Lead optimization focuses on the generation of analogue series (ASs) with sustainable structure-activity relationship (SAR) progression. If roadblocks are encountered during multi-property optimization, it is often desirable to replace an AS with another containing a different core structure but having similar SAR characteristics for a given target. This process represents target-based SAR transfer. A previously unexplored question is to what extent AS-based SAR transfer events might also occur across different targets. To address this question, we have developed and applied a new computational approach to systematically search for ASs with SAR transfer potential and align qualifying series in a chemically intuitive way. The methodology relies on fragment similarity scoring in combination with dynamic programming. Our large-scale analysis has revealed that SAR transfer events across different targets are more frequently observed than one might expect, providing many opportunities for the design of new SAR transfer analogues for evolving series.

先导优化侧重于生成具有可持续结构-活性关系 (SAR) 进展的类似物系列 (AS)。如果在多属性优化过程中遇到障碍，通常希望将一个 AS 替换为另一个包含不同核心结构但对于给定目标具有相似 SAR 特征的 AS。这个过程代表了基于目标的 SAR 转移。一个以前未探索过的问题是，基于 AS 的 SAR 转移事件在多大程度上也可能在不同的目标上发生。为了解决这个问题，我们开发并应用了一种新的计算方法来系统地搜索具有 SAR 转移潜力的 AS，并以化学直观的方式对齐合格系列。该方法依赖于片段相似度评分与动态规划相结合。