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Coronaviruses

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ISSN (Print): 2666-7967
ISSN (Online): 2666-7975

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Research Article

Chemi-Informatic Approach to Investigate Putative Pharmacoactive Agents of Plant Origin to Eradicate COVID-19

Author(s): Amit Joshi, Vandna Sharma, Joginder Singh and Vikas Kaushik*

Volume 3, Issue 3, 2022

Published on: 03 December, 2020

Article ID: e170322188687 Pages: 15

DOI: 10.2174/2666796701999201203210036

Abstract

Background: The scientific community has supported the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, Amentoflavone discovered as an anti-viral agent, and it is present as a bioactive constituent in many plants of different families like Selaginellaceae, Euphorbiaceae, and Calophyllaceae. Withania somnifera (Ashwagandha) is already considered a significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A and Withanolide-B.

Objective: In this study, phytochemicals such as withanolide-b, somniferine-a, stigmasterol, amentoflavone, and chavicine were analyzed to screen protein inhibitors, out of them; such proteins are involved in the internalization and interaction of SARS-CoV-2 with human cytological domains. This will help in developing a checkpoint for SARS-CoV-2 internalization.

Methods: Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were used to examine the action of pharmacoactive agents against SARS-CoV-2. The tools used in the study were based on the finest algorithms like artificial neural networking, machine learning, and artificial intelligence.

Results: On the basis of binding energies less than equal to -8.5 kcal/mol, amentoflavone, stigmasterol, and somniferine-A were found to be the most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and competitively inhibit major proteins (SARS-CoV-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-CoV-2 RNA binding protein) that are involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of the drug candidate Amentoflavone. ADMET properties were found to be in the feasible range for putative drug candidates.

Conclusion: Computational analysis was successfully used for searching pharmacoactive phytochemicals like Amentoflavone, Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was found to be efficient, as it reduces monetary expenditures and time consumption. Molecular wet-lab validations will provide approval for finalizing our selected drug model for controlling the COVID-19 pandemic.

Keywords: COVID-19, SARS-CoV-2, ACE-2 receptor, spike protein, amentoflavone, somniferine-A, and chemi-informatic tools.

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