Chinese Journal of Tissue Engineering Research ›› 2021, Vol. 25 ›› Issue (20): 3194-3201.doi: 10.3969/j.issn.2095-4344.3219
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Zhong Yuanming1, He Bingkun2, Wu Zhuotan2, Wu Sixian2, Wan Tong2, Zhong Xifeng2
Received:
2020-06-08
Revised:
2020-06-13
Accepted:
2020-07-11
Online:
2021-07-18
Published:
2021-01-15
Contact:
Zhong Yuanming, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530001, Guangxi Zhuang Autonomous Region, China
About author:
Zhong Yuanming, Chief physician, Professor, Doctoral supervisor, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530001, Guangxi Zhuang Autonomous Region, China
Supported by:
CLC Number:
Zhong Yuanming, He Bingkun, Wu Zhuotan, Wu Sixian, Wan Tong, Zhong Xifeng. An exploration on the mechanism of Shaoyao Gancao Decoction in treating early pain of lumbar disc herniation based on network pharmacology[J]. Chinese Journal of Tissue Engineering Research, 2021, 25(20): 3194-3201.
2.1 芍药甘草汤活性成分及作用靶点筛选结果 根据筛选条件进行筛选后,发现芍药甘草汤共有105种活性成分,去除重复及无法在UniProt数据库找到相应靶标的18种活性成分,最后纳入87种有效活性成分,其中白芍4种,甘草84种,对应靶标蛋白共217种,山奈酚为二者共有成分。甘草的化学成分主要包括黄酮类、二氢茋类、多糖类、酚类、甾体类、挥发油类、苷类和有机酸类[21]。白芍的化学成分主要包括单萜及其苷类、萜类、黄酮类、鞣质类和多糖类[22],其中,萜类、黄酮类、挥发油类、甾体类、苷类和有机酸类归属心经;黄酮类、有机酸类、挥发油类、萜类、苷类和多糖类归属于肝经,黄酮类、挥发油类、苷类、萜类、有机酸类、多糖类和甾体类归属于肺经[23]。部分关键活性成分见表2。"
2.3 药物-关键活性成分-靶标网络图构建结果 将筛选出来的47种芍药甘草汤治疗腰椎间盘突出症的交集靶标与芍药甘草汤中药物的关键活性成分进行逐一映射,构建两者对应关系。根据对应关系及相关属性,利用Cytoscape 3.7.2软件建立“药物-关键活性成分-靶标”调控网络并进一步可视化,结果见图2。通过软件中附属“CentiScape”功能计算各节点对应的“Degree”值,数值越大,提示该节点发挥的作用越重要。在计算结果中,有效活性化合物排在前4名的分别是:槲皮素(MOL000098,quercetin)、山柰酚(MOL000422,kaempferol)、芒柄花素(MOL000392,formononetin)及7-甲氧基-2-甲基异黄酮(MOL003896,7-Methoxy-2-methyl isoflavone),对应的“Degree”值由大到小分别是38,12,8,8,为该网络的主要化合物。靶标节点中,排在前5名的靶标分别是:环加氧酶2(PTGS2),雌激素受体1(ESR1),雄激素受体(AR),诱导型一氧化氮合酶(NOS2),丝裂原活化蛋白激酶14(MAPK14),对应的“Degree”值由大到小分别是83,78,66,65,47,为该网络的关键靶标。"
2.4 药物-疾病靶标蛋白相互作用网络(PPI)的构建结果 将芍药甘草汤及腰椎间盘突出症疾病交集靶标导入String线上分析平台中进行蛋白相互作用分析,保存为tsv文件,借助Cytoscape 3.7.2软件进行网络可视化构建,见图3,该网络中有47个节点通过661条边发生相互作用,蛋白互作富集(P < 0.001),平均局部聚类系数为0.81,平均节点Degree值28.1。网络中节点颜色深浅及形状大小根据“Degree”值进行设定,节点颜色越深,形状越大则对应的靶标蛋白的“Degree”值越大。当某一靶标蛋白的“Degree”值超过该网络平均值时,提示该靶标蛋白为该PPI网络的核心蛋白。文章结果中,超过均值的靶标蛋白有29个,其中“Degree”值排名前5的有白细胞介素6,白细胞介素1β,基质金属蛋白酶9,丝氨酸苏氨酸蛋白激酶1(AKT1),血管内皮生长因子A(VEGFA),这些靶标蛋白处于该网络的核心地位。 "
2.5 GO功能富集分析及KEGG通路富集分析结果 通过R软件中的 bioconductor集合工具包对药物-疾病交集靶标蛋白进行GO功能富集分析及KEGG通路富集分析,结果显示GO功能富集分析涉及27种分子组成,78项分子功能,1 329个生物过程,KEGG通路富集分析显示主要涉及130条信号通路。将排名前20的GO功能富集分析及KEGG通路进行可视化。 生物过程分析可得知,靶标主要涉及对细菌来源分子的反应、对脂多糖的反应、对活性氧的反应、氧化应激反应、对细菌来源分子的反应、对营养水平的反应等生物过程,见图4。分子组成分析可得知,这些靶标主要参与膜筏、膜微区、膜区、含胶原的细胞外基质、囊腔等分子组成。分子功能分析可得知,靶标主要影响细胞因子受体结合、内肽酶活性、受体配体活性及丝氨酸水解酶活性及细胞因子活性等分子功能。 "
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