Discovery of Inhibitors of SARS-CoV-2 Papain-like Protease Using Molecular Simulation and Markov State Model.

The global outbreak of COVID-19, caused by SARS-CoV-2, has highlighted the urgent need for antiviral treatments. The papain-like protease (PLpro) of SARS-CoV-2, essential for viral replication and the disruption of host signaling pathways, has emerged as a promising drug target. However, the scarcity of potent inhibitors and their limited biological activity pose significant challenges. This study investigates potential inhibitors by focusing on two known binding sites of PLpro, the catalytic triad and the ubiquitin-binding sites. Using mixed-solvent molecular dynamics (MixMD), five probe molecule-solvent systems were simulated to induce conformational changes at these binding sites, providing diverse trajectories for subsequent Markov state model (MSM) analysis. Conformations were analyzed using the Markov state model (MSM) to select functionally relevant states for inhibitor design. LigBuilder V3 was employed to evaluate the binding site druggability, followed by virtual screening with Schrödinger software to identify candidate inhibitors. Finally, in vitro activity assays confirmed the inhibitory potential of selected compounds, providing insight into the feasibility of these sites as drug targets. This research advances our understanding of PLpro and contributes to the development of effective antiviral therapies.