Molecular docking and 3D QSAR studies on 1-amino-2-phenyl-4-(piperidin-1-yl)-butanes based on the structural modeling of human CCR5 receptor

被引:49
|
作者
Xu, Y [1 ]
Liu, H [1 ]
Niu, CY [1 ]
Luo, C [1 ]
Luo, XM [1 ]
Shen, JH [1 ]
Chen, KX [1 ]
Jiang, HL [1 ]
机构
[1] Chinese Acad Sci, Shanghai Inst Mat Med, Shanghai Inst Biol Sci, Drug Discovery & Design Ctr,Sate Key Lab Drug Res, Shanghai 201203, Peoples R China
基金
中国国家自然科学基金;
关键词
CCR5; homology modeling; docking; 3D QSAR; CoMFA; CoMSIA;
D O I
10.1016/j.bmc.2004.08.045
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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 (313 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. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6193 / 6208
页数:16
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