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推进活性悬崖概念。

Advancing the activity cliff concept.

作者信息

Hu Ye, Stumpfe Dagmar, Bajorath Jürgen

机构信息

Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, D-53113, Germany.

出版信息

F1000Res. 2013 Sep 30;2:199. doi: 10.12688/f1000research.2-199.v1. eCollection 2013.

DOI:10.12688/f1000research.2-199.v1
PMID:24555097
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3869489/
Abstract

The activity cliff concept has experienced increasing interest in medicinal chemistry and chemoinformatics. Activity cliffs have originally been defined as pairs of structurally similar compounds that are active against the same target but have a large difference in potency. Activity cliffs are relevant for structure-activity relationship (SAR) analysis and compound optimization because small chemical modifications can be deduced from cliffs that result in large-magnitude changes in potency. In addition to studying activity cliffs on the basis of individual compounds series, they can be systematically identified through mining of compound activity data. This commentary aims to provide a concise yet detailed picture of our current understanding of activity cliffs. It is also meant to introduce the further refined activity cliff concept to a general audience in drug development.

摘要

活性悬崖概念在药物化学和化学信息学领域受到越来越多的关注。活性悬崖最初被定义为一对结构相似的化合物,它们对同一靶点具有活性,但效价存在很大差异。活性悬崖与构效关系(SAR)分析和化合物优化相关,因为可以从悬崖中推断出小的化学修饰,这些修饰会导致效价发生大幅度变化。除了基于单个化合物系列研究活性悬崖外,还可以通过挖掘化合物活性数据来系统地识别它们。本评论旨在对我们目前对活性悬崖的理解提供一个简洁而详细的概述。它还旨在向药物开发领域的普通读者介绍进一步完善的活性悬崖概念。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1306/3869489/570318348691/f1000research-2-2463-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1306/3869489/e05311e8349a/f1000research-2-2463-g0000.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1306/3869489/f71887ee0020/f1000research-2-2463-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1306/3869489/570318348691/f1000research-2-2463-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1306/3869489/e05311e8349a/f1000research-2-2463-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1306/3869489/6d871fe41902/f1000research-2-2463-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1306/3869489/973bc4459ada/f1000research-2-2463-g0002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1306/3869489/570318348691/f1000research-2-2463-g0004.jpg

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J Chem Inf Model. 2013 May 24;53(5):1067-72. doi: 10.1021/ci400141w. Epub 2013 Apr 22.
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Do medicinal chemists learn from activity cliffs? A systematic evaluation of cliff progression in evolving compound data sets.
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RSC Adv. 2019 Jan 29;9(7):3912-3917. doi: 10.1039/c8ra08915a. eCollection 2019 Jan 25.
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