Zhan N, Liu X H, Tang F Y, Zhang J Y
Zunyi Medical University, Zunyi 563000, China.
School of Pharmacy, Zunyi Medical University, China.
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2021 Oct 27;33(5):483-495. doi: 10.16250/j.32.1374.2021169.
To explore the potential targets and synergistic mechanisms of Kushen Decoction for the treatment of cryptosporidiosis using network pharmacology and molecular docking methods.
The main active ingredients of Kushen Decoction were captured from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TC-MSP) and the Universal Protein Resource (UniProt) database, and the potential targets were predicted. In addition, the active ingredients of Kushen Decoction that were not included in the TCMSP database were retrieved in CNKI, WanFang Data, CBM, PubMed and Web of Science databases, and the target genes of all supplemented active ingredients were predicted using the online TargetNet database. Network construction and analysis were performed using the Cytoscape software, and cryptosporidiosis-related targets were retrieved in the Comparative Toxicogenomics Database and GeneCards database. The protein-protein interaction (PPI) network was created using the STRING database, and the DAVID database was used for GO enrichment and KEGG pathway analyses. The tissue distribution of key targets was investigated using the BioGPS database, and the AutoDockTools software was employed to verify the molecular docking results.
A total of 38 active ingredients of Kushen Decoction were screened, and the core ingredients included quercetin, (+)-14α-hydroxymatrine and apigenin. A total of 831 targets of Kushen Decoction and 512 cryptosporidiosis-related targets were predicted, and PPI network analysis revealed 69 key targets, including AKT1, TNF and IL-6. There were 303 biological processes, 46 molecular functions and 29 cellular components involved in the treatment of cryptosporidiosis with Kushen Decoction, and 13 KEGG pathways played a therapeutic role in the synergistic mechanisms of multiple targets, such as Toll-like receptor (TLR), nuclear factor kappa B(NF)-κB, nucleotide binding oligomerization domain like receptor (NLR) signal pathways. The core targets were mainly distributed in the hematologic and immune systems. Molecular docking analysis showed that the binding energy between active ingredients and key targets were all less than 0 kJ/mol, indicating the strong binding of ligands to receptors.
The active ingredients of Kushen Decoction, such as quercetin, (+)-14α-hydroxymatrine and apigenin, may act on targets like AKT1, TNF, IL-6 to modulate TLR, NLR and NF-κB signaling pathways to play a synergistic role in the treatment of cryptosporidiosis in the hematologic and immune system.
采用网络药理学和分子对接方法,探讨苦参汤治疗隐孢子虫病的潜在靶点及协同作用机制。
从中药系统药理学数据库与分析平台(TC-MSP)和通用蛋白质资源(UniProt)数据库中获取苦参汤的主要活性成分,并预测潜在靶点。此外,在知网、万方数据、中国生物医学文献数据库、PubMed和Web of Science数据库中检索未包含在TCMSP数据库中的苦参汤活性成分,并使用在线TargetNet数据库预测所有补充活性成分的靶基因。使用Cytoscape软件进行网络构建和分析,并在比较毒理基因组学数据库和基因卡片数据库中检索隐孢子虫病相关靶点。使用STRING数据库创建蛋白质-蛋白质相互作用(PPI)网络,并使用DAVID数据库进行基因本体(GO)富集分析和京都基因与基因组百科全书(KEGG)通路分析。使用BioGPS数据库研究关键靶点的组织分布,并使用AutoDockTools软件验证分子对接结果。
共筛选出苦参汤38种活性成分,核心成分包括槲皮素、(+)-14α-羟基苦参碱和芹菜素。共预测出苦参汤831个靶点和512个隐孢子虫病相关靶点,PPI网络分析显示69个关键靶点,包括蛋白激酶B1(AKT1)、肿瘤坏死因子(TNF)和白细胞介素-6(IL-6)。苦参汤治疗隐孢子虫病涉及303个生物学过程、46个分子功能和29个细胞成分,13条KEGG通路在多个靶点的协同作用机制中发挥治疗作用,如Toll样受体(TLR)、核因子κB(NF)-κB、核苷酸结合寡聚化结构域样受体(NLR)信号通路。核心靶点主要分布在血液和免疫系统。分子对接分析表明活性成分与关键靶点之间的结合能均小于0 kJ/mol,表明配体与受体结合力强。
苦参汤中的活性成分,如槲皮素、(+)-14α-羟基苦参碱和芹菜素,可能作用于AKT1、TNF、IL-6等靶点,调节TLR、NLR和NF-κB信号通路,在血液和免疫系统中对隐孢子虫病的治疗发挥协同作用。