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10.1038/s41598-021-91625-1

http://scihub22266oqcxt.onion/10.1038/s41598-021-91625-1
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34112877!8192542!34112877
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suck abstract from ncbi


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pmid34112877      Sci+Rep 2021 ; 11 (1): 12310
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  • Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19 #MMPMID34112877
  • Le BL; Andreoletti G; Oskotsky T; Vallejo-Gracia A; Rosales R; Yu K; Kosti I; Leon KE; Bunis DG; Li C; Kumar GR; White KM; Garcia-Sastre A; Ott M; Sirota M
  • Sci Rep 2021[Jun]; 11 (1): 12310 PMID34112877show ga
  • 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 16 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.
  • |*COVID-19 Drug Treatment[MESH]
  • |Antiviral Agents/*pharmacology[MESH]
  • |COVID-19/genetics[MESH]
  • |Computational Biology/methods[MESH]
  • |Drug Repositioning/*methods[MESH]
  • |Humans[MESH]
  • |SARS-CoV-2/*drug effects/physiology[MESH]


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