Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universitat, Dahlmannstrasse 2, D-53113 Bonn, Germany.
J Chem Inf Model. 2010 Jun 28;50(6):1021-33. doi: 10.1021/ci100091e.
Activity landscapes are defined by potency and similarity distributions of active compounds and reflect the nature of structure-activity relationships (SARs). Three-dimensional (3D) activity landscapes are reminiscent of topographical maps and particularly intuitive representations of compound similarity and potency distributions. From their topologies, SAR characteristics can be deduced. Accordingly, idealized theoretical landscape models have been utilized to rationalize SAR features, but "true" 3D activity landscapes have not yet been described in detail. Herein we present a computational approach to derive approximate 3D activity landscapes for actual compound data sets and to analyze exemplary landscape representations. These activity landscapes are generated within a consistent reference frame so that they can be compared across different activity classes. We show that SAR features of compound data sets can be derived from the topology of landscape models. A notable correlation is observed between global SAR phenotypes, assigned on the basis of SAR discontinuity scoring, and characteristic landscape topologies. We also show that different molecular representations can substantially alter the topology of activity landscapes for a given data set and modulate the formation of activity cliffs, which represent the most prominent landscape features. Depending on the choice of molecular representations, compounds forming a steep activity cliff in a given landscape might be separated in another and no longer form a cliff. However, comparison of alternative activity landscapes makes it possible to focus on compound subsets having high SAR information content.
活性景观由活性化合物的效力和相似性分布定义，反映了结构活性关系（SAR）的本质。三维（3D）活性景观类似于地形地图，是化合物相似性和效力分布的特别直观表示。可以从它们的拓扑结构中推断出 SAR 特征。因此，已经利用理想化的理论景观模型来合理化 SAR 特征，但尚未详细描述“真实”3D 活性景观。在此，我们提出了一种计算方法，用于为实际化合物数据集推导出近似的 3D 活性景观，并分析示例景观表示。这些活性景观是在一致的参考框架内生成的，因此可以在不同的活性类别之间进行比较。我们表明，可以从景观模型的拓扑结构中推导出化合物数据集的 SAR 特征。在基于 SAR 不连续性评分的基础上分配的全局 SAR 表型与特征景观拓扑之间存在显著相关性。我们还表明，不同的分子表示形式可以极大地改变给定数据集的活性景观拓扑结构，并调节活性悬崖的形成，这是最突出的景观特征。根据分子表示形式的选择，在给定景观中形成陡峭活性悬崖的化合物在另一个景观中可能会分开，并且不再形成悬崖。然而，对替代活性景观的比较可以使我们能够专注于具有高 SAR 信息含量的化合物子集。
