Li Wei-Xia, Xu Shuang, Chen Yu-Long, Wang Xiao-Yan, Zhang Hui, Zhang Ming-Liang, Ni Wen-Juan, Ren Xian-Qing, Tang Jin-Fa
the First Affiliated Hospital of Henan University of Chinese Medicine Zhengzhou 450000, China Henan Province Engineering Research Center of Safety Evaluation and Risk Management of Traditional Chinese Medicine,Henan Provincial Key Laboratory for Clinical Pharmacy of Traditional Chinese Medicine,Henan Province Engineering Research Center of Clinical Application, Evaluation and Transformation of Traditional Chinese Medicine Zhengzhou 450000, China.
the First Affiliated Hospital of Henan University of Chinese Medicine Zhengzhou 450000, China School of Pediatrics, Henan University of Chinese Medicine Zhengzhou 450046, China.
Zhongguo Zhong Yao Za Zhi. 2023 Jun;48(12):3327-3344. doi: 10.19540/j.cnki.cjcmm.20230117.705.
Ultra-performance liquid chromatography-quadrupole time of fight/mass spectrometry(UPLC-Q-TOF-MS) and UNIFI were employed to rapidly determine the content of the components in Liangxue Tuizi Mixture. The targets of the active components and Henoch-Schönlein purpura(HSP) were obtained from SwissTargetPrediction, Online Mendelian Inheritance in Man(OMIM), and GeneCards. A "component-target-disease" network and a protein-protein interaction(PPI) network were constructed. Gene Ontology(GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed for the targets by Omishare. The interactions between the potential active components and the core targets were verified by molecular docking. Furthermore, rats were randomly assigned into a normal group, a model group, and low-, medium-, and high-dose Liangxue Tuizi Mixture groups. Non-targeted metabolomics was employed to screen the differential metabolites in the serum, analyze possible metabolic pathways, and construct the "component-target-differential metabolite" network. A total of 45 components of Liangxue Tuizi Mixture were identified, and 145 potential targets for the treatment of HSP were predicted. The main signaling pathways enriched included resistance to epidermal growth factor receptor tyrosine kinase inhibitors, phosphatidylinositol 3-kinase/protein kinase B(PI3K-AKT), and T cell receptor. The results of molecular docking showed that the active components in Liangxue Tuizi Mixture had strong binding ability with the key target proteins. A total of 13 differential metabolites in the serum were screened out, which shared 27 common targets with active components. The progression of HSP was related to metabolic abnormalities of glycerophospholipid and sphingolipid. The results indicate that the components in Liangxue Tuizi Mixture mainly treats HSP by regulating inflammation and immunity, providing a scientific basis for rational drug use in clinical practice.
采用超高效液相色谱-四极杆飞行时间质谱联用仪（UPLC-Q-TOF-MS）和UNIFI快速测定凉血退紫合剂中各成分的含量。活性成分的作用靶点及过敏性紫癜（HSP）相关靶点分别来源于SwissTargetPrediction、在线人类孟德尔遗传数据库（OMIM）和基因卡片数据库（GeneCards）。构建了“成分-靶点-疾病”网络和蛋白质-蛋白质相互作用（PPI）网络。通过Omishare对靶点进行基因本体论（GO）功能注释和京都基因与基因组百科全书（KEGG）通路富集分析。通过分子对接验证潜在活性成分与核心靶点之间的相互作用。此外，将大鼠随机分为正常组、模型组、凉血退紫合剂低、中、高剂量组。采用非靶向代谢组学技术筛选血清中的差异代谢物，分析可能的代谢途径，并构建“成分-靶点-差异代谢物”网络。共鉴定出凉血退紫合剂中的45种成分，预测出145个治疗HSP的潜在靶点。富集的主要信号通路包括对表皮生长因子受体酪氨酸激酶抑制剂的抗性、磷脂酰肌醇3激酶/蛋白激酶B（PI3K-AKT）和T细胞受体。分子对接结果表明，凉血退紫合剂中的活性成分与关键靶蛋白具有较强的结合能力。共筛选出13种血清差异代谢物，它们与活性成分共有27个共同靶点。HSP的进展与甘油磷脂和鞘脂的代谢异常有关。结果表明，凉血退紫合剂中的成分主要通过调节炎症和免疫来治疗HSP，为临床合理用药提供了科学依据。
