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Submitted on December 10, 2007
Revised on May 1, 2008
Accepted on May 6, 2008

GPS 2.0: Prediction of kinase-specific phosphorylation sites in hierarchy

Yu Xue, Jian Ren, Xinjiao Gao, Changjiang Jin, Longping Wen, and Xuebiao Yao

Life Science school, University of Science and Technology of China, Hefei, Anhui 230027

Corresponding Author: yaoxb{at}ustc.edu.cn

Identification of protein phosphorylation sites with their cognate protein kinases (PKs) is a key step to delineate molecular dynamics and plasticity underlying a variety of cellular processes. Although nearly 10 kinase-specific prediction programs were developed, numerous PKs were casually classified into sub-groups without a standard rule. For large-scale predictions, the false positive rate (FPR) was also never addressed. In this work, we adopted a well-established rule to classify PKs into a hierarchical structure with four levels, including group, family, subfamily and single PK. In addition, we developed a simple approach to estimate the theoretically maximal FPRs. The online service and local packages of the GPS (Group-based Prediction System) 2.0 were implemented in JAVA, with the modified version of Group-based Phosphorylation Scoring algorithm. As the first stand-alone software for predicting phosphorylation, GPS2.0 can predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. A large-scale prediction of more than 13,000 mammalian phosphorylation sites by GPS2.0 was exhibited with great performance and remarkable accuracy. Using Aurora B as an example, we also conducted a proteome-wide search and provided systemic prediction of Aurora-B specific substrates including protein-protein interaction information. Thus, the GPS 2.0 is a useful tool for predicting protein phosphorylation sites and their cognate kinases, which is freely available at: http://bioinformatics.lcd-ustc.org/gps2.







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