Author ORCID Identifier
Document Type
Article
Publication Date
7-1-2014
Abstract
Phosphorylation of serine, threonine and tyrosine plays significant roles in cellular signal transduction and in modifying multiple protein functions. Phosphoproteins are coordinated and regulated by a network of kinases, phosphatases and phospho-binding proteins, which modify the phosphorylation states, recognize unique phosphopeptides, or target proteins for degradation. Detailed and complete information on the structure and dynamics of these networks is required to better understand fundamental mechanisms of cellular proceßes and diseases. High-throughput technologies have been developed to investigate phosphoproteomes in model organisms and human diseases. Among them, maß spectrometry (MS)-based technologies are the major platforms and have been widely applied, which has led to explosive growth of phosphoproteomic data in recent years. New bioinformatics tools are needed to analyze and make sense of these data. Moreover, most research has focused on individual phosphoproteins and kinases. To gain a more complete knowledge of cellular proceßes, systems biology approaches, including pathways and networks modeling, have to be applied to integrate all components of the phosphorylation machinery, including kinases, phosphatases, their substrates, and phospho-binding proteins. This reviewpresents the latest developments of bioinformaticsmethods and attempts to apply systems biology to analyze phosphoproteomics data generated by MS-based technologies. Challenges and future directions in this field will be also discussed.
Keywords
kinases, mass spectrometry, phosphatases, phospho-binding proteins, phospho-signaling networks, phosphoproteomics, phosphorylation network, systems biology
Language
97
Publication Title
Computational and Structural Biotechnology Journal
Grant
P30-CA-043703
Rights
© 2014 Liu and Chance. Published by Elsevier B.V. on behalf of the Research Network of Computational and Structural Biotechnology. This is anopenaccessarticle under the CC BY license (http://creativecommons.org/licenses/by/4.0/). You are free to copy, distribute and transmit the work, provided the original author and source are credited.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Yu Liu, Mark R. Chance, Integrating phosphoproteomics in systems biology, Computational and Structural Biotechnology Journal, Volume 10, Issue 17, 2014, Pages 90-97, ISSN 2001-0370, https://doi.org/10.1016/j.csbj.2014.07.003..
Manuscript Version
Final Publisher Version