figure)
   • requires data generated from the script binding_kinetics_comparison.py for example drug N (also run in command Figure4)
3. Figure3
   • to reproduce Figure 3 (model comparison for example drug T)
4. Figure4
   • to reproduce Figure 4 (model comparison for example drug N)
5. Figure5
   • to reproduce Figure 5 (AP comparison at transient phase)
6. Figure6
   • to reproduce Figure 6 (protocol dependence of AP prolongation)
7. Figure7
   • to reproduce Figure 7 and Figure S12 (parameter space exploration)
8. FigureS1_S10
   • to reproduce Figure S1 to S10 (APD90, qNet and Hill curves for several drugs)
9. FigureS11
   • to reproduce Figure S11 (RMSD distribution with varying parameter N)
10. FigureS13_S14
    • to reproduce Figure S13 and S14 (RMSD and APD90 at different Vhalf-trap values)
    • requires data generated from the script SA_param_space.py (also run in command Figure7)

Some figures were modified for better visualisation, i.e. Figure 1 to Figure 4.

If you publish any work based on the contents of this repository please cite (CITATION file):

Farm, H. J., Clerx, M., Cooper, F., Polonchuk, L., Wang, K., Gavaghan, D. J. and Lei, C. L. (2023). Importance of modelling hERG binding in predicting drug-induced action potentials for drug safety assessment. Frontiers in Pharmacology, 14:1110555. doi:10.3389/fphar.2023.1110555.