Optimizing experimental designs for model selection of ion channel drug-binding mechanisms

Patten-Elliott, Frankie; Lei, Chon Lok; Preston, Simon P.; Wilkinson, Richard D.; Mirams, Gary R.

Abstract

The rapid delayed rectifier current carried by the human Ether-à-go-go-Related Gene (hERG) channel is susceptible to drug-induced reduction, which can lead to an increased risk of cardiac arrhythmia. Establishing the mechanism by which a specific drug compound binds to hERG can help reduce uncertainty when quantifying pro-arrhythmic risk. In this study, we introduce a methodology for optimizing experimental voltage protocols to produce data that enable different proposed models for the drug-binding mechanism to be distinguished. We demonstrate the performance of this methodology via a synthetic data study. If the underlying model of hERG current is known exactly, then the optimized protocols generated show noticeable improvements in our ability to select the true model when compared with a simple protocol used in previous studies. However, if the model is not known exactly, and we assume a discrepancy between the data-generating hERG model and the hERG model used in fitting the models, then the optimized protocols become less effective in determining the ‘true’ binding dynamics. While the introduced methodology shows promise, we must be careful to ensure that, if applied to a real data study, we have a well-calibrated model of hERG current gating.

Citation

Patten-Elliott, F., Lei, C. L., Preston, S. P., Wilkinson, R. D., & Mirams, G. R. (2025). Optimizing experimental designs for model selection of ion channel drug-binding mechanisms. Philosophical Transactions A: Mathematical, Physical and Engineering Sciences, 383(2292), https://doi.org/10.1098/rsta.2024.0227

• Journal Article Type: Article
• Acceptance Date: Oct 4, 2024
• Online Publication Date: Mar 13, 2025
• Publication Date: Mar 13, 2025
• Deposit Date: Mar 18, 2025
• Publicly Available Date: Mar 18, 2025
• Journal: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
• Print ISSN: 1364-503X
• Electronic ISSN: 1471-2962
• Publisher: The Royal Society
• Peer Reviewed: Peer Reviewed
• Volume: 383
• Issue: 2292
• DOI: https://doi.org/10.1098/rsta.2024.0227
• Public URL: https://nottingham-repository.worktribe.com/output/46582146
• Publisher URL: https://royalsocietypublishing.org/doi/10.1098/rsta.2024.0227
• Additional Information: Received: 2024-08-15; Revised: 2024-10-03; Accepted: 2024-10-04; Published: 2025-03-13