摘要
目的:基于R语言数据挖掘探讨全国名老中医王书臣教授治疗特发性肺间质纤维化的遣方用药规律,同时利用网络药理学预测核心药物组合的潜在作用机制,为后续实验研究及临床应用提供依据和参考。方法:收集整理2020年1月-2023年4月王书臣教授于中国中医科学院西苑医院门诊治疗的特发性肺间质纤维化患者的原始病历资料,采用R语言对处方中的中药进行用药频次分析、药物关联规则分析、聚类分析,运用网络药理学预测核心药物的核心作用靶点,构建“疾病–药物–成分–靶点”网络,通过基因本体论(GO)和京都基因与基因组百科全书(KEGG)信号通路富集分析研究核心药物组合的生物通路、与受体的结合能力,阐明其作用机制,最后通过分子对接技术对关键成分与靶点进行反向验证。结果:共收集中药处方438首,涉及中药222味,中药累计使用9380次,使用频次≥100的中药有29味,使用频次居前5位者依次为地龙、黄芪、莪术、威灵仙、麦冬,使用频次≥100的药物以补益药、化痰止咳平喘药为主,辅以祛风湿药、清热药、活血化瘀药等。置信度>90%、支持度>30%的关联规则共2472条,通过药物聚类得到2类核心药物组合。通过网络药理学方法筛选出47种有效成分、94个核心靶点,主要通过参与磷脂酰肌醇3激酶(Phosphatidylinositol 3 Kinase,PI3K)–蛋白激酶B(Protein Kinase B,Akt)信号通路、丝裂原活化蛋白激酶(Mitogen–Activated Protein Kinase,MAPK)信号通路、低氧诱导因子(Hypoxia–Inducible Factor,HIF)–1信号通路、肿瘤坏死因子(Tumor Necrosis Factor,TNF)信号通路等抑制细胞凋亡、炎性反应和氧化应激等病理过程,从而发挥抗特发性肺间质纤维化作用。分子对接显示,胆固醇、常春藤皂苷元、异鼠李素、丁子香菇与丝氨酸/苏氨酸蛋白激酶1(Akt Serine/threonine Protein Kinase 1,AKT1)、磷脂酰肌醇3激酶催化亚基α(Phosphatidylinositol–4,5–Bisphosphate 3–Kinase Catalytic Subunit Alpha,PIK3CA)、信号转导与转录激活因子3(Signal Transducer and Activator of Transcription 3,STAT3)、MAPK1、c–Jun原癌基因(c–Jun Proto–Oncogene,JUN)具有较好的结合活性。结论:挖掘王书臣教授处方数据得到治疗特发性肺间质纤维化的核心药物组合为“黄芪–地龙–莪术–络石藤–威灵仙”,其通过PI3K–Akt、MAPK、HIF–1、TNF等信号通路抑制细胞凋亡、炎性反应和氧化应激等病理过程抗特发性肺间质纤维化,为临床应用和实验研究提供依据。
Objective:To investigate the prescription rules of Professor WANG Shuchen,a nationally renowned traditional Chinese medicine(TCM)practitioner,in treating idiopathic pulmonary fibrosis(IPF)by R language-based data mining,and to predict the potential action mechanisms of core medicine combinations via network pharmacology,so as to provide a foundation and reference for further experimental research and clinical application.Methods:Original medical records of IPF patients treated by Professor WANG at Xiyuan Hospital of CACMS from January 2020 to April 2023 were collected to perform use frequency analysis,association rule analysis,and cluster analysis of the included Chinese medicinal materials by R language.Network pharmacology was used to predict core targets of core medicines,and a“disease-medicine-component-target”network was constructed.The biological pathways,ligand and receptor binding ability of the core medicine combination were studied by GO functional enrichment analysis and KEGG signaling pathway enrichment analysis to elucidate the action mechanism.Finally,molecular docking was performed to reversely validate interactions between key components and targets.Results:A total of 438 TCM prescriptions were collected,involving 222 Chinese medicinal materials with 9380 cumulative use frequencies,and 29 Chinese medicinal materials were used not less than 100 times.The top five Chinese medicinal materials used were Dilong(Pheretima),Huangqi(Radix Astragali),Ezhu(Rhizoma Curcumae),Weilingxian(Radix et Rhizoma Clematidis),and Maidong(Radix Ophiopogon).The medicines used more than 100 times were primarily tonifying medicines,and phlegm-resolving and cough-relieving to relieve asthma medicines,supplemented by wind-damp-dispelling medicines,heat-clearing medicines,and blood-activating to eliminate stasis medicines.With a confidence greater than 90%and a support greater than 30%,2472 association rules were identified totally.Cluster analysis yielded two core medicine combinations.A total of 47 active components and 94 core targets were screened out by network pharmacology.They mainly inhibited pathological processes such as apoptosis,inflammation response,and oxidative stress by participating in the PI3K-Akt,MAPK,HIF-1,and TNF signaling pathways,thereby exerting an anti-IPF effect.Molecular docking confirmed strong binding activities between cholesterol,hederagenin,isorhamnetin,clovane and AKT1,PIK3CA,STAT3,MAPK1,and JUN,respectively.Conclusion:According to the data mining on TCM prescriptions of Professor WANG Shuchen,the core medicine combination of“Huangqi-Dilong-Ezhu-Luoshiteng(Caulis Trachelospermi)-Weilingxian”exerts anti-IPF effects by suppressing pathological processes such as apoptosis,inflammation response,and oxidative stress via PI3K-Akt,MAPK,HIF-1,and TNF signaling pathways,offering a basis for clinical practice a nd experimental research.
出处
《中医临床研究》
2025年第26期1-16,共16页
Clinical Journal Of Chinese Medicine
基金
中国中医科学院名老中医经验传承研究(XYZX0101-06,XYZX0101-31)
中国中医科学院科技创新工程项目(CI2021A01103)
北京中医药薪火传承“3+3”项目(2019-SZC-77)。
关键词
特发性肺间质纤维化
中药复方
用药规律
作用机制
数据挖掘
Idiopathic interstitial pulmonary fibrosis
Traditional Chinese medicine compound
Medication rule
Action mechanism
Data mining
