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确定对抗COVID-19的新药物治疗方法:一种使用iLINCS的基于特征的方法。

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

作者信息

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

机构信息

University of Toledo.

University of Cincinnati College of Medicine.

出版信息

Res Sq. 2020 Apr 30:rs.3.rs-25643. doi: 10.21203/rs.3.rs-25643/v1.

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.

摘要

由新型严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的2019冠状病毒病大流行比其他冠状病毒更具传染性,死亡率也高于流感。由于目前尚无专门批准用于治疗2019冠状病毒病的疫苗或药物,因此确定有效的治疗方法对于治疗患者和限制疾病传播至关重要。我们采用了一种生物信息学工作流程来确定治疗2019冠状病毒病的候选药物。利用一个“组学”数据库——基于网络的细胞特征综合文库(LINCS),我们同时探究了推定的2019冠状病毒病药物的转录组特征以及冠状病毒感染细胞系的特征,以分别确定具有一致特征和不一致特征的治疗方法。我们的研究结果包括三种已获美国食品药品监督管理局(FDA)批准且具有抗病毒活性的药物,其中包括蛋白激酶抑制剂,这为2019冠状病毒病干预措施提供了一类有前景的新候选药物。

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