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PLoS One. 2009 Oct 6;4(10):e7310. doi: 10.1371/journal.pone.0007310.

Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

Author information

1
Stowers Institute for Medical Research, Kansas City, Missouri, United States of America.

Abstract

Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

PMID:
19806189
PMCID:
PMC2751824
DOI:
10.1371/journal.pone.0007310
[Indexed for MEDLINE]
Free PMC Article

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