Qiwen Xuan, Yi Ruan, Zifei Yin, Wei Gu, Changquan Ling
{"title":"结合血清药物化学和网络药理学,探讨仙参方预防运动性疲劳的可能机制。","authors":"Qiwen Xuan, Yi Ruan, Zifei Yin, Wei Gu, Changquan Ling","doi":"10.1016/j.fitote.2025.106621","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>On the basis of exploring the efficacy of XSF, the material basis and mechanism of XSF for the prevention of exercise-induced fatigue were clarified by network pharmacology using blood-absorbed components as the research object.</p><p><strong>Methods: </strong>UPLC-Q-TOF/MS was used to identify the blood components of XSF. On this basis, the target prediction of the blood-entering components was obtained from the Swiss Target Prediction and SuperPred database, and the target related to exercise-induced fatigue was acquired from OMIM, GeneCards, and other disease databases. The network model of \" components- targets-diseases\" of XSF was established by Cytoscape software. The String data analysis platform was used to build the PPI network to filter out the primary targets. The DAVID database was used for gene ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the key targets.</p><p><strong>Results: </strong>Administration of XSF increased swimming time, decreased BLA, BUN, and MDA levels, and elevated SOD levels in swimming exhausted rats and mice. A total of 60 in vitro active ingredients, 45 blood-entry prototype ingredients, and 41 blood-entry metabolized ingredients were identified. Out of 717 possible targets of action between medication components and exercise exhaustion, network pharmacology identified 176 nodes with a maximum value of TP53 (Degree = 81) according to PPI analysis. The key targets were involved in 96 KEGG pathways including the PI3K-Akt signaling pathway, MAPK signaling pathway, HIF-1 signaling pathway TNF signaling pathway, and 170 GO pathways. The top 10 targets in the \"component-target-pathway\" network of XSF against EIF were predicted to be NFKB1, PIK3R1, GRIN1, CACNA1B, SLC6A5, NTRK3, GRIA2, TRIM24, TOP2A, TLR4 and RORB, TLR4 and RORB.</p><p><strong>Conclusion: </strong>XSF is effective in the prevention of EIF and its potential pharmacological mechanisms may be related to the improvement of energy metabolism, regulation of inflammatory response, and regulation of oxidative stress.</p>","PeriodicalId":12147,"journal":{"name":"Fitoterapia","volume":" ","pages":"106621"},"PeriodicalIF":2.5000,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating serum pharmacochemistry and network pharmacology to explore the potential mechanisms of Xianshen formula in the prevention of exercise-induced fatigue.\",\"authors\":\"Qiwen Xuan, Yi Ruan, Zifei Yin, Wei Gu, Changquan Ling\",\"doi\":\"10.1016/j.fitote.2025.106621\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>On the basis of exploring the efficacy of XSF, the material basis and mechanism of XSF for the prevention of exercise-induced fatigue were clarified by network pharmacology using blood-absorbed components as the research object.</p><p><strong>Methods: </strong>UPLC-Q-TOF/MS was used to identify the blood components of XSF. On this basis, the target prediction of the blood-entering components was obtained from the Swiss Target Prediction and SuperPred database, and the target related to exercise-induced fatigue was acquired from OMIM, GeneCards, and other disease databases. The network model of \\\" components- targets-diseases\\\" of XSF was established by Cytoscape software. The String data analysis platform was used to build the PPI network to filter out the primary targets. The DAVID database was used for gene ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the key targets.</p><p><strong>Results: </strong>Administration of XSF increased swimming time, decreased BLA, BUN, and MDA levels, and elevated SOD levels in swimming exhausted rats and mice. A total of 60 in vitro active ingredients, 45 blood-entry prototype ingredients, and 41 blood-entry metabolized ingredients were identified. Out of 717 possible targets of action between medication components and exercise exhaustion, network pharmacology identified 176 nodes with a maximum value of TP53 (Degree = 81) according to PPI analysis. The key targets were involved in 96 KEGG pathways including the PI3K-Akt signaling pathway, MAPK signaling pathway, HIF-1 signaling pathway TNF signaling pathway, and 170 GO pathways. 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引用次数: 0
摘要
目的:在探讨XSF疗效的基础上,以血吸收成分为研究对象,运用网络药理学方法阐明XSF预防运动性疲劳的物质基础和作用机制。方法:采用UPLC-Q-TOF/MS对XSF血液成分进行鉴定。在此基础上,从Swiss target prediction and SuperPred数据库中获得血液进入成分的靶标预测,从OMIM、GeneCards等疾病数据库中获得运动性疲劳相关靶标。利用Cytoscape软件建立了XSF“组分-靶点-病害”网络模型。利用字符串数据分析平台构建PPI网络,过滤出主要目标。利用DAVID数据库对关键靶点进行基因本体(GO)富集分析和京都基因与基因组百科全书(KEGG)途径富集分析。结果:XSF增加了游泳疲劳大鼠和小鼠的游泳时间,降低了BLA、BUN和MDA水平,升高了SOD水平。共鉴定出60种体外活性成分,45种血液进入原型成分,41种血液进入代谢成分。在717个药物成分与运动衰竭可能的作用靶点中,网络药理学根据PPI分析鉴定出TP53最大值的176个节点(度 = 81)。关键靶点涉及96条KEGG通路,包括PI3K-Akt信号通路、MAPK信号通路、HIF-1信号通路、TNF信号通路和170条GO信号通路。预测XSF抗EIF“组件-目标-通路”网络中的前10个靶点分别为NFKB1、PIK3R1、GRIN1、CACNA1B、SLC6A5、NTRK3、GRIA2、TRIM24、TOP2A、TLR4和RORB、TLR4和RORB。结论:XSF具有预防EIF的作用,其潜在的药理机制可能与改善能量代谢、调节炎症反应、调节氧化应激有关。
Integrating serum pharmacochemistry and network pharmacology to explore the potential mechanisms of Xianshen formula in the prevention of exercise-induced fatigue.
Objective: On the basis of exploring the efficacy of XSF, the material basis and mechanism of XSF for the prevention of exercise-induced fatigue were clarified by network pharmacology using blood-absorbed components as the research object.
Methods: UPLC-Q-TOF/MS was used to identify the blood components of XSF. On this basis, the target prediction of the blood-entering components was obtained from the Swiss Target Prediction and SuperPred database, and the target related to exercise-induced fatigue was acquired from OMIM, GeneCards, and other disease databases. The network model of " components- targets-diseases" of XSF was established by Cytoscape software. The String data analysis platform was used to build the PPI network to filter out the primary targets. The DAVID database was used for gene ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the key targets.
Results: Administration of XSF increased swimming time, decreased BLA, BUN, and MDA levels, and elevated SOD levels in swimming exhausted rats and mice. A total of 60 in vitro active ingredients, 45 blood-entry prototype ingredients, and 41 blood-entry metabolized ingredients were identified. Out of 717 possible targets of action between medication components and exercise exhaustion, network pharmacology identified 176 nodes with a maximum value of TP53 (Degree = 81) according to PPI analysis. The key targets were involved in 96 KEGG pathways including the PI3K-Akt signaling pathway, MAPK signaling pathway, HIF-1 signaling pathway TNF signaling pathway, and 170 GO pathways. The top 10 targets in the "component-target-pathway" network of XSF against EIF were predicted to be NFKB1, PIK3R1, GRIN1, CACNA1B, SLC6A5, NTRK3, GRIA2, TRIM24, TOP2A, TLR4 and RORB, TLR4 and RORB.
Conclusion: XSF is effective in the prevention of EIF and its potential pharmacological mechanisms may be related to the improvement of energy metabolism, regulation of inflammatory response, and regulation of oxidative stress.
期刊介绍:
Fitoterapia is a Journal dedicated to medicinal plants and to bioactive natural products of plant origin. It publishes original contributions in seven major areas:
1. Characterization of active ingredients of medicinal plants
2. Development of standardization method for bioactive plant extracts and natural products
3. Identification of bioactivity in plant extracts
4. Identification of targets and mechanism of activity of plant extracts
5. Production and genomic characterization of medicinal plants biomass
6. Chemistry and biochemistry of bioactive natural products of plant origin
7. Critical reviews of the historical, clinical and legal status of medicinal plants, and accounts on topical issues.