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Research Articles

Synthetic flavonoids as potential antiviral agents against SARS-CoV-2 main protease

, , , , , , ORCID Icon & ORCID Icon show all
Pages 3777-3788 | Received 11 Sep 2020, Accepted 09 Nov 2020, Published online: 30 Nov 2020
 

Abstract

The COVID-19 pandemic has claimed more than a million lives worldwide within a short time span. Due to the unavailability of specific antiviral drugs or vaccine, the infections are causing panic both in general public and among healthcare providers. Therefore, an urgent discovery and development of effective antiviral drug for the treatment of COVID-19 is highly desired. Targeting the main protease (Mpro) of the causative agent, SARS-CoV-2 has great potential for drug discovery and drug repurposing efforts. Published crystal structures of SARS-CoV-2 Mpro further facilitated in silico investigations for discovering new inhibitors against Mpro. The present study aimed to screen several libraries of synthetic flavonoids and benzisothiazolinones as potential SARS-CoV-2 Mpro inhibitors using in silico methods. The short-listed compounds after virtual screening were filtered through SwissADME modeling tool to remove molecules with unfavorable pharmacokinetics and medicinal properties. The drug-like molecules were further subjected to iterative docking for the identification of top binders of SARS-CoV-2 Mpro. Finally, molecular dynamic (MD) simulations and binding free energy calculations were performed for the evaluation of the dynamic behavior, stability of protein–ligand complex, and binding affinity, resulting in the identification of thioflavonol, TF-9 as a potential inhibitor of Mpro. The computational studies further revealed the binding of TF-9 close to catalytic dyad and interactions with conserved residues in the S1 subsite of the substrate binding site. Our in-silico study demonstrated that synthetic analogs of flavonoids, particularly thioflavonols, have a strong tendency to inhibit the main protease Mpro, and thereby inhibit the reproduction of SARS-CoV-2.

Communicated by Ramaswamy H. Sarma

Acknowledgements

The authors are grateful to Shelvia Malik from Schrodinger Inc. for providing Glide evaluation license and invaluable instructions about the software

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

F.B. ran iterative docking experiments and ADME analyses. A.S and N.N. draw chemical structures and performed experimental work. A. J. formed some docking analyses. M. S. and E. U. M. conceived idea, supervised and wrote manuscript. M. S. designed computational study, analyzed data, and edited the manuscript. K. Z. and Z.U.-H. performed MD simulation study.

Additional information

Funding

The study was supported by Faculty Initiative Funding (FIF-642) from Lahore University of Management Sciences

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