An integrated mass spectrometric and computational framework for the analysis of protein interaction networks View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-02-25

AUTHORS

Oliver Rinner, Lukas N. Mueller, Martin Hubálek, Markus Müller, Matthias Gstaiger, Ruedi Aebersold

ABSTRACT

Biological systems are controlled by protein complexes that associate into dynamic protein interaction networks. We describe a strategy that analyzes protein complexes through the integration of label-free, quantitative mass spectrometry and computational analysis. By evaluating peptide intensity profiles throughout the sequential dilution of samples, the MasterMap system identifies specific interaction partners, detects changes in the composition of protein complexes and reveals variations in the phosphorylation states of components of protein complexes. We use the complexes containing the human forkhead transcription factor FoxO3A to demonstrate the validity and performance of this technology. Our analysis identifies previously known and unknown interactions of FoxO3A with 14-3-3 proteins, in addition to identifying FoxO3A phosphorylation sites and detecting reduced 14-3-3 binding following inhibition of phosphoinositide-3 kinase. By improving specificity and sensitivity of interaction networks, assessing post-translational modifications and providing dynamic interaction profiles, the MasterMap system addresses several limitations of current approaches for protein complexes. More... »

PAGES

345-352

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nbt1289

DOI

http://dx.doi.org/10.1038/nbt1289

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1049993666

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17322870


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