CACLENS: A Multitask Deep Learning System for Enzyme Discovery.

ABSTRACT: Deep learning greatly advances large-scale predictions of enzymatic structure, function, and properties. However, existing deep learning models remain limited in high-performance screen of functional enzymes, due to a lack of multimodal learning and multitask prediction capabilities. To address these challenges, CACLENS (Cross-Attention & Contrastive Learning-enabled Enzyme Selection) is introduced, a multitask deep learning framework incorporating Customized Gate Control, contrastive learning, and cross-attention mechanisms. CACLENS demonstrates robust performance across three key functions-reaction type classification, EC number prediction, and reaction feasibility assessment with fewer computational resources. These three functions are seamlessly incorporated into the enzyme screening p

SUBMITTER: Yi X 

PROVIDER: S-EPMC12904076 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature