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

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 management of Type 2 Diabetes or under clinical trial. In present study, combined pharmacophore and docking based virtual screening protocol was used for 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 binding site of DPP 4. Based on 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 almost similar binding orientation as that of 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 identification of new DPP 4 inhibitor, which can serve as starting point for the development of novel DPP4 inhibitors.