Identification of candidate repurposable drugs to combat COVID-19 using a signature-based approach.

Autor: O'Donovan SM; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Imami A; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Eby H; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Henkel ND; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Creeden JF; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Asah S; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Zhang X; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Wu X; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Alnafisah R; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA., Taylor RT; Department of Medical Microbiology and Immunology, University of Toledo, Toledo, OH, USA., Reigle J; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.; Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, OH, USA., Thorman A; Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, USA., Shamsaei B; Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, OH, USA., Meller J; Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.; Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.; Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, OH, USA.; Department of Electrical Engineering and Computing Systems, University of Cincinnati College of Medicine, Cincinnati, OH, USA.; Department of Informatics, Nicolaus Copernicus University, Torun, Poland., McCullumsmith RE; Department of Neurosciences, University of Toledo College of Medicine and Life Sciences, Health Science Campus, Mail Stop #1007, 3000 Arlington Avenue, Toledo, OH, 43614-2598, USA. Robert.mccullumsmith@utoledo.edu.; Neurosciences Institute, Promedica, Toledo, OH, USA. Robert.mccullumsmith@utoledo.edu.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2021 Feb 24; Vol. 11 (1), pp. 4495. Date of Electronic Publication: 2021 Feb 24.
DOI: 10.1038/s41598-021-84044-9
Abstrakt: The COVID-19 pandemic caused by the novel SARS-CoV-2 is more contagious than other coronaviruses and has higher rates of mortality than influenza. Identification of effective therapeutics is a crucial tool to treat those infected with SARS-CoV-2 and limit the spread of this novel disease globally. We deployed a bioinformatics workflow to identify candidate drugs for the treatment of COVID-19. Using an "omics" repository, the Library of Integrated Network-Based Cellular Signatures (LINCS), we simultaneously probed transcriptomic signatures of putative COVID-19 drugs and publicly available SARS-CoV-2 infected cell lines to identify novel therapeutics. We identified a shortlist of 20 candidate drugs: 8 are already under trial for the treatment of COVID-19, the remaining 12 have antiviral properties and 6 have antiviral efficacy against coronaviruses specifically, in vitro. All candidate drugs are either FDA approved or are under investigation. Our candidate drug findings are discordant with (i.e., reverse) SARS-CoV-2 transcriptome signatures generated in vitro, and a subset are also identified in transcriptome signatures generated from COVID-19 patient samples, like the MEK inhibitor selumetinib. Overall, our findings provide additional support for drugs that are already being explored as therapeutic agents for the treatment of COVID-19 and identify promising novel targets that are worthy of further investigation.
Databáze: MEDLINE
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