BPS2026 – Unraveling the complexity of drug binding to the hERG channel using a computational approach: From channel states to patient-specific variants

The human ether-à-go-go - related gene (hERG) or KCNH2 encodes the potassium channel K V 11.1. This channel underlies the major repolarizing potassium ion current ( I Kr ) in cardiomyocytes and is essential for cardiac repolarization. Many small-molecule drugs bind to and block this channel, leading to QT interval prolongation and drug-induced arrhythmias. Drug-induced hERG block has become a central concern in pharmacology and drug safety. However, not all hERG blockers cause arrhythmia, and the molecular basis of drug-induced arrhythmogenicity due to hERG binding remains incompletely understood. Structural and functional differences between conformational states, isoforms, and genetic variants add more complexity. To explore these questions, I use a computational framework that combines cryo-electron microscopy structures, AlphaFold and Rosetta modeling, molecular docking, and all-atom molecular dynamics simulations. One direction is to evaluate how drugs interact with the hERG channel in different functional states. The channel can be open, closed, or inactivated, and each state has distinct binding environments that may help explain why certain drugs are more arrhythmogenic than others. Another direction considers alternative hERG channel isoforms, hERG1a, hERG1b, and hERGuso, which can form homo- and hetero-tetramers. These studies help unravel structural and functional differences that influence hERG drug sensitivity and arrhythmogenicity. A third focus is on hERG genetic mutations associated with congenital long QT syndrome and variants of unknown significance. Mutations in the hERG pore and selectivity filter regions, such as S620T, Y652A, and F656C, can alter channel gating and disrupt drug binding. This work brings together state, isoform, and mutation effects to explore drug binding to the hERG channel. The goal is to describe the molecular basis and a deeper structural understanding of hERG blocking mechanisms and provide a framework for understanding drug-induced arrhythmia risks.