Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität , Dahlmannstraße 2, D-53113 Bonn, Germany.
J Med Chem. 2014 Aug 14;57(15):6553-63. doi: 10.1021/jm500577n. Epub 2014 Jul 17.
Activity cliffs are generally defined as pairs of active compounds having a large difference in potency. Although this definition of activity cliffs focuses on compound pairs, the vast majority of cliffs are formed in a coordinated manner. This means that multiple highly and weakly potent compounds form series of activity cliffs, which often overlap. In activity cliff networks, coordinated cliffs emerge as disjoint activity cliff clusters. Recently, we have identified all cliff clusters from current bioactive compounds and analyzed their topologies. For structure-activity relationship (SAR) analysis, activity cliff clusters are of high interest, since they contain more SAR information than cliffs that are individually considered. For medicinal chemistry applications, a key question becomes how to best extract SAR information from activity cliff clusters. This represents a challenging problem, given the complexity of many activity cliff configurations. Herein we introduce a generally applicable methodology to organize activity cliff clusters on the basis of structural relationships, prioritize clusters, and systematically extract SAR information from them.
活性悬崖通常被定义为一对活性化合物，它们的效力有很大的差异。尽管这一对活性化合物的定义侧重于悬崖的定义，但绝大多数悬崖都是以协调的方式形成的。这意味着多个高活性和低活性的化合物形成了一系列的活性悬崖，这些悬崖经常重叠。在活性悬崖网络中，协调的悬崖以不相交的活性悬崖簇的形式出现。最近，我们已经确定了当前生物活性化合物中的所有悬崖簇，并分析了它们的拓扑结构。对于构效关系（SAR）分析，活性悬崖簇非常重要，因为它们包含的 SAR 信息比单独考虑的悬崖多。对于药物化学应用，一个关键问题是如何从活性悬崖簇中最好地提取 SAR 信息。鉴于许多活性悬崖配置的复杂性，这是一个具有挑战性的问题。在此，我们引入了一种普遍适用的方法，基于结构关系对活性悬崖簇进行组织，对其进行优先级排序，并系统地从中提取 SAR 信息。
