Maryam Qasmi, Muhammad Mazhar Fareed, Haider Ali, Zarmina Khan, Sergey Shityakov
{"title":"治疗痛风性关节炎的荨麻多靶点综合分析:一种网络药理学和聚类方法。","authors":"Maryam Qasmi, Muhammad Mazhar Fareed, Haider Ali, Zarmina Khan, Sergey Shityakov","doi":"10.1007/s40203-024-00254-9","DOIUrl":null,"url":null,"abstract":"<p><p><i>Urtica dioica</i> (stinging nettle) has been traditionally used in Chinese medicine for the treatment of joint pain and rheumatoid arthritis. This study aims to elucidate the active compounds and mechanisms by which it acts against gout arthritis (GA). Gout-related genes were identified from the DisGeNet, GeneCards, and OMIM databases. These genes may play a role in inhibiting corresponding proteins targeted by the active compounds identified from the literature, which have an oral bioavailability of ≥ 30% and a drug-likeness score of ≥ 0.18. A human protein-protein interaction network was constructed, resulting in sixteen clusters containing plant-targeted genes, including ABCG2, SLC22A12, MAP2K7, ADCY10, RELA, and TP53. The key bioactive compounds, apigenin-7-O-glucoside and kaempferol, demonstrated significant binding to SLC22A12 and ABCG2, suggesting their potential to reduce uric acid levels and inflammation. Pathway enrichment analysis further identified key metabolic pathways involved, highlighting a dual mechanism of anti-inflammatory and urate-lowering effects. These findings underscore the potential of <i>U. dioica</i> in targeting multiple pathways involved in GA, combining traditional medicine with modern pharmacology. This integrated approach provides a foundation for future research and the development of multi-target therapeutic strategies for managing gout arthritis.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00254-9.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 2","pages":"88"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438756/pdf/","citationCount":"0","resultStr":"{\"title\":\"Integrative multi-target analysis of <i>Urtica dioica</i> for gout arthritis treatment: a network pharmacology and clustering approach.\",\"authors\":\"Maryam Qasmi, Muhammad Mazhar Fareed, Haider Ali, Zarmina Khan, Sergey Shityakov\",\"doi\":\"10.1007/s40203-024-00254-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><i>Urtica dioica</i> (stinging nettle) has been traditionally used in Chinese medicine for the treatment of joint pain and rheumatoid arthritis. This study aims to elucidate the active compounds and mechanisms by which it acts against gout arthritis (GA). Gout-related genes were identified from the DisGeNet, GeneCards, and OMIM databases. These genes may play a role in inhibiting corresponding proteins targeted by the active compounds identified from the literature, which have an oral bioavailability of ≥ 30% and a drug-likeness score of ≥ 0.18. A human protein-protein interaction network was constructed, resulting in sixteen clusters containing plant-targeted genes, including ABCG2, SLC22A12, MAP2K7, ADCY10, RELA, and TP53. The key bioactive compounds, apigenin-7-O-glucoside and kaempferol, demonstrated significant binding to SLC22A12 and ABCG2, suggesting their potential to reduce uric acid levels and inflammation. Pathway enrichment analysis further identified key metabolic pathways involved, highlighting a dual mechanism of anti-inflammatory and urate-lowering effects. These findings underscore the potential of <i>U. dioica</i> in targeting multiple pathways involved in GA, combining traditional medicine with modern pharmacology. This integrated approach provides a foundation for future research and the development of multi-target therapeutic strategies for managing gout arthritis.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00254-9.</p>\",\"PeriodicalId\":94038,\"journal\":{\"name\":\"In silico pharmacology\",\"volume\":\"12 2\",\"pages\":\"88\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438756/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"In silico pharmacology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40203-024-00254-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"In silico pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40203-024-00254-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
荨麻(荨麻)历来被中医用于治疗关节疼痛和类风湿性关节炎。本研究旨在阐明荨麻的活性化合物及其对痛风性关节炎(GA)的作用机制。研究人员从 DisGeNet、GeneCards 和 OMIM 数据库中发现了痛风相关基因。这些基因可能在抑制文献中发现的活性化合物所针对的相应蛋白质方面发挥作用,这些活性化合物的口服生物利用度≥30%,药物相似度得分≥0.18。构建的人类蛋白质-蛋白质相互作用网络产生了 16 个包含植物靶向基因的基因簇,包括 ABCG2、SLC22A12、MAP2K7、ADCY10、RELA 和 TP53。关键的生物活性化合物芹菜素-7-O-葡萄糖苷和山奈酚与 SLC22A12 和 ABCG2 有明显的结合,表明它们具有降低尿酸水平和减少炎症的潜力。通路富集分析进一步确定了所涉及的关键代谢通路,突出了抗炎和降尿酸作用的双重机制。这些发现强调了 U. dioica 在靶向参与 GA 的多种途径方面的潜力,将传统医学与现代药理学相结合。这种综合方法为未来的研究和开发治疗痛风性关节炎的多靶点治疗策略奠定了基础:在线版本包含补充材料,可查阅 10.1007/s40203-024-00254-9。
Integrative multi-target analysis of Urtica dioica for gout arthritis treatment: a network pharmacology and clustering approach.
Urtica dioica (stinging nettle) has been traditionally used in Chinese medicine for the treatment of joint pain and rheumatoid arthritis. This study aims to elucidate the active compounds and mechanisms by which it acts against gout arthritis (GA). Gout-related genes were identified from the DisGeNet, GeneCards, and OMIM databases. These genes may play a role in inhibiting corresponding proteins targeted by the active compounds identified from the literature, which have an oral bioavailability of ≥ 30% and a drug-likeness score of ≥ 0.18. A human protein-protein interaction network was constructed, resulting in sixteen clusters containing plant-targeted genes, including ABCG2, SLC22A12, MAP2K7, ADCY10, RELA, and TP53. The key bioactive compounds, apigenin-7-O-glucoside and kaempferol, demonstrated significant binding to SLC22A12 and ABCG2, suggesting their potential to reduce uric acid levels and inflammation. Pathway enrichment analysis further identified key metabolic pathways involved, highlighting a dual mechanism of anti-inflammatory and urate-lowering effects. These findings underscore the potential of U. dioica in targeting multiple pathways involved in GA, combining traditional medicine with modern pharmacology. This integrated approach provides a foundation for future research and the development of multi-target therapeutic strategies for managing gout arthritis.
Graphical abstract:
Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00254-9.