Molecular modelling as a tool for designing dipeptidylpeptidase-4 inhibitors

Abstract

Dipeptidyl peptidase-4 (DPP-4) is a relatively new target for the treatment of type-2 diabetes mellitus (T2DM). Most of the inhibitors designed to date have not relied on modelling studies to guide their lead optimization efforts. In our previous work, we designed compounds that retain the (R)-3-amino-4-(2,4,5-trifluorophenyl)butanamido S1-pocket binding moiety of sitagliptin, but have S2-pocket binding moieties that are more hydrophobic than the triazolopiperazine. In an effort to understand how Vina docking algorithm can be integrated in discovering new inhibitors of DPP-4; we designed, synthesized and evaluated new compounds that vary in the hydrophobic properties of the S2-pocket binding groups. Our results indicate that the minimum binding energy predicted from the docking studies was not reliable in designing more active candidates. However, visualizing the binding modes of each compound and modifying it to target neighboring key residues in the active site is a more effective implementation of the docking in the design of new compounds. Compounds in this study displayed IC50 values ranging from 0.37 µM to 11 µM.