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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...

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Autores principales: Parca, Luca, Ariano, Bruno, Cabibbo, Andrea, Paoletti, Marco, Tamburrini, Annalaura, Palmeri, Antonio, Ausiello, Gabriele, Helmer-Citterich, Manuela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
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.
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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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