Software-Aided Mass Spectrometry Analysis for Identification of Protein-Protein Interaction in Signal Transduction Pathways

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.