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A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases
The involvement of vitamins and other micronutrients in intermediary metabolism was elucidated in the mid 1900’s at the level of individual biochemical reactions. Biochemical pathways remain the foundational knowledgebase for understanding how micronutrient adequacy modulates health in all life stag...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726080/ https://www.ncbi.nlm.nih.gov/pubmed/26777674 http://dx.doi.org/10.1038/srep19633 |
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author | Scott-Boyer, Marie Pier Lacroix, Sébastien Scotti, Marco Morine, Melissa J. Kaput, Jim Priami, Corrado |
author_facet | Scott-Boyer, Marie Pier Lacroix, Sébastien Scotti, Marco Morine, Melissa J. Kaput, Jim Priami, Corrado |
author_sort | Scott-Boyer, Marie Pier |
collection | PubMed |
description | The involvement of vitamins and other micronutrients in intermediary metabolism was elucidated in the mid 1900’s at the level of individual biochemical reactions. Biochemical pathways remain the foundational knowledgebase for understanding how micronutrient adequacy modulates health in all life stages. Current daily recommended intakes were usually established on the basis of the association of a single nutrient to a single, most sensitive adverse effect and thus neglect interdependent and pleiotropic effects of micronutrients on biological systems. Hence, the understanding of the impact of overt or sub-clinical nutrient deficiencies on biological processes remains incomplete. Developing a more complete view of the role of micronutrients and their metabolic products in protein-mediated reactions is of importance. We thus integrated and represented cofactor-protein interaction data from multiple and diverse sources into a multi-layer network representation that links cofactors, cofactor-interacting proteins, biological processes, and diseases. Network representation of this information is a key feature of the present analysis and enables the integration of data from individual biochemical reactions and protein-protein interactions into a systems view, which may guide strategies for targeted nutritional interventions aimed at improving health and preventing diseases. |
format | Online Article Text |
id | pubmed-4726080 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47260802016-01-27 A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases Scott-Boyer, Marie Pier Lacroix, Sébastien Scotti, Marco Morine, Melissa J. Kaput, Jim Priami, Corrado Sci Rep Article The involvement of vitamins and other micronutrients in intermediary metabolism was elucidated in the mid 1900’s at the level of individual biochemical reactions. Biochemical pathways remain the foundational knowledgebase for understanding how micronutrient adequacy modulates health in all life stages. Current daily recommended intakes were usually established on the basis of the association of a single nutrient to a single, most sensitive adverse effect and thus neglect interdependent and pleiotropic effects of micronutrients on biological systems. Hence, the understanding of the impact of overt or sub-clinical nutrient deficiencies on biological processes remains incomplete. Developing a more complete view of the role of micronutrients and their metabolic products in protein-mediated reactions is of importance. We thus integrated and represented cofactor-protein interaction data from multiple and diverse sources into a multi-layer network representation that links cofactors, cofactor-interacting proteins, biological processes, and diseases. Network representation of this information is a key feature of the present analysis and enables the integration of data from individual biochemical reactions and protein-protein interactions into a systems view, which may guide strategies for targeted nutritional interventions aimed at improving health and preventing diseases. Nature Publishing Group 2016-01-18 /pmc/articles/PMC4726080/ /pubmed/26777674 http://dx.doi.org/10.1038/srep19633 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Scott-Boyer, Marie Pier Lacroix, Sébastien Scotti, Marco Morine, Melissa J. Kaput, Jim Priami, Corrado A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases |
title | A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases |
title_full | A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases |
title_fullStr | A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases |
title_full_unstemmed | A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases |
title_short | A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases |
title_sort | network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726080/ https://www.ncbi.nlm.nih.gov/pubmed/26777674 http://dx.doi.org/10.1038/srep19633 |
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