Volume 44 Issue 8
Aug.  2023
Turn off MathJax
Article Contents
Hualei DAI, Chengcheng HU, Guimin ZHANG, Siming TAO, Jiankun CHEN. Screening Biomarkers of Astragalus Membranaceus for Hypertensive Ventricular Remodeling Based on Network Pharmacology and Molecular Docking[J]. Journal of Kunming Medical University, 2023, 44(8): 27-36. doi: 10.12259/j.issn.2095-610X.S20230819
Citation: Hualei DAI, Chengcheng HU, Guimin ZHANG, Siming TAO, Jiankun CHEN. Screening Biomarkers of Astragalus Membranaceus for Hypertensive Ventricular Remodeling Based on Network Pharmacology and Molecular Docking[J]. Journal of Kunming Medical University, 2023, 44(8): 27-36. doi: 10.12259/j.issn.2095-610X.S20230819

Screening Biomarkers of Astragalus Membranaceus for Hypertensive Ventricular Remodeling Based on Network Pharmacology and Molecular Docking

doi: 10.12259/j.issn.2095-610X.S20230819
  • Received Date: 2023-05-08
    Available Online: 2023-09-05
  • Publish Date: 2023-08-30
  •   Objective  To investigate the mechanisms of Astragalus membranaceus in the treatment of hypertensive ventricular remodeling (VR) based on the principles of network pharmacology and molecular docking.   Method  The effective components of Astragalus membranaceus, drug targets and disease targets of hypertensive ventricular remodeling were obtained from the online database. The mRNA data were downloaded to screen the key modules and genes related to hypertensive ventricular remodeling, and then the disease targets of hypertensive ventricular remodeling were predicted, followed by GO functional/KEGG pathway enrichment analysis. PPI network were constructed and visualized. LASSO and Random Forest were used to construct the diagnostic model of hypertensive ventricular remodeling. After analyzing the biomarkers, the pharmacological regulatory network of traditional Chinese medicine was drawn and visualized for biomarkers and active components. Finally, the component structures were obtained through the database for molecular docking.  Results  87 active ingredients of Astragalus membranaceus, 390 drug targets, 3281 hypertensive ventricular remodeling disease targets and 2103 differentially expressed key module genes were obtained, and 24 key targets were obtained by taking the intersection. There were 288, 15 and 29 targets in terms of key target genes and biological processes, molecular functions and cell components, respectively. A total of 54 related signaling pathways were obtained, and the interaction network relationships of 21 proteins were obtained. Four biomarkers (MAPK1, IL2, CSNK2B, SELE) were obtained, and the molecular docking results showed the existence of binding hydrogen bonds between the proteins and small molecules of all four markers.   Conclusion  Screening to obtain markers of ventricular remodeling in hypertension by Astragalus membranaceus validated the effect of Astragalus membranaceus in the treatment of hypertensive ventricular remodeling and may become a molecular biomarker for the diagnosis and treatment of hypertensive ventricular remodeling.
  • loading
  • [1]
    Zhou Y P,Ruan C C,Kong L R,et al. Adenosine A(2A) receptor activation prevents DOCA-salt induced hypertensive cardiac remodeling via iBAT[J]. Biochem Biophys Res Commun,2020,525(1):224-230. doi: 10.1016/j.bbrc.2020.02.035
    [2]
    Zhang X,Dong S,Jia Q,et al. The microRNA in ventricular remodeling: the miR-30 family[J]. Biosci Rep,2019,39(8):1-11.
    [3]
    顾静,郭超,车敏,等. 黄芪对高血压大鼠血管重构中内质网应激反应的影响[J]. 中国实验动物学报,2019,27(1):65-71.
    [4]
    徐银祯,李兰芳,党万军. 黄芪注射液对老年高血压患者血管功能及左心室重塑的影响[J]. 内科,2018,13(6):843-846.
    [5]
    张王宁,高耀,李科,等. 基于网络药理学的黄芪总黄酮治疗肾病综合征的机制研究[J]. 药学学报,2018,53(9):1429-1441.
    [6]
    Lan S,Duan J,Zeng N,et al. Network pharmacology-based screening of the active ingredients and mechanisms of Huangqi against aging[J]. Medicine (Baltimore),2021,100(17):e25660.
    [7]
    Ritchie M E,Phipson B,Wu D,et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies[J]. Nucleic Acids Res,2015,43(7):e47. doi: 10.1093/nar/gkv007
    [8]
    Langfelder P,Horvath S,Wgcn A. An R package for weighted correlation network analysis[J]. BMC Bioinformatics,2008,9(1):559-559. doi: 10.1186/1471-2105-9-559
    [9]
    Yu G,Wang L G,Han Y,et al. ClusterProfiler: An R package for comparing biological themes among gene clusters[J]. OMICS,2012,16(5):284-287. doi: 10.1089/omi.2011.0118
    [10]
    Shannon P,Markiel A,Ozier O,et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks[J]. Genome Res,2003,13(11):2498-2504. doi: 10.1101/gr.1239303
    [11]
    Jerome Friedman T H,Robert Tibshirani. Regularization Paths for Generalized Linear Models via Coordinate Descent[J]. Journal of Statistical Software,2010,33(1):1-22.
    [12]
    Xavier Robin N T,Alexandre Hainard,et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves[J]. BMC Bioinformatics,2011,12(77):1471-2105.
    [13]
    Rossier B C,Bochud M,Devuyst O. The Hypertension Pandemic: An Evolutionary Perspective[J]. Physiology (Bethesda),2017,32(2):112-125.
    [14]
    Gao Q,Xu L,Cai J. New drug targets for hypertension: A literature review[J]. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease,2021,1867(3):166037-166037. doi: 10.1016/j.bbadis.2020.166037
    [15]
    王浩,张振贤. 心室重构发病机制及中医药防治的研究概述[J]. 中医药信息,2021,38(8):70-75. doi: 10.19656/j.cnki.1002-2406.210813
    [16]
    Park S,Lim W,Bazer F W,et al. Quercetin inhibits proliferation of endometriosis regulating cyclin D1 and its target microRNAs in vitro and in vivo[J]. J Nutr Biochem,2019,63:87-100. doi: 10.1016/j.jnutbio.2018.09.024
    [17]
    Kehat I,Davis J,Tiburcy M,et al. Extracellular signal-regulated kinases 1 and 2 regulate the balance between eccentric and concentric cardiac growth[J]. Circ Res,2011,108(2):176-183. doi: 10.1161/CIRCRESAHA.110.231514
    [18]
    Mutlak M,Kehat I. Extracellular signal-regulated kinases 1/2 as regulators of cardiac hypertrophy[J]. Front Pharmacol,2015,6:149-149.
    [19]
    Simons K H,De Jong A,Jukema J W,et al. T cell co-stimulation and co-inhibition in cardiovascular disease: a double-edged sword[J]. Nat Rev Cardiol,2019,16(6):325-343. doi: 10.1038/s41569-019-0164-7
    [20]
    Crouch S H,Botha-le roux S,Delles C,et al. Inflammation and hypertension development: A longitudinal analysis of the African-PREDICT study[J]. Int J Cardiol Hypertens,2020,7:100067-100067. doi: 10.1016/j.ijchy.2020.100067
    [21]
    Oparil S,Acelajado M C,Bakris G L,et al. Hypertension[J]. Nat Rev Dis Primers,2018,4:18014-18014. doi: 10.1038/nrdp.2018.14
    [22]
    Abbas A K T E,R Simeonov D,Marson A,et al. Revisiting IL-2: Biology and therapeutic prospects[J]. Sci Immunol,2018,3(25):1482. doi: 10.1126/sciimmunol.aat1482
    [23]
    Zeng Z,Yu K,Chen L,et al. Interleukin-2/Anti-Interleukin-2 Immune Complex Attenuates Cardiac Remodeling after Myocardial Infarction through Expansion of Regulatory T Cells[J]. J Immunol Res,2016,2016:8493767.
    [24]
    Li J,Gao K,Cai S,et al. Germline de novo variants in CSNK2B in Chinese patients with epilepsy[J]. Sci Rep,2019,9(1):17909. doi: 10.1038/s41598-019-53484-9
    [25]
    Stengel S T,Fazio A,Lipinski S,et al. Activating transcription factor 6 mediates inflammatory signals in intestinal epithelial cells upon endoplasmic reticulum stress[J]. Gastroenterology,2020,159(4):1357-1374. doi: 10.1053/j.gastro.2020.06.088
    [26]
    Naiel S C R,Lu C,Tat V,et al. Endoplasmic reticulum stress inhibition blunts the development of essential hypertension in the spontaneously hypertensive rat[J]. Am J Physiol Heart Circ Physiol,2019,316(5):H1214-H1223. doi: 10.1152/ajpheart.00523.2018
    [27]
    Liu G,Wu F,Jiang X,et al. Inactivation of Cys(674) in SERCA2 increases BP by inducing endoplasmic reticulum stress and soluble epoxide hydrolase[J]. Br J Pharmacol,2020,177(8):1793-1805. doi: 10.1111/bph.14937
    [28]
    Zhang B,Zhang P,Tan Y,et al. C1q-TNF-related protein-3 attenuates pressure overload-induced cardiac hypertrophy by suppressing the p38/CREB pathway and p38-induced ER stress[J]. Cell Death Dis,2019,10(7):520. doi: 10.1038/s41419-019-1749-0
    [29]
    Blackwood E A,Hofmann C,Santo Domingo M,et al. ATF6 Regulates Cardiac Hypertrophy by Transcriptional Induction of the mTORC1 Activator,Rheb[J]. Circ Res,2019,124(1):79-93. doi: 10.1161/CIRCRESAHA.118.313854
    [30]
    Bartolomaeus H,Balogh A,Yakoub M,et al. Short-chain fatty acid propionate protects from hypertensive cardiovascular damage[J]. Circulation,2019,139(11):1407-1421. doi: 10.1161/CIRCULATIONAHA.118.036652
    [31]
    Li N,Xiao H,Shen J,et al. SELE gene as a characteristic prognostic biomarker of colorectal cancer[J]. J Int Med Res,2021,49(4):3000605211004386.
    [32]
    Srivastava K,Chandra S,Narang R,et al. E-selectin gene in essential hypertension: a case-control study[J]. Eur J Clin Invest,2018,48(1):n/a-1.
    [33]
    Ouyang Y,Wu H,Tan A,et al. E-selectin gene polymorphism (A561C) and essential hypertension. Meta-analysis in the Chinese population[J]. Herz,2015,40(Suppl 2):197-202.
  • Relative Articles

    [1] Huijuan ZENG, Bo TIAN, Hongling YUAN, Jie HE, Guanxi LI, Guojia RU, Min XU, Dong ZHAN. Predictive Modeling of Chronic Kidney Disease with Hypertension or Diabetes Based on Machine Learning Algorithms. Journal of Kunming Medical University, 2024, 45(3): 99-105.  doi: 10.12259/j.issn.2095-610X.S20240315
    [2] Runlin FENG, Zongqi DENG, Mengyao WU, Yunna WANG, Yu WANG, Guilan LIU. GJB4 Gene Expression in Relation to Clinical and Pathological Features of Pancreatic Cancer Patients. Journal of Kunming Medical University, 2024, 45(8): 1-9.
    [3] Shaoyou DENG, Rong LI, Jintao LI, Yulan ZHAO, Peijin WANG, Hong ZHENG. Mechanism of Osteoking Improving Osteoarthritis based on Network Pharmacology and DDM Rats. Journal of Kunming Medical University, 2023, 44(7): 34-39.  doi: 10.12259/j.issn.2095-610X.S20230701
    [4] Ranxi SHI, Tao YANG, Qing CHENG, Liangchen ZHAO, Jiahui GUO, Limei WANG. Mechanism of Dendrobium Officinale Against Inflammatory Aging Based on Network Pharmacology and Molecular Docking. Journal of Kunming Medical University, 2023, 44(11): 1-8.  doi: 10.12259/j.issn.2095-610X.S20231101
    [5] Shunding TANG, Chonghua WAN, Ying SONG, Li DENG, Han WANG, Changwei SU, Xiaoqing ZHANG. Evaluation and Application of the Patients Reported Outcomes Measurement Scale for Hypertension. Journal of Kunming Medical University, 2022, 43(3): 60-66.  doi: 10.12259/j.issn.2095-610X.S20220312
    [6] Liu LI, Yaru WANG, Di ZHANG, Qincong CHEN, Ming WANG, Shuo WANG. Application of Gene Detection for Individualized Medication for Hypertension in Patients with Grade 3 Hypertension. Journal of Kunming Medical University, 2022, 43(4): 112-117.  doi: 10.12259/j.issn.2095-610X.S20220430
    [7] Li ZHANG, Yuting WANG, Jianing SHI, Dan YU, Renhua YANG, Zhiqiang SHEN, Jiang LONG, Peng CHEN. Network Pharmacology-based Analysis of the Anti-atherosclerosis Mechanism of Scutellarin and Experimental Validation in Vivo. Journal of Kunming Medical University, 2022, 43(8): 17-27.  doi: 10.12259/j.issn.2095-610X.S20220804
    [8] Lian-ju HE, Chun-mei ZUO, Lan LIU, Wen-long CUI, Jin-bo LI, Yi MO, Lu-ming FAN, Le CAI. Analysis of Trend in Prevalence of Hypertension and Its Relationship with Different Obesity Indices among Rural Adults in Fumin County of Yunnan Province. Journal of Kunming Medical University, 2021, 42(10): 38-44.  doi: 10.12259/j.issn.2095-610X.S20211008
    [9] Feng-ting MU, Chang-hong MU, Li-ping HE, Xiao-mei LI, Wen-jia ZHANG, Zhen YU, Qing-huan YANG, Hong-qin KE. Analysis of Hypertension and Its Influencing Factors in Dai and Jingpo Ethnic Groups in Dehong. Journal of Kunming Medical University, 2021, 42(8): 54-59.  doi: 10.12259/j.issn.2095-610X.S20210810
    [10] Xiu-qing WANG, Xin-tian LONG, Yong MAO, Jie CHEN, Jia ZHOU, Tian-shu CHU, Song-mei WANG, Cheng-huan SUN, Chun-mi LAI, Qian ZHANG. Prevalence and Determinants of Hypertension in Senior Nu Ethnic Group. Journal of Kunming Medical University, 2021, 42(9): 40-45.  doi: 10.12259/j.issn.2095-610X.S20210922
    [11] Xin-tian LONG, Jie CHEN, Yong MAO, Xiu-qing WANG, Shuang-yan LU, Hui-jie PU, Jia ZHOU, Cheng-huan SUN, Song-mei WANG, Ai-fang YE. Detection Rate and Determinants of Hypertension among Seniors in Anning City. Journal of Kunming Medical University, 2021, 42(12): 11-16.  doi: 10.12259/j.issn.2095-610X.S20211210
    [12] Zhang Li Qiong , Cai Le , Zhang Hong Qing , Cui Wen Long , Liu Ying Nan , Shen Jing Rong , He Lian Ju . . Journal of Kunming Medical University, 2020, 41(03): 30-34.
    [13] Dong Ling , Peng Yun Zhu , Huang Cheng , Huang Zhao , Chen Li Xing . Prevalence Rate and Associated Risk Factors of Hypertension in Bai Ethnic Group in Yunnan. Journal of Kunming Medical University, 2018, 39(07): 52-57.
    [14] Li Wen Hong . . Journal of Kunming Medical University,
    [15] Zhang Ti Ling . . Journal of Kunming Medical University,
    [16] Li Hong Fei . . Journal of Kunming Medical University,
    [17] Zhang Li Gang . . Journal of Kunming Medical University,
    [18] Pang Xing Mei . . Journal of Kunming Medical University,
    [19] Yang Zheng . . Journal of Kunming Medical University,
    [20] Chen Xue Qiang . . Journal of Kunming Medical University,
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(6)  / Tables(1)

    Article Metrics

    Article views (1589) PDF downloads(8) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return