PDF(Pubmed)
Abstract：
Background: Coronavirus (CoV) is an emerging human pathogen causing severe acute respiratory syndrome (SARS) around the world. Earlier identification of biomarkers for SARS can facilitate detection and reduce the mortality rate of the disease. Thus, by integrated network analysis and structural modeling approach, we aimed to explore the potential drug targets and the candidate drugs for coronavirus medicated SARS. Methods: Differentially expression (DE) analysis of CoV infected host genes (HGs) expression profiles was conducted by using the Limma. Highly integrated DE-CoV-HGs were selected to construct the protein-protein interaction (PPI) network. Results: Using the Walktrap algorithm highly interconnected modules include module 1 (202 nodes); module 2 (126 nodes) and module 3 (121 nodes) modules were retrieved from the PPI network. MYC, HDAC9, NCOA3, CEBPB, VEGFA, BCL3, SMAD3, SMURF1, KLHL12, CBL, ERBB4, and CRKL were identified as potential drug targets (PDTs), which are highly expressed in the human respiratory system after CoV infection. Functional terms growth factor receptor binding, c-type lectin receptor signaling, interleukin-1 mediated signaling, TAP dependent antigen processing and presentation of peptide antigen via MHC class I, stimulatory T cell receptor signaling, and innate immune response signaling pathways, signal transduction and cytokine immune signaling pathways were enriched in the modules. Protein-protein docking results demonstrated the strong binding affinity (-314.57 kcal/mol) of the ERBB4-3cLpro complex which was selected as a drug target. In addition, molecular dynamics simulations indicated the structural stability and flexibility of the ERBB4-3cLpro complex. Further, Wortmannin was proposed as a candidate drug to ERBB4 to control SARS-CoV-2 pathogenesis through inhibit receptor tyrosine kinase-dependent macropinocytosis, MAPK signaling, and NF-kb singling pathways that regulate host cell entry, replication, and modulation of the host immune system. Conclusion: We conclude that CoV drug target \"ERBB4\" and candidate drug \"Wortmannin\" provide insights on the possible personalized therapeutics for emerging COVID-19.
摘要：
背景：冠状病毒（CoV）是一种新兴的人类病原体，在世界各地引起严重的急性呼吸道综合症（SARS）。早期识别SARS的生物标志物可以促进检测并降低疾病的死亡率。因此，通过集成网络分析和结构建模方法，我们旨在探索冠状病毒治疗SARS的潜在药物靶点和候选药物。方法：使用Limma对CoV感染的宿主基因（HGs）表达谱进行差异表达（DE）分析。选择高度整合的DE-CoV-HG来构建蛋白质-蛋白质相互作用(PPI)网络。结果：使用Walktrap算法高度互联的模块包括模块1（202个节点）；模块2（126个节点）和模块3（121个节点）从PPI网络中检索到。MYC,HDAC9,NCOA3,CEBPB,VEGFA,BCL3,SMAD3,SMURF1,KLHL12,CBL,ERBB4和CRKL被确定为潜在的药物靶标(PDT)，在CoV感染后在人类呼吸系统中高度表达。功能术语生长因子受体结合，c型凝集素受体信号，白细胞介素-1介导的信号，TAP依赖性抗原加工和通过MHCI类呈递肽抗原，刺激性T细胞受体信号，和先天免疫应答信号通路，在模块中富集了信号转导和细胞因子免疫信号通路。蛋白质-蛋白质对接结果显示ERBB4-3cLpro复合物的强结合亲和力(〜314.57kcal/mol),其被选作药物靶标。此外,分子动力学模拟表明ERBB4-3cLpro复合物的结构稳定性和灵活性。Further,Wortmannin被提议作为ERBB4的候选药物，通过抑制受体酪氨酸激酶依赖性巨噬细胞增多来控制SARS-CoV-2的发病机理。MAPK信号，和调节宿主细胞进入的NF-kb单个通路，复制,和调节宿主免疫系统。结论：我们得出的结论是，CoV药物靶标“ERBB4”和候选药物“Wortmannin”为新兴COVID-19的可能个性化治疗提供了见解。
