Structure-Based Deep Learning Framework for Modeling Human-Gut Bacterial Protein Interactions.

ABSTRACT: Background: The interaction network between the human host proteins and the proteins of the gut bacteria is essential for the establishment of human health, and its dysregulation directly contributes to disease development. Despite its great importance, experimental data on protein-protein interactions (PPIs) between these species are sparse due to experimental limitations. Methods: This study presents a deep learning-based framework for predicting PPIs between human and gut bacterial proteins using structural data. The framework leverages graph-based protein representations and variational autoencoders (VAEs) to extract structural embeddings from protein graphs, which are then fused through a Bi-directional Cross-Attention module to predict interactions. The model addresses

SUBMITTER: Kiouri DP 

PROVIDER: S-EPMC11843979 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature