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This is a Quantitative Study study.

September 20, 2025Briefings in BioinformaticsOpen Access

Autoregressive enzyme function prediction with multi-scale multi-modality fusion

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Novel deep learning model predicts enzyme functions using sequence and structural data, suggesting improvements.

Predicting enzyme function using MAPred shows significant improvements over existing models.
Evaluation against benchmark datasets like New-392 and Price reveals enhanced reliability in function predictions.
MAPred employs a dual-pathway approach, integrating sequence data and 3D structural tokens for better accuracy.
The autoregressive prediction network captures the hierarchical nature of Enzyme Commission classifications, enhancing predictions.

Rong et al. (2025) studied this question.

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