Author: O’Donovan, Sinead M.; Imami, Ali; Eby, Hunter; Henkel, Nicholas D.; Creeden, Justin Fortune; Asah, Sophie; Zhang, Xiaolu; Wu, Xiaojun; Alnafisah, Rawan; Taylor, R. Travis; Reigle, James; Thorman, Alexander; Shamsaei, Behrouz; Meller, Jarek; McCullumsmith, Robert E.
Title: Identification of candidate repurposable drugs to combat COVID-19 using a signature-based approach Cord-id: h1o7m6l5 Document date: 2021_2_24
ID: h1o7m6l5
Snippet: 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
Document: 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.
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