Lee Tzong-Yi, Bo-Kai Hsu Justin, Chang Wen-Chi, Huang Hsien-Da
Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 320, Taiwan.
Nucleic Acids Res. 2011 Jan;39(Database issue):D777-87. doi: 10.1093/nar/gkq970. Epub 2010 Oct 30.
Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in intracellular signal transduction. With the increasing number of experimental phosphorylation sites that has been identified by mass spectrometry-based proteomics, the desire to explore the networks of protein kinases and substrates is motivated. Manning et al. have identified 518 human kinase genes, which provide a starting point for comprehensive analysis of protein phosphorylation networks. In this study, a knowledgebase is developed to integrate experimentally verified protein phosphorylation data and protein-protein interaction data for constructing the protein kinase-substrate phosphorylation networks in human. A total of 21,110 experimental verified phosphorylation sites within 5092 human proteins are collected. However, only 4138 phosphorylation sites (∼20%) have the annotation of catalytic kinases from public domain. In order to fully investigate how protein kinases regulate the intracellular processes, a published kinase-specific phosphorylation site prediction tool, named KinasePhos is incorporated for assigning the potential kinase. The web-based system, RegPhos, can let users input a group of human proteins; consequently, the phosphorylation network associated with the protein subcellular localization can be explored. Additionally, time-coursed microarray expression data is subsequently used to represent the degree of similarity in the expression profiles of network members. A case study demonstrates that the proposed scheme not only identify the correct network of insulin signaling but also detect a novel signaling pathway that may cross-talk with insulin signaling network. This effective system is now freely available at http://RegPhos.mbc.nctu.edu.tw.
激酶催化的蛋白质磷酸化在细胞内信号转导中起着关键的调节作用。随着基于质谱的蛋白质组学鉴定出的实验性磷酸化位点数量不断增加，探索蛋白质激酶和底物网络的需求也随之产生。曼宁等人已经鉴定出518个人类激酶基因，这为全面分析蛋白质磷酸化网络提供了一个起点。在本研究中，开发了一个知识库，用于整合经过实验验证的蛋白质磷酸化数据和蛋白质-蛋白质相互作用数据，以构建人类的蛋白质激酶-底物磷酸化网络。总共收集了5092个人类蛋白质中的21,110个经过实验验证的磷酸化位点。然而，只有4138个磷酸化位点（约20%）具有来自公共领域的催化激酶注释。为了全面研究蛋白质激酶如何调节细胞内过程，纳入了一个已发表的激酶特异性磷酸化位点预测工具，名为KinasePhos，用于分配潜在的激酶。基于网络的系统RegPhos可以让用户输入一组人类蛋白质；因此，可以探索与蛋白质亚细胞定位相关的磷酸化网络。此外，随后使用时间进程微阵列表达数据来表示网络成员表达谱的相似程度。一个案例研究表明，所提出的方案不仅能够识别正确的胰岛素信号网络，还能检测到一条可能与胰岛素信号网络相互作用的新信号通路。这个有效的系统现在可在http://RegPhos.mbc.nctu.edu.tw免费获取。
