RESEARCH ARTICLE


Identification of Naturally Occurring Antiviral Molecules for SARS-CoV-2 Mitigation



Shiwani Rana1, Prateek Kumar2, Anchal Sharma1, Sanjay Sharma1, Rajanish Giri2, *, Kalyan S. Ghosh1, *
1 Department of Chemistry, National Institute of Technology Hamirpur, Hamirpur, H.P. 177005, India
2 School of Basic Sciences, Indian Institute of Technology Mandi, Mandi, H.P. 175005, India


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Creative Commons License
© 2021 Rana et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to these authors at the Department of Chemistry, National Institute of Technology Hamirpur, H.P. 177005, India; Tel: +91-1972-254104; E-mail: kalyan@nith.ac.in and School of Basic Sciences, Indian Institute of Technology Mandi, H.P. 175005, India; Tel: +91-1905-267154; E-mail: rajanishgiri@iitmandi.ac.in


Abstract

Aim:

This study aimed to virtually screen the naturally occurring antiviral molecules for SARS-CoV-2 mitigation based on multiple molecular targets using docking and molecular dynamics simulations.

Background:

The coronavirus catastrophe (COVID-19) caused by a novel strain of coronavirus (SARS-CoV-2) has turned the world upside down at an unprecedented level and has been declared a pandemic by the World Health Organization. It has resulted in a huge number of infections as well as fatalities due to severe lower respiratory tract sickness.

Objective:

The objective of this study was the identification of inhibitors against the crucial molecular targets linked with viral infection caused by SARS-CoV-2.

Materials and Methods:

In silico screening of twenty naturally occurring antiviral molecules was performed using the Autodock docking tool. Further, molecular dynamics (MD) simulations were performed on the most stable docked complex between cysteine-like protease or 3CL protease (3CLpro) and the best-identified inhibitor (bilobetin).

Results:

3CLpros is one of the very important molecular targets as it is involved in the replication process of the virus. In the present study, we have initially investigated the inhibitory potential of naturally occurring antiviral molecules against the activity of main viral protease (3CLpro) to put a halt to viral replication. The investigation had been carried out through docking of the molecules with 3CLpro. Based on the results, the three most potential molecules (bilobetin, ginkgetin and sciadopitysin) have been screened. Further, these molecules were subjected to checking their activity on other molecular targets like papain-like protease (PLpro), spike protein S1, RNA dependent RNA polymerase (RdRp), and Angiotensin-Converting Enzyme 2 (ACE2) receptor. In addition to 3CLpro inhibition, ginkgetin was also predicted as an inhibitor of PLpro. However, none of these three compounds was found to be effective on the rest of the molecular targets. Molecular Dynamics (MD) simulations of the most stable docked complex between 3CLpro and its best inhibitor (bilobetin) confirmed notable conformational stability of the docked complex under a dynamic state.

Conclusion:

Bilobetin alone or a combination of bilobetin and ginkgetin may be used to impede viral replication. These observations are solely based on the results from blind docking with protein molecules and need to be further corroborated with experimental results.

Keywords: SARS-Cov-2, Cysteine like protease inhibition, Papain-like protease inhibition, Bilobetin, Ginkgetin, Sciadopitysin.