PDF(Pubmed)
Abstract：
BACKGROUND: Drug research is increasingly using Network Pharmacology (NP) to tackle complex conditions like Metabolic Syndrome (MetS), which is characterized by obesity, hyperglycemia, and dyslipidemia. Single-action drugs are inadequate to treat MetS, which is marked by a range of complications including glucose intolerance, hyperlipidemia, mitochondrial dysfunction, and inflammation.
OBJECTIVE: To analyze Chandraprabha vati using Network Pharmacology to assess its potential in alleviating MetS-related complications.
METHODS: The genes related to MetS, inflammation, and the target genes of the CPV components were identified using network pharmacology tools like DisgNET and BindingDB. Followed by mapping of the CPV target genes with the genes implicated in MetS and inflammation to identify putative potential targets. Gene ontology, pathway enrichment analysis, and STRING database were employed for further exploration. Furthermore, drug-target-protein interactions network were visualized using Cytoscape 3.9.1.
RESULTS: The results showed that out of the 225 target genes of the CPV components, 33 overlapping and 19 non-overlapping genes could be potential targets for MetS. Similarly, 14 overlapping and 7 non-overlapping genes could be potential targets for inflammation. The CPV bioactives target genes were found to be involved in lipid and insulin homeostasis via several pathways revealed by the pathway analysis. The importance of CPV in treating MetS was supported by GO enrichment data; this could be due to its potential to influence pathways linked to metabolism, ER stress, mitochondrial dysfunction, oxidative stress, and inflammation.
CONCLUSIONS: These results offer a promising approach to developing treatment and repurposing CPV for complex conditions such as MetS.
OBJECTIVE: To analyze Chandraprabha vati using Network Pharmacology to assess its potential in alleviating MetS-related complications.
METHODS: The genes related to MetS, inflammation, and the target genes of the CPV components were identified using network pharmacology tools like DisgNET and BindingDB. Followed by mapping of the CPV target genes with the genes implicated in MetS and inflammation to identify putative potential targets. Gene ontology, pathway enrichment analysis, and STRING database were employed for further exploration. Furthermore, drug-target-protein interactions network were visualized using Cytoscape 3.9.1.
RESULTS: The results showed that out of the 225 target genes of the CPV components, 33 overlapping and 19 non-overlapping genes could be potential targets for MetS. Similarly, 14 overlapping and 7 non-overlapping genes could be potential targets for inflammation. The CPV bioactives target genes were found to be involved in lipid and insulin homeostasis via several pathways revealed by the pathway analysis. The importance of CPV in treating MetS was supported by GO enrichment data; this could be due to its potential to influence pathways linked to metabolism, ER stress, mitochondrial dysfunction, oxidative stress, and inflammation.
CONCLUSIONS: These results offer a promising approach to developing treatment and repurposing CPV for complex conditions such as MetS.
摘要：
背景：药物研究越来越多地使用网络药理学（NP）来解决代谢综合征（MetS）等复杂疾病，以肥胖为特征，高血糖症,和血脂异常。单一作用药物不足以治疗MetS，其特征是一系列并发症，包括葡萄糖不耐受，高脂血症,线粒体功能障碍，和炎症。
目的：使用网络药理学分析Chandraprabhavati，以评估其缓解MetS相关并发症的潜力。
方法：与MetS相关的基因，炎症,和CPV组件的目标基因鉴定使用网络药理学工具，如DisgNET和BindingDB。随后用与MetS和炎症有关的基因对CPV靶基因进行定位以鉴定推定的潜在靶标。基因本体论，途径富集分析，和STRING数据库进行了进一步的探索。此外，使用Cytoscape3.9.1可视化药物-靶-蛋白相互作用网络。
结果：结果表明，在CPV成分的225个靶基因中，33个重叠和19个非重叠基因可能是MetS的潜在靶标。同样，14个重叠和7个非重叠基因可能是炎症的潜在靶标。发现CPV生物活性靶基因通过途径分析揭示的几种途径参与脂质和胰岛素稳态。GO富集数据支持CPV在治疗MetS中的重要性；这可能是由于其影响与代谢有关的途径的潜力。ER压力,线粒体功能障碍，氧化应激，和炎症。
结论：这些结果为开发针对MetS等复杂疾病的治疗和重新利用CPV提供了有希望的方法。
目的：使用网络药理学分析Chandraprabhavati，以评估其缓解MetS相关并发症的潜力。
方法：与MetS相关的基因，炎症,和CPV组件的目标基因鉴定使用网络药理学工具，如DisgNET和BindingDB。随后用与MetS和炎症有关的基因对CPV靶基因进行定位以鉴定推定的潜在靶标。基因本体论，途径富集分析，和STRING数据库进行了进一步的探索。此外，使用Cytoscape3.9.1可视化药物-靶-蛋白相互作用网络。
结果：结果表明，在CPV成分的225个靶基因中，33个重叠和19个非重叠基因可能是MetS的潜在靶标。同样，14个重叠和7个非重叠基因可能是炎症的潜在靶标。发现CPV生物活性靶基因通过途径分析揭示的几种途径参与脂质和胰岛素稳态。GO富集数据支持CPV在治疗MetS中的重要性；这可能是由于其影响与代谢有关的途径的潜力。ER压力,线粒体功能障碍，氧化应激，和炎症。
结论：这些结果为开发针对MetS等复杂疾病的治疗和重新利用CPV提供了有希望的方法。
