Molecular Modeling Approach to Study the PPARγ-Ligand Interactions

Methods Mol Biol. 2019:1966:261-289. doi: 10.1007/978-1-4939-9195-2_22.

Abstract

The chapter is focused on methods relevant for predictive toxicology and computer-aided drug design (adverse outcome pathway development, pharmacophore modeling, docking, and 3D QSAR analysis) and applied to study interactions between peroxisome proliferator-activated receptor γ (PPARγ) and its ligands. The methods have been combined to develop an integrated in silico approach allowing both to predict potential PPARγ-mediated hepatotoxicity of receptor's full agonists, thus supporting hazard characterization, and to identify naturally derived antidiabetic triterpenoids potentially acting through PPARγ partial agonism.

Keywords: 3D QSAR; AOP; Docking; In silico modeling; PPARγ full agonists; PPARγ partial agonists; Pharmacophore modeling.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Hypoglycemic Agents / pharmacology*
  • Ligands
  • Molecular Docking Simulation / methods*
  • Oxazoles / pharmacology
  • PPAR gamma / agonists
  • PPAR gamma / chemistry
  • PPAR gamma / metabolism*
  • Protein Conformation
  • Quantitative Structure-Activity Relationship
  • Rosiglitazone / pharmacology
  • Tyrosine / analogs & derivatives
  • Tyrosine / pharmacology

Substances

  • GW 409544
  • Hypoglycemic Agents
  • Ligands
  • Oxazoles
  • PPAR gamma
  • Rosiglitazone
  • Tyrosine