Abnormal cardiac electrical activity is a common side effect caused by unintended block of the promiscuous drug target human ether-à-go-go-related gene (hERG1), the pore-forming domain of the delayed rectifier K 1 channel in the heart. hERG1 block leads to a prolongation of the QT interval, a phase of the cardiac cycle that underlies myocyte repolarization detectable on the electrocardiogram. Even newly released drugs such as heart-rate lowering agent ivabradine block the rapid delayed rectifier current I Kr , prolong action potential duration, and induce potentially lethal arrhythmia known as torsades de pointes. In this study, we describe a critical drug-binding pocket located at the lateral pore surface facing the cellular membrane. Mutations of the conserved M651 residue alter ivabradine-induced block but not by the common hERG1 blocker dofetilide. As revealed by molecular dynamics simulations, binding of ivabradine to a lipophilic pore access site is coupled to a state-dependent reorientation of aromatic residues F557 and F656 in the S5 and S6 helices. We show that the M651 mutation impedes state-dependent dynamics of F557 and F656 aromatic cassettes at the protein-lipid interface, which has a potential to disrupt drug-induced block of the channel. This fundamentally new mechanism coupling the channel dynamics and small-molecule access from the membrane into the hERG1 intracavitary site provides a simple rationale for the well established state-dependence of drug blockade. SIGNIFICANCE STATEMENT The drug interference with the function of the cardiac hERG channels represents one of the major sources of drug-induced heart disturbances. We found a novel and a critical drug-binding pocket adjacent to a lipid-facing surface of the hERG1 channel, which furthers our molecular understanding of drug-induced QT syndrome.
Drug-induced cardiotoxicity is a potentially lethal and yet one of the most common side effects with the drugs in clinical use. Most of the drug-induced cardiotoxicity is associated with an off-target pharmacological blockade of K + currents carried out by the cardiac Human-Ether-a-go-go-Related (hERG1) potassium channel. There is a compulsory preclinical stage safety assessment for the hERG1 blockade for all classes of drugs, which adds substantially to the cost of drug development. The availability of a high-resolution cryogenic electron microscopy (cryo-EM) structure for the channel in its open/depolarized state solved in 2017 enabled the application of molecular modeling for rapid assessment of drug blockade by molecular docking and simulation techniques. More importantly, if successful, in silico methods may allow a path to lead-compound salvaging by mapping out key block determinants. Here, we report the blind application of the site identification by the ligand competitive saturation (SILCS) protocol to map out druggable/regulatory hotspots in the hERG1 channel available for blockers and activators. The SILCS simulations use small solutes representative of common functional groups to sample the chemical space for the entire protein and its environment using all-atom simulations. The resulting chemical maps, FragMaps, explicitly account for receptor flexibility, protein− fragment interactions, and fragment desolvation penalty allowing for rapid ranking of potential ligands as blockers or nonblockers of hERG1. To illustrate the power of the approach, SILCS was applied to a test set of 55 blockers with diverse chemical scaffolds and pIC50 values measured under uniform conditions. The original SILCS model was based on the all-atom modeling of the hERG1 channel in an explicit lipid bilayer and was further augmented with a Bayesian-optimization/machine-learning (BML) stage employing an independent literature-derived training set of 163 molecules. BML approach was used to determine weighting factors for the FragMaps contributions to the scoring function. pIC50 predictions from the combined SILCS/BML approach to the 55 blockers showed a Pearson correlation (PC) coefficient of >0.535 relative to the experimental data. SILCS/BML model was shown to yield substantially improved performance as compared to commonly used rigid and flexible molecular docking methods for a wellestablished cohort of hERG1 blockers, where no correlation with experimental data was recorded. SILCS/BML results also suggest that a proper weighting of protonation states of common blockers present at physiological pH is essential for accurate predictions of blocker potency. The precalculated and optimized SILCS FragMaps can now be used for the rapid screening of small molecules for their cardiotoxic potential as well as for exploring alternative binding pockets in the hERG1 channel with applications to the rational design of activators.
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