Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea.
Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea.
Comput Biol Chem. 2020 Dec;89:107375. doi: 10.1016/j.compbiolchem.2020.107375. Epub 2020 Sep 12.
Seasonal and pandemic influenza infections are serious threats to public health and the global economy. Since antigenic drift reduces the effectiveness of conventional therapies against the virus, herbal medicine has been proposed as an alternative. Fritillaria thunbergii (FT) have been traditionally used to treat airway inflammatory diseases such as coughs, bronchitis, pneumonia, and fever-based illnesses. Herein, we used a network pharmacology-based strategy to predict potential compounds from Fritillaria thunbergii (FT), target genes, and cellular pathways to better combat influenza and influenza-associated diseases. We identified five compounds, and 47 target genes using a compound-target network (C-T). Two compounds (beta-sitosterol and pelargonidin) and nine target genes (BCL2, CASP3, HSP90AA1, ICAM1, JUN, NOS2, PPARG, PTGS1, PTGS2) were identified using a compound-influenza disease target network (C-D). Protein-protein interaction (PPI) network was constructed and we identified eight proteins from nine target genes formed a network. The compound-disease-pathway network (C-D-P) revealed three classes of pathways linked to influenza: cancer, viral diseases, and inflammation. Taken together, our systems biology data from C-T, C-D, PPI and C-D-P networks predicted potent compounds from FT and new therapeutic targets and pathways involved in influenza.
季节性和大流行性流感感染是对公众健康和全球经济的严重威胁。由于抗原漂移降低了常规疗法对病毒的有效性,因此草药已被提议作为替代疗法。贝母一直被用于治疗气道炎症性疾病,如咳嗽、支气管炎、肺炎和发热性疾病。在此,我们使用基于网络药理学的策略来预测贝母中的潜在化合物、靶基因和细胞途径,以更好地对抗流感和流感相关疾病。我们使用化合物-靶标网络(C-T)鉴定了五种化合物和 47 个靶基因。使用化合物-流感疾病靶标网络(C-D)鉴定了两种化合物(β-谷甾醇和矢车菊素)和九个靶基因(BCL2、CASP3、HSP90AA1、ICAM1、JUN、NOS2、PPARG、PTGS1、PTGS2)。构建了蛋白质-蛋白质相互作用(PPI)网络,我们从九个靶基因中鉴定出 8 个蛋白质形成了一个网络。化合物-疾病-途径网络(C-D-P)揭示了与流感相关的三类途径:癌症、病毒疾病和炎症。总之,我们从 C-T、C-D、PPI 和 C-D-P 网络获得的系统生物学数据预测了 FT 中的有效化合物以及涉及流感的新治疗靶标和途径。