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从活动崖到活动脊:SAR 分析的信息数据结构。

From activity cliffs to activity ridges: informative data structures for SAR analysis.

机构信息

Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, Germany.

出版信息

J Chem Inf Model. 2011 Aug 22;51(8):1848-56. doi: 10.1021/ci2002473. Epub 2011 Aug 4.


DOI:10.1021/ci2002473
PMID:21761918
Abstract

The extraction of SAR information from structurally diverse compound data sets is a challenging task. One of the focal points of systematic SAR analysis is the search for activity cliffs, that is, structurally similar compounds having large potency differences, from which SAR determinants can be deduced. The assessment of SAR information is usually based on pairwise similarity and potency comparisons of data set compounds. As a consequence, activity cliffs are mostly evaluated at a compound pair level. Here, we present an extension of the activity cliff concept by introducing "activity ridges" that are formed by overlapping "combinatorial" activity cliffs between participating compounds, giving rise to ridge-like structures in activity landscapes. Activity ridges are rich in SAR information. In a systematic analysis of 242 compound data sets, we have identified well-defined activity ridges in 71 different sets. In addition, an information-theoretic approach has been devised to characterize the structural composition of activity ridges. Taken together, our results show that activity ridges frequently occur in sets of active compounds and that different categories of ridges can be distinguished on the basis of their structural content. The computational identification of activity ridges provides access to compound subsets having high priority for SAR analysis.

摘要

从结构多样的化合物数据集提取 SAR 信息是一项具有挑战性的任务。系统 SAR 分析的重点之一是寻找活性悬崖,即具有较大效力差异的结构相似的化合物,从中可以推导出 SAR 决定因素。SAR 信息的评估通常基于数据集化合物的两两相似性和效力比较。因此,活性悬崖大多在化合物对的水平上进行评估。在这里,我们通过引入“活性脊”来扩展活性悬崖的概念,这些活性脊是由参与化合物之间重叠的“组合”活性悬崖形成的,在活性景观中产生脊状结构。活性脊富含 SAR 信息。在对 242 个化合物数据集的系统分析中,我们在 71 个不同的数据集 中确定了明确的活性脊。此外,还设计了一种信息论方法来描述活性脊的结构组成。总的来说,我们的结果表明,活性脊经常出现在活性化合物的集合中,并且可以根据它们的结构内容来区分不同类别的脊。活性脊的计算识别为 SAR 分析提供了具有高优先级的化合物子集。

相似文献

[1]
From activity cliffs to activity ridges: informative data structures for SAR analysis.

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[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[10]
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引用本文的文献

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Sci Rep. 2024-4-20

[2]
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J Cheminform. 2023-4-17

[3]
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Int J Mol Sci. 2023-2-10

[4]
"Molecular Anatomy": a new multi-dimensional hierarchical scaffold analysis tool.

J Cheminform. 2021-7-23

[5]
Rationalizing the Formation of Activity Cliffs in Different Compound Data Sets.

ACS Omega. 2018-7-11

[6]
Prioritization of anti-malarial hits from nature: chemo-informatic profiling of natural products with in vitro antiplasmodial activities and currently registered anti-malarial drugs.

Malar J. 2016-1-29

[7]
Structure-based predictions of activity cliffs.

J Chem Inf Model. 2015-5-26

[8]
Advancing the activity cliff concept, part II.

F1000Res. 2014-3-18

[9]
Advancing the activity cliff concept.

F1000Res. 2013-9-30

[10]
Exploring Structure-Activity Data Using the Landscape Paradigm.

Wiley Interdiscip Rev Comput Mol Sci. 2012-11

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