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A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19
In this study we have developed a method based on Flux Balance Analysis to identify human metabolic enzymes which can be targeted for therapeutic intervention against COVID-19. A literature search was carried out in order to identify suitable inhibitors of these enzymes, which were confirmed by dock...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184994/ https://www.ncbi.nlm.nih.gov/pubmed/34099831 http://dx.doi.org/10.1038/s41598-021-91526-3 |
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author | Santos-Beneit, Fernando Raškevičius, Vytautas Skeberdis, Vytenis A. Bordel, Sergio |
author_facet | Santos-Beneit, Fernando Raškevičius, Vytautas Skeberdis, Vytenis A. Bordel, Sergio |
author_sort | Santos-Beneit, Fernando |
collection | PubMed |
description | In this study we have developed a method based on Flux Balance Analysis to identify human metabolic enzymes which can be targeted for therapeutic intervention against COVID-19. A literature search was carried out in order to identify suitable inhibitors of these enzymes, which were confirmed by docking calculations. In total, 10 targets and 12 bioactive molecules have been predicted. Among the most promising molecules we identified Triacsin C, which inhibits ACSL3, and which has been shown to be very effective against different viruses, including positive-sense single-stranded RNA viruses. Similarly, we also identified the drug Celgosivir, which has been successfully tested in cells infected with different types of viruses such as Dengue, Zika, Hepatitis C and Influenza. Finally, other drugs targeting enzymes of lipid metabolism, carbohydrate metabolism or protein palmitoylation (such as Propylthiouracil, 2-Bromopalmitate, Lipofermata, Tunicamycin, Benzyl Isothiocyanate, Tipifarnib and Lonafarnib) are also proposed. |
format | Online Article Text |
id | pubmed-8184994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81849942021-06-08 A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19 Santos-Beneit, Fernando Raškevičius, Vytautas Skeberdis, Vytenis A. Bordel, Sergio Sci Rep Article In this study we have developed a method based on Flux Balance Analysis to identify human metabolic enzymes which can be targeted for therapeutic intervention against COVID-19. A literature search was carried out in order to identify suitable inhibitors of these enzymes, which were confirmed by docking calculations. In total, 10 targets and 12 bioactive molecules have been predicted. Among the most promising molecules we identified Triacsin C, which inhibits ACSL3, and which has been shown to be very effective against different viruses, including positive-sense single-stranded RNA viruses. Similarly, we also identified the drug Celgosivir, which has been successfully tested in cells infected with different types of viruses such as Dengue, Zika, Hepatitis C and Influenza. Finally, other drugs targeting enzymes of lipid metabolism, carbohydrate metabolism or protein palmitoylation (such as Propylthiouracil, 2-Bromopalmitate, Lipofermata, Tunicamycin, Benzyl Isothiocyanate, Tipifarnib and Lonafarnib) are also proposed. Nature Publishing Group UK 2021-06-07 /pmc/articles/PMC8184994/ /pubmed/34099831 http://dx.doi.org/10.1038/s41598-021-91526-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Santos-Beneit, Fernando Raškevičius, Vytautas Skeberdis, Vytenis A. Bordel, Sergio A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19 |
title | A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19 |
title_full | A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19 |
title_fullStr | A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19 |
title_full_unstemmed | A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19 |
title_short | A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19 |
title_sort | metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184994/ https://www.ncbi.nlm.nih.gov/pubmed/34099831 http://dx.doi.org/10.1038/s41598-021-91526-3 |
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