Integrating virtual screening, pharmacoinformatics profiling, and molecular dynamics: identification of promising inhibitors targeting 3CLpro of SARS-CoV-2 - Mohammad, Abeer; Zheoat, Ahmed; Oraibi, Amjad; Manaithiya, Ajay; S. Almaary, Khalid; Allah Nafidi, Hiba; Bourhia, Mohammed; Kilani-Jaziri, Soumaya; A. Bin Jardan, Yousef (Frontiers in Molecular Biosciences, 2024)
To develop effective therapeutic solutions, existing compounds must be repurposed for effective treatment of SARS-CoV-2 infections and COVID-19 disease. In this study, the central protease, 3-chymotrypsin-like protease (3CLpro), is examined in detail, as it plays a crucial role in the replication of viruses. Molecular dynamics simulations and virtual screening were combined to identify potential 3CLpro inhibitors using pharmacoinformatics profiling and virtual screening. Following a thorough virtual screening of 7120 compounds from various databases, four potential inhibitors were identified: EN1036, F6548-4084, F6548-1613, and PUBT44123754. Compared to the co-crystallized ligands, these compounds demonstrated high binding affinity (from -5.003 to -5.772 Kcal/mol) and superior Induced Fit Docking scores (from -671.66 to -675.26 Kcal/mol). The compound F6548-1613 was remarkable in its Molecular Mechanics Generalized Born Surface Area and Molecular Dynamics simulation results, forming stable hydrogen bonds with amino acids His41 and Thr62 and recording a binding energy of -65.72 kcal/mol in MMGBSA simulations. As a result of Lipinski's rule of five and functional molecular interactions with 3CLpro, the identified compounds indicate promising therapeutic prospects. Integrated in silico methodologies contribute significantly to accelerating drug discovery, laying the groundwork for later experimental validation and optimization, thereby developing effective therapeutics for SARS-CoV-2.