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A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks
BACKGROUND: Abnormalities in glycan biosynthesis have been conclusively related to various diseases, whereas the complexity of the glycosylation process has impeded the quantitative analysis of biochemical experimental data for the identification of glycoforms contributing to disease. To overcome th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965717/ https://www.ncbi.nlm.nih.gov/pubmed/27454116 http://dx.doi.org/10.1186/s12859-016-1094-6 |
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author | Hou, Wenpin Qiu, Yushan Hashimoto, Nobuyuki Ching, Wai-Ki Aoki-Kinoshita, Kiyoko F. |
author_facet | Hou, Wenpin Qiu, Yushan Hashimoto, Nobuyuki Ching, Wai-Ki Aoki-Kinoshita, Kiyoko F. |
author_sort | Hou, Wenpin |
collection | PubMed |
description | BACKGROUND: Abnormalities in glycan biosynthesis have been conclusively related to various diseases, whereas the complexity of the glycosylation process has impeded the quantitative analysis of biochemical experimental data for the identification of glycoforms contributing to disease. To overcome this limitation, the automatic construction of glycosylation reaction networks in silico is a critical step. RESULTS: In this paper, a framework K2014 is developed to automatically construct N-glycosylation networks in MATLAB with the involvement of the 27 most-known enzyme reaction rules of 22 enzymes, as an extension of previous model KB2005. A toolbox named Glycosylation Network Analysis Toolbox (GNAT) is applied to define network properties systematically, including linkages, stereochemical specificity and reaction conditions of enzymes. Our network shows a strong ability to predict a wider range of glycans produced by the enzymes encountered in the Golgi Apparatus in human cell expression systems. CONCLUSIONS: Our results demonstrate a better understanding of the underlying glycosylation process and the potential of systems glycobiology tools for analyzing conventional biochemical or mass spectrometry-based experimental data quantitatively in a more realistic and practical way. |
format | Online Article Text |
id | pubmed-4965717 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49657172016-08-02 A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks Hou, Wenpin Qiu, Yushan Hashimoto, Nobuyuki Ching, Wai-Ki Aoki-Kinoshita, Kiyoko F. BMC Bioinformatics Research BACKGROUND: Abnormalities in glycan biosynthesis have been conclusively related to various diseases, whereas the complexity of the glycosylation process has impeded the quantitative analysis of biochemical experimental data for the identification of glycoforms contributing to disease. To overcome this limitation, the automatic construction of glycosylation reaction networks in silico is a critical step. RESULTS: In this paper, a framework K2014 is developed to automatically construct N-glycosylation networks in MATLAB with the involvement of the 27 most-known enzyme reaction rules of 22 enzymes, as an extension of previous model KB2005. A toolbox named Glycosylation Network Analysis Toolbox (GNAT) is applied to define network properties systematically, including linkages, stereochemical specificity and reaction conditions of enzymes. Our network shows a strong ability to predict a wider range of glycans produced by the enzymes encountered in the Golgi Apparatus in human cell expression systems. CONCLUSIONS: Our results demonstrate a better understanding of the underlying glycosylation process and the potential of systems glycobiology tools for analyzing conventional biochemical or mass spectrometry-based experimental data quantitatively in a more realistic and practical way. BioMed Central 2016-07-25 /pmc/articles/PMC4965717/ /pubmed/27454116 http://dx.doi.org/10.1186/s12859-016-1094-6 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the CreativeCommons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Hou, Wenpin Qiu, Yushan Hashimoto, Nobuyuki Ching, Wai-Ki Aoki-Kinoshita, Kiyoko F. A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks |
title | A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks |
title_full | A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks |
title_fullStr | A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks |
title_full_unstemmed | A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks |
title_short | A systematic framework to derive N-glycan biosynthesis process and the automated construction of glycosylation networks |
title_sort | systematic framework to derive n-glycan biosynthesis process and the automated construction of glycosylation networks |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965717/ https://www.ncbi.nlm.nih.gov/pubmed/27454116 http://dx.doi.org/10.1186/s12859-016-1094-6 |
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