目的 基于“無(wú)痰不作?！钡睦碚?，分析中藥組方治療梅尼埃病的用藥規(guī)律及作用機(jī)制。方法 通過(guò)計(jì)算機(jī)檢索中國(guó)知網(wǎng)（CNKI）、中國(guó)學(xué)術(shù)期刊數(shù)據(jù)庫(kù)（萬(wàn)方）、中文期刊數(shù)據(jù)庫(kù)（維普）和中國(guó)生物醫(yī)學(xué)文獻(xiàn)數(shù)據(jù)庫(kù)（CBM），根據(jù)篩選標(biāo)準(zhǔn)獲取文獻(xiàn)，對(duì)中藥頻次、性味、歸經(jīng)進(jìn)行挖掘，并通過(guò)SPSS Modeler 18.0和SPSS Statistics 25.0進(jìn)行關(guān)聯(lián)規(guī)則分析和聚類分析，得到核心方；通過(guò)中藥系統(tǒng)藥理學(xué)數(shù)據(jù)庫(kù)（Traditional Chinese Medicine Systems Pharmacology Database，TCMSP）檢索活性成分和作用靶點(diǎn)，通過(guò)GeneCards、OMIM和CTD數(shù)據(jù)庫(kù)檢索疾病靶點(diǎn)，使用Veeny 2.1.0在線平臺(tái)獲取藥物與梅尼埃病的交集靶點(diǎn)，利用String數(shù)據(jù)庫(kù)搭建蛋白質(zhì)相互作用（protein-protein interaction，PPI）網(wǎng)絡(luò)，通過(guò)Cytoscape 3.7.0軟件建立“藥物-活性成分-交集靶點(diǎn)-疾病”可視化網(wǎng)絡(luò)圖，使用DAVID數(shù)據(jù)平臺(tái)進(jìn)行基因本體（gene ontology，GO）和京都基因與基因組百科全書(shū)（Kyoto encyclopedia of genes and genomes，KEGG）富集分析，并使用AutoDockVina1.1.2、PyMol 2.3.0和DiscoveryStudio軟件進(jìn)行分子對(duì)接及可視化處理。根據(jù)分子對(duì)接的結(jié)果進(jìn)行實(shí)驗(yàn)驗(yàn)證。結(jié)果 共納入處方130個(gè)，中藥123味，性平、溫，味甘、苦，歸肝、脾經(jīng)的藥物最多，通過(guò)關(guān)聯(lián)規(guī)則得到半夏→茯苓、半夏→白術(shù)等藥物組合，聚類分析得到核心方半夏、茯苓、白術(shù)、澤瀉、陳皮。篩選出活性成分49個(gè)，疾病靶點(diǎn)8 342個(gè)，交集靶點(diǎn)61個(gè)，核心靶點(diǎn)有雌激素受體1（estrogen receptor 1，ESR1）、腫瘤蛋白53（tumor protein 53，TP53）、缺氧誘導(dǎo)因子1α（hypoxia inducible factor 1 alpha，HIF1A）等，核心成分有黃芩素、β-谷甾醇、卡維丁等，主要作用于環(huán)磷酸腺苷（cyclic adenosine monophosphate，cAMP）、磷脂酰肌醇-3-羥激酶（phosphatidylinositol-3-hydroxykinase，PI3K）/蛋白激酶B（protein kinase B，Akt）等信號(hào)通路。分子對(duì)接發(fā)現(xiàn)主要成分與靶點(diǎn)對(duì)接活性良好，HIF1A與卡維丁的結(jié)合能最低。驗(yàn)證實(shí)驗(yàn)發(fā)現(xiàn)，黃芩素、卡維丁可以明顯降低梅尼埃病大鼠耳蝸組織中ESR1、TP53、HIF1A基因的表達(dá)。結(jié)論 多維數(shù)據(jù)挖掘分析證實(shí)基于“無(wú)痰不作?！崩碚撝委熋纺岚２〉闹兴幪幏酱蠖嗑哂薪∑⒃餄?、息風(fēng)豁痰開(kāi)竅的特性，其關(guān)鍵活性成分黃芩素、β-谷甾醇、卡維丁主要作用于ESR1、TP53和HIF1A等梅尼埃病靶點(diǎn)；其中黃芩素可下調(diào)cAMP信號(hào)通路相關(guān)蛋白發(fā)揮治療梅尼埃病的效果。

Objective To analyze the medication pattern and mechanism of traditional Chinese medicine prescription for the treatment of Meniere’s disease based on the theory of “no phlegm, no vertigo”. Methods China National Knowledge Network (CNKI), China Academic Journal Database (Wanfang), Chinese Journal Database (VIP), and China Biomedical Literature Database (CBM) were searched using a computer program to find pertinent content that met predetermined screening criteria. The frequency, flavor, and attribution of Chinese drugs were investigated. Using SPSS Modeler 18.0 and SPSS Statistics 25.0, cluster analysis and association rule analysis were utilized to identify the key formulas. The remedial targets and vital elements came from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), while sickness targets were taken from the GeneCards, OMIM, and CTD databases. A protein-protein interaction (PPI) network was developed using the String data structure, and intersection targets were obtained using the Veeny 2.1.0 information platform. On the DAVID data platform, enrichment analysis was carried out using the gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) algorithms. Finally, PyMol 2.3.0, Discovery Studio, and Auto Dock Vina 1.1.2 were used for molecular docking and visualization, based on the previous findings. Results A total of 130 prescriptions were included, 123 traditional Chinese medicines with warm, supple qualities, bitter and sweet tastes, and connections to the liver and spleen meridians. Using association criteria, Banxia (Pinelliae Rhizoma)→Fuling (Poria), Pinelliae Rhizoma→Baizhu (Atractylodis Macrocephalae Rhizoma), and other pharmaceutical combinations were discovered. The core formulations included Pinelliae Rhizoma, Poria, Atractylodis Macrocephalae Rhizoma, Zexie (Alismatis Rhizoma), and Chenpi (Citri Reticulatae Pericarpium), were identified via cluster analysis. A total of 49 active components, 8 342 disease targets, and 61 intersecting targets were found in the study. The core targets include estrogen receptor 1 (ESR1), tumor protein 53 (TP53), hypoxia inducible factor 1 alpha (HIF1A), etc. and the core components include baicalein, β-sitosterol, cavidine, etc. It mainly acts on cyclic adenosine monophosphate (cAMP), and phosphatidylinositol-3-hydroxykinase (PI3K)/protein kinase B (Akt) signaling pathways. Molecular docking showed high docking activity between the target and the key components, with the lowest binding energy discovered between HIF1A and cavidine. The rat experiment was carried out according to the results of molecular docking. Conclusion Multidimensional data mining analysis confirmed that most of the Chinese herbal prescriptions for treating Meniere’s disease based on the theory of “no phlegm, no vertigo” have the properties of strengthening the spleen, drying dampness, resting wind, expelling phlegm, and opening the orifices, and that their key active ingredients, baicalein, β-sitosterol, and kavitin, mainly act on the MD targets, such as ESR1, TP53, and HIF1A; among them, baicalein down-regulates the cAMP signaling pathway to exert therapeutic effects on MD.

R285

東莞市社會(huì)科技發(fā)展項(xiàng)目（202050715002245）；東莞市社會(huì)科技發(fā)展項(xiàng)目（20211800900132）