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

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 IC ≤ 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.

In Silico Approaches Applied to the Study of Peptide Analogs of Ile-Pro-Ile in Relation to Their Dipeptidyl Peptidase IV Inhibitory Properties

“…Molecular docking showed that Ile-Pro-Ile and its associated peptide analogs established similar interactions with the active site of porcine DPP-IV (Figure 6 ). These interactions are consistent with those (i.e., with Glu205, Glu206, Tyr662) that have been demonstrated earlier with the S 1 pocket of the active site of DPP-IV ( 40 ). Nevertheless, there was no correlation between the computed scores and the experimentally determined DPP-IV IC 50 values (Figure 6 ; Table 2 ).…”

“…Several structural and physicochemical parameters of molecules have been shown to affect their ability to inhibit DPP-IV ( 40 ). The hydrophobicity of amino acids located within specific positions of peptides is thought to be of importance for the inhibition of DPP-IV ( 9 , 41 , 42 ).…”

“…Other than hydrophobicity, aromaticity and steric hindrance of amino acid residues may play a role in the ability of peptides to inhibit DPP-IV. In a recent review paper on DPP-IV inhibitory properties of molecules, Ojeda-Montes et al ( 40 ) suggested that potent DPP-IV inhibitors included molecules possessing aromatic rings, which can establish hydrophobic interactions with the S 1 subsite of the DPP-IV active site. Earlier studies have reported on the existence of exclusion volumes in the S 1 pocket of DPP-IV ( 45 ).…”

Bioactive Peptides from Germinated Soybean with Anti-Diabetic Potential by Inhibition of Dipeptidyl Peptidase-IV, α-Amylase, and α-Glucosidase Enzymes

“…Other than hydrophobicity, aromatic amino acid residues of peptides are important to inhibit DPP-IV. A previous study [ 33 ] suggested that the potency of DPP-IV inhibitors is related to the presence of aromatic rings as they form hydrophobic interactions with the DPP-IV catalytic domain. More recently, it has confirmed the importance of the presence of hydrophobic residues and a proline at the first, second, third, or fourth Nt position of peptides displaying potent DPP-IV inhibitory properties [ 13 , 34 ].…”

Improving the Virtual Screening Ability of Target-Specific Scoring Functions Using Deep Learning Methods

“…According to a recent review about DPP4 inhibitors, Glu205, Glu206, and Tyr662 in DPP4 are believed to be the most import anchor points helping inhibitors recognize DPP IV. Since we used different protein with (Ojeda-Montes et al, 2018), for the convenience of comparison, we performed sequence alignment and renumbered all residues so that the residue number we used could match (Ojeda-Montes et al, 2018). In Figure 10 , it can be seen that DeepScore also favored these three residues and gave them fairly high scores.…”