Microsecond MD Simulation and Multiple-Conformation Virtual Screening to Identify Potential Anti-COVID-19 Inhibitors Against SARS-CoV-2 Main Protease

利用微秒级分子动力学模拟和多构象虚拟筛选鉴定针对SARS-CoV-2主蛋白酶的潜在抗COVID-19抑制剂

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Abstract

The recent pandemic outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), raised global health and economic concerns. Phylogenetically, SARS-CoV-2 is closely related to SARS-CoV, and both encode the enzyme main protease (M(pro)/3CL(pro)), which can be a potential target inhibiting viral replication. Through this work, we have compiled the structural aspects of M(pro) conformational changes, with molecular modeling and 1-μs MD simulations. Long-scale MD simulation resolves the mechanism role of crucial amino acids involved in protein stability, followed by ensemble docking which provides potential compounds from the Traditional Chinese Medicine (TCM) database. These lead compounds directly interact with active site residues (His41, Gly143, and Cys145) of M(pro), which plays a crucial role in the enzymatic activity. Through the binding mode analysis in the S1, S1', S2, and S4 binding subsites, screened compounds may be functional for the distortion of the oxyanion hole in the reaction mechanism, and it may lead to the inhibition of M(pro) in SARS-CoV-2. The hit compounds are naturally occurring compounds; they provide a sustainable and readily available option for medical treatment in humans infected by SARS-CoV-2. Henceforth, extensive analysis through molecular modeling approaches explained that the proposed molecules might be promising SARS-CoV-2 inhibitors for the inhibition of COVID-19, subjected to experimental validation.

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