Protein language models uncover carbohydrate-active enzyme function in metagenomics.

ABSTRACT:

Background

The functional annotation of uncharacterized microbial enzymes from metagenomic data remains a significant challenge, limiting our understanding of microbial metabolic dynamics. Traditional annotation methods often rely on sequence homology, which can fail to identify remote homologs or enzymes with structural rather than sequence conservation. To address this gap, we developed CAZyLingua, the first annotation tool to use protein language models (pLMs) for the accurate classification of carbohydrate-active enzyme (CAZyme) families and subfamilies.

Results

CAZyLingua demonstrated high performance, maintaining precision and recall comparable to state-of-the-art hidden Markov model-based methods while outperforming purely sequence-based approaches. When applied to a

SUBMITTER: Thurimella K 

PROVIDER: S-EPMC12659350 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature