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Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19

While establishing worldwide collective immunity with anti SARS-CoV-2 vaccines, COVID-19 remains a major health issue with dramatic ensuing economic consequences. In the transition, repurposing existing drugs remains the fastest cost-effective approach to alleviate the burden on health services, mos...

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Autores principales: Desvaux, Emiko, Hamon, Antoine, Hubert, Sandra, Boudjeniba, Cheïma, Chassagnol, Bastien, Swindle, Jack, Aussy, Audrey, Laigle, Laurence, Laplume, Jessica, Soret, Perrine, Jean-François, Pierre, Dupin-Roger, Isabelle, Guedj, Mickaël, Moingeon, Philippe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297899/
https://www.ncbi.nlm.nih.gov/pubmed/34293006
http://dx.doi.org/10.1371/journal.pone.0254374
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author Desvaux, Emiko
Hamon, Antoine
Hubert, Sandra
Boudjeniba, Cheïma
Chassagnol, Bastien
Swindle, Jack
Aussy, Audrey
Laigle, Laurence
Laplume, Jessica
Soret, Perrine
Jean-François, Pierre
Dupin-Roger, Isabelle
Guedj, Mickaël
Moingeon, Philippe
author_facet Desvaux, Emiko
Hamon, Antoine
Hubert, Sandra
Boudjeniba, Cheïma
Chassagnol, Bastien
Swindle, Jack
Aussy, Audrey
Laigle, Laurence
Laplume, Jessica
Soret, Perrine
Jean-François, Pierre
Dupin-Roger, Isabelle
Guedj, Mickaël
Moingeon, Philippe
author_sort Desvaux, Emiko
collection PubMed
description While establishing worldwide collective immunity with anti SARS-CoV-2 vaccines, COVID-19 remains a major health issue with dramatic ensuing economic consequences. In the transition, repurposing existing drugs remains the fastest cost-effective approach to alleviate the burden on health services, most particularly by reducing the incidence of the acute respiratory distress syndrome associated with severe COVID-19. We undertook a computational repurposing approach to identify candidate therapeutic drugs to control progression towards severe airways inflammation during COVID-19. Molecular profiling data were obtained from public sources regarding SARS-CoV-2 infected epithelial or endothelial cells, immune dysregulations associated with severe COVID-19 and lung inflammation induced by other respiratory viruses. From these data, we generated a protein-protein interactome modeling the evolution of lung inflammation during COVID-19 from inception to an established cytokine release syndrome. This predictive model assembling severe COVID-19-related proteins supports a role for known contributors to the cytokine storm such as IL1β, IL6, TNFα, JAK2, but also less prominent actors such as IL17, IL23 and C5a. Importantly our analysis points out to alarmins such as TSLP, IL33, members of the S100 family and their receptors (ST2, RAGE) as targets of major therapeutic interest. By evaluating the network-based distances between severe COVID-19-related proteins and known drug targets, network computing identified drugs which could be repurposed to prevent or slow down progression towards severe airways inflammation. This analysis confirmed the interest of dexamethasone, JAK2 inhibitors, estrogens and further identified various drugs either available or in development interacting with the aforementioned targets. We most particularly recommend considering various inhibitors of alarmins or their receptors, currently receiving little attention in this indication, as candidate treatments for severe COVID-19.
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spelling pubmed-82978992021-07-31 Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19 Desvaux, Emiko Hamon, Antoine Hubert, Sandra Boudjeniba, Cheïma Chassagnol, Bastien Swindle, Jack Aussy, Audrey Laigle, Laurence Laplume, Jessica Soret, Perrine Jean-François, Pierre Dupin-Roger, Isabelle Guedj, Mickaël Moingeon, Philippe PLoS One Research Article While establishing worldwide collective immunity with anti SARS-CoV-2 vaccines, COVID-19 remains a major health issue with dramatic ensuing economic consequences. In the transition, repurposing existing drugs remains the fastest cost-effective approach to alleviate the burden on health services, most particularly by reducing the incidence of the acute respiratory distress syndrome associated with severe COVID-19. We undertook a computational repurposing approach to identify candidate therapeutic drugs to control progression towards severe airways inflammation during COVID-19. Molecular profiling data were obtained from public sources regarding SARS-CoV-2 infected epithelial or endothelial cells, immune dysregulations associated with severe COVID-19 and lung inflammation induced by other respiratory viruses. From these data, we generated a protein-protein interactome modeling the evolution of lung inflammation during COVID-19 from inception to an established cytokine release syndrome. This predictive model assembling severe COVID-19-related proteins supports a role for known contributors to the cytokine storm such as IL1β, IL6, TNFα, JAK2, but also less prominent actors such as IL17, IL23 and C5a. Importantly our analysis points out to alarmins such as TSLP, IL33, members of the S100 family and their receptors (ST2, RAGE) as targets of major therapeutic interest. By evaluating the network-based distances between severe COVID-19-related proteins and known drug targets, network computing identified drugs which could be repurposed to prevent or slow down progression towards severe airways inflammation. This analysis confirmed the interest of dexamethasone, JAK2 inhibitors, estrogens and further identified various drugs either available or in development interacting with the aforementioned targets. We most particularly recommend considering various inhibitors of alarmins or their receptors, currently receiving little attention in this indication, as candidate treatments for severe COVID-19. Public Library of Science 2021-07-22 /pmc/articles/PMC8297899/ /pubmed/34293006 http://dx.doi.org/10.1371/journal.pone.0254374 Text en © 2021 Desvaux et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Desvaux, Emiko
Hamon, Antoine
Hubert, Sandra
Boudjeniba, Cheïma
Chassagnol, Bastien
Swindle, Jack
Aussy, Audrey
Laigle, Laurence
Laplume, Jessica
Soret, Perrine
Jean-François, Pierre
Dupin-Roger, Isabelle
Guedj, Mickaël
Moingeon, Philippe
Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19
title Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19
title_full Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19
title_fullStr Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19
title_full_unstemmed Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19
title_short Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19
title_sort network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in covid-19
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297899/
https://www.ncbi.nlm.nih.gov/pubmed/34293006
http://dx.doi.org/10.1371/journal.pone.0254374
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