基于网络药理学及分子对接技术探讨中医防治阿尔茨海默病的作用机制

Exploring the Mechanism of Traditional Chinese Medicine in the Prevention and Treatment of Alzheimer’s Disease Based on Network Pharmacology and Molecular Docking Technology

摘要: 目的：通过网络药理学联合分子对接技术研究中医防治阿尔茨海默病的作用机制。方法：通过知网、维普等数据库收集经典名方并统计其中出现频次最高的前十味药材。借助SwissTargetPrediction、GeneCards、OMIM数据库分别获取活性成分靶点与阿尔茨海默病潜在靶点，并利用Venny图得交集靶点，String构建PPI网络(Cytoscape可视化)，DAVID富集分析，Autodock与PyMol完成对接及可视化。结果：筛选出117篇中文文献，24篇英文文献，含74个处方105味中药；截取出现频次前十的中药，关键活性成分包括槲皮素、山柰酚、β-谷甾醇、啤酒甾醇、环阿屯醇等，作用于MAPK与NF-κB通路。分子对接结果显示关键活性成分与核心靶点预测具有较好的结合潜力。结论：槲皮素等中药成分可通过“多靶点–多通路”协同机制对阿尔茨海默病进行防治。

Abstract: Objective: This study investigates the mechanism of traditional Chinese medicine in preventing and treating Alzheimer’s disease through network pharmacology combined with molecular docking technology. Methods: Classical famous prescriptions were collected from databases such as CNKI and VIP, and the top ten herbs with the highest frequency of occurrence were statistically analyzed. Then, active ingredient targets and potential targets of Alzheimer’s disease were obtained from the SwissTargetPrediction, GeneCards, and OMIM databases, respectively. Intersection targets were identified using a Venny diagram, a PPI network was constructed using the String database and visualized with Cytoscape, enrichment analysis was performed using DAVID, and molecular docking and visualization were carried out using Autodock and PyMol. Results: A total of 117 Chinese articles and 24 English articles were screened, containing 74 prescriptions and 105 Chinese herbs. The top ten herbs with the highest frequency of occurrence were selected. The key active ingredients included quercetin, kaempferol, β-sitosterol, cerevisterol, cycloartenol, etc., which acted on the MAPK and NF-κB pathways. Molecular docking results showed that the key active ingredients could bind stably to the core targets. Conclusion: Quercetin and other traditional Chinese medicine components may prevent and treat Alzheimer’s disease through a synergistic mechanism of “multi-target, multi-pathway”.