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HPPD抑制剂、PSA抑制剂和抗焦虑药的三维定量构效关系:互变异构对比较分子力场分析模型的影响。

Three-dimensional QSAR of HPPD inhibitors, PSA inhibitors, and anxiolytic agents: effect of tautomerism on the CoMFA models.

作者信息

Zou Jian-Wei, Luo Cheng-Cai, Zhang Hua-Xing, Liu Hai-Chun, Jiang Yong-Jun, Yu Qing-Sen

机构信息

Key Laboratory for Molecular Design and Nutrition Engineering, Ningbo Institute of Technology, Zhejiang University, Ningbo 315100, China.

出版信息

J Mol Graph Model. 2007 Sep;26(2):494-504. doi: 10.1016/j.jmgm.2007.03.002. Epub 2007 Mar 12.

Abstract

The present study was design to examine the effect of tautomerism upon the CoMFA results. Three selected data sets involving protropic tautomerism, which are 21 p-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitors, 35 inhibitors of puromycin-sensitive aminopeptidase (PSA), and 67 anxiolytic agents, were used for this purpose. Atom-by-atom alignment technique was adopted to superimpose the molecules in the data sets onto a template. The structural alignments using different tautomeric forms had no significant difference except the atoms involved in tautomerism, which ensures, to a great extent, that the differences of the CoMFA results result primarily from the tautomerism. All-orientation and all-placement search (AOS-APS) based CoMFA models, in addition to the conventional ones, were derived for each system and proved to be capable of yielding much improved statistical results. In the cases of the data sets of HPPD inhibitors and PSA inhibitors, excellent AOS-APS CoMFA models (q2>0.8 with four components for the former and q2>0.7 with seven components for the latter) were obtained, and almost no significant difference in statistical quality was observed when using different tautomeric forms to derive the models. However, it was not the case when treating the data set of anxiolytic agents. The keto tautomer, which was the active form of the PBI type inhibitors, produced measurably better results (q2=0.54 with eight components) than that the enol one (q2=0.37 with five components), indicating the importance of selecting proper tautomer in the CoMFA studies. Furthermore, there existed some substantial differences of the electrostatic field contours between the two different tautomeric forms for all of the three systems considered, whereas the differences in the steric field contour maps were limited. This implies that the resulting new potent ligands may be quite different if one utilizes the CoMFA models of different tautomeric forms for guiding further structural refinements.

摘要

本研究旨在考察互变异构对比较分子场分析(CoMFA)结果的影响。为此使用了三个选定的涉及质子互变异构的数据集,分别是21种对羟基苯丙酮酸双加氧酶(HPPD)抑制剂、35种嘌呤霉素敏感氨基肽酶(PSA)抑制剂和67种抗焦虑药。采用逐个原子对齐技术将数据集中的分子叠加到一个模板上。除了涉及互变异构的原子外,使用不同互变异构形式进行的结构对齐没有显著差异,这在很大程度上确保了CoMFA结果的差异主要源于互变异构。针对每个系统,除了传统的CoMFA模型外,还推导了基于全方向和全放置搜索(AOS-APS)的CoMFA模型,结果表明这些模型能够产生显著改进的统计结果。在HPPD抑制剂和PSA抑制剂的数据集案例中,获得了出色的AOS-APS CoMFA模型(前者四个成分时q2>0.8,后者七个成分时q2>0.7),并且使用不同互变异构形式推导模型时,在统计质量上几乎没有观察到显著差异。然而,在处理抗焦虑药数据集时情况并非如此。酮式互变异构体是PBI型抑制剂的活性形式,其产生的结果(八个成分时q=0.54)明显优于烯醇式互变异构体(五个成分时q2=0.37),这表明在CoMFA研究中选择合适的互变异构体很重要。此外,对于所考虑的所有三个系统,两种不同互变异构形式之间的静电场等高线存在一些实质性差异,而空间场等高线图的差异则有限。这意味着,如果利用不同互变异构形式的CoMFA模型来指导进一步的结构优化,所得到的新的强效配体可能会有很大不同。

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