Chigateri M Vinay, Kannath U Sanjay, Manjunath B Joshi, Padmalatha S Rai
{"title":"以代谢紊乱为靶点的铁杉属植物代谢物指纹的变化:一种综合代谢组学和网络药理学方法。","authors":"Chigateri M Vinay, Kannath U Sanjay, Manjunath B Joshi, Padmalatha S Rai","doi":"10.1007/s11306-024-02209-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Metabolic disorders are a global health concern, necessitating the development of drugs with fewer side effects and more efficacy. Traditional Indian medicine uses Tinospora cordifolia and Tinospora sinensis, but their metabolite fingerprints and impact on geographical location remains unknown.</p><p><strong>Objective: </strong>The present study aimed to identify metabolite fingerprints from T. cordifolia and T. sinensis species from different geographic locations and also to identify potential quality markers for treating metabolic disorders.</p><p><strong>Methods: </strong>Non-targeted metabolite fingerprinting of T. cordifolia and T. sinensis was performed using HPLC-QTOF-MS/MS analysis. Network pharmacology, molecular docking and molecular dynamics simulation analysis were performed to identify potential quality markers, hub targets, and key pathways associated with metabolic disorders.</p><p><strong>Results: </strong>In this study, six potential marker compounds and twenty-five differential compounds were identified between T. cordifolia and T. sinensis. Based on geography, five and one metabolite marker compounds were identified in T. cordifolia and T. sinensis respectively. Network pharmacology, molecular docking, and molecular dynamics simulation analysis revealed trans piceid, crustecdysone in T. cordifolia, and gallic acid in T. sinensis as potential quality markers against metabolic disorder related hub targets.</p><p><strong>Conclusion: </strong>Integration of non-targeted metabolomics and network pharmacology approach deciphers the pharmacological mechanism of action in terms of identifying potential quality markers from Tinospora species that can be used against metabolic disorders. However, further research is required to validate these findings in in vitro and in vivo studies for better assertion.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 1","pages":"11"},"PeriodicalIF":3.5000,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Variations in metabolite fingerprints of Tinospora species targeting metabolic disorders: an integrated metabolomics and network pharmacology approach.\",\"authors\":\"Chigateri M Vinay, Kannath U Sanjay, Manjunath B Joshi, Padmalatha S Rai\",\"doi\":\"10.1007/s11306-024-02209-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Metabolic disorders are a global health concern, necessitating the development of drugs with fewer side effects and more efficacy. Traditional Indian medicine uses Tinospora cordifolia and Tinospora sinensis, but their metabolite fingerprints and impact on geographical location remains unknown.</p><p><strong>Objective: </strong>The present study aimed to identify metabolite fingerprints from T. cordifolia and T. sinensis species from different geographic locations and also to identify potential quality markers for treating metabolic disorders.</p><p><strong>Methods: </strong>Non-targeted metabolite fingerprinting of T. cordifolia and T. sinensis was performed using HPLC-QTOF-MS/MS analysis. Network pharmacology, molecular docking and molecular dynamics simulation analysis were performed to identify potential quality markers, hub targets, and key pathways associated with metabolic disorders.</p><p><strong>Results: </strong>In this study, six potential marker compounds and twenty-five differential compounds were identified between T. cordifolia and T. sinensis. Based on geography, five and one metabolite marker compounds were identified in T. cordifolia and T. sinensis respectively. Network pharmacology, molecular docking, and molecular dynamics simulation analysis revealed trans piceid, crustecdysone in T. cordifolia, and gallic acid in T. sinensis as potential quality markers against metabolic disorder related hub targets.</p><p><strong>Conclusion: </strong>Integration of non-targeted metabolomics and network pharmacology approach deciphers the pharmacological mechanism of action in terms of identifying potential quality markers from Tinospora species that can be used against metabolic disorders. However, further research is required to validate these findings in in vitro and in vivo studies for better assertion.</p>\",\"PeriodicalId\":18506,\"journal\":{\"name\":\"Metabolomics\",\"volume\":\"21 1\",\"pages\":\"11\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metabolomics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11306-024-02209-9\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11306-024-02209-9","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Variations in metabolite fingerprints of Tinospora species targeting metabolic disorders: an integrated metabolomics and network pharmacology approach.
Introduction: Metabolic disorders are a global health concern, necessitating the development of drugs with fewer side effects and more efficacy. Traditional Indian medicine uses Tinospora cordifolia and Tinospora sinensis, but their metabolite fingerprints and impact on geographical location remains unknown.
Objective: The present study aimed to identify metabolite fingerprints from T. cordifolia and T. sinensis species from different geographic locations and also to identify potential quality markers for treating metabolic disorders.
Methods: Non-targeted metabolite fingerprinting of T. cordifolia and T. sinensis was performed using HPLC-QTOF-MS/MS analysis. Network pharmacology, molecular docking and molecular dynamics simulation analysis were performed to identify potential quality markers, hub targets, and key pathways associated with metabolic disorders.
Results: In this study, six potential marker compounds and twenty-five differential compounds were identified between T. cordifolia and T. sinensis. Based on geography, five and one metabolite marker compounds were identified in T. cordifolia and T. sinensis respectively. Network pharmacology, molecular docking, and molecular dynamics simulation analysis revealed trans piceid, crustecdysone in T. cordifolia, and gallic acid in T. sinensis as potential quality markers against metabolic disorder related hub targets.
Conclusion: Integration of non-targeted metabolomics and network pharmacology approach deciphers the pharmacological mechanism of action in terms of identifying potential quality markers from Tinospora species that can be used against metabolic disorders. However, further research is required to validate these findings in in vitro and in vivo studies for better assertion.
期刊介绍:
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.