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快速高效的计算机模拟3D筛选:迈向基于药效团和基于形状方法的最大计算效率

Fast and efficient in silico 3D screening: toward maximum computational efficiency of pharmacophore-based and shape-based approaches.

作者信息

Kirchmair Johannes, Ristic Stojanka, Eder Kathrin, Markt Patrick, Wolber Gerhard, Laggner Christian, Langer Thierry

机构信息

Department of Pharmaceutical Chemistry, Institute of Pharmacy and Center for Molecular Biosciences (CMBI), University of Innsbruck, Innrain 52, Innsbruck, Austria.

出版信息

J Chem Inf Model. 2007 Nov-Dec;47(6):2182-96. doi: 10.1021/ci700024q. Epub 2007 Oct 11.

Abstract

In continuation of our recent studies on the quality of conformational models generated with CATALYST and OMEGA we present a large-scale survey focusing on the impact of conformational model quality and several screening parameters on pharmacophore-based and shape-based virtual high throughput screening (vHTS). Therefore, we collected known active compounds of CDK2, p38 MAPK, PPAR-gamma, and factor Xa and built a set of druglike decoys using ilib:diverse. Subsequently, we generated 3D structures using CORINA and also calculated conformational models for all compounds using CAESAR, CATALYST FAST, and OMEGA. A widespread set of 103 structure-based pharmacophore models was developed with LigandScout for virtual screening with CATALYST. The performance of both database search modes (FAST and BEST flexible database search) as well as the fit value calculation procedures (FAST and BEST fit) available in CATALYST were analyzed in terms of their ability to discriminate between active and inactive compounds and in terms of efficiency. Moreover, these results are put in direct comparison to the performance of the shape-based virtual screening platform ROCS. Our results prove that high enrichment rates are not necessarily in conflict with efficient vHTS settings: In most of the experiments, we obtained the highest yield of actives in the hit list when parameter sets for the fastest search algorithm were used.

摘要

在我们近期关于使用CATALYST和OMEGA生成的构象模型质量的研究基础上,我们开展了一项大规模调查,重点关注构象模型质量和几个筛选参数对基于药效团和基于形状的虚拟高通量筛选(vHTS)的影响。因此,我们收集了细胞周期蛋白依赖性激酶2(CDK2)、p38丝裂原活化蛋白激酶(p38 MAPK)、过氧化物酶体增殖物激活受体γ(PPAR-γ)和凝血因子Xa的已知活性化合物,并使用ilib:diverse构建了一组类药诱饵。随后,我们使用CORINA生成三维结构,并使用CAESAR、CATALYST FAST和OMEGA计算所有化合物的构象模型。使用LigandScout开发了一套广泛的103个基于结构的药效团模型,用于使用CATALYST进行虚拟筛选。分析了CATALYST中可用的两种数据库搜索模式(FAST和BEST灵活数据库搜索)以及拟合值计算程序(FAST和BEST拟合)在区分活性和非活性化合物的能力以及效率方面的表现。此外,将这些结果与基于形状的虚拟筛选平台ROCS的性能进行了直接比较。我们的结果证明,高富集率不一定与高效的vHTS设置相冲突:在大多数实验中,当使用最快搜索算法的参数集时,我们在命中列表中获得了最高的活性化合物产量。

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