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比较基于结构和配体的虚拟筛选方案,考虑命中列表互补性和富集因子。

Comparison of structure- and ligand-based virtual screening protocols considering hit list complementarity and enrichment factors.

机构信息

Institut für pharmazeutische und medizinische Chemie, Heinrich-Heine-Universität Düsseldorf, Universitätsstrasse 1, 40225 Düsseldorf, Germany.

出版信息

ChemMedChem. 2010 Jan;5(1):148-58. doi: 10.1002/cmdc.200900314.

Abstract

Structure- and ligand-based virtual-screening methods (docking, 2D- and 3D-similarity searching) were analysed for their effectiveness in virtual screening against four different targets: angiotensin-converting enzyme (ACE), cyclooxygenase 2 (COX-2), thrombin and human immunodeficiency virus 1 (HIV-1) protease. The relative performance of the tools was compared by examining their ability to recognise known active compounds from a set of actives and nonactives. Furthermore, we investigated whether the application of different virtual-screening methods in parallel provides complementary or redundant hit lists. Docking was performed with GOLD, Glide, FlexX and Surflex. The obtained docking poses were rescored by using nine different scoring functions in addition to the scoring functions implemented as objective functions in the docking algorithms. Ligand-based virtual screening was done with ROCS (3D-similarity searching), Feature Trees and Scitegic Functional Fingerprints (2D-similarity searching). The results show that structure- and ligand-based virtual-screening methods provide comparable enrichments in detecting active compounds. Interestingly, the hit lists that are obtained from different virtual-screening methods are generally highly complementary. These results suggest that a parallel application of different structure- and ligand-based virtual-screening methods increases the chance of identifying more (and more diverse) active compounds from a virtual-screening campaign.

摘要

基于结构和基于配体的虚拟筛选方法(对接、2D 和 3D 相似性搜索)针对针对四个不同的靶标:血管紧张素转化酶(ACE)、环氧化酶 2(COX-2)、凝血酶和人类免疫缺陷病毒 1(HIV-1)蛋白酶,分析了它们的有效性。通过检查它们识别一组活性和非活性化合物中已知活性化合物的能力,比较了工具的相对性能。此外,我们还研究了不同虚拟筛选方法的并行应用是否提供互补或冗余的命中列表。使用 GOLD、Glide、FlexX 和 Surflex 进行对接。除了对接算法中实现的作为目标函数的评分函数之外,还使用了九个不同的评分函数对获得的对接构象进行重新评分。使用 ROCS(3D 相似性搜索)、Feature Trees 和 Scitegic 功能指纹(2D 相似性搜索)进行基于配体的虚拟筛选。结果表明,基于结构和基于配体的虚拟筛选方法在检测活性化合物方面提供了相当的富集。有趣的是,来自不同虚拟筛选方法的命中列表通常具有高度的互补性。这些结果表明,不同的基于结构和基于配体的虚拟筛选方法的并行应用增加了从虚拟筛选活动中识别更多(更多样化)活性化合物的机会。

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