期刊文献+

Prediction of quality markers of traditional Chinese medicines based on network pharmacology 被引量:60

Prediction of quality markers of traditional Chinese medicines based on network pharmacology
原文传递
导出
摘要 Network pharmacology is a powerful tool to reflect the pharmacologically active effects,mechanism of action and toxic activity of traditional Chinese medicines(TCMs).The ingredients of TCMs,associated with quality control of TCM products,are those fundamental chemicals that exhibit biological activities.A great amount of effort has been made by scientists in that field in order to improve the quality of TCMs,though the approaches to determine their quality and the TCM theory and compatibility rules remain ambiguous.Now some methods and technologies must be applied to predict and explore the quality marker(Q-marker)for quality control,as well as to clarify the factors affecting the quality of TCM,which may give new insight into rational ground of establishment of appropriate quality control and assessment system.In this review paper,authors focus on the prediction of quality markers of TCMs by network pharmacology based on three aspects:(1)from network medicine to network pharmacology,(2)complex network system of traditional Chinese medicine,and(3)predicting TCM quality markers based on network pharmacology.Authors proposed the research pattern on network pharmacology based on biological and medical networks,and further TCM network pharmacology based on substantial basis of TCM formulae,and the idea of"effect-ingredient-target-fingerprint"to predict and recognize the TCM Qmarker was the ultimate goal.In addition,authors yet noted how to make full use of the advantages of network toxicology to provide new ideas for the toxicity study of complex TCM systems and the prediction of TCM toxicity markers. Network pharmacology is a powerful tool to reflect the pharmacologically active effects, mechanism of action and toxic activity of traditional Chinese medicines(TCMs). The ingredients of TCMs, associated with quality control of TCM products, are those fundamental chemicals that exhibit biological activities.A great amount of effort has been made by scientists in that field in order to improve the quality of TCMs, though the approaches to determine their quality and the TCM theory and compatibility rules remain ambiguous. Now some methods and technologies must be applied to predict and explore the quality marker(Q-marker) for quality control, as well as to clarify the factors affecting the quality of TCM,which may give new insight into rational ground of establishment of appropriate quality control and assessment system. In this review paper, authors focus on the prediction of quality markers of TCMs by network pharmacology based on three aspects:(1) from network medicine to network pharmacology,(2)complex network system of traditional Chinese medicine, and(3) predicting TCM quality markers based on network pharmacology. Authors proposed the research pattern on network pharmacology based on biological and medical networks, and further TCM network pharmacology based on substantial basis of TCM formulae, and the idea of "effect-ingredient-target-fingerprint" to predict and recognize the TCM Qmarker was the ultimate goal. In addition, authors yet noted how to make full use of the advantages of network toxicology to provide new ideas for the toxicity study of complex TCM systems and the prediction of TCM toxicity markers.
出处 《Chinese Herbal Medicines》 CAS 2019年第4期349-356,共8页 中草药(英文版)
基金 supported by National Nature Science Foundation for Key Projects(No.81430096) National New Drug Innovation(No.2017ZX09301062.) Tianjin Science and Technology Plan Project(No.19YFSLQY00110).
关键词 NETWORK PHARMACOLOGY NETWORK TOXICOLOGY PREDICTION QUALITY marker traditional Chinese MEDICINES network pharmacology network toxicology prediction quality marker traditional Chinese medicines
作者简介 Corresponding author:He Huang,E-mail addresses:huang@tju.edu.cn(H.Huang);Corresponding author:Chang-xiao Liu,E-mail addresses:liuchangxiao@163.com(C.-x.Liu).
  • 相关文献

参考文献23

二级参考文献516

共引文献2055

同被引文献1719

引证文献60

二级引证文献769

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部