Modeling of Open, Closed, and Open-Inactivated States of the hERG1 Channel: Structural Mechanisms of the State-Dependent Drug Binding

• Published in: Journal of chemical information and modeling 2012-10, Vol.52 (10), p.2760-2774
• Main Authors: Durdagi, Serdar, Deshpande, Sumukh, Duff, Henry J, Noskov, Sergei Y
• Format: Article
• Language: English
• Subjects: Bacterial Proteins - chemistry; Binding Sites; Biological and medical sciences; Cardiomyocytes; Crystallography, X-Ray; Ether-A-Go-Go Potassium Channels - chemistry; Fundamental and applied biological sciences. Psychology; General pharmacology; Humans; Interactions. Associations; Intermolecular phenomena; Kinetics; Kv1.2 Potassium Channel - chemistry; Ligands; Medical sciences; Molecular biophysics; Molecular Docking Simulation; Molecules; Myocytes, Cardiac - metabolism; Pharmacology; Pharmacology. Drug treatments; Physicochemical properties. Structure-activity relationships; Potassium; Potassium Channels - chemistry; Protein Binding; Protein Conformation; Proteins; Scorpion Venoms - chemistry; Simulation; Structural Homology, Protein; Thermodynamics
• ISSN: 1549-9596; 1549-960X
• DOI: 10.1021/ci300353u

The human ether-a-go-go related gene 1 (hERG1) K ion channel is a key element for the rapid component of the delayed rectified potassium current in cardiac myocytes. Since there are no crystal structures for hERG channels, creation and validation of its reliable atomistic models have been key targets in molecular cardiology for the past decade. In this study, we developed and vigorously validated models for open, closed, and open-inactivated states of hERG1 using a multistep protocol. The conserved elements were derived using multiple-template homology modeling utilizing available structures for Kv1.2, Kv1.2/2.1 chimera, and KcsA channels. Then missing elements were modeled with the ROSETTA De Novo protein-designing suite and further refined with all-atom molecular dynamics simulations. The final ensemble of models was evaluated for consistency to the reported experimental data from biochemical, biophysical, and electrophysiological studies. The closed state models were cross-validated against available experimental data on toxin footprinting with protein–protein docking using hERG state-selective toxin BeKm-1. Poisson–Boltzmann calculations were performed to determine gating charge and compare it to electrophysiological measurements. The validated structures offered us a unique chance to assess molecular mechanisms of state-dependent drug binding in three different states of the channel.