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

The computational modeling of chemical reactions is fundamental to modern synthetic chemistry, yet progress is often hindered by a fragmented software ecosystem and the challenge of representing complex reaction mechanisms with high fidelity. To address these challenges, we introduce SynKit, a streamlined, open-source Python library that provides a unified and chemically intuitive framework for reaction informatics. SynKit provides a comprehensive suite of tools for core tasks via algorithms implemented directly in the package, including reaction canonicalization and classification of transformation types, while other tasks are accomplished through integrated external libraries, e.g., the construction of synthetic routes via a flexible rule composition engine. Moving beyond the static, net-change representations of the Imaginary Transition State, SynKit introduces the Mechanistic Transition Graph, a graph that explicitly models the sequence of bond-forming and -breaking events, thereby capturing transient intermediates and providing deeper mechanistic insight. The package can be installed with minimal dependencies on the ubiquitous RDKit and NetworkX libraries, and thus SynKit ensures broad accessibility and seamless integration into existing computational workflows for exploring complex Chemical Reaction Networks; when deeper network exploration is required, SynKit can wrap and orchestrate specialist mechanistic packages (e.g., MØD) to perform exhaustive mechanistic enumeration and kinetics-aware analyses. By combining advanced mechanistic modeling with a robust and accessible design, SynKit empowers researchers to advance the field of automated synthesis planning with greater clarity and reproducibility.