Computational screening of dipeptidyl peptidase IV inhibitors from micoroalgal metabolites by pharmacophore modeling and molecular docking

Dipeptidyl peptidase IV (DPP-IV) catalyzes conversion of GLP1 (glucagon like peptide 1) to inert structure, which results in insufficient secretion of insulin and increase in postprandial blood glucose level. The present study attempts to identify novel inhibitors from bioactive metabolites present in microalgae against DPP-IV through virtual screening, molecular docking, and pharmacophore modeling for the active target. Possible binding modes of all 60 ligands against DPP-IV receptor were constructed using MTiOpenScreen virtual screening server. Pharmacophore model was built based on identified 38 DPP-IV test ligands by using the web-based PharmaGist program which encompasses hydrogen-bond acceptors, hydrophobic groups, spatial features, and aromatic rings. The pharmacophore model having highest scores was selected to screen active DPP-IV ligands. Highest scoring model was used as a query in ZincPharmer screening. All identified ligands were filtered, based on the Lipinski's ruleof- five and were subjected to docking studies. In the process of docking analyses, we considered different bonding modes of one ligand with multiple active cavities of DPP-IV with the help of AutoDock 4.0. The docking analyses indicate that the bioactive constituents, namely, beta-stigmasterol, barbamide, docosahexaenoic acid, arachidonic acid, and harman showed the best binding energies on DPP-IV receptor and hydrogen bonding with ASP545, GLY741, TYR754, TYR666, ARG125, TYR547, SER630, and LYS554 residues. This study concludes that docosahexaenoic acid, arachidonic acid, beta-stigmasterol, barbamide, harman, ZINC58564986, ZINC56907325, ZINC69432950, ZINC69431828, ZINC73533041, ZINC84287073, ZINC69849395, and ZINC10508406 act as possible DPP-IV inhibitors.