In silico Identification of Novel SARS-CoV-2 Main Protease and Non-structural Protein 13 (nsp13) Inhibitors through Consensus Docking and Free Binding Energy Calculations

Background A new strain of a novel disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been recently declared a pandemic by the World Health Organization (WHO). The virus results in significant mortality and morbidity across the planet; therefore, novel treatments are urgently required. Recently deposited crystallographic structures of SARS-CoV-2 proteins have ignited the interest in virtual screenings of large databases. Objective In the current study, we evaluated the inhibitory capacity of the IMPPAT phytochemical database (8500 compounds) and the SuperDRUG2 dataset (4000 compounds) in SARS-CoV-2 main protease and helicase Nsp13 through consensus-based docking simulations. Methods Glide and GOLD 5.3 were implemented in the in silico process. Further MM/GBSA calculations of the top 10 inhibitors in each protein were carried out to investigate the binding free energy of the complexes. An analysis of the major ligand-protein interactions was also conducted. Results After the docking simulations, we acquired 10 prominent phytochemicals and 10 FDA-approved drugs capable of inhibiting Nsp5 and Nsp13. Delphinidin 3,5,3'-triglucoside and hirsutidin 3-O-(6-O-p-coumaroyl)glucoside demonstrated the most favorable binding free energies against Nsp5 and Nsp13, respectively. Conclusion In conclusion, the analysis of the results identified that the phytochemicals demonstrated enhanced binding capacities compared to the FDA-approved database.