SynKit: A Graph-Based Python Framework for Rule-Based Reaction Modeling and Analysis

Abstract

Computational modeling of chemical reactions is fundamental to modern synthetic chemistry but is often hindered by a fragmented software ecosystem and the complexity of accurately representing the reaction mechanisms. To address this, we introduce SynKit, an open-source Python library that provides a unified, chemically intuitive framework for reaction informatics. SynKit performs core tasks such as reaction canonicalization and transformation classification, while other functionalities─such as synthetic route construction through rule composition─are supported through integration with external libraries. The newly introduced Mechanistic Transition Graph extends the traditional net-change representation of the Imaginary Transition State by explicitly modeling the sequence of bond-forming and bond-breaking events, capturing transient intermediates, and providing deeper mechanistic insight. Designed for easy installation and broad compatibility, SynKit integrates smoothly into existing computational workflows for exploring complex Chemical Reaction Networks. For more advanced network analyses, it interfaces with specialized tools (e.g., MØD) to support exhaustive mechanism enumeration and kinetics-aware studies. By combining advanced mechanistic modeling with an accessible, modular design, SynKit supports more reproducible and rigorous research in automated synthesis planning.