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随着人们生活方式的改变,心血管疾病成为全球发病和死亡的重要原因,临床上以冠状动脉粥样硬化性心脏病(CHD,简称冠心病)最为常见,给患者、家庭和社会带来了巨大的负担[1,2]。血管性痴呆(VD)是缺血或出血性脑血管病引起脑组织损伤所致的痴呆类型[3]。最新研究估计,我国60岁以上的痴呆患者约有
1507 万人,其中VD患者约有392万人[4]。特发性膜性肾病(IMN)是常见的自身免疫性肾小球疾病,该病严重时可引起心、脑等器官障碍。研究显示,IMN患者约有40%可进展为终末期肾病,极大威胁患者生命安全[5]。冠心病、血管性痴呆、特发性膜性肾病虽属不同系统疾病,但文献研究发现,他们都有痰瘀互结的共同病因病机。冠心病不同阶段病人痰瘀互结的比例超过50%,血管性痴呆和特发性膜性肾病也有近50%,这为三类疾病的异病同治提供了重要的理论基础[6,7]。
异病同治是中医的重要理念,该理念提供了认识疾病的共同规律,帮助找到治疗方向,是辨证识机论治的根本。国医大师朱良春倡导“顽疾必兼痰和瘀”,痰瘀同治重大疾病疗效卓著。项目组前期提出“益气化痰活血、清热散结法”异病同治冠心病、血管性痴呆、特发性膜性肾病的组方用药新方案,根据中药组方规律结合经典方剂,按照“君、臣、佐、使”的原则,组建益气活血化痰、清热散结方-丹参白术方,该方剂从治疗湿热、血瘀、气虚、痰瘀等方面结合中药的用药特性组建,在临床取得了较好的治疗效果。
网络药理学是以系统生物学为基础,多学科、多领域融合形成的新兴学科。其综合性、系统性、整体性的理念与中药多成分、多靶点、多通路的特点相吻合。本研究基于网络药理学的方法,对丹参白术方治疗冠心病、血管性痴呆、特发性膜性肾病的靶点进行测试,初步探究其可能的物质基础和作用机制,为临床进一步研究提供依据。
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将丹参白术方中的9味中药上传至TCMSP、PubChem数据库搜索到1 121个化合物。按照OB≥30%且DL≥0.18的筛选标准,筛选出177个活性化合物,排除13个未发现相关靶点的化合物,共收集到164个活性化合物。基本信息见附件1。通过TCMSP、PharmMapper、UniProt数据库共获得活性化合物潜在作用靶点509个。通过Cytoscape3.8.2软件,构建“中药-活性化合物-药物靶点”网络,见图1。
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通过GeneCards、OMIM和DrugBank数据库,按照筛选标准搜集三种疾病的潜在靶点,去重后获得冠心病疾病靶点1 993个,血管性痴呆疾病靶点1 164个,特发性膜性肾病疾病靶点1 098个。将以上3种疾病靶点与丹参白术方509个潜在作用靶点进行交集,最终获得丹参白术方对三种疾病“异病同治”的共有靶点141个,通过Venny 2.1.0,将数据绘制韦恩图,见图2。将共有靶点导入Cytoscape 3.8.2构建“丹参白术方-共有靶点-疾病”网络图,见图3。
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将以上获得的141个共有靶点输入STRING 11.5数据库,得出共有靶点的蛋白质间相互作用关系,通过平台分析得到节点数141个,边数3 564条,平均节点度值50.6,以intersection score>0.4为筛选标准,将筛选后的信息导入Cytoscape 3.8.2,使用其插件cytoHubba进行分析,cytoHubba提供了11种拓扑学分析方法搜寻关键靶点,我们使用三种算法:连接度(Degree)、最大团体中心性(MCC)、最大邻域分量(MNC),各提取排名前30位的关键靶点,取交集,得到关键共有靶点25个,分别是:ALB、IL6、TNF、AKT1、JUN、CASP3、VEGFA、STAT3、INS、PTGS2、MAPK3、IL1B、TP53、MMP9、HIF1A、CTNNB1、SRC、FOS、MYC、CXCL8、CCND1、EGFR、EGF、HSP90AA1、PPARG,见图4。图形的面积和颜色深浅表示靶点度值的大小,面积越大,颜色越深说明靶点度值越大。
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为进一步探究丹参白术方“异病同治”的作用机制,将上述获得的25个关键共有靶点上传至Metascape,进行GO功能分析和KEGG信号通路富集分析。共获得生物过程(BP)817个,细胞组成(CC)30个,分子功能(MF)44个,根据其P值大小,分别列举前10位的条目,具体见图5。KEGG通路富集分析筛选得到142条P<0.01的通路。将P值较小的,富集靶点较多的20条通路,使用在线作图工具微生信进行可视化分析,结果以散点图的形式呈现,具体见图6。
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应用Schrödinger软件对丹参白术方的主要共有活性成分槲皮素(Quercetin)、β-甾谷醇与核心靶点AKT1和ALB进行分子对接,对接结果见表1。靶蛋白AKT1、ALB与其原配体的对接打分值(Docking score)分别为−10.807 kcal/mol、−7.664 kcal/mol。若活性成分的Docking score值低于或接近原配体则表明该活性成分与该靶点的结合能力较强。其中槲皮素对ALB的Docking score值低于原配体且对AKT1的Docking score值与其原配体接近,表明活性成分槲皮素与关键蛋白受体AKT1与ALB均具有较强的结合稳定性。活性成分β-甾谷醇对ALB的Docking score值与原配体接近,虽然对AKT1的Docking score值相对原配体较低,但小于−6 kcal/mol,也被认为具有良好的结合活性。绘制分子对接模式图见图7。
表 1 丹参白术方的主要共有活性成分与核心蛋白的分子对接结果
活性成分 核心靶点 PDB ID 对接分数(kcal/mol) 槲皮素 AKT1 3O96 −10.332 β-甾谷醇 AKT1 3O96 −6.755 槲皮素 ALB 4LB2 −8.049 β-甾谷醇 ALB 4LB2 −7.358
Network pharmacological mechanism of Danshen Baizhu prescription on the treatment of coronary heart disease, vascular dementia and idiopathic membranous nephropathy
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摘要:
目的 基于网络药理学探讨丹参白术方“异病同治”冠心病、血管性痴呆、特发性膜性肾病的物质基础和作用机制。 方法 通过TCMSP、PubChem、UniProt、GeneCards、OMIM和DrugBank数据库获取药物和疾病靶点,使用STRING数据库和Cytoscape软件绘制中药-化合物-药物靶点网络、复方-共有靶点-疾病网络、蛋白-蛋白互作图,运用Metascape数据库进行基因富集分析。 结果 共筛选出活性化合物164个,潜在作用靶点509个,“异病同治”的共有靶点141个。其中主要活性成分为丹参酮ⅡA、异鼠李素、槲皮素、木犀草素、山奈酚、β-谷甾醇、豆甾醇等;关键靶点为清蛋白、白细胞介素6、肿瘤坏死因子、丝氨酸/苏氨酸激酶1、血管内皮生长因子A;主要富集于细胞迁移的正向调控、细胞活力的正向调节、蛋白质磷酸化的正向调节、对生长因子的反应、氧化应激反应等生物过程及脂质和动脉粥样硬化、MAPK、动脉粥样硬化和流体剪切力、AGE-RAGE、IL-17、PI3K-Akt等信号通路。 结论 丹参白术方“异病同治”冠心病、血管性痴呆、特发性膜性肾病的作用机制可能主要通过抑制炎症、抑制氧化应激反应、扩张血管等多靶点、多通路发挥作用。 Abstract:Objective To investigate the material basis and mechanism of Danshen Baizhu prescription in coronary heart disease, vascular dementia and idiopathic membranous nephropathy based on network pharmacology. Methods TCMSP, PubChem, UniProt, GeneCards, OMIM, and DrugBank databases were used to obtain drug and disease targets, and the TCM-compound-drug target network, compound-common target-disease network, and protein-protein interaction map were drawn by STRING database and Cytoscape software, and gene enrichment analysis was performed by Metascape database. Results A total of 164 active compounds, 509 potential targets, and 141 common targets were screened out. The main active ingredients are Tanshinone II A, Isorhamnetin, Quercetin, Luteolin, Kampferol, β-sitosterol, Stigmasterol, etc. The key targets are albumin, interleukin 6, Tumor necrosis factor , serine/threonine kinase 1, vascular endothelial growth factor A , mainly enriching in the positive regulation of cell migration, cell viability, protein phosphorylation, response to growth factors, oxidative stress and other biological processes and lipid and atherosclerosis, MAPK, atherosclerosis and fluid shear force, AGE-RAGE, IL-17, PI3K-Akt and other signaling pathways. Conclusion The mechanism of action of Danshen Baizhu prescription for coronary heart disease, vascular dementia and idiopathic membranous nephropathy may mainly play a role in multiple targets and pathways such as inhibition of inflammation, inhibition of oxidative stress, and vasodilation. -
表 1 丹参白术方的主要共有活性成分与核心蛋白的分子对接结果
活性成分 核心靶点 PDB ID 对接分数(kcal/mol) 槲皮素 AKT1 3O96 −10.332 β-甾谷醇 AKT1 3O96 −6.755 槲皮素 ALB 4LB2 −8.049 β-甾谷醇 ALB 4LB2 −7.358 -
[1] 《心肺血管病杂志》编辑部. 中国心血管健康与疾病报告2019[J]. 心肺血管病杂志, 2020, 39(9):1145-1156. doi: 10.3969/j.issn.1007-5062.2020.09.028 [2] 胡盛寿, 高润霖, 刘力生, 等. 《中国心血管病报告2018》概要[J]. 中国循环杂志, 2019, 34(3):209-220. doi: 10.3969/j.issn.1000-3614.2019.03.001 [3] 王维治. 神经病学[M]. 2版. 北京: 人民卫生出版社, 2013: 1787. [4] JIA L F, DU Y F, CHU L, et al. Prevalence, risk factors, and management of dementia and mild cognitive impairment in adults aged 60 years or older in China: a cross-sectional study[J]. Lancet Public Health, 2020, 5(12):e661-e671. doi: 10.1016/S2468-2667(20)30185-7 [5] UNCANIN S, DZEMIDZIC J, SERDAREVIC N, et al. Idiopathic membranous nephropathy and treatment related complications[J]. Med Arch, 2020, 74(3):228-232. doi: 10.5455/medarh.2020.74.228-232 [6] 蒋恬, 胡镜清, 陈党红. “痰瘀互结”的3个致病特征[J]. 中华中医药杂志, 2022, 37(11):6376-6379. [7] 胡镜清, 韩晶岩. 痰瘀互结: 基础与临床[M]. 上海: 上海科学技术出版社, 2023. [8] RU J L, LI P, WANG J N, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines[J]. J Cheminform, 2014, 6:13. doi: 10.1186/1758-2946-6-13 [9] WANG Y L, BRYANT S H, CHENG T J, et al. PubChem BioAssay: 2017 update[J]. Nucleic Acids Res, 2017, 45(D1):D955-D963. doi: 10.1093/nar/gkw1118 [10] LIU H, WANG J N, ZHOU W, et al. Systems approaches and polypharmacology for drug discovery from herbal medicines: an example using licorice[J]. J Ethnopharmacol, 2013, 146(3):773-793. doi: 10.1016/j.jep.2013.02.004 [11] LIU X F, OUYANG S S, YU B, et al. PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach[J]. Nucleic Acids Res, 2010, 38(Web Server issue): W609-W614. [12] WANG X, PAN C X, GONG J Y, et al. Enhancing the enrichment of pharmacophore-based target prediction for the polypharmacological profiles of drugs[J]. J Chem Inf Model, 2016, 56(6):1175-1183. doi: 10.1021/acs.jcim.5b00690 [13] WANG X, SHEN Y H, WANG S W, et al. PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database[J]. Nucleic Acids Res, 2017, 45(W1):W356-W360. doi: 10.1093/nar/gkx374 [14] CONSORTIUM U. UniProt: a hub for protein information[J]. Nucleic Acids Res, 2015, 43(Database issue): D204-D212. [15] REBHAN M, CHALIFA-CASPI V, PRILUSKY J, et al. GeneCards: integrating information about genes, proteins and diseases[J]. Trends Genet, 1997, 13(4):163. doi: 10.1016/S0168-9525(97)01103-7 [16] AMBERGER J S, BOCCHINI C A, SCHIETTECATTE F, et al. OMIM. org: online Mendelian Inheritance in Man(OMIM®), an online catalog of human genes and genetic disorders[J]. Nucleic Acids Res, 2015, 43(D1):D789-D798. doi: 10.1093/nar/gku1205 [17] WISHART D S, FEUNANG Y D, GUO A C, et al. DrugBank 5.0: a major update to the DrugBank database for 2018[J]. Nucleic Acids Res, 2018, 46(D1):D1074-D1082. doi: 10.1093/nar/gkx1037 [18] SZKLARCZYK D, GABLE A L, NASTOU K C, et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets[J]. Nucleic Acids Res, 2021, 49(D1):D605-D612. doi: 10.1093/nar/gkaa1074 [19] LIANG B, LI C N, ZHAO J Y. Identification of key pathways and genes in colorectal cancer using bioinformatics analysis[J]. Med Oncol, 2016, 33(10):111. doi: 10.1007/s12032-016-0829-6 [20] ZHOU Y Y, ZHOU B, PACHE L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets[J]. Nat Commun, 2019, 10(1):1523. doi: 10.1038/s41467-019-09234-6 [21] HAN J Y, LI Q, MA Z Z, et al. Effects and mechanisms of compound Chinese medicine and major ingredients on microcirculatory dysfunction and organ injury induced by ischemia/reperfusion[J]. Pharmacol Ther, 2017, 177:146-173. doi: 10.1016/j.pharmthera.2017.03.005 [22] GARCIA-MARTINEZ R, CARACENI P, BERNARDI M, et al. Albumin: pathophysiologic basis of its role in the treatment of cirrhosis and its complications[J]. Hepatology, 2013, 58(5):1836-1846. doi: 10.1002/hep.26338 [23] ARQUES S. Human serum albumin in cardiovascular diseases[J]. Eur J Intern Med, 2018, 52:8-12. doi: 10.1016/j.ejim.2018.04.014 [24] VIRDIS A, DELL’AGNELLO U, TADDEI S. Impact of inflammation on vascular disease in hypertension[J]. Maturitas, 2014, 78(3):179-183. doi: 10.1016/j.maturitas.2014.04.012 [25] HOT A, LENIEF V, MIOSSEC P. Combination of IL-17 and TNFα induces a pro-inflammatory, pro-coagulant and pro-thrombotic phenotype in human endothelial cells[J]. Ann Rheum Dis, 2012, 71(5):768-776. doi: 10.1136/annrheumdis-2011-200468 [26] CHEN Y L, WU X M, YU S S, et al. Neuroprotective capabilities of Tanshinone IIA against cerebral ischemia/reperfusion injury via anti-apoptotic pathway in rats[J]. Biol Pharm Bull, 2012, 35(2):164-170. doi: 10.1248/bpb.35.164 [27] SUN S K, YIN Y, YIN X, et al. Anti-nociceptive effects of Tanshinone IIA(TIIA)in a rat model of complete Freund’s adjuvant(CFA)-induced inflammatory pain[J]. Brain Res Bull, 2012, 88(6):581-588. doi: 10.1016/j.brainresbull.2012.06.002 [28] 于倩, 巫冠中. 木犀草素抗炎机制的研究进展[J]. 药学研究, 2019, 38(2):108-111,119. [29] LIN H Y H, CHEN Y, CHEN Y H, et al. Tubular mitochondrial AKT1 is activated during ischemia reperfusion injury and has a critical role in predisposition to chronic kidney disease[J]. Kidney Int, 2021, 99(4):870-884. doi: 10.1016/j.kint.2020.10.038 [30] BRAILE M, MARCELLA S, CRISTINZIANO L, et al. VEGF-A in cardiomyocytes and heart diseases[J]. Int J Mol Sci, 2020, 21(15):5294. doi: 10.3390/ijms21155294 [31] CARRANZA K, VERON D, CERCADO A, et al. Cellular and molecular aspects of diabetic nephropathy; the role of VEGF-A[J]. Nefrologia, 2015, 35(2):131-138. doi: 10.1016/j.nefro.2015.05.013 [32] 孙霁寒. 木犀草素对高脂血症SD大鼠的降脂作用及初步机制研究[C] //营养研究与临床实践——第十四届全国营养科学大会暨第十一届亚太临床营养大会、第二届全球华人营养科学家大会.