Maria Naomi I, Rapicavoli Rosaria Valentina, Alaimo Salvatore, Bischof Evelyne, Stasuzzo Alessia, Broek Jantine A C, Pulvirenti Alfredo, Mishra Bud, Duits Ashley J, Ferro Alfredo
Department of Computer Science, Mathematics, Engineering and Cell Biology, Courant Institute, Tandon and School of Medicine, New York University, New York, USA.
Institute of Molecular Medicine, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
Heliyon. 2023 Mar;9(3):e14115. doi: 10.1016/j.heliyon.2023.e14115. Epub 2023 Mar 6.
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 to 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 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.
当前迅速多样化的疫情加速了对高效识别新冠病毒潜在候选药物的需求。然而，关于宿主对新冠病毒感染的免疫反应的知识仍然有限，迄今获批的药物寥寥无几。为应对这一情况，可行的策略和工具正在迅速涌现，特别是现有药物的重新利用前景广阔。在此，我们介绍一种系统生物学工具——表型模拟器，它通过利用现有的转录组学和蛋白质组学数据库，能够对宿主细胞中的新冠病毒感染进行建模，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，从而产生特定的细胞新冠病毒特征，并利用这些细胞特异性特征来识别有前景的可重新利用的治疗方法。借助这一工具，结合专业领域知识，我们识别出了几种潜在的新冠治疗药物，包括甲泼尼龙和二甲双胍，并进一步识别出受新冠病毒影响的关键细胞途径，作为新冠发病机制中的潜在可药物作用靶点。
