Computational modeling and analysis of Ayurvedic compounds in fighting against COVID-19

AIM: To screen the selective Ayurvedic amalgams against severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) main protease in the investigation of antiviral activity using computational-based methods. MATERIALS AND METHODS: The current research study endeavors to gauge the in silico potency of Ayurvedic molecules/drugs, chosen from primeval classical literature and former human medication protocols of Ayurveda for the preemption and treatment of contagion (COVID-19). Overall, 84 Ayurvedic compounds on the basis of antiviral activity were searched from literature and public database sources and canonical smiles format molecular information was retrieved from the PubChem database. All the compounds were sketched using Chemsketch tool and optimized using UFF force field. The selected molecules were then virtually screened against the SARS-CoV-2 main protease available structure. RESULTS: The outcomes were evaluated based on docking scores and pharmacophoric-based interactions; five compounds exhibited an optimum interaction within the binding site of SARS-CoV-2 main protease. CONCLUSION: The current research study lay the foundation of drug repurposing with the amalgamation of knowledge of Ayurveda and computational aided modeling in fighting against COVID-19. Therefore, the pragmatic dogma proposed here will facilitate learning, generate evidence, and pave the way forward.