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中国精品科技期刊2020
张宇欣,刘魏魏,杨娟,等. 基于网络药理学和分子对接探讨常见酚酸提高机体免疫力的作用机制[J]. 华体会体育,2023,44(2):29−40. doi: 10.13386/j.issn1002-0306.2022030227.
引用本文: 张宇欣,刘魏魏,杨娟,等. 基于网络药理学和分子对接探讨常见酚酸提高机体免疫力的作用机制[J]. 华体会体育,2023,44(2):29−40. doi: 10.13386/j.issn1002-0306.2022030227.
ZHANG Yuxin, LIU Weiwei, YANG Juan, et al. Molecular Mechanism of Common Phenolic Acids on Enhancing Immunity Based on Network Pharmacology and Molecular Docking[J]. Science and Technology of Food Industry, 2023, 44(2): 29−40. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022030227.
Citation: ZHANG Yuxin, LIU Weiwei, YANG Juan, et al. Molecular Mechanism of Common Phenolic Acids on Enhancing Immunity Based on Network Pharmacology and Molecular Docking[J]. Science and Technology of Food Industry, 2023, 44(2): 29−40. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022030227.

基于网络药理学和分子对接探讨常见酚酸提高机体免疫力的作用机制

Molecular Mechanism of Common Phenolic Acids on Enhancing Immunity Based on Network Pharmacology and Molecular Docking

  • 摘要: 目的:运用网络药理学和分子对接研究常见酚酸类化合物提高机体免疫力的分子机制。方法:利用TCMSP数据库、STITCH数据库、SwissTargetPrediction在线靶点筛选平台收集常见酚酸类化合物潜在靶点,并利用Cytoscape3.8.0软件构建酚酸类化合物-靶点网络图。在GeneCard数据库、OMIM数据库收集免疫力相关靶点,与常见酚酸类化合物靶点取交集并导入STRING数据库进行蛋白质与蛋白质相互作用(protein-protein interaction,PPI)分析,得到酚酸类化合物提高免疫力的核心作用靶点,将核心靶点导入DAVID数据库进行GO功能富集及KEGG通路富集。最后,应用AutoDock软件对关键成分与关键靶点进行分子对接验证。结果:共收集到常见酚酸类化合物36个,对应靶点496个,提高免疫力靶点16691个,二者取交集,获得酚酸类化合物增强免疫作用靶点454个,其中关键作用的靶点为SRC、MAPK1、HSP90AA1、AKT1、TP53等,发挥作用的主要成分为迷迭香酸、迷迭香酸甲酯、鞣花酸、阿魏酸乙酯、芥子酸等。GO及KEGG分析结果显示,常见酚酸类化合物通过调控正调控RNA聚合酶II启动子转录、转录的正调控,DNA模板化、凋亡过程的负调节等生物过程,通过癌症通路、多聚糖肿瘤通路、MAPK信号通路等多条通路发挥增强免疫作用。分子对接结果表明,关键化合物与靶点分子对接结果良好,验证了网络药理学预测结果的准确性。结论:本研究揭示常见酚酸类化合物通过调控多靶点、多途径发挥增强机体免疫力的作用,为酚酸类化合物的开发及进一步研究奠定基础。

     

    Abstract: Objective: To study the molecular mechanism of common phenolic acids on enhancing immunity by network pharmacology and molecular docking. Method: The potential targets of common phenolic acids were acquired from TCMSP database, STITCH database, and SwissTargetPrediction online target screening platform, and the component-target network map of common phenolic acids was constructed using Cytoscape 3.8.0 software. Then, candidate targets of each phenolic acids and known therapeutic targets of enhancing immunity were collected from the GeneCard database and OMIM database, and the overlapping genes were imported into STRING database for protein-protein interaction (PPI) analysis to obtaining the key immune-enhancing targets. GO annotation and KEGG signal pathway enrichment of the key targets were analyzed using DAVID platform. Moreover, this study verified the key targets predicted by using AutoDock molecular docking. Results: The results indicated that there were 496 targets corresponding to 36 phenolic acid compounds and 16691 targets for enhancing immunity. At that time, 454 intersection targets were obtained, and these 454 targets were used as candidate targets for enhancing immunity of phenolic acid compounds, among which the key targets were SRC, MAPK1, HSP90AA1, AKT1, TP53, etc. Rosmarinic acid, methyl rosmarinate, ellagic acid, ethyl ferulate, and sinapic acid and so on were the main components that could enhance immunity. GO annotation and KEGG pathway enrichment analysis showed that common phenolic acids played an immune-enhancing role through multiple pathways such as positive regulation of transcription from RNA polymerase II promoter, positive regulation of transcription, DNA-templated, negative regulation of apoptotic process, as well as signal pathways including pathways in cancer, proteoglycans in cancer, and MAPK signaling pathway. Moreover, the molecular docking analysis revealed that the core targets had good binding affinities with key components, which verified the accuracy of the prediction results of network pharmacology. Conclusion: This study revealed that common phenolic acid compounds played a role in enhancing immunity through regulating multiple targets and multiple pathways, laying a foundation for the development and further research of common phenolic acid compounds.

     

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