Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany.
J Chem Inf Model. 2012 Jun 25;52(6):1490-8. doi: 10.1021/ci300158v. Epub 2012 Jun 1.
Activity cliffs were systematically extracted from public domain X-ray structures of targets for which complexes with multiple ligands were available, following the concept of three-dimensional (3D) cliffs. Binding modes of ligands with well-defined potency measurements were compared in a pairwise manner, and their 3D similarity was calculated using a previously reported property density function-based method taking conformational, positional, and chemical differences into account. Requiring the presence of at least 80% 3D similarity and a potency difference of at least 2 orders of magnitude as cliff criteria, a total of 216 well-defined 3D activity cliffs were detected in the Protein Data Bank (PDB). These 3D-cliffs involved a total of 269 ligands active against 38 different targets belonging to 17 protein families. For 255 of these compounds, binding modes were available at high crystallographic resolution. All 3D-cliffs were analyzed in detail and assigned to different categories on the basis of crystallographic interaction patterns. In many instances, differences in ligand-target interactions suggested plausible causes for origins of 3D-cliffs. In other cases, short-range interactions seen in X-ray structures were insufficient to deduce possible reasons for cliff formation. The 3D-cliffs described herein further advance the rationalization of activity cliffs at the level of ligand-target interactions and should also be useful for other applications such as the calibration of energy functions for structure-based design. The pool of identified activity cliffs is provided to enable subsequent structure-based analyses of cliffs.
活性悬崖是从具有多个配体复合物的目标的公共领域 X 射线结构中系统地提取出来的,遵循三维(3D)悬崖的概念。以配对的方式比较了具有明确效力测量的配体的结合模式,并使用先前报道的基于属性密度函数的方法计算它们的 3D 相似性,该方法考虑了构象、位置和化学差异。要求至少存在 80%的 3D 相似性和至少 2 个数量级的效力差异作为悬崖标准,总共在蛋白质数据库(PDB)中检测到 216 个明确的 3D 活性悬崖。这些 3D 悬崖总共涉及 269 种针对属于 17 个蛋白质家族的 38 个不同靶标的活性配体。对于这些化合物中的 255 种,结合模式具有高晶体学分辨率。所有的 3D 悬崖都进行了详细分析,并根据晶体学相互作用模式被分配到不同的类别。在许多情况下,配体-靶标相互作用的差异表明了 3D 悬崖起源的合理原因。在其他情况下,在 X 射线结构中看到的短程相互作用不足以推断出形成悬崖的可能原因。本文描述的 3D 悬崖进一步推进了配体-靶标相互作用水平上的活性悬崖的合理化,并且对于其他应用(例如基于结构设计的能量函数校准)也应该是有用的。所确定的活性悬崖池可用于随后的基于结构的悬崖分析。