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.
【저자키워드】 Drug discovery, Virtual drug screening, 【초록키워드】 COVID-19, Treatment, Transcriptome, SARS-CoV-2, coronavirus, Mortality, Trial, Influenza, COVID-19 pandemic, bioinformatics, drug, in vitro, FDA, Spread, antiviral efficacy, target, therapeutic agent, therapeutic agents, disease, antiviral property, COVID-19 patient, identification, Support, Repository, selumetinib, treatment of COVID-19, other coronaviruses, antiviral properties, treat, signature, candidate drugs, library, MEK inhibitor, shortlist, contagious, infected cell, transcriptomic, effective, limit, SARS-CoV-2 transcriptome, identify, caused, approved, other coronavirus, subset, candidate drug, infected with SARS-CoV-2, 【제목키워드】 COVID-19, drug, identification, approach,