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Research Articles

Withanone and Withaferin-A are predicted to interact with transmembrane protease serine 2 (TMPRSS2) and block entry of SARS-CoV-2 into cells

, , , , , , , & show all
Pages 1-13 | Received 16 May 2020, Accepted 25 May 2020, Published online: 16 Jun 2020
 

Abstract

Coronavirus disease 2019 (COVID-19) initiated in December 2019 in Wuhan, China and became pandemic causing high fatality and disrupted normal life calling world almost to a halt. Causative agent is a novel coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2/2019-nCoV). While new line of drug/vaccine development has been initiated world-wide, in the current scenario of high infected numbers, severity of the disease and high morbidity, repurposing of the existing drugs is heavily explored. Here, we used a homology-based structural model of transmembrane protease serine 2 (TMPRSS2), a cell surface receptor, required for entry of virus to the target host cell. Using the strengths of molecular docking and molecular dynamics simulations, we examined the binding potential of Withaferin-A (Wi-A), Withanone (Wi-N) and caffeic acid phenethyl ester to TPMRSS2 in comparison to its known inhibitor, Camostat mesylate. We found that both Wi-A and Wi-N could bind and stably interact at the catalytic site of TMPRSS2. Wi-N showed stronger interactions with TMPRSS2 catalytic residues than Wi-A and was also able to induce changes in its allosteric site. Furthermore, we investigated the effect of Wi-N on TMPRSS2 expression in MCF7 cells and found remarkable downregulation of TMPRSS2 mRNA in treated cells predicting dual action of Wi-N to block SARS-CoV-2 entry into the host cells. Since the natural compounds are easily available/affordable, they may even offer a timely therapeutic/preventive value for the management of SARS-CoV-2 pandemic. We also report that Wi-A/Wi-N content varies in different parts of Ashwagandha and warrants careful attention for their use.

Communicated by Ramaswamy H. Sarma

Acknowledgments

The computations were performed at the Bioinformatics Centre supported by the Department of Biotechnology (DBT) Govt. of India at IIT Delhi.

Author contributions

Conceptualization - V.K., D.S, R.W.; Bioinformatics work and formal analysis- V.K., J.K.D., D.S.; Experimental work - A.K., J.K.D, J.W., H.Z., P.B.; Funding acquisition - S.C.K., R.W., D.S.; Writing - review & editing V.K., J. K.D., S.C.K., R.W., D.S. All authors contributed to the development of this manuscript and read and approved the final version.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was supported by the funds granted by AIST (Japan) and DBT (Government of India).

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