Three-dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factor Xa
Three-dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factor Xa
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DOI：
10.1021/jm981062r
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发表时间：
1999-02-11
影响因子：
7.3
通讯作者：
Klebe, G
中科院分区：
文献类型：
--
作者：
Böhm, M;Stürzebecher, J;Klebe, G
三维定量构效关系（3D QSAR）方法应用于使用72个苄脒型抑制剂的训练集，就其对凝血酶，胰蛋白酶和因子Xa的结合亲和力（Ki值），以产生良好的预测能力的统计可靠的模型。比较了两种方法：比较分子场分析（CoMFA）和最近报道的比较分子相似性指数分析（CoMSIA）。CoMSIA产生了显着更好的结果，所有的相关性。此外，与CoMFA相反，CoMSIA对晶格中叠加分子的取向变化不敏感。通过CoMSIA获得的相关性结果进行了图形化解释的字段贡献地图，使相关的结合的物理化学性质很容易映射回分子结构。利用这些图谱设计新的分子，证明了这一特征的优势。最后，CoMSIA方法被施加到阐明的结构特征之间的配体是负责对凝血酶和胰蛋白酶的亲和力差异。这些选择性决定功能解释图形方面的空间区域负责亲和力歧视。这样的指标对于关于选择性增强的铅优化过程是高度信息化的。
Three-dimensional quantitative structure-activity relationship (3D QSAR) methods were applied using a training set of 72 inhibitors of the benzamidine type with respect to their binding affinities (K-i values) toward thrombin, trypsin, and factor Xa to yield statistically reliable models of good predictive power. Two methods were compared: the widely used comparative molecular field analysis (CoMFA) and the recently reported CoMSIA approach (comparative molecular similarity indices analysis). CoMSIA produced significantly better results for all correlations. Furthermore, in contrast to CoMFA, CoMSIA is not sensitive to changes in orientation of the superimposed molecules in the lattice. The correlation results obtained by CoMSIA were graphically interpreted in terms of field contribution maps allowing physicochemical properties relevant for binding to be easily mapped back onto molecular structures. The advantage of this feature is demonstrated using the maps to design new molecules. Finally, the CoMSIA method was applied to elucidate structural features among ligands which are responsible for affinity differences toward thrombin and trypsin. These selectivity-determining features were interpreted graphically in terms of spatial regions responsible for affinity discrimination. Such indicators are highly informative for the lead optimization process with respect to selectivity enhancement.