A computational drug-target network for yuanhu zhitong prescription.
A computational drug-target network for yuanhu zhitong prescription.
复制标题
元胡止痛方计算药物靶点网络
DOI：
10.1155/2013/658531
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Huang L
中科院分区：
文献类型：
--
作者：
Xu H;Tao Y;Lu P;Wang P;Zhang F;Yuan Y;Wang S;Xiao X;Yang H;Huang L
元胡止痛方是一种典型的、相对简单的中药方剂，临床上广泛用于治疗头痛、胃痛、痛经等。然而，YZP作用的潜在分子机制尚不清楚。在本研究中，基于先前的化学和代谢物分析，开发了一种复杂的方法，包括预测代谢物的结构，高通量的计算机筛选，以及网络重建和分析，以获得YZP的计算药物-靶标网络。随后通过CNOGO进行功能和途径分析，以确定一些药理学活性。此外，通过斑马鱼和小鼠模型的动物实验验证了YZP的两种新药理作用，即抗抑郁和抗焦虑。强迫游泳实验和悬尾实验结果表明，YZP 4 mg/kg和8 mg/kg剂量组的抗抑郁作用优于对照组。抗焦虑活性实验表明，YZP在100、150、200 mg/L剂量下，与对照组相比，具有显著的抗焦虑作用。这些结果不仅为深入了解YZP治疗疾病的分子机制提供了理论依据，也为探索经典方剂的临床应用提供了依据。
Yuanhu Zhitong prescription (YZP) is a typical and relatively simple traditional Chinese medicine (TCM), widely used in the clinical treatment of headache, gastralgia, and dysmenorrhea. However, the underlying molecular mechanism of action of YZP is not clear. In this study, based on the previous chemical and metabolite analysis, a complex approach including the prediction of the structure of metabolite, high-throughput in silico screening, and network reconstruction and analysis was developed to obtain a computational drug-target network for YZP. This was followed by a functional and pathway analysis by ClueGO to determine some of the pharmacologic activities. Further, two new pharmacologic actions, antidepressant and antianxiety, of YZP were validated by animal experiments using zebrafish and mice models. The forced swimming test and the tail suspension test demonstrated that YZP at the doses of 4 mg/kg and 8 mg/kg had better antidepressive activity when compared with the control group. The anxiolytic activity experiment showed that YZP at the doses of 100 mg/L, 150 mg/L, and 200 mg/L had significant decrease in diving compared to controls. These results not only shed light on the better understanding of the molecular mechanisms of YZP for curing diseases, but also provide some evidence for exploring the classic TCM formulas for new clinical application.