目的 基于数据挖掘结合网络药理学方法探究国家专利中药复方治疗胃食管反流病（GERD）的组方规律 及作用机制。方法 （1）检索国家知识产权局专利数据库中治疗 GERD 的专利中药复方，并建立标准化数据 库。通过 Microsoft Excel 2021 软件对标准化数据库中药物的使用频率、功效分类及性味归经分布情况进行描述 性统计分析；通过 IBM SPSS Modeler 18.0（Apriori 算法）和 IBM SPSS Statistics 26 软件对高频药物进行关联规则 挖掘与系统聚类分析；采用 R 语言中的 psych 包完成高频药物 Phi 相关性分析，以识别并筛选核心药物组合。 （2）基于中药系统药理学数据库获取核心药物的活性成分及其作用靶点。通过 GeneCards、OMIM、TTD 数据库 获取 GERD 疾病相关靶点。对核心药物作用靶点与疾病相关靶点进行映射，获得核心药物治疗 GERD 的潜在 作用靶点。运用 Cytoscape 3.9.1 软件构建“药物-成分-靶点”互作关系网络，筛选核心活性成分。将潜在作用 靶点导入 STRING 数据库，构建蛋白互作（PPI）网络，筛选核心靶点。对潜在作用靶点进行 GO 功能注释与 KEGG 通路富集分析。使用 AutoDock Vina 1.1.2 软件对核心活性成分与核心靶点进行分子对接验证。结果 （1）最 终共纳入 128 项专利中药复方，涵盖 444 味中药。其中高频用药（频数≥20 次）有黄连、柴胡、甘草、海螵蛸、 吴茱萸等；功效分类主要包括清热药、补虚药、理气药以及活血化瘀药等；药性以温性为主，药味以苦、辛、 甘味多见，主要归经为肝、胃、肺经。关联规则识别出赭石-枳壳-柴胡、赭石-吴茱萸-黄连等药物组合；聚 类分析获得黄连-吴茱萸-赭石-柴胡-枳壳-白芍等 5 类新聚类；Phi 相关性分析提示柴胡-枳壳-黄连-吴茱萸- 赭石组合的相关性较强，并确定柴胡-枳壳-黄连-吴茱萸为核心药物组合。（2）对“柴胡-枳壳-黄连-吴茱萸” 核心药物组合筛选获得 41 个药物活性成分，以及 216 个作用靶点；通过 GeneCards、OMIM、TTD 数据库检索 得到疾病相关靶点 1 244 个；将核心药物作用靶点与疾病相关靶点取交集，共获得核心药物治疗 GERD 的潜在 作用靶点 88 个。通过“药物-成分-靶点”网络分析得到核心药物治疗 GERD 的核心活性成分：槲皮素、山柰 酚、柚皮素、川陈皮素和异鼠李素。通过潜在作用靶点 PPI 网络分析得到核心药物治疗 GERD 的核心靶点： AKT1、MAPK3、PTGS2、MMP9、IL1B、BCL2、PPARG、CASP3、TNF、IL6、TP53。潜在作用靶点主要通过 影响凋亡信号通路的调节、上皮细胞增殖、对外源性刺激的反应、泛素样蛋白连接酶结合、蛋白激酶调节剂活 性及 DNA 结合转录因子结合等生物学过程；主要富集在 PI3K-Akt、MAPK、IL-17、Lipid and atherosclerosis 和 AGE-RAGE 等信号通路。5 个核心成分均能与 11 个核心靶点稳定结合，其中柚皮素与 MMP9、山柰酚与 PTGS2 的结合能最强。结论 GERD 专利中药复方以清热为主，兼以补虚、理气、活血为治则，其核心药物组 合“柴胡-枳壳-黄连-吴茱萸”可能是通过靶向调控 AKT1、MAPK3、PTGS2 等关键靶点，介导 PI3K-Akt、 MAPK、IL-17 等信号通路，从而发挥治疗 GERD 的作用。

Objective To investigate the prescription rules and mechanisms of national patent Chinese herbal compounds in treating gastroesophageal reflux disease （GERD） using data mining combined with network pharmacology. Methods （1） Patent Chinese herbal compounds for GERD treatment were retrieved from the patent database of the China National Intellectual Property Administration， and a standardized database was established. Descriptive statistical analysis was performed on the frequency of medication use， efficacy classification， and distribution of properties，flavors，and meridian tropisms in the standardized database using Microsoft Excel 2021. Association rule mining and systematic cluster analysis for high-frequency herbs were conducted using IBM SPSS Modeler 18.0（Apriori algorithm） and IBM SPSS Statistics 26. Phi correlation analysis for high-frequency herbs was performed using the psych package in R language to identify and screen core herb combinations.（2） Active ingredients and their corresponding targets of the core herbs were obtained from the Traditional Chinese Medicine Systems Pharmacology Database. GERDrelated targets were retrieved from the GeneCards， OMIM， and TTD databases. By mapping the core herb targets against the disease-related targets，potential targets of the core herbs for GERD treatment were identified. An “herbcomponent-target” interaction network was constructed using Cytoscape 3.9.1 to screen core active ingredients. The potential targets were imported into the STRING database to construct a protein-protein interaction （PPI） network and identify core targets. GO functional annotation and KEGG pathway enrichment analyses were performed for the potential targets. Molecular docking validation between core active ingredients and core targets was conducted using AutoDock Vina 1.1.2. Results （1） A total of 128 patent Chinese herbal compounds were included， encompassing 444 herbs. High-frequency herbs （frequency≥20） included Coptidis Rhizoma，Bupleuri Radix，Glycyrrhizae Radix et Rhizoma， Endoconcha Sepiae and Euodiae Fructus. Efficacy classifications primarily included heat-clearing， deficiencytonifying， qi-regulating， and blood-activating and stasis-resolving. The medicinal properties were predominantly warm，while flavors were mainly bitter，pungent，and sweet，with primary meridian tropisms in the liver，stomach， and lung. Association rule mining identified herb combinations such as Haematitum-Aurantii Fructus-Bupleuri Radix， Haematitum-Euodiae Fructus-Coptidis Rhizoma. Cluster analysis yielded five new clusters， including Coptidis Rhizoma-Euodiae Fructus-Haematitum-Bupleuri Radix-Aurantii Fructus-Paeoniae Radix Alba. Phi correlation analysis suggested a strong correlation among the Bupleuri Radix-Aurantii Fructus-Coptidis Rhizoma-Euodiae FructusHaematitum combination，and this combination was identified as the core herb set.（2） A total of 41 active ingredients and 216 corresponding targets were identified for the core herb combination “Bupleuri Radix-Aurantii Fructus-Coptidis Rhizoma-Euodiae Fructus”. A total of 1 244 GERD-related targets were retrieved from the GeneCards，OMIM，and TTD databases. By intersecting the core herb targets with the disease-related targets，88 potential targets of the core herbs for GERD treatment were obtained. Network analysis of the “herb-component-target” network identified the core active ingredients for GERD treatment as quercetin， kaempferol， naringenin， nobiletin， and isorhamnetin. PPI network analysis of the potential targets identified core targets including AKT1， MAPK3， PTGS2， MMP9， IL1B， BCL2，PPARG，CASP3，TNF，IL6，and TP53. The potential targets were primarily involved in biological processes such as regulation of apoptotic signaling pathway， epithelial cell proliferation， response to xenobiotic stimulus， ubiquitin-like protein ligase binding，protein kinase regulator activity，and DNA-binding transcription factor binding， and were mainly enriched in signaling pathways including PI3K-Akt，MAPK，IL-17，lipid and atherosclerosis，and AGE-RAGE. All five core ingredients showed stable binding with the 11 core targets， with naringenin-MMP9 and kaempferol-PTGS2 exhibiting the strongest binding energies. Conclusion GERD patent Chinese herbal compounds primarily adopt a therapeutic principle of heat-clearing， supplemented by deficiency-tonifying， qi-regulating， and blood-activating methods. The core herb combination “Bupleuri Radix-Aurantii Fructus-Coptidis Rhizoma-Euodiae Fructus” may exert its therapeutic effects in GERD by targeting key targets such as AKT1， MAPK3， and PTGS2， thereby mediating pathways including PI3K-Akt，MAPK，and IL-17.

R259 ；G255.53；R289

国家自然科学基金项目（82460917）；国家中医药管理局高水平中医药重点学科建设项目（zyyzdxk-2023187）；贵州省高等学校中西医 结合防治疾病转化医学重点实验室项目（黔教技 〔2020〕 017 号）；贵州中医药大学中西医结合防治消化系统疾病科技创新人才团队建设项目 （贵中医 TD 合字 〔2023〕 001号）。