Identification of New Drug Treatments to Combat COVID19: A Signature-based Approach Using ILINCS

Overview

Journal Res Sq

Date 2020 Jul 24

PMID 32702077

Authors

Sinead M ODonovan

Hunter Eby

Nicholas D Henkel

Justin Creeden

Ali Imami

Sophie Asah

Xiaolu Zhang

Xiaojun Wu

Rawan Alnafisah

R Travis Taylor

James Reigle

Alexander Thorman

Behrouz Shamsaei

Jarek Meller

Robert E McCullumsmith

Affiliations

Soon will be listed here.

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. As no vaccine or drugs are currently approved to specifically treat COVID-19, identification of effective therapeutics is crucial to treat the afflicted and limit disease spread. 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 signatures of coronavirus-infected cell lines to identify therapeutics with concordant signatures and discordant signatures, respectively. Our findings include three FDA approved drugs that have established antiviral activity, including protein kinase inhibitors, providing a promising new category of candidates for COVID-19 interventions.

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