Litcius/Paper detail

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

Sinead M. O’Donovan, Ali Sajid Imami, Hunter Eby, Nicholas Henkel, Justin F. Creeden, Sophie M. Asah, Xiaolu Zhang, Xiaojun Wu, Rawan Alnafisah, R. Travis Taylor, James Reigle, Alexander W. Thorman, Behrouz Shamsaei, Jarek Meller, Robert E. McCullumsmith

2021Scientific Reports34 citationsDOIOpen Access PDF

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.

Topics & Concepts

TranscriptomeCoronavirus disease 2019 (COVID-19)Drug repositioningComputational biologyPandemicIdentification (biology)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Drug discoveryDrugBioinformaticsMedicineBiologyDiseasePharmacologyGeneInfectious disease (medical specialty)GeneticsGene expressionPathologyBotanySARS-CoV-2 and COVID-19 ResearchCOVID-19 Clinical Research StudiesComputational Drug Discovery Methods