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Predicting physical interactions between protein complexes.


ABSTRACT: Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships.

SUBMITTER: Clancy T 

PROVIDER: S-EPMC3675826 | biostudies-other | 2013 Jun

REPOSITORIES: biostudies-other

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Predicting physical interactions between protein complexes.

Clancy Trevor T   Rødland Einar Andreas EA   Nygard Ståle S   Hovig Eivind E  

Molecular & cellular proteomics : MCP 20130225 6


Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we desi  ...[more]

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2022-02-07 | GSE196130 | GEO