Multistep structure-based virtual screening approach toward the identification of potential potent SARS-CoV-2 Mpro inhibitors.

Around four years have passed since the globe was shaken by the COVID-19 pandemic, triggered by SARS-CoV-2, affecting almost one billion individuals worldwide and claiming the lives of millions. Despite stringent safety measures and the swift expansion of vaccination initiatives, managing waves of illness has proven challenging. Given its crucial involvement in replication and notable conservation, our team persisted in focusing on the SARS-CoV-2 main protease enzyme (Mpro) as a highly promising therapeutic objective. Accordingly, a multistep computer-aided drug discovery process was used in this study to elucidate potential lead candidates targeting SARS-CoV-2 Mpro. A protein-ligand interaction fingerprint (PLIF) tool was utilized to help design a structure-based pharmacophore based on critical interactions between known ligands and the Mpro active site. The produced pharmacophore was used to filter a fraction of the ZINC database of chemical substances, resulting in 703 possible hits. All the filtered compounds achieved acceptable docking scores and four compounds achieved higher docking scores of selected Mpro inhibitor reference, and the top-ranked compound W1 (ZINC000150656136) was selected for more simulations. A combination of traditional molecular dynamics (MD) and MM-PBSA was used in the final step. W1 has been predicted to engage with multiple essential interactions with key residues in the Mpro active with a docking score and binding free energy of 11.1 kcal/mol and -324.7 ± 9.7 Kj/mol, respectively. As a result, we propose as a lead compound candidate towards the SARS-CoV-2 Mpro enzyme that can be forwarded for experimental validation and clinical studies for COVID-19 management.