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Unravelling lead antiviral phytochemicals for the inhibition of SARS-CoV-2 Mpro enzyme through in silico approach.

Arun Bahadur Gurung | Mohammad Ajmal Ali | Joongku Lee | Mohammad Abul Farah | Khalid Mashay Al-Anazi
Life sciences | 2020

A new SARS coronavirus (SARS-CoV-2) belonging to the genus Betacoronavirus has caused a pandemic known as COVID-19. Among coronaviruses, the main protease (Mpro) is an essential drug target which, along with papain-like proteases catalyzes the processing of polyproteins translated from viral RNA and recognizes specific cleavage sites. There are no human proteases with similar cleavage specificity and therefore, inhibitors are highly likely to be nontoxic. Therefore, targeting the SARS-CoV-2 Mpro enzyme with small molecules can block viral replication. The present study is aimed at the identification of promising lead molecules for SARS-CoV-2 Mpro enzyme through virtual screening of antiviral compounds from plants. The binding affinity of selected small drug-like molecules to SARS-CoV-2 Mpro, SARS-CoV Mpro and MERS-CoV Mpro were studied using molecular docking. Bonducellpin D was identified as the best lead molecule which shows higher binding affinity (-9.28 kcal/mol) as compared to the control (-8.24 kcal/mol). The molecular binding was stabilized through four hydrogen bonds with Glu166 and Thr190 as well as hydrophobic interactions via eight residues. The SARS-CoV-2 Mpro shows identities of 96.08% and 50.65% to that of SARS-CoV Mpro and MERS-CoV Mpro respectively at the sequence level. At the structural level, the root mean square deviation (RMSD) between SARS-CoV-2 Mpro and SARS-CoV Mpro was found to be 0.517 Å and 0.817 Å between SARS-CoV-2 Mpro and MERS-CoV Mpro. Bonducellpin D exhibited broad-spectrum inhibition potential against SARS-CoV Mpro and MERS-CoV Mpro and therefore is a promising drug candidate, which needs further validations through in vitro and in vivo studies.

Pubmed ID: 32450166

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Collection of information about chemical structures and biological properties of small molecules and siRNA reagents hosted by the National Center for Biotechnology Information (NCBI).

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Software tool for automatic generation of multiple 2D ligand-protein interaction diagrams from 3D coordinates. Diagrams portray hydrogen-bond interaction patterns and hydrophobic contacts between ligand(s) and main-chain or side-chain elements of protein. Used for drug discovery for analyzing series of small molecules binding to same protein target, single ligand binding to homologous proteins, or where both protein and ligand change.

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