1. Identification of new drug treatments to combat COVID19: A signature-based approach using iLINCS
- Author
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Hunter M. Eby, Xiaolu Zhang, Sinead M. O’Donovan, James Reigle, Rawan Alnafisah, Alexander William Thorman, Jarek Meller, Nicholas D. Henkel, Sophie Asah, Justin F. Creeden, Ali S Imami, Behrouz Shamsaei, Xiaojun Wu, R. Travis Taylor, and Robert E. McCullumsmith
- Subjects
Drug ,2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,business.industry ,media_common.quotation_subject ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Disease ,Computational biology ,Omics ,Article ,Pandemic ,Medicine ,Identification (biology) ,business ,media_common - 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.
- Published
- 2020