Journal
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
Volume 20, Issue -, Pages 882-890Publisher
ELSEVIER
DOI: 10.1016/j.csbj.2022.02.001
Keywords
SARS-CoV-2; Coronavirus; Inhibitor; Molecular docking; Virtual screening; Drug discovery
Funding
- National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand [P-2051635]
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This study analyzed the amino acid sequence conservation of RNA-dependent RNA polymerase (RdRp) across coronaviruses and identified compounds with promising antiviral activity. Molecular dynamics simulations and binding free-energy calculations were performed to elucidate critical interactions, providing a foundation for developing lead compounds effective against SARS-CoV-2.
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 has posed a serious threat to global health and the economy for over two years, prompting the need for development of antiviral inhibitors. Due to its vital role in viral replication, RNA-dependent RNA polymerase (RdRp) is a promising therapeutic target. Herein, we analyzed amino acid sequence conservation of RdRp across coronaviruses. The conserved amino acids at the catalytic binding site served as the ligand-contacting residues for in silico screening to elucidate possible resistant mutation. Molecular docking was employed to screen inhibitors of SARS-CoV-2 from the ZINC ChemDiv database. The top-ranked compounds selected from GOLD docking were further investigated for binding modes at the conserved residues of RdRp, and ten compounds were selected for experimental validation. Of which, three compounds exhibited promising antiviral activity. The most promising candidate showed a half-maximal effective concentration (EC50) of 5.04 mu M. Molecular dynamics simulations, binding free-energy calculation and hydrogen bond analysis were performed to elucidate the critical interactions providing a foundation for developing lead compounds effective against SARS-CoV-2. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
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