Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19.
Journal
Research square
Titre abrégé: Res Sq
Pays: United States
ID NLM: 101768035
Informations de publication
Date de publication:
30 Mar 2021
30 Mar 2021
Historique:
entrez:
6
4
2021
pubmed:
7
4
2021
medline:
7
4
2021
Statut:
epublish
Résumé
The novel SARS-CoV-2 virus emerged in December 2019 and has few effective treatments. We applied a computational drug repositioning pipeline to SARS-CoV-2 differential gene expression signatures derived from publicly available data. We utilized three independent published studies to acquire or generate lists of differentially expressed genes between control and SARS-CoV-2-infected samples. Using a rank-based pattern matching strategy based on the Kolmogorov-Smirnov Statistic, the signatures were queried against drug profiles from Connectivity Map (CMap). We validated sixteen of our top predicted hits in live SARS-CoV-2 antiviral assays in either Calu-3 or 293T-ACE2 cells. Validation experiments in human cell lines showed that 11 of the 16 compounds tested to date (including clofazimine, haloperidol and others) had measurable antiviral activity against SARS-CoV-2. These initial results are encouraging as we continue to work towards a further analysis of these predicted drugs as potential therapeutics for the treatment of COVID-19.
Identifiants
pubmed: 33821262
doi: 10.21203/rs.3.rs-333578/v1
pmc: PMC8020993
pii:
doi:
Types de publication
Preprint
Langues
eng
Subventions
Organisme : NIGMS NIH HHS
ID : T32 GM007618
Pays : United States
Commentaires et corrections
Type : UpdateIn
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