{"title":"综合研究网络药理学、计算模型和药代动力学评估,评估类黄酮对类风湿性关节炎的疗效。","authors":"Sukanya Vijayan, Thirumal Margesan","doi":"10.1007/s11030-024-10989-4","DOIUrl":null,"url":null,"abstract":"<p><p>Rheumatoid arthritis is a chronic autoimmune disease characterized by inflammation and joint damage, imposing a significant burden on affected individuals worldwide. Flavonoids, a class of natural compounds abundant in various plant-based foods, have shown promising anti-inflammatory and immunomodulatory effects, suggesting their potential as therapeutic agents for RA. In this study, we conducted a comprehensive investigation of identified LCMS compounds utilizing network pharmacology, computational modeling, in silico approaches, and pharmacokinetic assessment to evaluate the efficacy of flavonoids in RA treatment. The study identified 5 flavonoid structures with common targets via LCMS and Integration of network pharmacology approaches enabled a comprehensive evaluation of the pharmacological profile of flavonoids in the context of RA treatment, guiding the selection of promising candidates for further experimental validation and clinical development. The top 10 targets were AKT1, PI3KR1, CDK2, EGFR, CDK6, NOS2, FLT3, ALOX5, CCNB1, and PTPRS via PPI network. The investigation emphasized several pathways, including the AGE-RAGE signaling pathway, resistance to EGFR tyrosine kinase inhibitors, the PI3K-AKT signaling network, and the Rap 1 signaling pathway. In silico studies estimated binding affinities that ranged from - 7.0 to - 10.0 kcal/mol. Schaftoside and Vitexin showed no toxicity in computational approach and found suitable for further investigations. Overall, our study underscores the potential of flavonoids as therapeutic agents for RA and highlights the utility of integrative approaches combining network pharmacology, computational modeling, in silico methods, and pharmacokinetic assessment in drug discovery and development processes.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive investigation of network pharmacology, computational modeling, and pharmacokinetic assessment to evaluate the efficacy of flavonoids in rheumatoid arthritis.\",\"authors\":\"Sukanya Vijayan, Thirumal Margesan\",\"doi\":\"10.1007/s11030-024-10989-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Rheumatoid arthritis is a chronic autoimmune disease characterized by inflammation and joint damage, imposing a significant burden on affected individuals worldwide. Flavonoids, a class of natural compounds abundant in various plant-based foods, have shown promising anti-inflammatory and immunomodulatory effects, suggesting their potential as therapeutic agents for RA. In this study, we conducted a comprehensive investigation of identified LCMS compounds utilizing network pharmacology, computational modeling, in silico approaches, and pharmacokinetic assessment to evaluate the efficacy of flavonoids in RA treatment. The study identified 5 flavonoid structures with common targets via LCMS and Integration of network pharmacology approaches enabled a comprehensive evaluation of the pharmacological profile of flavonoids in the context of RA treatment, guiding the selection of promising candidates for further experimental validation and clinical development. The top 10 targets were AKT1, PI3KR1, CDK2, EGFR, CDK6, NOS2, FLT3, ALOX5, CCNB1, and PTPRS via PPI network. The investigation emphasized several pathways, including the AGE-RAGE signaling pathway, resistance to EGFR tyrosine kinase inhibitors, the PI3K-AKT signaling network, and the Rap 1 signaling pathway. In silico studies estimated binding affinities that ranged from - 7.0 to - 10.0 kcal/mol. Schaftoside and Vitexin showed no toxicity in computational approach and found suitable for further investigations. Overall, our study underscores the potential of flavonoids as therapeutic agents for RA and highlights the utility of integrative approaches combining network pharmacology, computational modeling, in silico methods, and pharmacokinetic assessment in drug discovery and development processes.</p>\",\"PeriodicalId\":708,\"journal\":{\"name\":\"Molecular Diversity\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Diversity\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1007/s11030-024-10989-4\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Diversity","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s11030-024-10989-4","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
Comprehensive investigation of network pharmacology, computational modeling, and pharmacokinetic assessment to evaluate the efficacy of flavonoids in rheumatoid arthritis.
Rheumatoid arthritis is a chronic autoimmune disease characterized by inflammation and joint damage, imposing a significant burden on affected individuals worldwide. Flavonoids, a class of natural compounds abundant in various plant-based foods, have shown promising anti-inflammatory and immunomodulatory effects, suggesting their potential as therapeutic agents for RA. In this study, we conducted a comprehensive investigation of identified LCMS compounds utilizing network pharmacology, computational modeling, in silico approaches, and pharmacokinetic assessment to evaluate the efficacy of flavonoids in RA treatment. The study identified 5 flavonoid structures with common targets via LCMS and Integration of network pharmacology approaches enabled a comprehensive evaluation of the pharmacological profile of flavonoids in the context of RA treatment, guiding the selection of promising candidates for further experimental validation and clinical development. The top 10 targets were AKT1, PI3KR1, CDK2, EGFR, CDK6, NOS2, FLT3, ALOX5, CCNB1, and PTPRS via PPI network. The investigation emphasized several pathways, including the AGE-RAGE signaling pathway, resistance to EGFR tyrosine kinase inhibitors, the PI3K-AKT signaling network, and the Rap 1 signaling pathway. In silico studies estimated binding affinities that ranged from - 7.0 to - 10.0 kcal/mol. Schaftoside and Vitexin showed no toxicity in computational approach and found suitable for further investigations. Overall, our study underscores the potential of flavonoids as therapeutic agents for RA and highlights the utility of integrative approaches combining network pharmacology, computational modeling, in silico methods, and pharmacokinetic assessment in drug discovery and development processes.
期刊介绍:
Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including:
combinatorial chemistry and parallel synthesis;
small molecule libraries;
microwave synthesis;
flow synthesis;
fluorous synthesis;
diversity oriented synthesis (DOS);
nanoreactors;
click chemistry;
multiplex technologies;
fragment- and ligand-based design;
structure/function/SAR;
computational chemistry and molecular design;
chemoinformatics;
screening techniques and screening interfaces;
analytical and purification methods;
robotics, automation and miniaturization;
targeted libraries;
display libraries;
peptides and peptoids;
proteins;
oligonucleotides;
carbohydrates;
natural diversity;
new methods of library formulation and deconvolution;
directed evolution, origin of life and recombination;
search techniques, landscapes, random chemistry and more;