MGMA-PPIS: Predicting the protein-protein interaction site with multiview graph embedding and multiscale attention fusion.

ABSTRACT:

Background

Protein-protein interactions (PPIs) play a crucial role in numerous biological processes. Accurate identification of protein-protein interaction sites is critical for a comprehensive understanding of protein functions and pathological mechanisms. However, conventional experimental approaches for detecting PPIs are often time-consuming and labor-intensive, thereby motivating the development of efficient computational methods to identify PPI sites.

Results

In this work, we propose a novel graph neural network-based method (called MGMA-PPIS) to predict PPI sites by adopting multiview graph embedding and multiscale attention fusion. MGMA-PPIS integrates global node features extracted by an equivariant graph neural network and multiscale local node features extracted b

SUBMITTER: Han Y 

PROVIDER: S-EPMC12486388 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature