A Novel Strategy for Designing the Selective PPAR Agonist by the “Sum of Activity” Model

Abstract

Peroxisome proliferator-activated receptors alpha, delta and gamma are a collection of ligand-activated transcription factors crucial in lipid and glucose homeostasis. The involvement of these receptors in lipid metabolism makes them perfect therapeutic target for treating obesity and stroke. In this study, 'sum of activity' model was employed to design multi-target agonists. We used a new strategy to design agonists that fit both alpha and delta but not gamma, to avoid side effect. The CoMFA and CoMSIA models were used to explore the pharmacophore features by constructing three individual models: (a) alpha-model, (b) delta-model and (c) gamma-model, and two sum models: (d) alpha, delta- model, and (e) alpha, delta and gamma-model. The CoMFA model yielded a significant cross validation value, q(2), of 0.729 and non-cross validation value, r(2), of 0.933 in the alpha, delta-model. The CoMSIA studies yielded the best predictive models with q(2) of 0.622 in A+S and with r(2) of 0.911 in the alpha, delta-model. Finally, we proposed that distinct features shown in models (a), (b), (d) but not (c) and (e) should be accounted in designing weight-controlling drugs.