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PMID: 19243629 Published · epublish English Journal Article Research Support, Non-U.S. Gov't

Protein-protein interaction as a predictor of subcellular location.

BMC systems biology ·Vol. 3 ·2009-02-25 ·Pages 28

Shin CJ, Wong S, Davis MJ, Ragan MA

Abstract

Many biological processes are mediated by dynamic interactions between and among proteins. In order to interact, two proteins must co-occur spatially and temporally. As protein-protein interactions (PPIs) and subcellular location (SCL) are discovered via separate empirical approaches, PPI and SCL annotations are independent and might complement each other in helping us to understand the role of individual proteins in cellular networks. We expect reliable PPI annotations to show that proteins interacting in vivo are co-located in the same cellular compartment. Our goal here is to evaluate the potential of using PPI annotation in determining SCL of proteins in human, mouse, fly and yeast, and to identify and quantify the factors that contribute to this complementarity. Using publicly available data, we evaluate the hypothesis that interacting proteins must be co-located within the same subcellular compartment. Based on a large, manually curated PPI dataset, we demonstrate that a substantial proportion of interacting proteins are in fact co-located. We develop an approach to predict the SCL of a protein based on the SCL of its interaction partners, given sufficient confidence in the interaction itself. The frequency of false positive PPIs can be reduced by use of six lines of supporting evidence, three based on type of recorded evidence (empirical approach, multiplicity of databases, and multiplicity of literature citations) and three based on type of biological evidence (inferred biological process, domain-domain interactions, and orthology relationships), with biological evidence more-effective than recorded evidence. Our approach performs better than four existing prediction methods in identifying the SCL of membrane proteins, and as well as or better for soluble proteins. Understanding cellular systems requires knowledge of the SCL of interacting proteins. We show how PPI data can be used more effectively to yield reliable SCL predictions for both soluble and membrane proteins. Scope exists for further improvement in our understanding of cellular function through consideration of the biological context of molecular interactions.

MeSH Terms
Animals Computational Biology/methods Databases, Genetic Humans Intracellular Space/metabolism Mice Protein Interaction Mapping/methods Proteins/metabolism Yeasts
Chemicals
Proteins
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Shin Chang Jin
The University of Queensland, Institute for Molecular Bioscience, and ARC Centre of Excellence in Bioinformatics, QLD, Australia. [email protected]
Wong Simon
Davis Melissa J
Ragan Mark A
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Article Info
Journal
BMC systems biology
Abbr.
BMC Syst Biol
ISSN
1752-0509
Published
2009-02-25
Epub
2009-00-25
Pages
28
Language
English
Region
England
NLM ID
101301827
PMCID
PMC2663780
Subset
IM
Analysis Services
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