The BioGRID | PUBLICATION VIEW

	PLoS ONE (2009); 4(10):e7310
Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.
Sardiu ME, Gilmore JM, Carrozza MJ, Li B, Workman JL, Florens L, Washburn MP
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.
[PUBMED: 19806189]