论文标题
SARS-COV-2表达和衰老的因果网络模型，以识别药物重新利用的候选者
Causal Network Models of SARS-CoV-2 Expression and Aging to Identify Candidates for Drug Repurposing
论文作者
论文摘要
鉴于SARS-COV-2大流行的严重程度，一个主要的挑战是快速重新利用现有批准的临床干预药物。虽然在药物重新使用的背景下，已经提出了许多数据驱动和实验方法，但该平台系统地整合了可用的转录组，蛋白质组学和结构数据。更重要的是，鉴于SARS-COV-2的致病性高度依赖于年龄，因此将衰老的签名整合到药物发现平台中至关重要。在这里，我们利用大规模转录药物筛选以及与SARS-COV-2感染以及衰老肺的肺上皮的RNA-Seq数据相结合。为了识别可强大的可药蛋白靶标，我们提出了一种利用多种数据模式的原则因果框架。我们的分析强调了丝氨酸/苏氨酸和酪氨酸激酶作为与SARS-COV-2和衰老途径相交的潜在靶标的重要性。通过整合用于许多疾病的转录组，蛋白质组学和结构数据，我们的药物发现平台非常适用。需要进行严格的体外实验以及临床试验，以验证已确定的候选药物。
Given the severity of the SARS-CoV-2 pandemic, a major challenge is to rapidly repurpose existing approved drugs for clinical interventions. While a number of data-driven and experimental approaches have been suggested in the context of drug repurposing, a platform that systematically integrates available transcriptomic, proteomic and structural data is missing. More importantly, given that SARS-CoV-2 pathogenicity is highly age-dependent, it is critical to integrate aging signatures into drug discovery platforms. We here take advantage of large-scale transcriptional drug screens combined with RNA-seq data of the lung epithelium with SARS-CoV-2 infection as well as the aging lung. To identify robust druggable protein targets, we propose a principled causal framework that makes use of multiple data modalities. Our analysis highlights the importance of serine/threonine and tyrosine kinases as potential targets that intersect the SARS-CoV-2 and aging pathways. By integrating transcriptomic, proteomic and structural data that is available for many diseases, our drug discovery platform is broadly applicable. Rigorous in vitro experiments as well as clinical trials are needed to validate the identified candidate drugs.
