中药毒性预测研究进展与思考

doi:10.19803/j.1672-8629.20220255

摘要/Abstract

摘要： 目的了解中药毒性预测研究现状,为全面深入认识中药毒性提供参考。方法基于文献检索和阅读,对近年来有关中药毒性预测思路和方法进行梳理、归纳和总结。结果根据不同的预测理念,中药毒性预测方法大致可分为3类：基于定量结构-活性关系、网络毒理学及传统中药药性理论的中药毒性预测方法,对中药毒性预测的发展及其在临床用药的指导作用提出了展望,提出“基于多元层面的中药全成分组复合毒性效应网络”的中药毒性预测理念,期望实现一体化中药毒性完整预测,有助于中药毒性的系统性研究和应用,为进一步认识中药毒性预测提供了思路。结论现有的中药毒性预测方法能够为“有毒”中药无毒用药方案的制定提供理论依据,对临床上的中药配伍减毒具有一定的参考。

关键词: 中药毒性预测, 定量结构-活性关系, 网络毒理学, 中药药性理论

Abstract: Objective To keep track of current research on toxicity prediction of traditional Chinese medicines (TCM) so as to help gain keen insights into the toxicity of TCM. Methods Based on literature, this paper categorized and summarized the concepts and methods of TCM toxicity prediction in recent years. Results According to concepts of prediction, the methods for toxicity prediction TCM could be roughly divided into three categories: those based on quantitative structure-activity relationships, network toxicology, and on theories of properties of TCM. Future developments of toxicity prediction of TCM and its guidance in clinical medications were presented. The concept of “compound toxic effect network of ingredient-omics based on multiple levels” was proposed for TCM toxicity prediction in hopes of implementing integrated TCM toxicity prediction. Conclusion The TCM toxicity prediction methods currently available can not only provide evidence for the formulation of non-toxic drug regimens for “toxic” TCM, but also facilitate clinical compatibility and attenuation of TCM.

Key words: toxicity prediction of traditional Chinese medicines, QSAR, network toxicology, theory of properties of traditional Chinese medicines

中图分类号:

R994.1
R932

沈磐, 孙德志, 周维, 高月. 中药毒性预测研究进展与思考[J]. 中国药物警戒, 2023, 20(4): 473-479.

SHEN Pan, SUN Dezhi, ZHOU Wei, GAO Yue. Research progress in toxicity prediction of traditional Chinese medicines[J]. Chinese Journal of Pharmacovigilance, 2023, 20(4): 473-479.

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