Treffer: GPS 2.0, a tool to predict kinase-specific phosphorylation sites in hierarchy.

Title:
GPS 2.0, a tool to predict kinase-specific phosphorylation sites in hierarchy.
Authors:
Xue Y; Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230027, China., Ren J, Gao X, Jin C, Wen L, Yao X
Source:
Molecular & cellular proteomics : MCP [Mol Cell Proteomics] 2008 Sep; Vol. 7 (9), pp. 1598-608. Date of Electronic Publication: 2008 May 06.
Publication Type:
Evaluation Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Elsevier Inc. on behalf of American Society for Biochemistry and Molecular Biology Country of Publication: United States NLM ID: 101125647 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1535-9484 (Electronic) Linking ISSN: 15359476 NLM ISO Abbreviation: Mol Cell Proteomics Subsets: MEDLINE
Imprint Name(s):
Publication: 2021- : [New York, NY] : Elsevier Inc. on behalf of American Society for Biochemistry and Molecular Biology
Original Publication: Bethesda, MD : American Society for Biochemistry and Molecular Biology, [2002-
MeSH Terms:
Protein Processing, Post-Translational* , Software Design* , Software Validation*, Cyclic AMP-Dependent Protein Kinases/*metabolism , Proteome/*metabolism, Algorithms ; Amino Acid Sequence ; Aurora Kinase B ; Aurora Kinases ; Humans ; Molecular Sequence Data ; Phosphorylation ; Protein Serine-Threonine Kinases/metabolism
References:
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Grant Information:
R01 DK056292 United States DK NIDDK NIH HHS; DK56292 United States DK NIDDK NIH HHS
Substance Nomenclature:
0 (Proteome)
EC 2.7.11.1 (AURKB protein, human)
EC 2.7.11.1 (Aurora Kinase B)
EC 2.7.11.1 (Aurora Kinases)
EC 2.7.11.1 (Protein Serine-Threonine Kinases)
EC 2.7.11.11 (Cyclic AMP-Dependent Protein Kinases)
Entry Date(s):
Date Created: 20080509 Date Completed: 20080930 Latest Revision: 20220316
Update Code:
20250114
PubMed Central ID:
PMC2528073
DOI:
10.1074/mcp.M700574-MCP200
PMID:
18463090
Database:
MEDLINE

Weitere Informationen

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 have been developed, numerous PKs have been casually classified into subgroups without a standard rule. For large scale predictions, the false positive rate has also never been 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 false positive rates. The on-line service and local packages of the GPS (Group-based Prediction System) 2.0 were implemented in Java with the modified version of the Group-based Phosphorylation Scoring algorithm. As the first stand alone software for predicting phosphorylation, GPS 2.0 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 GPS 2.0 was exhibited with great performance and remarkable accuracy. Using Aurora-B as an example, we also conducted a proteome-wide search and provided systematic 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 and is freely available on line.