Homology modelling and molecular docking study of TMPRSS2 with small-molecule protease inhibitors to control SARS-CoV-2
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COVID-19, SARS-Coronavirus 2, serine protease
Abstract
Due to the urgent need of drugs to control the COVID-19 pandemic, repositioning of already marketed drugs could be a fast and convenient option to identify agents to aid in controlling and treating COVID-19. This work presented a computational work regarding homology modeling and molecular docking of repurposing drugs related to the SARS-CoV-2. We have created a homology model of the cell surface transmembrane protease serine 2 protein (TMPRSS2) in order to investigate and analyze the interactions of already known small-molecules. This study indicates the most active inhibitors, poceprevir, simeprevir and neoandrgrapholide, that can be used further to search for better TMPRSS2 inhibitors. Moreover, we analyzed the most important atomistic connections between these compounds and the modeled protein pockets. This study will focus on TMPRSS2-targeted drugs by comparing the binding mode of approved and experimentally used TMRSS2 inhibitors with other agents with TMPRSS2 inhibitory activity and could potentially inhibit SARS-CoV-2 and therefore could lead to the identification of new agents for further clinical evaluation of SARS-CoV-2 and potential treatment of COVID-19.
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