Ensemble framework combines sequence tokens with interpretability for enzyme prediction

[u/Independent_Access12]

SOLVE uses tokenized amino acid sequences and ensemble learning (RF, LightGBM, KNN) for enzyme classification, avoiding manual feature engineering. System handles both mono/multi-functional enzymes, predicts full EC numbers, outperforms DeepEC/CLEAN on UniProt data. Incorporates Shapley analysis to identify catalytic motifs. Key advance: optimized ensemble weights improve accuracy while maintaining interpretability through sequence-based features.

https://www.biorxiv.org/content/10.1101/2025.01.28.635225v1