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A computational interactome and functional annotation for the human proteome

Authors :
José Ignacio Garzón
Lei Deng
Diana Murray
Sagi Shapira
Donald Petrey
Barry Honig
Source :
eLife, Vol 5 (2016)
Publication Year :
2016
Publisher :
eLife Sciences Publications Ltd, 2016.

Abstract

We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein’s function. We provide annotations for most human proteins, including many annotated as having unknown function.

Details

Language :
English
ISSN :
2050084X
Volume :
5
Database :
Directory of Open Access Journals
Journal :
eLife
Publication Type :
Academic Journal
Accession number :
edsdoj.f89e7a154b88446d80f3afa2470caad7
Document Type :
article
Full Text :
https://doi.org/10.7554/eLife.18715