RegPhos: a system to explore the protein kinase-substrate phosphorylation network in humans

Area of Science:

• Molecular Biology
• Systems Biology
• Bioinformatics

Background:

• Protein phosphorylation by kinases is vital for intracellular signal transduction.
• Mass spectrometry has identified numerous experimental phosphorylation sites, driving interest in kinase-substrate networks.
• Understanding these networks is crucial for deciphering cellular regulatory mechanisms.

Purpose of the Study:

• To develop a knowledgebase integrating experimental phosphorylation and protein-protein interaction data for human kinase-substrate networks.
• To incorporate a prediction tool for assigning potential kinases to phosphorylation sites.
• To create a web-based system (RegPhos) for exploring these networks and their association with subcellular localization and expression profiles.

Main Methods:

• Collected and integrated experimentally verified protein phosphorylation data (21,110 sites in 5092 proteins) with protein-protein interaction data.
• Utilized the KinasePhos tool to predict catalytic kinases for sites lacking annotation.
• Developed the RegPhos web-based system incorporating subcellular localization and time-coursed microarray expression data.

Main Results:

• Successfully constructed human protein kinase-substrate phosphorylation networks.
• Identified potential kinases for a significant portion of phosphorylation sites.
• The RegPhos system demonstrated its utility in exploring signaling pathways, including the insulin signaling network.

Conclusions:

• The integrated approach effectively maps protein phosphorylation networks.
• RegPhos provides a valuable tool for exploring kinase-substrate interactions and signaling pathways.
• The system identified known pathways and suggested novel cross-talk with the insulin signaling network.