Abstract 15504: High-Throughput Assessment of Molecular Mechanisms of Drug-Induced Arrhythmia Proclivities and Their Sex Dependence

Abstract

Introduction: The hERG K + channel is responsible for the repolarizing cardiac current I Kr . Drug block of hERG can prolong the QT interval on the surface electrocardiogram and in some cases promote deadly arrhythmias. Previous studies suggested that drugs that preferentially bind to the hERG channel’s inactivated state have higher proarrhythmic proclivities. Electrophysiology experiments and multiscale simulations also predicted that sex hormones can suppress hERG current and exacerbate drug-induced cardiotoxicity. Hypothesis: Atomistic simulations can make reliable correlations between a drug’s chemical structure and its state-dependent hERG binding affinities allowing us to distinguish safe from dangerous hERG blockers. Methods: We utilized site identification by ligand competitive saturation (SILCS), a pre-compute ensemble molecular docking technique, to predict hERG-channel binding poses and affinities of drug molecules. To improve agreement of SILCS results with experimental and molecular dynamics simulation data, we used a Bayesian machine learning protocol to optimize docking parameters. Results: We analyzed state-dependent binding of a sample set of 55 known hERG blockers and seven sex hormones to available structural models of the hERG channel. SILCS computed dissociation constants, K D , show good correlation with experimental IC 50 values for our open-state model (Panel A) and predict drug and hormone binding sites in agreement with previous studies (Panel B) validating the methodology. Conclusions: Our computational methodology allows us to do high-throughput screening and differentiation of open vs. inactivated-state hERG channel drug binding and can also predict how hormones may modulate a drug’s hERG blocking activity. This provides more selective criteria for differentiating cardiac safe and dangerous drugs compared to using only hERG block and QT prolongation as surrogate markers of pro-arrhythmia risk.