摘要： 目的 通过网络药理学和分子对接方法探讨大黄在胃癌中的抗肿瘤机制。方法 通过TCMSP网站收集大黄的活性成分及对应的靶点，利用肿瘤与癌症基因组图谱（TCGA）数据库、GeneCards网站得到胃癌相关基因，两者取交集，利用Cytoscape软件绘制胃癌-大黄-活性成分-靶点的网络图。通过Metascape网站对交集靶点进行功能、同路富集分析以及蛋白-蛋白相互作用网络分析，利用MCODE算法确定关键基因簇，最后利用分子对接方法找到可能的作用靶点。结果 通过筛选得到大黄的主要活性成分16个，共获得46个治疗胃癌的潜在靶点，京都基因和基因组数据库（KEGG）通路、基因本体论（GO）分类富集分析结果显示，大黄治疗胃癌的机制涉及多个生物学过程，包括凋亡、程序性细胞死亡、MAPK通路调节、细胞周期、PI3K-Akt等信号通路。蛋白-蛋白互作后发现关键基因簇包括BCL2、CASP8、AR、IL1B、CASP3、PRKCA、TP53、CDKN1A、PCNA，主要为凋亡相关基因，进一步分子对接验证了其与对应活性成分之间亲合度均较高，其中PKCNA与芦荟大黄素亲合度最高。结论 大黄治疗胃癌通过多成分、多靶点、多通路协同起效，本研究为后续进一步研究提供了充分的理论依据。

基于网络药理学和分子对接预测大黄治疗胃癌的作用机制

何欣^1,2, 刘云鹏^1,2, 李冬阳^1,2, 车晓芳^1,2

1. 中国医科大学附属第一医院肿瘤内科, 沈阳 110001;
2. 辽宁省肿瘤药物与生物治疗重点实验室, 沈阳 110001

收稿日期:2022-05-05出版日期:2023-01-30发布日期:2023-02-01
通讯作者:车晓芳E-mail:chexf_2015@126.com
作者简介:何欣（1988-），女，医师，博士研究生.
基金资助:国家自然科学基金（81972751，32170791）；重大疑难疾病中西医临床协作能力建设项目


关键词: 大黄, 胃癌, 网络药理学, 作用机制, 分子对接
Abstract: Objective To explore the molecular mechanism of Rheum officinale in gastric cancer treatment based on network pharmacology and molecular docking. Methods The TCMSP database was used to identify the active ingredients and effective targets of Rheum officinale. Both the TCGA database and GeneCards database were then used to determine potential therapeutic targets of gastric cancer. Intersecting targets of these two target groups were then used to establish a network of targets for Rheum officinale active components and gastric cancer using Cytoscape. The intersection targets were applied to the Metascape website for GO/KEGG enrichment analysis and protein-protein interaction. From this, a key gene cluster was determined by MCODE method. Molecular docking was conducted using AutoDock Vina software to predict the combination. Results In total, 16 active ingredients and 46 potential targets of Rheum officinale were linked with gastric cancer. The KEGG pathway analysis showed that apoptosis, MAPK cascade, cell cycle, and PI3K-Akt signaling pathways were all potential gastric cancer targets for the identified active components of Rheum officinale. Using protein-protein interaction, key gene clusters were identified, mainly in apoptosis-related genes including BCL2, CASP8, AR, IL1B, CASP3, PRKCA, TP53, CDKN1A, and PCNA. Molecular docking results showed that PKNCA to have the highest affinity to the Rheum officinale active ingredient, aloe-emodin. Conclusion This study explored the molecular mechanism of Rheum officinale in the treatment of gastric cancer through an integrated method analysis of network pharmacology and molecular docking. The results provide theoretical clues for further research.
Key words: rheum officinale, gastric cancer, network pharmacology, mechanism of action, molecular docking
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