Chemistry-Informed Dual Encoders for Enzyme-Reaction Discovery

Enzyme discovery often begins by uncovering promiscuous activities in known enzymes or characterizing the reactions catalyzed by newly identified sequences. Understanding an enzyme’s substrate and reaction scope requires connecting active-site features to reaction chemistry, a relationship that existing prediction methods often overlook. We propose Chemistry-Informed Reaction–Catalyst Embeddings (CIRCE), a contrastive dual encoder for bidirectional enzyme–reaction retrieval. CIRCE integrates function-aware protein representations with reaction representations that encode reactants, products, stoichiometry, cofactors, and additional chemical annotations. Incorporating chemical knowledge into both its representations and training objective enables CIRCE to learn features relevant to enzyme reactivity and promiscuity, with the aim of improving generalization to new reactions and accelerating enzyme discovery. Across enzyme screening and bidirectional retrieval benchmarks, CIRCE achieves state-of-the-art performance and robust generalization. These results establish its utility for enzyme discovery and provide a foundation for investigating the active-site determinants of catalytic promiscuity.