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Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data

Cascades of phosphorylation between protein kinases comprise a core mechanism in the integration and propagation of intracellular signals. Although we have accumulated a wealth of knowledge around some such pathways, this is subject to study biases and much remains to be uncovered. Phosphoproteomics...

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Detalles Bibliográficos
Autores principales: Invergo, Brandon M., Beltrao, Pedro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6204553/
https://www.ncbi.nlm.nih.gov/pubmed/30072490
http://dx.doi.org/10.1042/EBC20180019
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author Invergo, Brandon M.
Beltrao, Pedro
author_facet Invergo, Brandon M.
Beltrao, Pedro
author_sort Invergo, Brandon M.
collection PubMed
description Cascades of phosphorylation between protein kinases comprise a core mechanism in the integration and propagation of intracellular signals. Although we have accumulated a wealth of knowledge around some such pathways, this is subject to study biases and much remains to be uncovered. Phosphoproteomics, the identification and quantification of phosphorylated proteins on a proteomic scale, provides a high-throughput means of interrogating the state of intracellular phosphorylation, both at the pathway level and at the whole-cell level. In this review, we discuss methods for using human quantitative phosphoproteomic data to reconstruct the underlying signalling networks that generated it. We address several challenges imposed by the data on such analyses and we consider promising advances towards reconstructing unbiased, kinome-scale signalling networks.
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spelling pubmed-62045532018-11-05 Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data Invergo, Brandon M. Beltrao, Pedro Essays Biochem Review Articles Cascades of phosphorylation between protein kinases comprise a core mechanism in the integration and propagation of intracellular signals. Although we have accumulated a wealth of knowledge around some such pathways, this is subject to study biases and much remains to be uncovered. Phosphoproteomics, the identification and quantification of phosphorylated proteins on a proteomic scale, provides a high-throughput means of interrogating the state of intracellular phosphorylation, both at the pathway level and at the whole-cell level. In this review, we discuss methods for using human quantitative phosphoproteomic data to reconstruct the underlying signalling networks that generated it. We address several challenges imposed by the data on such analyses and we consider promising advances towards reconstructing unbiased, kinome-scale signalling networks. Portland Press Ltd. 2018-08-02 /pmc/articles/PMC6204553/ /pubmed/30072490 http://dx.doi.org/10.1042/EBC20180019 Text en © 2018 The Author(s). http://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review Articles
Invergo, Brandon M.
Beltrao, Pedro
Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data
title Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data
title_full Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data
title_fullStr Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data
title_full_unstemmed Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data
title_short Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data
title_sort reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6204553/
https://www.ncbi.nlm.nih.gov/pubmed/30072490
http://dx.doi.org/10.1042/EBC20180019
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