Combined Ligand-Based and Structure-Based Virtual Screening Approach for Identification of New Dipeptidyl Peptidase 4 Inhibitors

Abstract

Background: Dipeptidyl Peptidase 4 (DPP 4) enzyme cleaves an incretin-based glucoregulatory hormone Glucagon Like Peptide -1 from N-terminal where penultimate amino acid is either alanine or proline. Several DPP 4 inhibitors, “gliptins”, are approved for the management of Type 2 Diabetes or are under clinical trial. In the present study, combined pharmacophore and docking-based virtual screening protocol were used for the identification of new hits from the Specs Database, which would inhibit DPP 4. Methods: The entire computational studies were performed using the Discovery Studio v. 4.1 software package, Pipeline Pilot v. 9.2 (Accelrys Inc.) and FRED v. 2.2.5 (OpenEye Scientific Software). Common feature pharmacophore model was generated from known DPP 4 inhibitors and validated by Receiver Operating curve analysis and GH-scoring method. Database search of Specs commercial database was performed using validated pharmacophore. Hits obtained from pharmacophore search were further docked into the binding site of DPP 4. Based on the analysis of docked poses of hits, 10 compounds were selected for in- vitro DPP 4 enzyme inhibition assay. Results: Based on docking studies, virtual hits were predicted to form interaction with essential amino acid residues of DPP 4 and have an almost similar binding orientation as that of the reference molecule. Three compounds having Specs database ID- AN-465/42837213, AP-064/42049348 and AN- 465/43369427 were found to inhibit DPP 4 enzyme moderately. Conclusion: The present study demonstrates a successful utilization of in-silico tools in the identification of new DPP 4 inhibitor, which can serve as a starting point for the development of novel DPP 4 inhibitors.