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  Large-scale de novo prediction of physical protein-protein association.

Elefsinioti, A., Saraç, Ö. S., Hegele, A., Plake, C., Hubner, N. C., Poser, I., et al. (2011). Large-scale de novo prediction of physical protein-protein association. Molecular & Cellular Proteomics: Mcp, 10(11): DOI 10.1074/mcp.M111.010629.

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Elefsinioti, Antigoni, Autor
Saraç, Ömer Sinan, Autor
Hegele, Anna, Autor
Plake, Conrad, Autor
Hubner, Nina C, Autor
Poser, Ina1, Autor           
Sarov, Mihail1, Autor           
Hyman, Anthony A.1, Autor           
Mann, Matthias, Autor
Schroeder, Michael1, Autor           
Stelzl, Ulrich, Autor
Beyer, Andreas2, Autor
Affiliations:
1Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society, ou_2340692              
2Max Planck Society, ou_persistent13              

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 Zusammenfassung: Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding. Our network classifies more than 5 million protein pairs predicting 94,009 new interactions with high confidence. We experimentally tested a subset of these predictions using yeast two-hybrid analysis and affinity purification followed by quantitative mass spectrometry. Thus we identified 462 new protein-protein interactions and confirmed the predictive power of the network. These independent experiments address potential issues of circular reasoning and are a distinctive feature of this work. Analysis of the physical interactome unravels subnetworks mediating between different functional and physical subunits of the cell. Finally, we demonstrate the utility of the network for the analysis of molecular mechanisms of complex diseases by applying it to genome-wide association studies of neurodegenerative diseases. This analysis provides new evidence implying TOMM40 as a factor involved in Alzheimer's disease. The network provides a high-quality resource for the analysis of genomic data sets and genetic association studies in particular. Our interactome is available via the hPRINT web server at: www.print-db.org.

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 Datum: 2011
 Publikationsstatus: Erschienen
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 Identifikatoren: eDoc: 585132
Anderer: 4614
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Titel: Molecular & Cellular Proteomics : Mcp
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 10 (11) Artikelnummer: DOI 10.1074/mcp.M111.010629 Start- / Endseite: - Identifikator: -