CASyM: Chemotype Annotation through Synthesis Mapping

Abstract

Abstract The identification and annotation of chemotypes is central to structure–activity relationship studies and property optimization in drug discovery. Current computational approaches rely on predefined fragmentation rules or structural similarity to identify these molecular scaffolds, often overlooking the rich information available in reaction data. Here, we introduce CASyM (Chemotype Annotation through Synthesis Mapping), a novel approach that leverages hierarchical reaction data to systematically identify chemotypes within compound libraries. CASyM constructs synthesis graphs from curated reaction data sets, detects major common intermediates, and builds chemotype graphs that capture the hierarchical and interconnected nature of chemical synthesis. SMARTS patterns are extracted to define chemotypes, enabling robust assignment of target molecules, including those absent from the original reaction data. We demonstrate the approach across three case studies using public patent data, proprietary electronic laboratory notebook data from drug discovery projects, and simulated multistep synthesis data for compounds lacking experimental synthesis records. CASyM achieves high coverage of target molecules (85–99%), reveals chemotype-property relationships, and enables chemotype assignment in the absence of experimental data. This reaction-centric approach provides a powerful framework for chemotype annotation, facilitating series exploration and optimization in medicinal chemistry.