Abstract: Objective Parkinson's disease (PD) is a complex neurodegenerative disorder,and Gastrodia elata,a plant used in traditional Chinese medicine,may hold potential therapeutic value for its treatment.This study employs network pharmacology,bioinformatics,and molecular docking techniques to systematically investigate the molecular mechanisms of Gastrodia elata in treating Parkinson's disease (PD). Methods Active components of Gastrodia elata were screened using the BATMAN database,their targets were predicted using the Swiss Target Prediction database,and PD-related targets were obtained from the GeneCards database.A “component-target-PD” network was constructed,and topological analysis was performed to screen for core targets.GO function and KEGG pathway enrichment analyses of the core targets were conducted using the DAVID database.Molecular docking validation was performed using CB-Dock2,and differential expression validation was conducted using the GEO dataset GSE20291、GSE20292和GSE20295. Results A total of 35 active components of Gastrodia elata were screened,corresponding to 569 targets.Intersection with PD-related targets yielded 130 potential targets.PPI network analysis identified 15 core targets,forming four major functional modules:energy metabolism (PRKAA1/PPARGCA),hormone signaling (ESR1/ESR2/AR/CYP19A1),neurotransmitter regulation (DRD2/SLC6A3/MAOB/ACHE),and inflammatory oxidative stress (PTGS2/NOX4/CYBB).GO and KEGG enrichment analyses revealed that Gastrodia elata acts on four major pathway networks:neurotransmitter regulation,AMPK energy metabolism,estrogen signaling,and purine metabolism-iron metabolism-oxidative stress,forming a multi-dimensional “metabolism-inflammation-hormone-neural function” regulatory axis.Molecular docking verified the good binding affinity (binding energy <0) between active components and core targets such as MAOB and DRD2.The GSE54536 dataset confirmed significant expression changes of CDC25A,ESR1,ESR2,and PTGS2 in PD patients. Conclusion Gastrodia elata intervenes in PD through a synergistic mechanism involving multiple components,multiple targets,and multiple pathways,providing a new paradigm shift from “single-target regulation” to “multi-target network synergistic regulation” for PD treatment,while also offering a methodological reference for the modernization of traditional Chinese medicine research.

Key words: Network pharmacology, Gastrodia elata, Bioinformatics, Parkinson's disease, molecular docking

摘要： 目的 帕金森病(Parkinson's disease ,PD)是一种复杂的神经退行性疾病,而天麻(Gastrodia elata)这种用于传统中医治疗的植物或许在该疾病的治疗中具有潜在的治疗价值。本研究采用网络药理学、生物信息学和分子对接技术,系统探究天麻治疗帕金森病(PD)的分子机制。方法 通过BATMAN数据库筛选天麻活性成分,Swiss Target Prediction数据库预测靶点,GeneCards数据库获取PD相关靶点;构建“活性成分-靶点-PD”网络并进行拓扑分析筛选核心靶点;通过DAVID数据库进行GO和KEGG通路富集分析;采用CB-Dock2进行分子对接验证;利用GEO数据集GSE20291、GSE20292和GSE20295进行差异表达验证。结果 从天麻中筛选出35个活性成分,对应569个作用靶点,与PD靶点交集获得130个潜在靶点。PPI网络识别出15个核心靶点,形成能量代谢(PRKAA1/PPARGCA)、激素信号(ESR1/ESR2/AR/CYP19A1)、神经递质调控(DRD2/SLC6A3/MAOB/ACHE)及炎症氧化应激(PTGS2/NOX4/CYBB)四大功能模块。GO和KEGG富集分析显示天麻作用于神经递质调控、AMPK能量代谢、雌激素信号及嘌呤代谢-铁代谢-氧化应激四大通路网络,形成“代谢-炎症-激素-神经功能”多维调控轴。分子对接验证了活性成分与MAOB、DRD2等核心靶点的良好结合能力。结论 天麻通过多成分、多靶点、多通路协同干预PD,为PD治疗提供了从“单靶点调控”向“多靶点网络协同调控”转变的新思路,也为中药现代化研究提供了方法学参考。

关键词: 网络药理学, 天麻, 生物信息学, 帕金森病, 分子对接