Identification of protein interactions involved in cellular signaling
- PMID: 23481661
- PMCID: PMC3708163
- DOI: 10.1074/mcp.R113.027771
Identification of protein interactions involved in cellular signaling
Abstract
Protein-protein interactions drive biological processes. They are critical for all intra- and extracellular functions, and the technologies to analyze them are widely applied throughout the various fields of biological sciences. This study takes an in-depth view of some common principles of cellular regulation and provides a detailed account of approaches required to comprehensively map signaling protein-protein interactions in any particular cellular system or condition. We provide a critical review of the benefits and disadvantages of the yeast two-hybrid method and affinity purification coupled with mass spectrometric procedures for identification of signaling protein-protein interactions. In particular, we emphasize the quantitative and qualitative differences between tandem affinity and one-step purification (such as FLAG and Strep tag) methods. Although applicable to all types of interaction studies, a special section is devoted in this review to aspects that should be considered when attempting to identify signaling protein interactions that often are transient and weak by nature. Finally, we discuss shotgun and quantitative information that can be gleaned by MS-coupled methods for analysis of multiprotein complexes.
Figures
References
-
- Reményi A., Good M. C., Bhattacharyya R. P., Lim W. A. (2005) The role of docking interactions in mediating signaling input, output, and discrimination in the yeast MAPK network. Mol. Cell 20, 951–962 - PubMed
-
- Pawson T., Nash P. (2000) Protein-protein interactions define specificity in signal transduction. Genes Dev. 14, 1027–1047 - PubMed
-
- Jaeger S., Aloy P. (2012) From protein interaction networks to novel therapeutic strategies. IUBMB Life 64, 529–537 - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Molecular Biology Databases
