A Dual-Response Partial Least Squares Regression QSAR Model and its Application in Design of Dual Activators of PPARα and PPARγ

In this paper, in attempt was made to develop a dual-response Quantitative Structure-Activity Relationship (QSAR) model on a series of 5-aryl thiazolidinedione and oxazolidinedione derivatives acting as dual activators of PPAR alpha and PPAR gamma (Peroxisome Proliferator-Activated Receptors) using. partial least squares regression method. Various 2D descriptors were calculated and used in the present analysis. For model validation, the dataset was divided into various training and test Sets using both rational and random selection procedures. The developed QSAR models were found to be statistically significant with respect to training (r(2) > 0.8), cross-validation (q(2) > 0.7). and external validation (pred_r(2)>0.8). The developed dual-response model suggests that descriptors such as HBA, HBD. Xlog P, polar surface area play an important role in determining both biological activities. In addition, it allows comparison of the behavior of common subset descriptors toward each activity which may aid in the rational design of novel selective/non-selective potent molecules.