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一种用于筛选高亲和力细胞色素P450cam底物的虚拟高通量筛选方法。对药物代谢的计算机模拟预测的启示。

A virtual high throughput screen for high affinity cytochrome P450cam substrates. Implications for in silico prediction of drug metabolism.

作者信息

Keseru G M

机构信息

Computer Assisted Drug Discovery, Gedeon Richter Ltd., Budapest, Hungary.

出版信息

J Comput Aided Mol Des. 2001 Jul;15(7):649-57. doi: 10.1023/a:1011911204383.

DOI:10.1023/a:1011911204383
PMID:11688945
Abstract

Structure-based virtual screening techniques require reliable scoring functions to discriminate potential substrates effectively. In this study we compared the performance of GOLD, PMF, DOCK and FlexX scoring functions in FlexX flexible docking to cytochrome P450cam binding site. Crystal structures of protein-substrate complexes were most effectively reproduced by the FlexX/PMF method. On the other hand, the FlexX/GOLD approach provided the best correlation between experimental binding constants and predicted scores. Binding modes selected by the FlexX/PMF approach were rescored by GOLD to obtain a reliable measure of binding energetics. The effectiveness of the FlexX/PMF/GOLD method was demonstrated by the correct classification of 32 out of the 33 experimentally studied compounds and also in a virtual HTS test on a library of 10,000 compounds. Although almost all the available functions were developed to be general, our study on cytochrome P450cam substrates suggests that careful selection or even tailoring the scoring function might increase the prediction power of virtual screens significantly. The FlexX/PMF/GOLD methodology was tested on cytochrome P450 3A4 substrates and inhibitors. This preliminary study revealed that the combined function was able to recognise 334 out of the 345 compounds bound to 3A4.

摘要

基于结构的虚拟筛选技术需要可靠的评分函数来有效区分潜在底物。在本研究中,我们比较了GOLD、PMF、DOCK和FlexX评分函数在FlexX柔性对接细胞色素P450cam结合位点中的性能。蛋白质 - 底物复合物的晶体结构通过FlexX/PMF方法得到了最有效的重现。另一方面,FlexX/GOLD方法在实验结合常数和预测分数之间提供了最佳相关性。通过GOLD对FlexX/PMF方法选择的结合模式进行重新评分,以获得可靠的结合能测量值。FlexX/PMF/GOLD方法的有效性通过对33种实验研究化合物中的32种进行正确分类以及在对10000种化合物库的虚拟高通量筛选测试中得到了证明。尽管几乎所有可用的函数都是通用开发的,但我们对细胞色素P450cam底物的研究表明,仔细选择甚至定制评分函数可能会显著提高虚拟筛选的预测能力。FlexX/PMF/GOLD方法在细胞色素P450 3A4底物和抑制剂上进行了测试。这项初步研究表明,组合函数能够识别与3A4结合的345种化合物中的334种。

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