Structure-based virtual screening, molecular dynamics and binding affinity calculations of some potential phytocompounds against SARS-CoV-2

Abstract

COVID-19 caused by a positive-sense single stranded RNA virus named as severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) triggered the global pandemic. This virus has infected about 10.37 Crores and taken lives of 2.24 Crores people of 213 countries to date. To cope-up this emergency clinical trials are undergoing with some existing drugs like remdesivir, flavipiravir, lopinavir-ritonavir, nafamostat, doxycycline, hydroxy-chloroquine, dexamethasone, etc., despite their severe toxicity and health hazards among diabetics, hypertensive, cardiac patients or normal individuals. The lack of safe and approved treatment for COVID-19 has forced the scientific community to find novel and safe compounds with potential efficacy. This study evaluates a few selective herbal compounds like glucoraphanin, vitexin, niazinin, etc., as a potential inhibitor of the spike protein and 3-chymotrypsin-like protease (3CLpro) or main protease (Mpro) of SARS-COV-2 through in-silico virtual studies such as molecular docking, target analysis, toxicity prediction and ADME prediction and supported by a Molecular-Dynamic simulation. Selective phytocompounds were docked successfully in the binding site of spike glycoprotein and 3CLpro (Mpro) of SARS-CoV-2. In-silico approaches also predict this molecule to have good solubility, pharmacodynamic property and target accuracy through MD simulation and ADME studies. These hit molecules niazinin, vitexin, glucoraphanin also obey Lipinski’s rule along with their stable binding towards target protein of the virus, which makes them suitable for further biochemical and cell-based assays followed by clinical investigations to highlight their potential use in COVID-19 treatment.

Communicated by Ramaswamy H. Sarma

Keywords:

• Indian bioactive herbal molecule
• SARS-nCoV-2
• antiviral agents
• protein-ligand interactions
• in-silico docking
• 3CLpro
• MD simulation
• spike glycoprotein

Disclosure statement

No potential conflict of interest was reported by the authors.

Acknowledgements

This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund to AG and KS. AG and KS also acknowledge the support provided by Compute Canada through access to high performance GPU clusters of GRAHAM and Cedar.