Ma Jing, Ren Yue, Zhang Jia-Ning, Lin Li, Zhang Yan-Ling
State Administration of Traditional Chinese Medicine, Research Center of Traditional Chinese Medicine-Information Engineering, Key Technology of Traditional Chinese Medicine Pharmacy and New Drug Development Engineering Research Center of Ministry of Education, School of Chinese Materia Medica, Beijing University of Chinese Medicine Beijing 102488, China.
Beijing Key Laboratory of Pharmacology of Chinese Materia Medica, Institute of Basic Medical Sciences of Xiyuan Hospital, China Academy of Chinese Medical Sciences Beijing 100091, China.
Zhongguo Zhong Yao Za Zhi. 2021 Aug;46(15):3970-3979. doi: 10.19540/j.cnki.cjcmm.20210303.401.
The traditional Chinese medicines(TCM) for activating blood circulation and the TCM for regulating Qi are often used in combination in clinical practice. However, their mechanisms are still unclear. The activity spectrum of targets can fuse the active components, targets and intensity of action, which provides support for the discussion of efficacy targets. The chemical components of common TCM sets for activating blood circulation and regulating Qi, as well as the negative sets not for activating blood circulation and re-gulating Qi were obtained from the database of TCM. By the similarity analysis of chemical components in TCM for activating blood circulation and DrugBank database, the predicted targets of chemical components in TCM for activating blood circulation were obtained, and the similarity value of the two was taken as the activity value of the active components and predicted targets. Then, the component-target activity value was weighted. The activity values of herb acting on the same target were fused to construct activity spectra of targets of the herbs for activating blood circulation, herbs for regulating Qi and negative herbs. The targets whose activity values of activating blood circulation and regulating Qi were higher than those of negative herbs were selected as potential targets of efficacy. Protein-protein interaction networks were constructed for topological, GO and KEGG enrichment analysis to determine the key targets of efficacy of activating blood circulation and regulating Qi. The component-target activity information collected from DrugBank database contained 4 499 compounds, 627 targets and 11 295 action relationships. The activating blood function protein-protein interaction network contained 206 nodes and 1 728 edges, while the regulating Qi function protein-protein interaction network contained 230 nodes and 986 edges. The enrichment analysis of topology, GO and KEGG showed that TCM for activating blood circulation mainly exerted its anti-inflammatory, neuroprotective and angiogenic effects on signaling cascade pathway mediated by VEGF/VEGFR2, ERK signaling pathway, calcium signaling pathway and PI3 K-AKT signaling pathway, and the key targets included mitogen activated protein kinases 3(MAPK3), proto-oncogene tyrosine-protein kinase Src(SRC), mitogen activated protein kinases 1(MAPK1), epidermal growth factor receptor(EGFR), phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform(PIK3 CA), peroxisome proliferators-activated receptor gamma(PPARG), nitric oxide synthase 3(NOS3), prostaglandin G/H synthetase 2(PTGS2), matrix metalloproteinase-9(MMP9), and vascular endothelial growth factor A(VEGFA). TCM for regulating Qi mainly exerted anti-inflammatory and neuroprotective effects by acting on MAPK signaling pathway and PI3 K-AKT signaling pathway, and the key targets included mitogen activated protein kinases 8(MAPK8), SRC, mitogen activated protein kinases 14(MAPK14), and RAC-alpha serine/threonine-protein kinase(AKT1), mitogen activated protein kinases 3(MAPK3). Based on the activity spectrum of targets, the targets of the TCM for activating blood and the targets of the TCM for regulating Qi were analyzed to provide reference for the study of efficacy targets of TCM, and also provide some scientific basis for clinical application.
活血化瘀类中药与理气类中药在临床中常联合应用。然而，其作用机制尚不清楚。靶点活性谱能够融合活性成分、靶点及作用强度，为探讨药效靶点提供支持。从中药数据库中获取常用活血化瘀类中药集与理气类中药集的化学成分，以及非活血化瘀理气类中药集。通过活血化瘀类中药化学成分与DrugBank数据库的相似性分析，获得活血化瘀类中药化学成分的预测靶点，并将二者的相似性值作为活性成分与预测靶点的活性值。然后，对成分-靶点活性值进行加权。将作用于同一靶点的中药活性值进行融合，构建活血化瘀类中药、理气类中药及阴性对照中药的靶点活性谱。选取活血化瘀与理气活性值高于阴性对照中药的靶点作为潜在药效靶点。构建蛋白质-蛋白质相互作用网络进行拓扑、GO和KEGG富集分析，以确定活血化瘀与理气的关键药效靶点。从DrugBank数据库收集的成分-靶点活性信息包含4499种化合物、627个靶点及11295个作用关系。活血化瘀功能蛋白质-蛋白质相互作用网络包含206个节点和1728条边，理气功能蛋白质-蛋白质相互作用网络包含230个节点和986条边。拓扑、GO和KEGG富集分析表明，活血化瘀类中药主要通过VEGF/VEGFR2、ERK信号通路、钙信号通路和PI3K-AKT信号通路介导的信号级联途径发挥抗炎、神经保护和血管生成作用，关键靶点包括丝裂原活化蛋白激酶3（MAPK3）、原癌基因酪氨酸蛋白激酶Src（SRC）、丝裂原活化蛋白激酶1（MAPK1）、表皮生长因子受体（EGFR）、磷脂酰肌醇-4,5-二磷酸3-激酶催化亚基α异构体（PIK3CA）、过氧化物酶体增殖物激活受体γ（PPARG）、一氧化氮合酶3（NOS3）、前列腺素G/H合成酶2（PTGS2）、基质金属蛋白酶-9（MMP9）和血管内皮生长因子A（VEGFA）。理气类中药主要通过作用于MAPK信号通路和PI3K-AKT信号通路发挥抗炎和神经保护作用，关键靶点包括丝裂原活化蛋白激酶8（MAPK8）、SRC、丝裂原活化蛋白激酶14（MAPK14）、RAC-α丝氨酸/苏氨酸蛋白激酶（AKT1）、丝裂原活化蛋白激酶3（MAPK3）。基于靶点活性谱，对活血化瘀类中药与理气类中药的靶点进行分析，为中药药效靶点研究提供参考，也为临床应用提供一定的科学依据。
