基于UPLC-Zone TOF-MS/MS联合网络药理学探讨脉复生防治NAFLD作用  

Applying the UPLC-Zone TOF-MS/MS combined network pharmacology to explore the effects of MFS intervention on NAFLD

作　　者：胡涛 王冰钰 苏薇薇[2] 彭维[2] 黎建华 李常青 周毅业 郭洁文 HU Tao;WANG Bingyu;SU Weiwei;PENG Wei;LI Jianhua;LI Changqing;ZHOU Yiye;GUO Jiewen(The Affiliated Traditional Chinese Medicine Hospital,Guangzhou Medical University,Guangzhou510000,China;Guangdong Engineering and Technology Research Center for Quality and Efficacy Re-evaluation ofPost-marketed TCM/Guangdong Key Laboratory of Plant Resources/School of Life Sciences,SunYat-sen University,Guangzhou 510275,China;Center for Artemisinin Research,Guangzhou University of Chinese Medicine,Guangzhou 510006,China)

机构地区：[1]广州医科大学附属中医医院,广东广州510000 [2]广东省中药上市后质量与药效再评价工程技术研究中心/广东省热带亚热带植物资源重点实验室/中山大学生命科学学院,广东广州510275 [3]广州中医药大学青蒿研究中心,广东广州510006

出　　处：《中山大学学报（自然科学版）（中英文）》2024年第5期73-82,共10页Acta Scientiarum Naturalium Universitatis Sunyatseni

基　　金：广州市基础研究计划(2023A03J0781)全文阅读增强出版。

摘　　要：依据脉复生的化学成分,采用网络药理学、分子对接技术、构建NAFLD小鼠模型,探究脉复生防治NAFLD的作用机制。通过UPLC-Zone TOF-MS/MS对脉复生全成分进行检测;借助Swiss生物信息学研究平台获取活性成分和靶点,在OMIM、Disgenet数据库筛选NAFLD疾病靶点,对交集靶点进行PPI分析;在Metascape网站进行GO与KEGG富集分析,对核心靶点与活性成分展开分子对接;采用HFD诱导C57BL/6J小鼠构建NAFLD模型进行核心靶点验证;指认得到130个化学成分,筛选得到54个活性成分与176个可能作用于NAFLD的潜在靶点;根据Degree值对排名前10的成分与靶点进行分子对接实验,对结合能最优的对接模型TNF与Quercetin、IL-17与Asiatic acid、IL-1β与Quercetin进行可视化分析;筛选炎症因子和脂肪代谢相关基因进行qPCR测序。富集分析表明脉复生治疗NAFLD与脂肪酸转化、脂质代谢正向调节等生物过程相关,涉及AGE-RAGE、HIF-1、IL-17等信号通路;与对照组相比,模型组血清学检测ALT、TG、LDL-C指标上升并且HDL-C指标下降(P<0.05);与模型组相比,脉复生给药组和辛伐他汀组能够降低小鼠体质量、肝脏和脂肪质量占比(P<0.05),降低血清中TNF-α、IL-1β和IL-17的含量和mRNA表达,在高剂量时具有显著性差异(P<0.01);与对照组相比,脉复生给药组能够通过调节脂质代谢相关基因的表达,降低肝脏脂质堆积,缓解肝脏脂肪变性。The mechanism of MaiFuSheng(MFS)on inhibiting Nonalcoholic Fatty Liver Disease(NAFLD)were investigated based on the exploration of chemical compositions,the techniques of network pharmacology and molecular docking,and the validation using NAFLD mice model.The components of MFS were identified through UPLC-Zeno TOF-MS/MS.The Swiss Bioinformatics Research Platform were applied to obtain active components and potential targets of MFS.The DisGeNet and OMIM databases were used to screen disease targets of NAFLD.The intersection between disease targets and potential targets of MFS were obtained from Venn diagram,which were analyzed by constructing cross-target protein-protein interaction(PPI)network.The Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment were conducted on Metascape database.The molecular docking about core targets and active components of MFS were carried out.Using high-fat diet(HFD)-induced C57BL/6J mice as NAFLD animal model to validate key targets.A total of 130 compounds were recognized,54 active constituents and 176 potential targets of NAFLD were collected.The molecular docking experiments for the top 10 components with the targets are based on the degree value.We found docking models with the best binding energy for TNF-αwith Quercetin,IL-17 with Asiatic acid,and IL-1βwith Quercetin.We applied qPCR technique to detect above inflammation and lipid metabolism related indicators.Enrichment analysis demonstrated that MFS protects NAFLD via biological processes such as fatty acid transformation and positive regulation of lipid metabolism,as well as signaling pathways such as AGE-RAGE,HIF-1,and IL-17.Compared to the control groups,the model group's ALT,TG,and LDL-C indicators increased,whereas HDL-C indicators dropped(P<0.05).MFS and Simvastatin treatment groups significantly reduced body weight,liver weight,and fat weight compared to the model groups(P<0.05).Higher doses resulted in significant reductions in serum levels and expression of TNF-α,IL-1β,and IL-17(P<0.01).Com

关 键 词：UPLC-Zone TOF-MS/MS 脉复生 非酒精性脂肪肝 网络药理学 实验验证 

分 类 号：R285.5[医药卫生—中药学]