The extensive bioactivity data available in public databases, such as ChEMBL, has facilitated in-depth structure-activity relationship (SAR) analyses, which are essential for understanding the impact of molecular modifications on biological activity. A central strategy in SAR analysis is the assessment of molecular similarity. Several approaches preferred by medicinal chemists have been developed to efficiently capture structurally related compounds on a large scale. Represented as a popular molecular editing strategy in hit-to-lead and lead optimization processes, we previously introduced four types of single-atom modifications (SAMs) and conducted a systematic analysis of their application in compound design. In this study, we expanded the analysis to cover 10 common SAMs, including carbon-nitrogen (N↔C), O↔C, N↔O, S↔O, as well as simpler modifications such as OH↔H, CH₃↔H, and halogen-hydrogen (F, Cl, Br, I ↔ H) exchanges. Leveraging high-confidence bioactivity data from ChEMBL (version 34), we assembled the largest dataset of SAM pairs to date, comprising 374,979 pairs. Following an evaluation of the frequency of these SAM types in medicinal chemistry, we focused on SAM-induced activity cliffs (ACs), yielding over 7,400 ACs involving SAMs, substantially expanding the current knowledgebase of ACs associated with single-atom changes. Furthermore, structural analysis of these ACs, supported by experimental data, provides critical insights into the role of single-atom modifications in modulating compound activity, offering practical guidance for the structure-based optimization of molecular properties in drug development. As a result, we are providing open access to all identified ACs along with their associated structural information.

中文翻译：

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鉴定具有常用单原子修饰的生物活性化合物：综合分析及其对化合物设计的意义


公共数据库（如 ChEMBL）中提供的大量生物活性数据有助于深入的构效关系 （SAR） 分析，这对于了解分子修饰对生物活性的影响至关重要。SAR 分析的一个核心策略是评估分子相似性。已经开发了药物化学家首选的几种方法，以大规模有效地捕获结构相关的化合物。作为苗头化合物到先导化合物和先导化合物优化过程中流行的分子编辑策略，我们之前介绍了四种类型的单原子修饰 （SAM），并对其在化合物设计中的应用进行了系统分析。在这项研究中，我们将分析扩展到涵盖 10 种常见的 SAM，包括碳-氮 （N↔C）、O↔C、N↔O、S↔O，以及更简单的修饰，如 OH↔H、_{CH 3}↔H 和卤氢 （F、Cl、Br、I ↔ H） 交换。利用来自 ChEMBL（第 34 版）的高置信度生物活性数据，我们组装了迄今为止最大的 SAM 对数据集，包括 374,979 对。在评估了这些 SAM 类型在药物化学中的频率后，我们专注于 SAM 诱导的活性悬崖 （AC），产生了超过 7,400 个涉及 SAM 的 AC，大大扩展了当前与单原子变化相关的 AC 知识库。此外，这些 AC 的结构分析在实验数据的支持下，为单原子修饰在调节化合物活性中的作用提供了重要见解，为药物开发中基于结构的分子特性优化提供了实用指导。因此，我们提供了对所有已识别的 AC 及其相关结构信息的开放访问。