3D-QSAR-based pharmacophore determination and design of novel DPP-4 inhibitors

Abstract

Background/Aim: Therapy of diabetes mellitus type 2 includes drugs that act as inhibitors of dipeptidyl peptidase 4 (DPP-4) enzyme. Several DPP-4 inhibitors are marketed today and although they have favourable safety profile and tolerability, they show moderate activity in controlling glycaemia. The 3D quantitative structure-activity relationship (3D-QSAR) methodology was employed in order to find pharmacophore responsible for good DPP-4 inhibitory activity and designed new compounds with enhanced activity. Methods: For 3D-QSAR model development, 48 compounds structurally related to sitagliptin were collected from ChEMBL database. Structures of all compounds were optimised in order to find the best 3D conformations prior to QSAR modelling. To establish correlation between structure and biological activity Partial Least Squares (PLS) regression method integrated in Pentacle software was used. Results: Parameters of internal and external validation (R2 = 0.80, Q2 = 0.64 and R2 pred = 0.610) confirmed reliability of developed QSAR model. Analysis of obtained structural descriptors enabled identification of key structural characteristics that influenced DPP-4 inhibitory activity. Based on that information, new compounds were designed, of which 35 compounds had a better predicted activity, compared to sitagliptin. Conclusion: This QSAR model can be used for DPP-4 inhibitory activity prediction of structurally related compounds and resulting pharmacophore contains information useful for optimisation and design of new DPP-4 inhibitors. Finally, authors propose designed compounds for further synthesis, in vitro and in vivo testing, as new potential DPP-4 inhibitors.