Investigation of state-specific drug binding to cardiac ion channels to reveals mechanisms of arrhythmogenesis

Project Summary/Abstract Unintended drug block of cardiac ion channels remains a major problem in drug development. The voltage-gated potassium channel KV11.1 also known as the hERG channel is a major drug anti-target that binds a diverse set of small molecule drugs. Drug-induced inhibition of the hERG channel reduces the critical repolarizing current IKr

and thereby prolongs the cardiac action potential. Many drugs that bind the hERG channel promote deadly arrythmias like Torsades de Pointes while some hERG blockers present significantly lower proarrhythmic risk. Two hypotheses were proposed to elucidate this discrepancy: (1) preferential drug binding to the inactivated

state of the hERG channel confers greater proarrhythmic risk and (2) simultaneous drug binding to other cardiac ion channels can ameliorate the risk associated with hERG channel block. Here, we present a state-specific molecular modeling assessment of drug binding to different conformations of the hERG and voltage-gated

sodium hNaV1.5 and calcium hCaV1.2 channels. We have developed structural models of these cardiac ion channels in open and inactivated conformations and will perform all-atom molecular dynamics simulations to validate structural stabilities and assess ion conduction. Ligand docking was then performed using Site

Identification by Ligand Competitive Saturation (SILCS), a pre-compute ensemble molecular docking technique. SILCS allows us to perform a high-throughput assessment of ligand binding affinities using molecular fragment energy maps derived from molecular dynamics simulations of state-specific ion channel models. Bayesian

machine learning was used to provide improved correlation of SILCS-computed affinities with experimental data. Using SILCS multi-ligand docking we also estimated interactions of drugs with sex hormones in the hERG channel pore to assess a potential molecular mechanism for an increased proarrhythmia risk in females. We aim

to use SILCS computed state-specific drug affinity data to inform multi-scale functional kinetic models of cardiac electrophysiology to estimate emergent drug effects on the cardiac action potential and heart rhythm. These modeling results will be validated by performing voltage-clamp electrophysiology measurements in vitro and

compared to other published work. Upon completion of this project, the applicant will have refined expertise in computational modeling of ion channel-drug interactions and will have received training in experimental electrophysiology for the first time. Throughout the project, the sponsors will implement a training plan to

strengthen the applicant’s knowledge of cardiac physiology and pharmacology while also broadening their scientific network, and improving the applicant’s scientific communication skills. This plan is tailored such that the applicant is prepared for a career as an academic scientist, investigating drug interactions with ion channels.