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Updated: Apr 30, 2026

Identification of Kinase-substrate Pairs Using High Throughput Screening
Published on: August 29, 2015
RegPhos 2.0: an updated resource to explore protein kinase-substrate phosphorylation networks in mammals
Kai-Yao Huang1, Hsin-Yi Wu, Yi-Ju Chen
1Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, Taiwan, Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan, Genomics Research Center, Academia Sinica, Taipei 115, Taiwan, Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan and Department of Biological Science and Technology, National Chiao Tung University, Hsin-Chu 300, Taiwan.
Abstract:
Protein phosphorylation catalyzed by kinases plays crucial roles in regulating a variety of intracellular processes. Owing to an increasing number of in vivo phosphorylation sites that have been identified by mass spectrometry (MS)-based proteomics, the RegPhos, available online at http://csb.cse.yzu.edu.tw/RegPhos2/, was developed to explore protein phosphorylation networks in human. In this update, we not only enhance the data content in human but also investigate kinase-substrate phosphorylation networks in mouse and rat. The experimentally validated phosphorylation sites as well as their catalytic kinases were extracted from public resources, and MS/MS phosphopeptides were manually curated from research articles. RegPhos 2.0 aims to provide a more comprehensive view of intracellular signaling networks by integrating the information of metabolic pathways and protein-protein interactions. A case study shows that analyzing the phosphoproteome profile of time-dependent cell activation obtained from Liquid chromatography-mass spectrometry (LC-MS/MS) analysis, the RegPhos deciphered not only the consistent scheme in B cell receptor (BCR) signaling pathway but also novel regulatory molecules that may involve in it. With an attempt to help users efficiently identify the candidate biomarkers in cancers, 30 microarray experiments, including 39 cancerous versus normal cells, were analyzed for detecting cancer-specific expressed genes coding for kinases and their substrates. Furthermore, this update features an improved web interface to facilitate convenient access to the exploration of phosphorylation networks for a group of genes/proteins. Database URL: http://csb.cse.yzu.edu.tw/RegPhos2/
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