Journal of Cheminformatics· 2026Q1
Representing chemical and enzymatic reactions in fingerprint space for applicability filtering and classification
- 1citations
- Q1SCImago
- 2026year
Short summary
A new framework maps chemical and enzymatic reactions to fingerprint space by representing them as differences between product and substrate fingerprints, enabling filtering and classification.
AI-generated from the title and abstract; the full text is not read.
Key points
- Reactions are represented in fingerprint space as the signed difference between product and substrate fingerprints.
- ECFP-compatible templates induce constant fingerprint displacements, creating a functorial mapping.
- Reaction-center ECFPs encode local environments and serve as a prefilter for reaction applicability.
- The framework successfully classifies reaction and enzyme classes using USPTO-50k and MetaNetX datasets.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract Molecular and reaction fingerprints are widely used as static descriptors, but their relationship to graph-level reaction application remains unclear. We address this question in counted Extended-Connectivity Fingerprint (ECFP) space, representing reactions as signed differences between product and substrate fingerprints. We define ECFP-compatible templates, for which graph-level reaction application induces a constant fingerprint displacement, yielding a functorial mapping from graph transformations to affine translations in fingerprint space. We also introduce reaction-center ECFPs to encode the local environments required for template application and to provide a fast coordinate-wise prefilter for graph-level reaction applicability. We evaluate this framework on USPTO-50k and MetaNetX reactions across a range of ECFP radii. Both representations carry predictive information for reaction-class and enzyme-class classification, with reaction-center ECFPs contributing information not captured by reaction ECFPs alone. This framework connects reaction templates and reaction fingerprints to molecular pathway search and reaction-property prediction in fingerprint space.
The authors' abstract, as published at the source. Journal of Cheminformatics, 2026 · DOI ↗
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