ASCE-PPIS: a protein-protein interaction sites predictor based on equivariant graph neural network with fusion of structure-aware pooling and graph collapse.

ABSTRACT:

Motivation

Identifying protein-protein interaction sites constitute a crucial step in understanding disease mechanisms and drug development. As experimental methods for PPIS identification are expensive and time-consuming, numerous computational screening approaches have been developed, among which graph neural network-based methods have achieved remarkable progress in recent years. However, existing methods lack the utilization of interactions between amino acid molecules and fail to address the dense characteristics of protein graphs.

Results

We propose ASCE-PPIS, an equivariant graph neural network-based method for protein-protein interaction prediction. This novel approach integrates graph pooling and graph collapse to address the aforementioned challenges. Our model lea

SUBMITTER: Shen G 

PROVIDER: S-EPMC12342974 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature