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首页> 外文期刊>Journal of chemical information and modeling >A Discussion of Measures of Enrichment in Virtual Screening:Comparing the Information Content of Descriptors with Increasing Levels of Sophistication
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A Discussion of Measures of Enrichment in Virtual Screening:Comparing the Information Content of Descriptors with Increasing Levels of Sophistication

机译:探讨虚拟筛选中丰富措施的探讨:比较描述符的信息含量随着复杂程度的增加

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摘要

We have performed virtual screening using some very simple features,by employing the number of atoms per element as molecular descriptors but without regard to any structural information whatsoever.Surprisingly,these atom counts are able to outperform virtual-affinity-based fingerprints and Unity fingerprints in some activity classes.Although molecular weight and other biases were known in target-based virtual screening settings (docking),we report the effect of using very simple descriptors for ligand-based virtual screening,by using clearly defined biological targets and employing a large data set (> 100 000 compounds) containing multiple (11) activity classes.Structure-unaware atom count vectors as descriptors in combination with the Euclidean distance measure are able to achieve "enrichment factors" over random selection of around 4 (depending on the particular class of active compounds),putting the enrichment factors reported for more sophisticated virtual screening methods in a different light.They are also able to retrieve active compounds with novel scaffolds instead of merely the expected structural analogues.The added value of many currently used virtual screening methods (calculated as enrichment factors) drops down to a factor of between 1 and 2,instead of often reported double-digit figures.The observed effect is much less profound for simple descriptors such as molecular weight and is only present in cases of atypical (larger) ligands.The current state of virtual screening is not as sophisticated as might.be expected,which is due to descriptors still not being able to capture structural properties relevant to binding.This fact can partly be explained by highly nonlinear structure-activity relationships,which represent a severe limitation of the "similar property principle" in the context of bioactivity.
机译:我们使用一些非常简单的功能进行了虚拟筛选,通过使用每个元素的原子数量作为分子描述符,但没有考虑任何结构信息。难以实现这些原子计数能够优于基于虚拟亲和的指纹和单位指纹。一些活动类。虽然在基于目标的虚拟筛选设置(对接)中已知分子量和其他偏差,但我们通过使用明确定义的生物学目标并采用大数据来报告使用基于LigAnd的虚拟筛选的非常简单的描述符的效果含有多个(11)活动类的(> 100 000化合物)。结构 - 不识别原子计数矢量作为描述符与欧几里德距离测量相结合,能够在随机选择的约4(取决于特定的类)的“富集因子”活性化合物),提出了富集因子,以便在广告中获得更复杂的虚拟筛选方法IFFerent Light。他们还能够用新颖的支架检索活性化合物,而不是仅仅是预期的结构类似物。许多目前使用的虚拟筛选方法的附加值(计算为富集因子)下降到1到2之间的因素通常报告的两位数字。观察到的效果远低于分子量的简单描述符,并且仅存在于非典型(较大)配体的情况下存在。当前的虚拟筛选状态并不像最复杂的那样复杂。预期,这是由于描述符仍然不能能够捕获与绑定相关的结构性。这可以通过高度非线性结构 - 活动关系部分解释,这在生物活性的背景下代表了对“类似的性质原理”的严重限制。

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  • 作者

    Andreas Bender; Robert C.Glen;

  • 作者单位

    Unilever Centre for Molecular Science Informatics Chemistry Department University of Cambridge Cambridge CB2 1EW United Kingdom;

    Unilever Centre for Molecular Science Informatics Chemistry Department University of Cambridge Cambridge CB2 1EW United Kingdom;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 化学;
  • 关键词

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