Protein functional site annotation using local structure embeddings.

ABSTRACT: The rapid expansion of protein sequence and structure databases has resulted in a significant number of proteins with ambiguous or unknown function. While advances in machine learning techniques hold great potential to fill this annotation gap, current methods for function prediction are unable to associate global function reliably to the specific residues responsible for that function. We address this issue by introducing PARSE (Protein Annotation by Residue-Specific Enrichment), a knowledge-based method which combines pretrained embeddings of local structural environments with traditional statistical techniques to simultaneously predict function and provide residue-level annotations. For the task of predicting the catalytic function of enzymes, PARSE achieves comparable or superior globa

SUBMITTER: Derry A 

PROVIDER: S-EPMC12403137 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature