INTREPPPID-an orthologue-informed quintuplet network for cross-species prediction of protein-protein interaction.

ABSTRACT: An overwhelming majority of protein-protein interaction (PPI) studies are conducted in a select few model organisms largely due to constraints in time and cost of the associated 'wet lab' experiments. In silico PPI inference methods are ideal tools to overcome these limitations, but often struggle with cross-species predictions. We present INTREPPPID, a method that incorporates orthology data using a new 'quintuplet' neural network, which is constructed with five parallel encoders with shared parameters. INTREPPPID incorporates both a PPI classification task and an orthologous locality task. The latter learns embeddings of orthologues that have small Euclidean distances between them and large distances between embeddings of all other proteins. INTREPPPID outperforms all other leading PPI i

SUBMITTER: Szymborski J 

PROVIDER: S-EPMC11339867 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature