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Kinome-wide identification of phosphorylation networks in eukaryotic proteomes
MOTIVATION: Signaling and metabolic pathways are finely regulated by a network of protein phosphorylation events. Unraveling the nature of this intricate network, composed of kinases, target proteins and their interactions, is therefore of crucial importance. Although thousands of kinase-specific ph...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6361239/ https://www.ncbi.nlm.nih.gov/pubmed/30016513 http://dx.doi.org/10.1093/bioinformatics/bty545 |
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author | Parca, Luca Ariano, Bruno Cabibbo, Andrea Paoletti, Marco Tamburrini, Annalaura Palmeri, Antonio Ausiello, Gabriele Helmer-Citterich, Manuela |
author_facet | Parca, Luca Ariano, Bruno Cabibbo, Andrea Paoletti, Marco Tamburrini, Annalaura Palmeri, Antonio Ausiello, Gabriele Helmer-Citterich, Manuela |
author_sort | Parca, Luca |
collection | PubMed |
description | MOTIVATION: Signaling and metabolic pathways are finely regulated by a network of protein phosphorylation events. Unraveling the nature of this intricate network, composed of kinases, target proteins and their interactions, is therefore of crucial importance. Although thousands of kinase-specific phosphorylations (KsP) have been annotated in model organisms their kinase-target network is far from being complete, with less studied organisms lagging behind. RESULTS: In this work, we achieved an automated and accurate identification of kinase domains, inferring the residues that most likely contribute to peptide specificity. We integrated this information with the target peptides of known human KsP to predict kinase-specific interactions in other eukaryotes through a deep neural network, outperforming similar methods. We analyzed the differential conservation of kinase specificity among eukaryotes revealing the high conservation of the specificity of tyrosine kinases. With this approach we discovered 1590 novel KsP of potential clinical relevance in the human proteome. AVAILABILITY AND IMPLEMENTATION: http://akid.bio.uniroma2.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6361239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63612392019-02-08 Kinome-wide identification of phosphorylation networks in eukaryotic proteomes Parca, Luca Ariano, Bruno Cabibbo, Andrea Paoletti, Marco Tamburrini, Annalaura Palmeri, Antonio Ausiello, Gabriele Helmer-Citterich, Manuela Bioinformatics Original Papers MOTIVATION: Signaling and metabolic pathways are finely regulated by a network of protein phosphorylation events. Unraveling the nature of this intricate network, composed of kinases, target proteins and their interactions, is therefore of crucial importance. Although thousands of kinase-specific phosphorylations (KsP) have been annotated in model organisms their kinase-target network is far from being complete, with less studied organisms lagging behind. RESULTS: In this work, we achieved an automated and accurate identification of kinase domains, inferring the residues that most likely contribute to peptide specificity. We integrated this information with the target peptides of known human KsP to predict kinase-specific interactions in other eukaryotes through a deep neural network, outperforming similar methods. We analyzed the differential conservation of kinase specificity among eukaryotes revealing the high conservation of the specificity of tyrosine kinases. With this approach we discovered 1590 novel KsP of potential clinical relevance in the human proteome. AVAILABILITY AND IMPLEMENTATION: http://akid.bio.uniroma2.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-02-01 2018-07-17 /pmc/articles/PMC6361239/ /pubmed/30016513 http://dx.doi.org/10.1093/bioinformatics/bty545 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Parca, Luca Ariano, Bruno Cabibbo, Andrea Paoletti, Marco Tamburrini, Annalaura Palmeri, Antonio Ausiello, Gabriele Helmer-Citterich, Manuela Kinome-wide identification of phosphorylation networks in eukaryotic proteomes |
title | Kinome-wide identification of phosphorylation networks in eukaryotic proteomes |
title_full | Kinome-wide identification of phosphorylation networks in eukaryotic proteomes |
title_fullStr | Kinome-wide identification of phosphorylation networks in eukaryotic proteomes |
title_full_unstemmed | Kinome-wide identification of phosphorylation networks in eukaryotic proteomes |
title_short | Kinome-wide identification of phosphorylation networks in eukaryotic proteomes |
title_sort | kinome-wide identification of phosphorylation networks in eukaryotic proteomes |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6361239/ https://www.ncbi.nlm.nih.gov/pubmed/30016513 http://dx.doi.org/10.1093/bioinformatics/bty545 |
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