Materials and Process Simulation Center (MC139-74), California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA.
J Struct Biol. 2010 Apr;170(1):10-20. doi: 10.1016/j.jsb.2010.01.001. Epub 2010 Jan 15.
G protein-coupled receptors (GPCRs) are therapeutic targets for many diseases, but progress in developing active and selective therapeutics has been severely hampered by the difficulty in obtaining accurate structures. We have been developing methods for predicting the structures for GPCR ligand complexes, but validation has been hampered by a lack of experimental structures with which to compare our predictions. We report here the predicted structures of the human adenosine GPCR subtypes (A(1), A(2A), A(2B), and A(3)) and the binding sites for adenosine agonist and eight antagonists to this predicted structure, making no use of structural data, and compare with recent experimental crystal structure for ZM241385 bound human A(2A) receptor. The predicted structure correctly identifies 9 of the 12 crystal binding site residues. Moreover, the predicted binding energies of eight antagonists to the predicted structure of A(2A) correlate quite well with experiment. These excellent predictions resulted when we used Monte Carlo techniques to optimize the loop structures, particularly the cysteine linkages. Ignoring these linkages led to a much worse predicted binding site (identifying only 3 of the 12 important residues). These results indicate that computational methods can predict the three-dimensional structure of GPCR membrane proteins sufficiently accurately for use in designing subtype selective ligands for important GPCR therapeutics targets.
G 蛋白偶联受体 (GPCR) 是许多疾病的治疗靶点,但由于难以获得准确的结构,开发活性和选择性治疗药物的进展受到了严重阻碍。我们一直在开发预测 GPCR 配体复合物结构的方法,但由于缺乏可用于比较我们预测结果的实验结构,验证受到了阻碍。我们在此报告了人类腺苷 GPCR 亚型 (A(1)、A(2A)、A(2B) 和 A(3)) 的预测结构,以及与该预测结构结合的腺苷激动剂和 8 种拮抗剂的结合位点,不使用结构数据,并与最近报道的 ZM241385 结合人 A(2A) 受体的实验晶体结构进行比较。预测结构正确识别了 12 个晶体结合位点残基中的 9 个。此外,预测的 8 种拮抗剂与 A(2A) 预测结构的结合能与实验结果相当吻合。当我们使用蒙特卡罗技术优化环结构,特别是半胱氨酸键时,产生了这些出色的预测结果。忽略这些键会导致预测的结合位点变差(仅识别 12 个重要残基中的 3 个)。这些结果表明,计算方法可以足够准确地预测 GPCR 膜蛋白的三维结构,可用于设计针对重要 GPCR 治疗靶点的亚型选择性配体。