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Predicting global diet-disease relationships at the atomic level: a COVID-19 case study
Over the past few months, numerous studies harnessed in silico methods such as molecular docking to evaluate food compounds for inhibitory activity against coronavirus infection and replication. These studies capitalize on the efficiency of computational methods to quickly guide subsequent research...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8721929/ https://www.ncbi.nlm.nih.gov/pubmed/35004187 http://dx.doi.org/10.1016/j.cofs.2021.12.013 |
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author | Cheung, Lennie KY Yada, Rickey Y |
author_facet | Cheung, Lennie KY Yada, Rickey Y |
author_sort | Cheung, Lennie KY |
collection | PubMed |
description | Over the past few months, numerous studies harnessed in silico methods such as molecular docking to evaluate food compounds for inhibitory activity against coronavirus infection and replication. These studies capitalize on the efficiency of computational methods to quickly guide subsequent research and examine diet-disease relationships, and their sudden widespread utility may signal new opportunities for future antiviral and bioactive food research. Using Coronavirus Disease 2019 (COVID-19) research as a case study, we herein provide an overview of findings from studies using molecular docking to study food compounds as potential inhibitors of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), explore considerations for the critical interpretation of study findings, and discuss how these studies help shape larger conversations of diet and disease. |
format | Online Article Text |
id | pubmed-8721929 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87219292022-01-03 Predicting global diet-disease relationships at the atomic level: a COVID-19 case study Cheung, Lennie KY Yada, Rickey Y Curr Opin Food Sci Article Over the past few months, numerous studies harnessed in silico methods such as molecular docking to evaluate food compounds for inhibitory activity against coronavirus infection and replication. These studies capitalize on the efficiency of computational methods to quickly guide subsequent research and examine diet-disease relationships, and their sudden widespread utility may signal new opportunities for future antiviral and bioactive food research. Using Coronavirus Disease 2019 (COVID-19) research as a case study, we herein provide an overview of findings from studies using molecular docking to study food compounds as potential inhibitors of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), explore considerations for the critical interpretation of study findings, and discuss how these studies help shape larger conversations of diet and disease. Elsevier Ltd. 2022-04 2022-01-03 /pmc/articles/PMC8721929/ /pubmed/35004187 http://dx.doi.org/10.1016/j.cofs.2021.12.013 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Cheung, Lennie KY Yada, Rickey Y Predicting global diet-disease relationships at the atomic level: a COVID-19 case study |
title | Predicting global diet-disease relationships at the atomic level: a COVID-19 case study |
title_full | Predicting global diet-disease relationships at the atomic level: a COVID-19 case study |
title_fullStr | Predicting global diet-disease relationships at the atomic level: a COVID-19 case study |
title_full_unstemmed | Predicting global diet-disease relationships at the atomic level: a COVID-19 case study |
title_short | Predicting global diet-disease relationships at the atomic level: a COVID-19 case study |
title_sort | predicting global diet-disease relationships at the atomic level: a covid-19 case study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8721929/ https://www.ncbi.nlm.nih.gov/pubmed/35004187 http://dx.doi.org/10.1016/j.cofs.2021.12.013 |
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