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A Selectivity Study of FFAR4/FFAR1 Agonists by Molecular Modeling.

Xiangying ZhangHong-Bin SunXiaoan WenHaoliang Yuan
Published in: Journal of chemical information and modeling (2019)
FFAR4 has been considered as a potential target for metabolic diseases, including diabetes. Some compounds with biphenyl scaffold, represented by compound SR13 reported by our group, showed significant FFAR4 selectivity. However, the molecular basis for their selectivity has not been definitely disclosed. This study provided insights into the protein-ligand interactions between agonists and FFAR4/FFAR1 by molecular modeling. The important residues identified were consistent with those found in experimental studies. Moreover, the results proposed that the selectivity of SR13 between FFAR4 and FFAR1 depended on whether it can enter the ligand-binding site through the entrance region by adopting its preferential conformation. The big difference between the preferential conformation of SR13 and the narrow entrance region determined its poor agonist activity against FFAR1. These findings will facilitate the further development of selective FFAR4 agonists.
Keyphrases
  • type diabetes
  • cardiovascular disease
  • adipose tissue
  • machine learning
  • climate change
  • weight loss
  • binding protein
  • crystal structure
  • glycemic control