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Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data

As of today (7 April 2020), more than 81,000 people around the world have died from the coronavirus disease 19 (COVID-19) pandemic. There is no approved drug or vaccine for COVID-19, although more than 10 clinical trials have been launched to test potential drugs. In an urgent response to this pande...

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Autor principal: Alakwaa, Fadhl M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7159901/
https://www.ncbi.nlm.nih.gov/pubmed/32291351
http://dx.doi.org/10.1128/mSystems.00297-20
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author Alakwaa, Fadhl M.
author_facet Alakwaa, Fadhl M.
author_sort Alakwaa, Fadhl M.
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description As of today (7 April 2020), more than 81,000 people around the world have died from the coronavirus disease 19 (COVID-19) pandemic. There is no approved drug or vaccine for COVID-19, although more than 10 clinical trials have been launched to test potential drugs. In an urgent response to this pandemic, I developed a bioinformatics pipeline to identify compounds and drug candidates to potentially treat COVID-19. This pipeline is based on publicly available single-cell RNA sequencing (scRNA-seq) data and the drug perturbation database “Library of Integrated Network-Based Cellular Signatures” (LINCS). I developed a ranking score system that prioritizes these drugs or small molecules. The four drugs with the highest total score are didanosine, benzyl-quinazolin-4-yl-amine, camptothecin, and RO-90-7501. In conclusion, I have demonstrated the utility of bioinformatics for identifying drugs than can be repurposed for potentially treating COVID-19 patients.
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spelling pubmed-71599012020-04-20 Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data Alakwaa, Fadhl M. mSystems Opinion/Hypothesis As of today (7 April 2020), more than 81,000 people around the world have died from the coronavirus disease 19 (COVID-19) pandemic. There is no approved drug or vaccine for COVID-19, although more than 10 clinical trials have been launched to test potential drugs. In an urgent response to this pandemic, I developed a bioinformatics pipeline to identify compounds and drug candidates to potentially treat COVID-19. This pipeline is based on publicly available single-cell RNA sequencing (scRNA-seq) data and the drug perturbation database “Library of Integrated Network-Based Cellular Signatures” (LINCS). I developed a ranking score system that prioritizes these drugs or small molecules. The four drugs with the highest total score are didanosine, benzyl-quinazolin-4-yl-amine, camptothecin, and RO-90-7501. In conclusion, I have demonstrated the utility of bioinformatics for identifying drugs than can be repurposed for potentially treating COVID-19 patients. American Society for Microbiology 2020-04-14 /pmc/articles/PMC7159901/ /pubmed/32291351 http://dx.doi.org/10.1128/mSystems.00297-20 Text en Copyright © 2020 Alakwaa. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Opinion/Hypothesis
Alakwaa, Fadhl M.
Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data
title Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data
title_full Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data
title_fullStr Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data
title_full_unstemmed Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data
title_short Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data
title_sort repurposing didanosine as a potential treatment for covid-19 using single-cell rna sequencing data
topic Opinion/Hypothesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7159901/
https://www.ncbi.nlm.nih.gov/pubmed/32291351
http://dx.doi.org/10.1128/mSystems.00297-20
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