DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling

Summary: The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks. Here, FBA was applied on human lung cells infected with severe acute respiratory syndrom...

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Autores principales:	Ali Kishk, Maria Pires Pacheco, Thomas Sauter
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Virology Pharmaceutical science Bioinformatics Science Q
Acceso en línea:	https://doaj.org/article/d4b8d6e3557e45218daa87b84f6a4c37
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spelling	oai:doaj.org-article:d4b8d6e3557e45218daa87b84f6a4c372021-11-20T05:10:02ZDCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling2589-004210.1016/j.isci.2021.103331https://doaj.org/article/d4b8d6e3557e45218daa87b84f6a4c372021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2589004221013006https://doaj.org/toc/2589-0042Summary: The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks. Here, FBA was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the virus replication within the host tissue. Making use of expression datasets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then, host-specific essential genes and gene pairs were determined through in silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, ferroptosis, and pyrimidine metabolism. By in silico screening of Food and Drug Administration (FDA)-approved drugs on the putative disease-specific essential genes and gene pairs, 85 drugs and 52 drug combinations were predicted as promising candidates for COVID-19 (https://github.com/sysbiolux/DCcov).Ali KishkMaria Pires PachecoThomas SauterElsevierarticleVirologyPharmaceutical scienceBioinformaticsScienceQENiScience, Vol 24, Iss 11, Pp 103331- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Virology Pharmaceutical science Bioinformatics Science Q
spellingShingle	Virology Pharmaceutical science Bioinformatics Science Q Ali Kishk Maria Pires Pacheco Thomas Sauter DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling
description	Summary: The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks. Here, FBA was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the virus replication within the host tissue. Making use of expression datasets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then, host-specific essential genes and gene pairs were determined through in silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, ferroptosis, and pyrimidine metabolism. By in silico screening of Food and Drug Administration (FDA)-approved drugs on the putative disease-specific essential genes and gene pairs, 85 drugs and 52 drug combinations were predicted as promising candidates for COVID-19 (https://github.com/sysbiolux/DCcov).
format	article
author	Ali Kishk Maria Pires Pacheco Thomas Sauter
author_facet	Ali Kishk Maria Pires Pacheco Thomas Sauter
author_sort	Ali Kishk
title	DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling
title_short	DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling
title_full	DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling
title_fullStr	DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling
title_full_unstemmed	DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling
title_sort	dccov: repositioning of drugs and drug combinations for sars-cov-2 infected lung through constraint-based modeling
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/d4b8d6e3557e45218daa87b84f6a4c37
work_keys_str_mv	AT alikishk dccovrepositioningofdrugsanddrugcombinationsforsarscov2infectedlungthroughconstraintbasedmodeling AT mariapirespacheco dccovrepositioningofdrugsanddrugcombinationsforsarscov2infectedlungthroughconstraintbasedmodeling AT thomassauter dccovrepositioningofdrugsanddrugcombinationsforsarscov2infectedlungthroughconstraintbasedmodeling
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DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling

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