ProtFun: A Protein Function Prediction Model Using Graph Attention Networks with a Protein Large Language Model.

ABSTRACT: Understanding protein functions facilitates the identification of the underlying causes of many diseases and guides the research for discovering new therapeutic targets and medications. With the advancement of high throughput technologies, obtaining novel protein sequences has been a routine process. However, determining protein functions experimentally is cost- and labor-prohibitive. Therefore, it is crucial to develop computational methods for automatic protein function prediction. In this study, we propose a multi-modal deep learning architecture called ProtFun to predict protein functions. ProtFun integrates protein large language model (LLM) embeddings as node features in a protein family network. Employing graph attention networks (GAT) on this protein family network, ProtFun learns

SUBMITTER: Talo M 

PROVIDER: S-EPMC12132266 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature