MPI-VGAE: protein-metabolite enzymatic reaction link learning by variational graph autoencoders.

ABSTRACT: Enzymatic reactions are crucial to explore the mechanistic function of metabolites and proteins in cellular processes and to understand the etiology of diseases. The increasing number of interconnected metabolic reactions allows the development of in silico deep learning-based methods to discover new enzymatic reaction links between metabolites and proteins to further expand the landscape of existing metabolite-protein interactome. Computational approaches to predict the enzymatic reaction link by metabolite-protein interaction (MPI) prediction are still very limited. In this study, we developed a Variational Graph Autoencoders (VGAE)-based framework to predict MPI in genome-scale heterogeneous enzymatic reaction networks across ten organisms. By incorporating molecular features of metabol

SUBMITTER: Wang C 

PROVIDER: S-EPMC10359079 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature