The molecular basis of ligand interaction at free fatty acid receptor 4 (FFA4/GPR120).

The molecular basis of ligand interaction at free fatty acid receptor 4 (FFA4/GPR120).
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DOI:
10.1074/jbc.m114.561449
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发表时间:
2014-07-18
期刊:
The Journal of biological chemistry
影响因子:
--
通讯作者:
Ulven T
Ulven T
中科院分区:
其他
文献类型:
--
作者:
Hudson BD;Shimpukade B;Milligan G;Ulven T

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背景:FFA 4是长链脂肪酸的受体,被认为是代谢性疾病的新靶点。结果:结合分子建模,受体突变,和配体的结构-活性关系定义的结合口袋。结论:脂肪酸和合成激动剂共有一个重叠的结合位点。意义:验证的同源性模型将有助于寻找新的配体。长链脂肪酸受体FFA 4(以前称为GPR 120)作为治疗代谢和炎症性疾病的新靶点受到了极大的关注。本研究第一次检查的详细模式结合的长链脂肪酸和合成激动剂配体在FFA 4通过整合分子建模,受体诱变,和配体的结构-活性关系的方法在一个迭代格式。在这样做时,已经鉴定了脂肪酸和合成激动剂与FFA 4结合所需的残基。这使得一个很好的验证模型的配体-FFA 4相互作用的模式,这将是非常宝贵的识别新的配体和这种受体作为治疗靶点的未来发展的细化。该模型可靠地预测了取代基变化对激动剂效力的影响,并且在大多数情况下也能够预测结合位点突变的定性影响。
Background: FFA4 is a receptor for long-chain fatty acids and is considered a novel target for metabolic diseases. Results: Combinations of molecular modeling, receptor mutagenesis, and ligand structure-activity relationships defined the binding pocket. Conclusion: Fatty acid and synthetic agonists share an overlapping binding site. Significance: The validated homology model will assist the search for novel ligands. The long-chain fatty acid receptor FFA4 (previously GPR120) is receiving substantial interest as a novel target for the treatment of metabolic and inflammatory disease. This study examines for the first time the detailed mode of binding of both long-chain fatty acid and synthetic agonist ligands at FFA4 by integrating molecular modeling, receptor mutagenesis, and ligand structure-activity relationship approaches in an iterative format. In doing so, residues required for binding of fatty acid and synthetic agonists to FFA4 have been identified. This has allowed for the refinement of a well validated model of the mode of ligand-FFA4 interaction that will be invaluable in the identification of novel ligands and the future development of this receptor as a therapeutic target. The model reliably predicted the effects of substituent variations on agonist potency, and it was also able to predict the qualitative effect of binding site mutations in the majority of cases.