Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 Variants

The present study explores the efficacy of plant-derived natural products (PDNPs) against spike glycoproteins (S-glycoprotein) SARS-CoV-2 variants using molecular docking, ADMET, dynamics (MD) simulation and density-functional theory (DFT) analysis. In all, 100 PDNPs were screened glycoprotein variants, namely alpha (B.1.1.17), beta (B.1.351), delta (B.1.617), gamma (P.1) omicron (B.1.1.529). Results showed that rutin, EGCG, hesperidin, withanolide G, rosmarinic acid, diosmetin, myricetin, epicatechin quercetin top hit compounds each variants. most active compounds, EGCG acid gave binding scores ?10.2, ?8.1, ?8.9, ?8.3 ?9.2 kcal/mol, omicron, delta, alpha, respectively. Further, stability docked complexes was confirmed by analysis descriptors (RMSD, RMSF, SASA, Rg H-bonds) in dynamic Moreover, physiochemical properties drug-likeness tested they have no toxicity or carcinogenicity may be used as druggable targets. addition, DFT revealed higher activity target proteins. This led us to conclude are good candidates S-glycoproteins vivo clinical studies needed develop them drug leads existing new currently underway our laboratory.