FAPM: functional annotation of proteins using multimodal models beyond structural modeling.

ABSTRACT:

Motivation

Assigning accurate property labels to proteins, like functional terms and catalytic activity, is challenging, especially for proteins without homologs and "tail labels" with few known examples. Previous methods mainly focused on protein sequence features, overlooking the semantic meaning of protein labels.

Results

We introduce functional annotation of proteins using multimodal models (FAPM), a contrastive multimodal model that links natural language with protein sequence language. This model combines a pretrained protein sequence model with a pretrained large language model to generate labels, such as Gene Ontology (GO) functional terms and catalytic activity predictions, in natural language. Our results show that FAPM excels in understanding protein properties, o

SUBMITTER: Xiang W 

PROVIDER: S-EPMC11630832 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature