Xu Yong, Liu Hong, Niu Chunying, Luo Cheng, Luo Xiaomin, Shen Jianhua, Chen Kaixian, Jiang Hualiang
Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 201203, China.
Bioorg Med Chem. 2004 Dec 1;12(23):6193-208. doi: 10.1016/j.bmc.2004.08.045.
In the present study, we have used an approach combining protein structure modeling, molecular dynamics (MD) simulation, automated docking, and 3D QSAR analyses to investigate the detailed interactions of CCR5 with their antagonists. Homology modeling and MD simulation were used to build the 3D model of CCR5 receptor based on the high-resolution X-ray structure of bovine rhodopsin. A series of 64 CCR5 antagonists, 1-amino-2-phenyl-4-(piperidin-1-yl)-butanes, were docked into the putative binding site of the 3D model of CCR5 using the docking method, and the probable interaction model between CCR5 and the antagonists were obtained. The predicted binding affinities of the antagonists to CCR5 correlate well with the antagonist activities, and the interaction model could be used to explain many mutagenesis results. All these indicate that the 3D model of antagonist-CCR5 interaction is reliable. Based on the binding conformations and their alignment inside the binding pocket of CCR5, three-dimensional structure-activity relationship (3D QSAR) analyses were performed on these antagonists using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods. Both CoMFA and CoMSIA provide statistically valid models with good correlation and predictive power. The q(2)(r(cross)(2)) values are 0.568 and 0.587 for CoMFA and CoMSIA, respectively. The predictive ability of these models was validated by six compounds that were not included in the training set. Mapping these models back to the topology of the active site of CCR5 leads to a better understanding of antagonist-CCR5 interaction. These results suggest that the 3D model of CCR5 can be used in structure-based drug design and the 3D QSAR models provide clear guidelines and accurate activity predictions for novel antagonist design.
在本研究中，我们采用了一种结合蛋白质结构建模、分子动力学（MD）模拟、自动对接和三维定量构效关系（3D QSAR）分析的方法，来研究CCR5与其拮抗剂之间的详细相互作用。基于牛视紫红质的高分辨率X射线结构，利用同源建模和MD模拟构建了CCR5受体的三维模型。使用对接方法将一系列64种CCR5拮抗剂1-氨基-2-苯基-4-（哌啶-1-基）丁烷对接至CCR5三维模型的假定结合位点，从而获得了CCR5与拮抗剂之间可能的相互作用模型。拮抗剂对CCR5的预测结合亲和力与拮抗剂活性具有良好的相关性，且该相互作用模型可用于解释许多诱变结果。所有这些都表明拮抗剂-CCR5相互作用的三维模型是可靠的。基于CCR5结合口袋内的结合构象及其比对，使用比较分子场分析（CoMFA）和比较分子相似性分析（CoMSIA）方法对这些拮抗剂进行了三维结构-活性关系（3D QSAR）分析。CoMFA和CoMSIA均提供了具有良好相关性和预测能力的统计学有效模型。CoMFA和CoMSIA的q(2)(r(cross)(2))值分别为0.568和0.587。这些模型的预测能力通过训练集中未包含的六种化合物进行了验证。将这些模型映射回CCR5活性位点的拓扑结构，有助于更好地理解拮抗剂与CCR5的相互作用。这些结果表明，CCR5的三维模型可用于基于结构的药物设计，且3D QSAR模型为新型拮抗剂设计提供了清晰的指导方针和准确的活性预测。
