Name
Title | ||
|---|---|---|
Software-Aided Mass Spectrometry Analysis for Identification of Protein-Protein Interaction in Signal Transduction Pathways |
Abstract | ||
|---|---|---|
Protein-protein interaction (PPI) networks, which are caused by extracellular stimuli in the signal transduction pathways, are not fully understood for all cells. Mass spectrometric analysis is one of the powerful tools available for revealing these interactions. However, this analytical method is sometimes inefficient because of the many false positive candidates resulting from extracellular matrix or exogenous protein contaminants. To efficiently identify PPIs in signal transduction pathways, we developed a software program 'PROMISS' for LC/MS/MS. PROMISS contains all known PPIs and domain information, which are very useful for deducting the PPIs in different signal transduction pathways. By referring to the domain and interaction information in PROMISS, users can effectively select from enormous numbers of candidates the proteins that are related to specific PPIs. We also show that gel filtration chromatography is useful for pretreating and fractioning the interacting protein complex in the cell. In this study, we report a method of identifying epidermal growth factor receptor (EGFR) binding protein in EGF-treated A431 cells using PROMISS and gel filtration. Based on mass spectrometry analysis and bioinformatics approaches, this strategy is effective for identification of PPIs in signal transduction pathways. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICDE.2005.286 | ICDE Workshops |
Keywords | Field | DocType |
software-aided mass spectrometry analysis,known ppis,mass spectrometric analysis,interacting protein complex,protein-protein interaction,different signal transduction pathway,analytical method,signal transduction pathway,exogenous protein contaminant,signal transduction pathways,binding protein,specific ppis,genomics,extracellular matrix,signal analysis,mass spectroscopy,amino acids,proteins,databases,false positive,mass spectrometry,protein complex,extracellular,protein protein interaction,signal processing,bioinformatics,filtration | Data mining,Protein–protein interaction,Computer science,Binding protein,Extracellular,Cell,Signal transduction,Computational biology,Interaction information,Bioinformatics,Epidermal growth factor receptor,A431 cells | Conference |
ISBN | Citations | PageRank |
0-7695-2657-8 | 0 | 0.34 |
References | Authors | |
7 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aki Hasegawa | 1 | 81 | 5.30 |
| Kazumi Kuriyama-Matsumura | 2 | 0 | 0.34 |
| Xiaomei Yu | 3 | 0 | 0.34 |
| Mariko Hatakeyama | 4 | 175 | 12.17 |
| Akihiko Konagaya | 5 | 578 | 94.32 |
| Kuriyama-Matsumura, K. | 6 | 0 | 0.34 |