...
首页> 外文期刊>Evidence-based complementary and alternative medicine: eCAM >A Computational Drug-Target Network for Yuanhu Zhitong Prescription
【24h】

A Computational Drug-Target Network for Yuanhu Zhitong Prescription

机译:元虎止痛方剂的计算机靶标网络

获取原文

摘要

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-throughputin silicoscreening, 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.
机译:元虎止痛处方(YZP)是一种典型且相对简单的中药(TCM),广泛用于头痛,胃痛和痛经的临床治疗。但是,YZP作用的潜在分子机制尚不清楚。在这项研究中,在先前的化学和代谢物分析的基础上,开发了一种复杂的方法,包括预测代谢物的结构,高通量硅蛋白筛查以及网络重构和分析,从而获得了针对YZP的计算药物目标网络。随后由ClueGO进行功能和途径分析,以确定某些药理活性。此外,通过使用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,抗抑郁药和抗焦虑药。强迫游泳试验和尾部悬吊试验表明,与对照组相比,YZP 4 mg / kg和8 mg / kg剂量具有更好的抗抑郁活性。抗焦虑活性实验表明,与对照组相比,YZP在100μmg/ L,150μmg/ L和200μmg/ L的剂量下,潜水作用明显降低。这些结果不仅为更好地理解YZP治愈疾病的分子机制提供了依据,而且为探索经典的中药配方在新的临床应用中提供了一些证据。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号