4.7 Article

FFA1-selective agonistic activity based on docking simulation using FFA1 and GPR120 homology models

期刊

BRITISH JOURNAL OF PHARMACOLOGY
卷 168, 期 7, 页码 1570-1583

出版社

WILEY
DOI: 10.1111/j.1476-5381.2012.02052.x

关键词

G-protein coupled receptor; FFA1; GPR120; agonist; homology modelling

资金

  1. Grants-in-Aid for Scientific Research [23659038] Funding Source: KAKEN

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BACKGROUND AND PURPOSE The free fatty acid FFA1 receptor and GPR120 are GPCRs whose endogenous ligands are medium- and long-chain FFAs, and they are important in regulating insulin and GLP-1 secretion respectively. Given that the ligands of FFA1 receptor and GPR120 have similar properties, selective pharmacological tools are required to study their functions further. EXPERIMENTAL APPROACH We used a docking simulation approach using homology models for each receptor. Biological activity was assessed by phosphorylation of ERK and elevation of intracellular calcium ([Ca2+]i) in cells transfected with FFA1 receptor or GPR120. Insulin secretion from murine pancreatic beta cells (MIN6) was also measured. KEY RESULTS Calculated hydrogen bonding energies between a series of synthetic carboxylic acid compounds and the homology models of the FFA1 receptor and GPR120, using docking simulations, correlated well with the effects of the compounds on ERK phosphorylation in transfected cells (R2= 0.65 for FFA1 receptor and 0.76 for GPR120). NCG75, the compound with the highest predicted selectivity for FFA1 receptors from this structure-activity relationship analysis, activated ERK and increased [Ca2+]i as potently as the known FFA1 receptor-selective agonist, Compound 1. Site-directed mutagenesis analysis based on the docking simulation showed that different amino acid residues were important for the recognition and activation by FFA1 receptor agonists. Moreover, NCG75 strongly induced ERK and [Ca2+]i responses, and promoted insulin secretion from MIN6 cells, which express endogenous FFA1 receptors. CONCLUSION AND IMPLICATIONS A docking simulation approach using FFA1 receptor and GPR120 homology models could be useful in predicting FFA1 receptor-selective agonists.

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