Stilbene-based natural compounds as promising drug candidates against COVID-19

J Biomol Struct Dyn. 2020 May 12;1-10. doi: 10.1080/07391102.2020.1762743. Online ahead of print.

Abstract

The pandemic coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a great threat to public health. Currently, no potent medicine is available to treat COVID-19. Quest for new drugs especially from natural plant sources is an area of immense potential. The current study aimed to repurpose stilbenoid analogs, reported for some other biological activities, against SARS-CoV-2 spike protein and human ACE2 receptor complex for their affinity and stability using molecular dynamics simulation and binding free energy analysis based on molecular docking. Four compounds in total were probed for their binding affinity using molecular docking. All of the compounds showed good affinity (> -7 kcal/mol). However, fifty nanoseconds molecular dynamic simulation in aqueous solution revealed highly stable bound conformation of resveratrol to the viral protein: ACE2 receptor complex. Net free energy of binding using MM-PBSA also affirmed the stability of the resveratrol-protein complex. Based on the results, we report that stilbene based compounds in general and resveratrol, in particular, can be promising anti-COVID-19 drug candidates acting through disruption of the spike protein. Our findings in this study are promising and call for further in vitro and in vivo testing of stiblenoids, especially resveratrol against the COVID-19. [Formula: see text] Communicated by Ramaswamy H. SarmaHighlightsStilbenoid analogs could be potential disruptors of SARS-CoV-2 spike protein and human ACE2 receptor complex.In particular, resveratrol revealed highly stable conformation to the viral protein: ACE2 receptor complex.The strong interaction of resveratrol is affirmed by molecular dynamic simulation studies and better net free energies.

Keywords: COVID-19; MM-PBSA; Stilbenoids; molecular docking; molecular dynamic simulations.