SAR and Computer-Aided Drug Design Approaches in the Discovery of Peroxisome Proliferator-Activated Receptor γ Activators: A Perspective. (4th April 2013)

• Record Type: Journal Article
• Authors: Dixit, Vaibhav A.; Bharatam, Prasad V.
• Other Names: Migliore Michele Academic Editor.
• Is Part Of: Journal of computational medicine. Volume 2013(2013)
• Publication Date: 2013-04-04
• Subjects: Medical informatics -- Periodicals; Computational intelligence -- Periodicals; Computational intelligence; Medical informatics; Periodicals; Electronic journals; 610.285
• DOI: 10.1155/2013/406049
• Languages: English
• ISSNs: 2314-5080

Abstract

Abstract : Activators of PPAR γ, Troglitazone (TGZ), Rosiglitazone (RGZ), and Pioglitazone (PGZ) were introduced for treatment of Type 2 diabetes, but TGZ and RGZ have been withdrawn from the market along with other promising leads due cardiovascular side effects and hepatotoxicity. However, the continuously improving understanding of the structure/function of PPAR γ and its interactions with potential ligands maintain the importance of PPAR γ as an antidiabetic target. Extensive structure activity relationship (SAR) studies have thus been performed on a variety of structural scaffolds by various research groups. Computer-aided drug discovery (CADD) approaches have also played a vital role in the search and optimization of potential lead compounds. This paper focuses on these approaches adopted for the discovery of PPAR γ ligands for the treatment of Type 2 diabetes. Key concepts employed during the discovery phase, classification based on agonistic character, applications of various QSAR, pharmacophore mapping, virtual screening, molecular docking, and molecular dynamics studies are highlighted. Molecular level analysis of the dynamic nature of ligand-receptor interaction is presented for the future design of ligands with better potency and safety profiles. Recently identified mechanism of inhibition of phosphorylation of PPAR γ at SER273 by ligands is reviewed as a new strategy to identify novel drug candidates.