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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...

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Detalles Bibliográficos
Autores principales: Cheung, Lennie KY, Yada, Rickey Y
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
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.
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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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