Components in Prunus mume and their targets in the alleviation of severe depression identified using network pharmacology analysis.

IF 0.7 4区 医学 Q4 PHARMACOLOGY & PHARMACY International journal of clinical pharmacology and therapeutics Pub Date : 2025-06-01 DOI:10.5414/CP204729
Xiao-Han Diao, Qiang Tao, Shao-Jun Zheng, Nai-Dong Chen, Sheng Li
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Abstract

Background: Prunus mume (PM), a traditional Chinese medicinal herb, is well known for relieving depression.

Study design: To elucidate its potential therapeutic benefits for major depressive disorder (MDD), further research is required to investigate its underlying mechanisms.

Materials and methods: Using UPLC-QE-MS and the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), we analyzed PM's ingredients and targets. The Gene Expression Omnibus (GEO) database identified MDD-related targets. Enrichment analysis identified key components for MDD treatment, refined via protein-protein interaction (PPI) networks and machine learning. Molecular docking with AutoDock software assessed binding affinity.

Results: We identified 35 PM components and 691 targets. Bioinformatics revealed 1,105 differentially expressed genes in MDD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed significant enrichment in protease binding, protein tyrosine kinase activity, and pathways like mTOR, Ras, and VEGF. PPI networks and machine learning identified five hub genes - SELP, MMP8, HK2, ATP1A1, and DAO - as therapeutic targets. Molecular docking analysis showed that PM ingredients - Quercetin, Luteolin, Tamarixetin, Isorhamnetin, 8-Hydroxykaempferol, Morin - bind effectively to key targets.

Conclusion: This study elucidates active components and potential mechanisms for treating MDD with PM, providing insights for future therapeutic targets and drug development.

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利用网络药理学分析鉴定梅子中的成分及其缓解重度抑郁症的靶点。
背景:梅子(Prunus mume, PM)是一种传统的中草药,以缓解抑郁症而闻名。研究设计:为了阐明其对重度抑郁症(MDD)的潜在治疗效果,需要进一步研究其潜在机制。材料与方法:利用UPLC-QE-MS和中药系统药理学数据库(TCMSP)对中药粉末的成分和靶点进行分析。Gene Expression Omnibus (GEO)数据库确定了mdd相关靶点。富集分析确定了MDD治疗的关键成分,通过蛋白质蛋白质相互作用(PPI)网络和机器学习进行了提炼。分子对接与AutoDock软件评估结合亲和力。结果:共鉴定出35种PM成分和691个靶点。生物信息学揭示了1105个MDD差异表达基因。基因本体(GO)和京都基因与基因组百科全书(KEGG)分析显示,蛋白酶结合、蛋白酪氨酸激酶活性以及mTOR、Ras和VEGF等途径显著富集。PPI网络和机器学习确定了5个中心基因——SELP、MMP8、HK2、ATP1A1和DAO——作为治疗靶点。分子对接分析表明,槲皮素、木犀草素、柽柳西汀、异鼠李素、8-羟基山奈酚、桑虫素等PM成分能有效结合关键靶点。结论:本研究阐明了PM治疗重度抑郁症的有效成分和潜在机制,为未来的治疗靶点和药物开发提供了见解。
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来源期刊
CiteScore
1.70
自引率
12.50%
发文量
116
审稿时长
4-8 weeks
期刊介绍: The International Journal of Clinical Pharmacology and Therapeutics appears monthly and publishes manuscripts containing original material with emphasis on the following topics: Clinical trials, Pharmacoepidemiology - Pharmacovigilance, Pharmacodynamics, Drug disposition and Pharmacokinetics, Quality assurance, Pharmacogenetics, Biotechnological drugs such as cytokines and recombinant antibiotics. Case reports on adverse reactions are also of interest.
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