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Large‐scale mapping of human protein–protein interactions by mass spectrometry
- Source :
- Molecular Systems Biology
- Publication Year :
- 2007
- Publisher :
- EMBO, 2007.
-
Abstract
- Mapping protein-protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein-protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24,540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein-protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.
- Subjects :
- Spectrometry, Mass, Electrospray Ionization
Immunoprecipitation
human interactome
Plasma protein binding
Computational biology
Biology
Bioinformatics
Mass spectrometry
Article
General Biochemistry, Genetics and Molecular Biology
Protein–protein interaction
03 medical and health sciences
0302 clinical medicine
Human interactome
False positive paradox
Humans
030304 developmental biology
0303 health sciences
General Immunology and Microbiology
Applied Mathematics
Proteins
Data set
protein–protein interaction
Computational Theory and Mathematics
030220 oncology & carcinogenesis
IP-HTMS
Protein–protein interaction prediction
General Agricultural and Biological Sciences
Protein Binding
Information Systems
Subjects
Details
- ISSN :
- 17444292
- Volume :
- 3
- Database :
- OpenAIRE
- Journal :
- Molecular Systems Biology
- Accession number :
- edsair.doi.dedup.....b63cee908506c7aad7ce219f49513fdc
- Full Text :
- https://doi.org/10.1038/msb4100134