2.2. Molecular docking study

We have used AutoDock 4.1 for molecular docking studies and the BIOVIA Discovery Studio (BIOVIA DSB v4.5) for target–ligand interaction visualization study. Saved the retrieved target structure, SARS-CoV-2-M^pro and selected ligands in dot (.) pdb format before single- and double-blind docking study (Aanouz et al., 2020; Mishra et al., 2019; Swain et al., 2018; Swain, Paidesetty et al. 2020). Then, the energy minimized structure of the SARS-CoV-2-M^pro was produced through simulation at 100 nanoseconds (ns) and cleaned the geometry of each ligand to get reliability-cum-stability of the docking complexes. A default AutoDock parameter as Kollman charges-polar hydrogen bonds for the target protein and Geister partial charges-polar hydrogen for ligands were added before the docking study. Then, followed blind docking study for single and double docking with selected phyto-flavonoids and anti-HIV drugs (Swain et al., 2018; Swain, Paidesetty et al. 2020). Out of generated 10 interaction poses for each ligand, the most effective pose was selected based on its binding energy/docking score (Aanouz et al., 2020; Mishra et al., 2019; Swain, Paidesetty et al., 2020). Notably, the inter-changeable double docking study between most potential phyto-flavonoids, quercetin-3-rhamnoside and LPRP-Et-97543 were re-docked against SARS-CoV-2-M^pro-darunavir and SARS-CoV-2-M^pro-tipranavir complexes, individually. Additionally, a ligand–ligand docking study was performed between darunavir-quercetin-3-rhamnoside, darunavir-LPRP-Et-97543, tipranavir-quercetin-3-rhamnoside and tipranavir-LPRP-Et-97543 (Aanouz et al., 2020; Mishra et al., 2019; Swain, Paidesetty et al., 2020). Finally, the most effective protein with double ligand docking complexes was selected for a molecular dynamic (MD) simulation study to explore the solidity of protein–ligand binding.