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. 2012 Feb 9;55(3):1215-26. doi: 10.1021/jm201362h. Epub 2012 Jan 27.
A graphical method is introduced to study details of structure-activity relationships (SARs) in analogue series that further extends conventional analysis of analogues using R-group tables or related approaches and that provides additional and more differentiated SAR information. The newly designed graph structure represents entire series of analogues in a consistent manner, regardless of their size and complexity of substitution patterns. The approach is specifically tailored toward a systematic exploration and intuitive interpretation of SAR features involving different R-groups and their combinations. Analogues and their potency information are systematically organized on the basis of R-group combinations that are present in a series. This organization scheme results in graph components that represent well-defined SAR patterns. Analysis of these patterns provides an immediate access to critical substitution sites and R-group combinations, favorable and unfavorable R-groups, or nonadditive potency effects of multisite substitutions. Furthermore, the data structure makes it possible to design new analogues by combining favorable R-group combinations derived from different compounds.
引入了一种图形方法来研究类似物系列中的结构-活性关系 (SAR) 的细节,该方法进一步扩展了使用 R 基团表或相关方法对类似物进行的常规分析,并提供了更多的、更具区分度的 SAR 信息。新设计的图形结构以一致的方式表示整个类似物系列,而不考虑它们的大小和取代模式的复杂性。该方法特别针对不同 R 基团及其组合的 SAR 特征进行系统探索和直观解释。根据系列中存在的 R 基团组合,系统地组织类似物及其效价信息。这种组织方案产生了表示明确 SAR 模式的图形组件。对这些模式的分析可直接访问关键取代部位和 R 基团组合、有利和不利的 R 基团,或多部位取代的非加和效价效应。此外,该数据结构使得通过组合来自不同化合物的有利 R 基团组合来设计新的类似物成为可能。