Activity cliffs (ACs) consist of structurally similar compounds with a large difference in potency against their target. Accordingly, ACs introduce discontinuity in structure-activity relationships (SARs) and are a prime source of SAR information. In compound data sets, the vast majority of ACs are formed by differently sized groups of structurally similar compounds with large potency variations. As a consequence, many of these compounds participate in multiple ACs. This coordinated formation of ACs increases their SAR information content compared to ACs considered as individual compound pairs, but complicates AC analysis. In network representations, coordinated ACs give rise to clusters of varying size and topology, which can be interactively and computationally analyzed. While AC networks are indispensable tools to study coordinated ACs, they become difficult to navigate and interpret in the presence of clusters of increasing size and complex topologies. Herein, we introduce reduced network representations that transform AC networks into an easily interpretable format from which SAR information in the form of R-group tables can be readily obtained. The simplified network variant greatly improves the interpretability of large and complex AC networks and substantially supports SAR exploration.

活性悬崖 (AC) 由结构相似的化合物组成，它们对靶标的效力差异很大。因此，AC 引入了构效关系 (SAR) 的不连续性，并且是 SAR 信息的主要来源。在化合物数据集中，绝大多数 ACs 是由不同大小的结构相似化合物组形成的，具有很大的效力变化。因此，许多这些化合物参与多个 AC。与被视为单个化合物对的 AC 相比，AC 的这种协调形成增加了它们的 SAR 信息含量，但使 AC 分析复杂化。在网络表示中，协调的 AC 会产生不同大小和拓扑的集群，这些集群可以进行交互和计算分析。虽然 AC 网络是研究协调 AC 不可或缺的工具，在存在越来越大的规模和复杂拓扑的集群时，它们变得难以导航和解释。在这里，我们引入了简化的网络表示，将 AC 网络转换为易于解释的格式，从中可以轻松获得 R 组表形式的 SAR 信息。简化的网络变体极大地提高了大型复杂 AC 网络的可解释性，并大大支持了 SAR 探索。