Design of Multitarget Activity Landscapes That Capture Hierarchical Activity Cliff Distributions
Design of Multitarget Activity Landscapes That Capture Hierarchical Activity Cliff Distributions
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DOI：
10.1021/ci100477m
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发表时间：
2011-02-01
影响因子：
5.6
通讯作者：
Bajorath, Juergen
中科院分区：
文献类型：
--
作者：
Dimova, Dilyana;Wawer, Mathias;Bajorath, Juergen
化合物数据集的活性景观模型可以合理化为整合分子相似性和效力关系的图形表示。不同设计的活动景观表示被用来帮助结构活性关系的分析和信息化合物的选择。迄今为止报告的活动景观模型侧重于单一目标（即，单一生物活性）或至多两个目标，从而产生选择性景观。对于对两个以上目标有活性的化合物，代表多目标活性的景观很难概念化，尚未报告。在此，我们提出了第一个活动景观设计，其以形式上一致的方式整合了多个靶标之间的化合物效力关系。这些多目标活动景观是基于一般的活动悬崖分类方案，并在图形表示，其中活动悬崖表示为边缘可视化。此外，监测单个化合物对跨多个靶标的结构活性关系不连续性的贡献。该方法已被应用于推导多目标活动景观的复合数据集活跃对不同的目标家庭。由此产生的景观识别单，双，和三重目标活动的悬崖，并揭示了分层悬崖分布的存在。从这些多靶点活性景观中，可以容易地选择形成复杂活性悬崖的化合物。
An activity landscape model of a compound data set can be rationalized as a graphical representation that integrates molecular similarity and potency relationships. Activity landscape representations of different design are utilized to aid in the analysis of structure activity relationships and the selection of informative compounds. Activity landscape models reported thus far focus on a single target (i.e., a single biological activity) or at most two targets, giving rise to selectivity landscapes. For compounds active against more than two targets, landscapes representing multitarget activities are difficult to conceptualize and have not yet been reported. Herein, we present a first activity landscape design that integrates compound potency relationships across multiple targets in a formally consistent manner. These multitarget activity landscapes are based on a general activity cliff classification scheme and are visualized in graph representations, where activity cliffs are represented as edges. Furthermore, the contributions of individual compounds to structure activity relationship discontinuity across multiple targets are monitored. The methodology has been applied to derive multitarget activity landscapes for compound data sets active against different target families. The resulting landscapes identify single-, dual-, and triple-target activity cliffs and reveal the presence of hierarchical cliff distributions. From these multitarget activity landscapes, compounds forming complex activity cliffs can be readily selected.