Massive Virtual screening and evaluation of small molecule inhibitors of the Papain-like protease of SARS-CoV-2

With the rapid emergence and spread of new variants of coronavirus type 2 causing acute respiratory syndrome, it is necessary to search for new pharmacological treatments for the disease, especially for patients infected by the new and more aggressive variants of the virus. In the present work, we selected from the PubChem database, ~ 18,000 compounds with similar structure to GRL0617, a papain-like protease inhibitor of SARS-CoV-2. Then, based on the ligand efficacy index obtained by molecular docking, the 500 compounds with higher affinity than GRL0617 for the protease were evaluated. Finally, the seven compounds with ADME parameters within the acceptable range for such a drug were selected. Then, 200 ns molecular dynamics simulation studies, ∆G calculations using Molecular mechanics with generalized Born and surface area solvation, and quantum mechanical calculations were performed with the selected compounds. Using this In Silico protocol, seven papain-like protease inhibitors are proposed: three compounds with binding free energy like GRL0617 (D28, D04 and D59), three compounds with binding free energy higher than GRL0617 (D60, D99 and D06) and one compound (D24) that could bind to the ubiquitin binding region and reduce the effect on the host immune system. The proposed compounds could be used in in vitro tests, and the described protocol could be used for intelligent drug design.