Literature DB >> 24858253

A single amino acid change humanizes long-chain fatty acid binding and activation of mouse peroxisome proliferator-activated receptor α.

Dhawal P Oswal1, Gerald M Alter1, S Dean Rider1, Heather A Hostetler2.   

Abstract

Peroxisome proliferator-activated receptor α (PPARα) is an important regulator of hepatic lipid metabolism which functions through ligand binding. Despite high amino acid sequence identity (>90%), marked differences in PPARα ligand binding, activation and gene regulation have been noted across species. Similar to previous observations with synthetic agonists, we have recently reported differences in ligand affinities and extent of activation between human PPARα (hPPARα) and mouse PPARα (mPPARα) in response to long chain fatty acids (LCFA). The present study was aimed to determine if structural alterations could account for these differences. The binding of PPARα to LCFA was examined through in silico molecular modeling and docking simulations. Modeling suggested that variances at amino acid position 272 are likely to be responsible for differences in saturated LCFA binding to hPPARα and mPPARα. To confirm these results experimentally, LCFA binding, circular dichroism, and transactivation studies were performed using a F272I mutant form of mPPARα. Experimental data correlated with in silico docking simulations, further confirming the importance of amino acid 272 in LCFA binding. Although the driving force for evolution of species differences at this position are yet unidentified, this study enhances our understanding of ligand-induced regulation by PPARα and demonstrates the efficacy of molecular modeling and docking simulations.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Amino acid differences; Endogenous ligand; Fatty acid; PPAR; Species differences; Transcription factor

Mesh:

Substances:

Year:  2014        PMID: 24858253      PMCID: PMC4079465          DOI: 10.1016/j.jmgm.2014.04.006

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  38 in total

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