Identification of new drug treatments to combat COVID19: A signature-based approach using iLINCS.

Autor:	O'Donovan SM; University of Toledo., Eby H; University of Toledo., Henkel ND; University of Toledo., Creeden J; University of Toledo., Imami A; University of Toledo., Asah S; University of Toledo., Zhang X; University of Toledo., Wu X; University of Toledo., Alnafisah R; University of Toledo., Taylor RT; University of Toledo., Reigle J; University of Cincinnati College of Medicine., Thorman A; University of Cincinnati College of Medicine., Shamsaei B; University of Cincinnati College of Medicine., Meller J; University of Cincinnati College of Medicine., McCullumsmith RE; University of Toledo College of Medicine and Life Sciences.
Jazyk:	angličtina
Zdroj:	Research square [Res Sq] 2020 Apr 30. Date of Electronic Publication: 2020 Apr 30.
DOI:	10.21203/rs.3.rs-25643/v1
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. 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. Competing Interests: Competing Interests: The authors have no conflicts to declare.
Databáze:	MEDLINE
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