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

  • Sinead M O'Donovan
  • , Ali S Imami
  • , Hunter Eby
  • , Nicholas D Henkel
  • , Justin Fortune Creeden
  • , Sophie M Asah
  • , Xiaolu Zhang
  • , Xiaojun Wu
  • , Rawan Alnafisah
  • , R Travis Taylor
  • , James Reigle
  • , Alexander Thorman
  • , Behrouz Shamsaei
  • , Jarek Meller
  • , Robert E McCullumsmith

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number4495
Pages (from-to)4495
JournalScientific Reports
Volume11
Issue number1
DOIs
Publication statusPublished - Dec 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Antiviral Agents/pharmacology
  • COVID-19/genetics
  • Computational Biology/methods
  • Databases, Factual
  • Drug Discovery/methods
  • Drug Repositioning/methods
  • Humans
  • Pandemics
  • Pharmaceutical Preparations
  • SARS-CoV-2/drug effects
  • Transcriptome/drug effects
  • COVID-19 Drug Treatment

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