Determining Protein Complex Connectivity Using a Probabilistic Deletion Network Derived from Quantitative Proteomics

Mihaela E Sardiu, Joshua M Gilmore, Michael J Carrozza, Bing Li, Jerry L Workman, Laurence Florens and Michael P Washburn

PLOS ONE, 2009, vol. 4, issue 10, 1-10

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.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0007310

DOI: 10.1371/journal.pone.0007310

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