Altern Ther Health Med. 2023 Mar;29(2):155-161.
Drug-resistant tuberculosis (TB), especially multidrug-resistant TB, has continued to increase and pan-drug-resistant TB and even fully drug-resistant TB have emerged, bringing great challenges to the treatment of TB. Development of new, safe, and effective antituberculosis drugs is an urgent need.
The study intended to evaluate the use of the network pharmacology method to comprehensively and systematically analyze the network relationship of Kushen's main components, targets, and signaling pathways, aiming to provide new ideas and clues for an in-depth study of the mechanism of Kushen's main components in the treatment of pulmonary TB.
The research team performed a Network pharmacology analysis.
The study took place in the Department of Respiratory and Critical Care Medicine at the Third People's Hospital of Yichang City in Yichang, Hubei, China.
The research team: (1) screened Kushen's active ingredients and related targets using the Traditional Chinese Medicine System Pharmacology (TCMSP) database and analysis platform; (2) used the GeneCards database and the Online Mendelian Inheritance in Man (OMIM) database to search for disease targets, (3) connected the active ingredient's targets to the disease targets to obtain predictive targets for Kushen to act against TB, (4) used the STRING database to construct a protein-protein interaction (PPI) network map, (5) used the Database for Annotation, Visualization and Integrated Discovery (DAVID) to subject the intersecting genes to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and (6) used the TCMSP and Protein Data Bank (PDB) databases to dock the active ingredients with target-protein molecules.
The research team found 45 active ingredients for Kushen and 177 target-protein genes related to active ingredients. The PPI network map of the Kushen-TB targets and found that the top 10 targets of Kushen were: (1) mitogen-activated protein kinase 8 (MAPK8); (2) protein kinase B (AKT1); (3) MAPK1, (4) estrogen receptor 1 (ESR1), (5) rel avian reticuloendotheliosis viral oncogene homolog A (RELA), (6) interleukin-6 (IL6), (7) MYC proto-oncogene, basic helix-loop-helix (bHLH) transcription factor MYC), (8) retinoid X receptor alpha (RXRA), (9) FOS proto-oncogene activator protein 1 (AP-1) transcription factor subunit (FOS), and (10) JUN proto-oncogene AP-1 transcription factor subunit (JUN). The KEGG analysis suggested that Kushen can intervene in TB through the hypoxia-inducible factor 1 (HIF-1) signaling pathway.
The network pharmacology analysis showed that Kushen's active ingredients can play a role in the treatment of TB through the HIF-1 signaling pathway.
耐药结核病（TB），尤其是耐多药结核病（MDR-TB）持续增加，甚至出现了泛耐药结核病和完全耐药结核病，给结核病的治疗带来了巨大挑战。开发新的、安全和有效的抗结核药物是当务之急。
本研究旨在采用网络药理学方法全面系统地分析苦参主要成分、靶点和信号通路的网络关系，为深入研究苦参主要成分治疗肺结核的作用机制提供新的思路和线索。
研究团队进行了网络药理学分析。
中国湖北省宜昌市第三人民医院呼吸与危重症医学科。
研究团队：（1）利用中药系统药理学（TCMSP）数据库和分析平台筛选苦参的活性成分和相关靶点；（2）使用基因卡片数据库和在线孟德尔遗传数据库（OMIM）搜索疾病靶点；（3）将活性成分的靶点与疾病靶点连接，获得苦参治疗结核病的预测靶点；（4）使用 STRING 数据库构建蛋白质-蛋白质相互作用（PPI）网络图；（5）使用数据库注释、可视化和综合发现（DAVID）对交集基因进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析；（6）使用 TCMSP 和蛋白质数据银行（PDB）数据库将活性成分与靶蛋白分子对接。
研究团队发现苦参的 45 种活性成分和 177 种与活性成分相关的靶蛋白基因。苦参-TB 靶标 PPI 网络图发现，苦参的前 10 个靶标为：（1）有丝分裂原激活蛋白激酶 8（MAPK8）；（2）蛋白激酶 B（AKT1）；（3）MAPK1；（4）雌激素受体 1（ESR1）；（5）禽网状内皮增生病病毒癌基因同源物 A（RELA）；（6）白细胞介素 6（IL6）；（7）原癌基因 MYC，碱性螺旋-环-螺旋（bHLH）转录因子 MYC）；（8）视黄醇 X 受体 alpha（RXRA）；（9）FOS 原癌基因激活蛋白 1（AP-1）转录因子亚基（FOS）；（10）JUN 原癌基因 AP-1 转录因子亚基（JUN）。KEGG 分析表明，苦参可通过缺氧诱导因子 1（HIF-1）信号通路干预结核病。
网络药理学分析表明，苦参的活性成分可通过 HIF-1 信号通路发挥治疗结核病的作用。
