PDF(Pubmed)
Abstract：
The current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which -by leveraging available transcriptomic and proteomic databases-allows modeling of SARS-CoV-2 infection in host cells in silico to i) determine with high sensitivity and specificity (both>96%) the viral effects on cellular host-immune response, resulting in specific cellular SARS-CoV-2 signatures and ii) utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis.
摘要：
当前,迅速多样化的大流行加速了对有效和有效地识别COVID-19潜在候选药物的需求。对SARS-CoV-2感染的宿主免疫应答的知识，然而,仍然有限，迄今为止批准的药物很少。可行的战略和工具正在迅速出现，以解决这一问题，特别是对现有药物的再利用提供了重大的希望。这里我们介绍一个系统生物学工具，表型标志，通过利用可用的转录组学和蛋白质组学数据库，可以对宿主细胞中的SARS-CoV-2感染进行建模，以i）以高灵敏度和特异性（均>96％）确定病毒对细胞宿主免疫反应的影响，产生特定的细胞SARS-CoV-2特征，并且ii）利用这些细胞特异性特征来鉴定有希望的可再利用的疗法。在这个工具的推动下，加上领域专业知识，我们确定了几种潜在的COVID-19药物，包括甲泼尼龙和二甲双胍，并进一步将影响SARS-CoV-2的关键细胞途径识别为COVID-19发病机制的潜在药物靶标。
