Activity and selectivity cliffs for DPP-IV inhibitors: Lessons we can learn from SAR studies and their application to virtual screening

Identifier:  imarina:5132032

Handle: https://hdl.handle.net/20.500.11797/imarina5132032

Authors:  Jose Ojeda-Montes, Maria; Gimeno, Aleix; Tomas-Hernandez, Sarah; Cereto-Massague, Adria; Beltran-Debon, Raul; Valls, Cristina; Mulero, Miquel; Pujadas, Gerard; Garcia-Vallve, Santiago

Abstract:
The inhibition of dipeptidyl peptidase‐IV (DPP‐IV) has emerged over the last decade as one of the most effective treatments for type 2 diabetes mellitus, and consequently (a) 11 DPP‐IV inhibitors have been on the market since 2006 (three in 2015), and (b) 74 noncovalent complexes involving human DPP‐IV and drug‐like inhibitors are available at the Protein Data Bank (PDB). The present review aims to (a) explain the most important activity cliffs for DPP‐IV noncovalent inhibition according to the binding site structure of DPP‐IV, (b) explain the most important selectivity cliffs for DPP‐IV noncovalent inhibition in comparison with other related enzymes (i.e., DPP8 and DPP9), and (c) use the information deriving from this activity/selectivity cliff analysis to suggest how virtual screening protocols might be improved to favor the early identification of potent and selective DPP‐IV inhibitors in molecular databases (because they have not succeeded in identifying selective DPP‐IV inhibitors with IC50 ≤ 100 nM). All these goals are achieved with the help of available homology models for DPP8 and DPP9 and an analysis of the structure-activity studies used to develop the noncovalent inhibitors that form part of some of the complexes with human DPP‐IV available at the PDB.