Pharmacophore and Docking Based Combined In-Silico Study of DPP-IV Inhibitors

Abstract

Type-2 diabetes mellitus (T2DM) is characterized by variable degrees of insulin resistance and pancreatic beta-cell dysfunction, which leads to hyperglycaemia. With the progressive nature of T2DM, development of drugs that retard or prevent the transition from the pre-diabetic state of impaired glucose tolerance to overt diabetes have therapeutic potential in attenuating the rapid rise in the disease prevalence. Furthermore, with the currently existing forms of therapy, insulin secretory capacity is ultimately lost in later stages of diabetes. Dipeptidyl peptidase IV (DPP-IV) is a valid drug target for type-2 diabetes and DPP-IV inhibitors have been proven to efficiently improve glucose tolerance. Ligand Based Pharmacophore model was developed using Discotech module of SYBYL X1.2 software with training set of 16 structurally and biologically diverse DPP-IV inhibitors. The best pharmacophore model, was selected based on highest score of 0.5859, a tolerance of 0.500, and a D-Mean of 3.9179.It consists of five feature namely, one positive nitrogen (PN), one hydrophobic point (HY), two acceptor sites (AS) and one donor atom. The model was validated by test set of 51 known DPP-IV inhibitors and was used as query in NCI and Maybridge hit finder databases. The model demonstrated the capability to retrieve inhibitors from databases with more than 80% Qfit value. Thirty (38) molecules having more than 90% Qfit value were docked into DPP-IV enzyme. Among these, 2 molecules showed higher docking score compared to the reference standard Vildagliptin. In silico pharmacokinetic properties and toxicities were predicted for these 2 molecules using OSIRIS property explorer and were reported as novel virtual DPP-IV inhibitors.