Identification and Application of Antitarget Activity Hotspots to Guide Compound Optimization
Identification and Application of Antitarget Activity Hotspots to Guide Compound Optimization
复制标题
识别并应用抗靶点活性热点来指导化合物优化
作者：
G. Hessler;H. Matter;Friedemann Schmidt;Clemens Giegerich;Li;S. Güssregen;K. Baringhaus
开发候选者的前导结构的最优化通常需要去除不想要的抗靶标活性。为此，我们开发了一种方法，从更大的数据库中提取抗靶活性热点，并将这些知识转移到新的化学系列中。这些抗靶标活性热点将被捕获为一对信息分子，它们在化学上密切相关，但在生物活性上有显著差异。我们举例说明了抗靶标活性热点作为信息化合物对在药物研究中用于优化相关抗靶标的先导结构的副作用。为了使用前瞻性设计，需要在已知的反目标热点对和新的引线结构之间建立结构联系：我们使用基于3D的相似性比较来完成这项任务。在早期的优化中，整个工作流程就像是想法的生成器。在几个与HERG抑制和CYP3A4抑制相关的优化问题中，证明了该方法的可行性。几个结构实例展示了3D形状搜索识别相关支架的能力，以及反目标热点信息通过调节不期望的反目标活动来指导优化的有用性。这种基于局部相似性分析和向3D相关序列转换的概念在构建反目标QSAR模型时尤其有希望，因为构建的反目标QSAR模型无法检测局部SAR趋势以指导下一个优化周期。
The optimization of a lead structure to a development candidate often requires removal of undesirable antitarget activities. To this end, we have developed an approach to extract antitarget activity hotspots from larger databases and to transfer this knowledge onto novel chemical series. These antitarget activity hotspots will be captured as pairs of informative molecules, which are chemically closely related, but differ significantly in biological activity. We illustrate the application of antitarget activity hotspots as informative compound pairs for the optimization of side effects in lead structures for relevant antitargets in pharmaceutical research. The use for prospective design requires establishing a structural link between known antitarget hotspot pairs and a new lead structure: we employ 3D‐based similarity comparison for this task. The entire workflow serves as idea generator in early optimization. The feasibility of this approach is demonstrated in several optimization problems related to hERG inhibition, and CYP3A4 inhibition. Several structural examples demonstrate the ability of the 3D‐shape searching to identify related scaffolds and the usefulness of the antitarget hotspot information to guide optimization by modulating the undesirable antitarget activity. Such a concept based on the analysis of local similarities and the transfer to 3D‐related series is especially promising in those cases, where the construction of antitarget QSAR models fails to detect local SAR trends for guiding the next optimization cycle.