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


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.

SUBMITTER: Sardiu ME 

PROVIDER: S-EPMC2751824 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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

Sardiu Mihaela E ME   Gilmore Joshua M JM   Carrozza Michael J MJ   Li Bing B   Workman Jerry L JL   Florens Laurence L   Washburn Michael P MP  

PloS one 20091006 10


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 w  ...[more]

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