The peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that acts as a transcription factor, regulating glucose, lipid and inflammation signaling and it is exploited in type 2 diabetes treatment. However, the selective activation of this PPAR subtype has been linked to important adverse effects which can be mitigated through concomitant activation of PPARα and PPARδ. In this study, we proposed new PPARγ agonists using PharmaGist Server for pharmacophore prediction, the molecular docking was performed by GOLD (genetic optimization for ligand docking) v2.2, AutoDock 4.2 and AutoDock Vina 1.1 and QikProp v4.0 and Derek for absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment. One molecule showed high predicted affinity to PPARγ and favorable pharmacokinetic and toxicity properties. It was then evaluated against PPARα and PPARδ and showed greater affinity to these receptors than the controls. Therefore this molecule is a promising drug lead for the development of derivatives and for the treatment of metabolic syndrome with the benefits of a PPAR pan activation.
Keywords:
type 2 diabetes; PPAR pan agonist; molecular modeling; ADMET prediction
