Zhuo Ya, Kong Ren, Cong Xiao-jing, Chen Wei-zu, Wang Cun-xin
College of Life Science and Bioengineering, Beijing University of Technology, Ping Le Yuan 100, Chao Yang District, Beijing 100124, China.
Eur J Med Chem. 2008 Dec;43(12):2724-34. doi: 10.1016/j.ejmech.2008.01.040. Epub 2008 Feb 8.
In this study, a series of 1,3,4-trisubstituted pyrrolidine-based CCR5 receptor inhibitors were taken as our target with the method of the three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses in order to investigate the interactions between CCR5 receptor and their inhibitors. For a comparison, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were, respectively, used to build predictive models, which were generated from a training set consisting of 72 selected molecules, derived from literatures. Two alignment rules, including rigid body rms (root mean square) fit and field fit, were performed in the superimposition of inhibitors structures. As a result, a better CoMFA model based on common structure alignment obtains a conventional correlation coefficient r(2) of 0.952 and a leave-one-out cross-validated coefficient q(2) of 0.637, while the desirable CoMSIA model based on the same alignment rule acquires the r(2) of 0.958 and the q(2) of 0.677. To further validate the reliability of the models, we also investigated into the externally test set composed of 39 molecules under the criterions of squared correlation coefficient between experimental and predicted activities with intercept R(2) and without intercept R(0)(2), along with R(m)(2) as the modified R(2) with a penalty function due to difference between R(2) and R(0)(2). At last, the contour map also provides a visual representation of contributions of steric, electrostatic, hydrogen bond and hydrophobic fields, as well as the prospective binding modes. These results may provide meaningful guidance to the further work including the similar lead compounds' structure modification and activity prediction.
在本研究中,一系列基于1,3,4-三取代吡咯烷的CCR5受体抑制剂被作为研究对象,采用三维定量构效关系(3D-QSAR)分析方法,以研究CCR5受体与其抑制剂之间的相互作用。为作比较,分别使用比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)构建预测模型,这些模型由一个包含72个从文献中选取的分子的训练集生成。在抑制剂结构的叠加中执行了两种对齐规则,包括刚体均方根(rms,root mean square)拟合和场拟合。结果,基于共同结构对齐的更好的CoMFA模型获得了0.952的常规相关系数r²和0.637的留一法交叉验证系数q²,而基于相同对齐规则的理想CoMSIA模型获得了0.958的r²和0.677的q²。为进一步验证模型的可靠性,我们还在实验活性与预测活性之间的平方相关系数标准下,研究了由39个分子组成的外部测试集,该标准包括有截距R²和无截距R₀²,以及作为因R²与R₀²差异而带有惩罚函数的修正R²的Rₘ²。最后,等高线图还直观展示了空间、静电、氢键和疏水场的贡献以及潜在的结合模式。这些结果可能为包括类似先导化合物的结构修饰和活性预测在内的进一步工作提供有意义的指导。