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Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review
Scientific and consumer interest in healthy foods (also known as functional foods), nutraceuticals and cosmeceuticals has increased in the recent years, leading to an increased presence of these products in the market. However, the regulations across different countries that define the type of claim...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277569/ https://www.ncbi.nlm.nih.gov/pubmed/34258685 http://dx.doi.org/10.1007/s11030-021-10277-5 |
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author | Carpio, Laureano E. Sanz, Yolanda Gozalbes, Rafael Barigye, Stephen J. |
author_facet | Carpio, Laureano E. Sanz, Yolanda Gozalbes, Rafael Barigye, Stephen J. |
author_sort | Carpio, Laureano E. |
collection | PubMed |
description | Scientific and consumer interest in healthy foods (also known as functional foods), nutraceuticals and cosmeceuticals has increased in the recent years, leading to an increased presence of these products in the market. However, the regulations across different countries that define the type of claims that may be made, and the degree of evidence required to support these claims, are rather inconsistent. Moreover, there is also controversy on the effectiveness and biological mode of action of many of these products, which should undergo an exhaustive approval process to guarantee the consumer rights. Computational approaches constitute invaluable tools to facilitate the discovery of bioactive molecules and provide biological plausibility on the mode of action of these products. Indeed, methodologies like QSAR, docking or molecular dynamics have been used in drug discovery protocols for decades and can now aid in the discovery of bioactive food components. Thanks to these approaches, it is possible to search for new functions in food constituents, which may be part of our daily diet, and help to prevent disorders like diabetes, hypercholesterolemia or obesity. In the present manuscript, computational studies applied to this field are reviewed to illustrate the potential of these approaches to guide the first screening steps and the mechanistic studies of nutraceutical, cosmeceutical and functional foods. GRAPHICAL ABSTRACT: [Image: see text] |
format | Online Article Text |
id | pubmed-8277569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-82775692021-07-14 Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review Carpio, Laureano E. Sanz, Yolanda Gozalbes, Rafael Barigye, Stephen J. Mol Divers Original Article Scientific and consumer interest in healthy foods (also known as functional foods), nutraceuticals and cosmeceuticals has increased in the recent years, leading to an increased presence of these products in the market. However, the regulations across different countries that define the type of claims that may be made, and the degree of evidence required to support these claims, are rather inconsistent. Moreover, there is also controversy on the effectiveness and biological mode of action of many of these products, which should undergo an exhaustive approval process to guarantee the consumer rights. Computational approaches constitute invaluable tools to facilitate the discovery of bioactive molecules and provide biological plausibility on the mode of action of these products. Indeed, methodologies like QSAR, docking or molecular dynamics have been used in drug discovery protocols for decades and can now aid in the discovery of bioactive food components. Thanks to these approaches, it is possible to search for new functions in food constituents, which may be part of our daily diet, and help to prevent disorders like diabetes, hypercholesterolemia or obesity. In the present manuscript, computational studies applied to this field are reviewed to illustrate the potential of these approaches to guide the first screening steps and the mechanistic studies of nutraceutical, cosmeceutical and functional foods. GRAPHICAL ABSTRACT: [Image: see text] Springer International Publishing 2021-07-14 2021 /pmc/articles/PMC8277569/ /pubmed/34258685 http://dx.doi.org/10.1007/s11030-021-10277-5 Text en © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Carpio, Laureano E. Sanz, Yolanda Gozalbes, Rafael Barigye, Stephen J. Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review |
title | Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review |
title_full | Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review |
title_fullStr | Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review |
title_full_unstemmed | Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review |
title_short | Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review |
title_sort | computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277569/ https://www.ncbi.nlm.nih.gov/pubmed/34258685 http://dx.doi.org/10.1007/s11030-021-10277-5 |
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