Computational assessment of molecular mechanisms underlying hERG K + channel conduction and affinity for drug binding.

During drug development, one of the most significant regulatory concerns is drug-induced cardiotoxicity in the form of abnormal heart rhythms known as arrhythmias. Detrimental drug side effects are often linked to the block of the cardiac ion channel KV11.1, also known as hERG, responsible for a significant repolarizing K+ current, IKr, in cardiac myocytes. Blockage of the channel conductance can lead to prolongation of the cardiac action potential and the QT interval on the surface electrocardiogram, which may result in deadly arrhythmias. hERG channel blockade is a leading cause for drug withdrawal from the drug development pipeline or marketplace. However, not all hERG-blocking and QT-prolonging drugs lead to a high risk for arrhythmia, and there is still no robust and accurate way to distinguish between safe and unsafe hERG blockers. One proposed mechanism is that preferential high-affinity drug binding to hERG inactivated conformation is correlated with its high arrhythmogenic risk. Here, we construct and validate wild-type and mutant hERG channel models in different conformational states based on cryo-EM structures using Rosetta comparative modeling. Using molecular dynamics (MD) simulations, we assessed the ability of these hERG models to conduct ions, interact with drugs, and observed results consistent with published literature. Ultimately, such computer-generated data can be used in conjunction with experimental data to construct state-dependent functional kinetic models of drug-induced hERG channel blockade. The presented model will provide a basis for a new-generation multi-scale model of cardiac safety pharmacology, explicitly incorporating drug modulation of hERG channel gating and thus allowing accurate predictions of drug-induced cardiotoxicity from drug chemical structures.