Receptor-based 3D QSAR Studies on PPAR? Agonists using CoMFA and CoMSIA Approaches

Abstract

Receptor-based (RB) quantitative structure-activity relationship (QSAR) studies were performed on the peroxisome proliferator-activated receptors gamma (PPARγ) agonists with antihyperglycemic property using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) implemented in the SYBYL packages. The initial X-ray structure of PPARγ with GI262570 agonist was used to sketch 36 training set molecules having the receptor bound conformation. These structures were subjected to subset energy minimization using TRIPOS force field and aligned against an α-helix of PPARγ receptor. Four models were generated using CoMFA and CoMSIA with two different grid spacing, 2 Å and 1 Å. After PLS analysis, the best predicted CoMSIA model with grid spacing 1 Å, Model 4, showed that a leave-one out (LOO) cross validated value (r) and non-cross validated conventional value (r) are 0.758 and 0.994, respectively. From the CoMFA and CoMSIA contour maps, important interactions crucial to strong binding to the receptor can be identified and verified. This information on the pharmacophore models can be used to design new ligands. Traditional ligand-based (LB) QSAR studies were also performed using the global minima of the same training set molecules. Compared to LB QSAR study, advantage of using subset-minimized RB QSAR study is discussed in detail.