Mapping Ligand Binding Sites in hERG1 Channel with Biomolecular Simulations

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2021-03-01
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Abstract
The human ether-a-go-go related gene 1 (hERG1) K+ ion channel generates the rapid delayed rectifier potassium current, or IKr, which is essential for the normal repolarization phase in the ventricular action potential. The drug-induced blockade of the channel is a frequent side effect of various classes of drugs which can cause QT interval prolongation. The consequent cardiac arrhythmia, known as acquired long QT syndrome, has led to the withdrawal of several approved drugs and a mandatory preclinical stage safety assessment for hERG1 blockade. However, cardiotoxicity detection due to the hERG1 blockade remains a challenging task because of the variability of the methodologies employed. In vitro studies are costly, labor-intensive, and technically demanding. Recent development of various in-silico predictive tools has paved the way for a cost-effective cardiotoxicity determination. The availability of the cryo-EM structure of hERG1 at a 3.8 Å resolution provides a unique opportunity for the application of rapidly evolving fragment-based approaches for mapping of potential drug binding sites in hERG1 and rapid assessment of drug blockade. In this thesis, first, we used free energy sampling methods to establish a connection between the cryo-EM structure of the hERG1 channel and its functionality. Furthermore, using the hERG1 cryo-EM structure, we studied the putative druggable binding pockets of hERG1 with the site identification by ligand competitive saturation (SILCS) simulation method. The generated affinity maps from SILCS account for protein flexibility, solutes desolvation effects, and protein-fragments interaction. Using SILCS, we mapped the binding sites of the hERG1 channel including the intracellular cavity, lipid phasing domains, and voltage sensor domains. Our SILCS- Hotspots model showed the existence of two distinct regions inside the IC in agreement with the previously proposed “deep” and “shallow” binding pockets in this region. Finally, using the optimized SILCS Monte-Carlo, SILCS-based docking method, we designed a protocol for rapid prediction of the ligands binding affinity to hERG1. The outcome of this research will be used for rapid and cost-effective computer-aided drug design.
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Mousaei, M. (2021). Mapping Ligand Binding Sites in hERG1 Channel with Biomolecular Simulations (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.