Issue 96, 2016

Computational investigation of the interaction mechanism between the estrogen related receptor α and its agonists

Abstract

Estrogen related receptor alpha (ERRα), the first identified orphan nuclear receptor, participates in the metabolism of body and adjusts some diseases such as breast cancer, osteoporosis and diabetes. Recent experiments have identified several ligands such as 7a, 7b, DK1 and DK3 toward ERRα as agonists, to have a therapeutic ability in reducing blood glucose, and impact the activity of ERRα receptor. Nevertheless, the detailed interaction modes between the agonists and the ERRα have not been fully understood, which will hinder the design and development of more potent agonists targeting ERRα for the treatment of diabetes. To address this issue, molecular docking and molecular dynamic simulation (MD) were performed to study how the four agonists regulate the behavior of ERRα. It was found that a proved residue Phe232 and some others such as Arg276, Phe286, His398 and Phe399 were the key residues in the ligand binding pocket. Hydrogen bonds between agonists and residues Arg276 and His398 and the pi–pi interactions between agonists and Phe232/Phe286/Phe399 both play important roles for agonist–ERRα binding. Interestingly, we observed that the agonists kept the binding of ERRα and its coactivator PGC-1α by stabilizing the site of helix12 (H12). All these findings are not only beneficial to understand the interaction mechanism between ERRα and its agonists, but also provide clues for designing novel and potent agonists of ERRα for the treatment of diabetes.

Graphical abstract: Computational investigation of the interaction mechanism between the estrogen related receptor α and its agonists

Article information

Article type
Paper
Submitted
02 Aug 2016
Accepted
27 Sep 2016
First published
27 Sep 2016

RSC Adv., 2016,6, 94119-94127

Computational investigation of the interaction mechanism between the estrogen related receptor α and its agonists

F. Li, X. Sun, Y. Cai, D. Fan, W. Li, Y. Tang and G. Liu, RSC Adv., 2016, 6, 94119 DOI: 10.1039/C6RA19536A

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