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A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection
SARS-CoV-2 is a novel coronavirus responsible for the COVID-19 pandemic, in which acute respiratory infections are associated with high socio-economic burden. We applied high-content screening to a well-defined collection of 5632 compounds including 3488 that have undergone previous clinical investi...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910569/ https://www.ncbi.nlm.nih.gov/pubmed/33637768 http://dx.doi.org/10.1038/s41597-021-00848-4 |
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author | Ellinger, Bernhard Bojkova, Denisa Zaliani, Andrea Cinatl, Jindrich Claussen, Carsten Westhaus, Sandra Keminer, Oliver Reinshagen, Jeanette Kuzikov, Maria Wolf, Markus Geisslinger, Gerd Gribbon, Philip Ciesek, Sandra |
author_facet | Ellinger, Bernhard Bojkova, Denisa Zaliani, Andrea Cinatl, Jindrich Claussen, Carsten Westhaus, Sandra Keminer, Oliver Reinshagen, Jeanette Kuzikov, Maria Wolf, Markus Geisslinger, Gerd Gribbon, Philip Ciesek, Sandra |
author_sort | Ellinger, Bernhard |
collection | PubMed |
description | SARS-CoV-2 is a novel coronavirus responsible for the COVID-19 pandemic, in which acute respiratory infections are associated with high socio-economic burden. We applied high-content screening to a well-defined collection of 5632 compounds including 3488 that have undergone previous clinical investigations across 600 indications. The compounds were screened by microscopy for their ability to inhibit SARS-CoV-2 cytopathicity in the human epithelial colorectal adenocarcinoma cell line, Caco-2. The primary screen identified 258 hits that inhibited cytopathicity by more than 75%, most of which were not previously known to be active against SARS-CoV-2 in vitro. These compounds were tested in an eight-point dose response screen using the same image-based cytopathicity readout. For the 67 most active molecules, cytotoxicity data were generated to confirm activity against SARS-CoV-2. We verified the ability of known inhibitors camostat, nafamostat, lopinavir, mefloquine, papaverine and cetylpyridinium to reduce the cytopathic effects of SARS-CoV-2, providing confidence in the validity of the assay. The high-content screening data are suitable for reanalysis across numerous drug classes and indications and may yield additional insights into SARS-CoV-2 mechanisms and potential therapeutic strategies. |
format | Online Article Text |
id | pubmed-7910569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79105692021-03-04 A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection Ellinger, Bernhard Bojkova, Denisa Zaliani, Andrea Cinatl, Jindrich Claussen, Carsten Westhaus, Sandra Keminer, Oliver Reinshagen, Jeanette Kuzikov, Maria Wolf, Markus Geisslinger, Gerd Gribbon, Philip Ciesek, Sandra Sci Data Data Descriptor SARS-CoV-2 is a novel coronavirus responsible for the COVID-19 pandemic, in which acute respiratory infections are associated with high socio-economic burden. We applied high-content screening to a well-defined collection of 5632 compounds including 3488 that have undergone previous clinical investigations across 600 indications. The compounds were screened by microscopy for their ability to inhibit SARS-CoV-2 cytopathicity in the human epithelial colorectal adenocarcinoma cell line, Caco-2. The primary screen identified 258 hits that inhibited cytopathicity by more than 75%, most of which were not previously known to be active against SARS-CoV-2 in vitro. These compounds were tested in an eight-point dose response screen using the same image-based cytopathicity readout. For the 67 most active molecules, cytotoxicity data were generated to confirm activity against SARS-CoV-2. We verified the ability of known inhibitors camostat, nafamostat, lopinavir, mefloquine, papaverine and cetylpyridinium to reduce the cytopathic effects of SARS-CoV-2, providing confidence in the validity of the assay. The high-content screening data are suitable for reanalysis across numerous drug classes and indications and may yield additional insights into SARS-CoV-2 mechanisms and potential therapeutic strategies. Nature Publishing Group UK 2021-02-26 /pmc/articles/PMC7910569/ /pubmed/33637768 http://dx.doi.org/10.1038/s41597-021-00848-4 Text en © The Author(s) 2021 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Ellinger, Bernhard Bojkova, Denisa Zaliani, Andrea Cinatl, Jindrich Claussen, Carsten Westhaus, Sandra Keminer, Oliver Reinshagen, Jeanette Kuzikov, Maria Wolf, Markus Geisslinger, Gerd Gribbon, Philip Ciesek, Sandra A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection |
title | A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection |
title_full | A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection |
title_fullStr | A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection |
title_full_unstemmed | A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection |
title_short | A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection |
title_sort | sars-cov-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910569/ https://www.ncbi.nlm.nih.gov/pubmed/33637768 http://dx.doi.org/10.1038/s41597-021-00848-4 |
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