Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Structural Elucidation of SARS-CoV-2 Vital Proteins: Computational Methods Reveal Potential Drug Candidates Against Main Protease, Nsp12 RNA-dependent RNA Polymerase and Nsp13 Helicase

Version 1 : Received: 4 March 2020 / Approved: 5 March 2020 / Online: 5 March 2020 (11:50:45 CET)

A peer-reviewed article of this Preprint also exists.

Journal reference: Journal of Pharmaceutical Analysis 2020
DOI: 10.1016/j.jpha.2020.04.008

Abstract

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a major outbreak of coronavirus disease 2019 (COVID-19) and instigated a widespread fear and has threatened global health security. Although phenomenal efforts are in progress to effectively combat this COVID-19 outbreak. Still, no licensed antiviral drugs or vaccines are available, and treatment is limited to supportive care and few repurposed drugs. In this urgency situation, computational drug discovery methods provide both an alternative and a supplement to tiresome high-throughput screening, particularly in the hit-to-lead-optimization stage. Identification of small molecules that specifically target viral replication apparatus has shown the most successful strategy in antiviral drug discovery. The present study deals with the identification of potential compounds that specifically interact with SARS-CoV-2 vital proteins, including main protease (Mpro), Nsp12 RNA-dependent-RNA-polymerase (RdRp) and Nsp13 helicase. A constructive and integrated virtual screening efforts together with molecular dynamics simulations identified potential binding modes and favourable molecular interaction profile of corresponding compounds. Moreover, structurally important binding site residues in conserved motifs located inside the active site are elucidated, which displayed relative importance in ligand binding based on residual energy decomposition analysis. Although the current study lacks experimental validation, the structural information obtained from this computational study paved the way to identify and design specific targeted inhibitors to combat COVID-19 outbreak.

Subject Areas

SARS-CoV-2; COVID-19; CoV-Mpro; CoV-Nsp12 polymerase; CoV-Nsp13 helicase

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