Abstract
BACKGROUND: Temporomandibular joint pain dysfunction syndrome (TMJPDS) is a musculoligamentous condition causing dull, aching pain in the masticatory muscles, influenced by jaw movement. Computer-aided drug design (CADD) uses computational methods to support modern drug discovery. Molecular docking, a core CADD technique, predicts drug-target interactions, aiding in stable, specific, and effective drug design. AIM: The aim of this study was to use the docking technique for COMT inhibitors. MATERIALS AND METHODS: Four COMT inhibitors were selected from the literature, and their compound structures were obtained from the Zinc15 database. The COMT protein was designated as the target and was refined utilizing the RCSB Protein Data Bank. After pharmacophore modeling, 20 novel compounds were found, and SwissDock was used to dock them with the target protein. We compared the binding energies of the newly discovered compounds to those of the previously published molecules with the target. RESULTS: The findings revealed that out of the 20 molecules, ZINC101880339 and ZINC100287288 demonstrated the highest binding energy and showcased superior characteristics compared to the remaining molecules. CONCLUSION: The study concluded that ZINC101880339 and ZINC100287288 demonstrated higher binding affinity than known COMT inhibitors. Consequently, these two molecules hold promise as potential leads for treating TMJPDS and may be utilized in targeted drug therapy. CATEGORIES: Dentistry, TMJ, Computational Screening.