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

(E-pub Ahead of Print)

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

Journal Name: Coronaviruses
The World's First International Journal Dedicated to Coronaviruses

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Background: The scientific community has supported from the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, it was discovered Amentoflavone as an anti-viral agent and its presence as a bioactive constituent in many plants of different families Selaginellaceae, Euphorbiaceae, and Calophyllaceae etc. Withania somnifera (Ashwagandha) is already considered significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A, 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 SARS-Cov-2's internalization and interaction with human cytological domains. This will help in developing check point for SARS-Cov-2 internalization.

Material and methods: Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were deployed to examine the action of pharmacoactive agents against SARS-Cov-2. The many tools deployed in the study were based on 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 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 found to involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of drug candidate Amentoflavone. ADMET properties were found to be in feasible range for putative drug candidates.

Conclusion: Computational analysis was successfully deployed in 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 reduces monetary expenditures and time consumption, aftermath molecular wet-lab validations will provide better approval for finalizing our selected drug model for controlling 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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(E-pub Ahead of Print)
DOI: 10.2174/2666796701999201203210036