Conventional molecular graphs are often unable to reliably encode stereochemistry, especially for symmetric molecules, nontetrahedral centers, and transition states. To overcome this, we present StereoMolGraph, an open-source Python library implementing a stereochemistry-aware graph representation for molecules and condensed graphs of reactions. Our method uses permutation-invariant local stereodescriptors, grounded in group theory, to provide an extensible representation of chirality. Based on this we introduce methods allowing for robust comparison of stereoisomers, including the identification of enantiomerism and diastereomerism, and support fleeting stereochemistry in transition states. We demonstrate the library's utility for complex organic molecules and metal complexes and analysis of distinct chiral reaction pathways. With RDKit interoperability and visualization features, StereoMolGraph offers a practical and transparent tool for advanced stereochemically aware chemoinformatics workflows.
Papusha et al. (Fri,) studied this question.