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Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry

BACKGROUND: Vaccination programs have been launched worldwide to halt the spread of COVID-19. However, the identification of existing, safe compounds with combined treatment and prophylactic properties would be beneficial to individuals who are waiting to be vaccinated, particularly in less economic...

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Autores principales: Duarte, Rodrigo R. R., Copertino, Dennis C., Iñiguez, Luis P., Marston, Jez L., Bram, Yaron, Han, Yuling, Schwartz, Robert E., Chen, Shuibing, Nixon, Douglas F., Powell, Timothy R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426591/
https://www.ncbi.nlm.nih.gov/pubmed/34503440
http://dx.doi.org/10.1186/s10020-021-00356-6
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author Duarte, Rodrigo R. R.
Copertino, Dennis C.
Iñiguez, Luis P.
Marston, Jez L.
Bram, Yaron
Han, Yuling
Schwartz, Robert E.
Chen, Shuibing
Nixon, Douglas F.
Powell, Timothy R.
author_facet Duarte, Rodrigo R. R.
Copertino, Dennis C.
Iñiguez, Luis P.
Marston, Jez L.
Bram, Yaron
Han, Yuling
Schwartz, Robert E.
Chen, Shuibing
Nixon, Douglas F.
Powell, Timothy R.
author_sort Duarte, Rodrigo R. R.
collection PubMed
description BACKGROUND: Vaccination programs have been launched worldwide to halt the spread of COVID-19. However, the identification of existing, safe compounds with combined treatment and prophylactic properties would be beneficial to individuals who are waiting to be vaccinated, particularly in less economically developed countries, where vaccine availability may be initially limited. METHODS: We used a data-driven approach, combining results from the screening of a large transcriptomic database (L1000) and molecular docking analyses, with in vitro tests using a lung organoid model of SARS-CoV-2 entry, to identify drugs with putative multimodal properties against COVID-19. RESULTS: Out of thousands of FDA-approved drugs considered, we observed that atorvastatin was the most promising candidate, as its effects negatively correlated with the transcriptional changes associated with infection. Atorvastatin was further predicted to bind to SARS-CoV-2’s main protease and RNA-dependent RNA polymerase, and was shown to inhibit viral entry in our lung organoid model. CONCLUSIONS: Small clinical studies reported that general statin use, and specifically, atorvastatin use, are associated with protective effects against COVID-19. Our study corroborrates these findings and supports the investigation of atorvastatin in larger clinical studies. Ultimately, our framework demonstrates one promising way to fast-track the identification of compounds for COVID-19, which could similarly be applied when tackling future pandemics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s10020-021-00356-6.
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spelling pubmed-84265912021-09-09 Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry Duarte, Rodrigo R. R. Copertino, Dennis C. Iñiguez, Luis P. Marston, Jez L. Bram, Yaron Han, Yuling Schwartz, Robert E. Chen, Shuibing Nixon, Douglas F. Powell, Timothy R. Mol Med Research Article BACKGROUND: Vaccination programs have been launched worldwide to halt the spread of COVID-19. However, the identification of existing, safe compounds with combined treatment and prophylactic properties would be beneficial to individuals who are waiting to be vaccinated, particularly in less economically developed countries, where vaccine availability may be initially limited. METHODS: We used a data-driven approach, combining results from the screening of a large transcriptomic database (L1000) and molecular docking analyses, with in vitro tests using a lung organoid model of SARS-CoV-2 entry, to identify drugs with putative multimodal properties against COVID-19. RESULTS: Out of thousands of FDA-approved drugs considered, we observed that atorvastatin was the most promising candidate, as its effects negatively correlated with the transcriptional changes associated with infection. Atorvastatin was further predicted to bind to SARS-CoV-2’s main protease and RNA-dependent RNA polymerase, and was shown to inhibit viral entry in our lung organoid model. CONCLUSIONS: Small clinical studies reported that general statin use, and specifically, atorvastatin use, are associated with protective effects against COVID-19. Our study corroborrates these findings and supports the investigation of atorvastatin in larger clinical studies. Ultimately, our framework demonstrates one promising way to fast-track the identification of compounds for COVID-19, which could similarly be applied when tackling future pandemics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s10020-021-00356-6. BioMed Central 2021-09-09 /pmc/articles/PMC8426591/ /pubmed/34503440 http://dx.doi.org/10.1186/s10020-021-00356-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Research Article
Duarte, Rodrigo R. R.
Copertino, Dennis C.
Iñiguez, Luis P.
Marston, Jez L.
Bram, Yaron
Han, Yuling
Schwartz, Robert E.
Chen, Shuibing
Nixon, Douglas F.
Powell, Timothy R.
Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry
title Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry
title_full Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry
title_fullStr Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry
title_full_unstemmed Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry
title_short Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry
title_sort identifying fda-approved drugs with multimodal properties against covid-19 using a data-driven approach and a lung organoid model of sars-cov-2 entry
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426591/
https://www.ncbi.nlm.nih.gov/pubmed/34503440
http://dx.doi.org/10.1186/s10020-021-00356-6
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