In Silico approach for screening of the indonesian medicinal plants database to discover potential dipeptidyl peptidase-4 inhibitors

Background: Dipeptidyl peptidase-4 (DPP4) is an enzyme responsible for inactivating the hormone incretin, which potentiates insulin secretion and glucagon inhibition; inhibitors of DPP4 are used as therapeutic drugs for type-2 diabetes. Objective: In this study, we evaluated potential DPP4 inhibitors from the Indonesian Medicinal Plants Database using an in silico approach. Methods: A ligand-based pharmacophore model was used for screening the database using LigandScout 4.2. This model was validated using several parameters of enrichment metrics, including receiver operating characteristics, area under curve (AUC), and enrichment factor (EF). Hit compounds were also docked with DPP4 to calculate the free binding energy and analyze the interaction between the ligand and DPP4. In addition, bioavailability and medicinal chemistry predictions were performed for the hit compounds. Results: The best pharmacophore model demonstrated AUC100% and EF values of 0.82 and 33.8, respectively. The pharmacophore features of the model included hydrogen bond donors, hydrogen bonds, hydrophobic interactions, and positive ionization areas. Based on our results of virtual screening and molecular docking, six hit compounds were ultimately identified, namely, L-noradrenaline, octopamine, Nb-demethylechitamine, alliin, isoalliin, and subaphylline. Conclusion: Collectively, our findings indicate that subaphylline is the most promising compound for further studies, including in vitro and in vivo experiments and those focused on molecular dynamics and structural modification.