一种基于因果关系发现的方法来鉴定草药的活性成分。

A causal relationship discovery-based approach to identifying active components of herbal medicine.

作者信息

Cheng Yiyu, Wang Yi, Wang Xuewei

机构信息

College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310027, China.

出版信息

Comput Biol Chem. 2006 Apr;30(2):148-54. doi: 10.1016/j.compbiolchem.2005.11.003. Epub 2006 Mar 20.

DOI:10.1016/j.compbiolchem.2005.11.003

PMID:16542877

Abstract

Herbal medicine is widely applied for clinical use in East Asia and other countries. However, unclear correlation between its complex chemical composition and bioactivity prevents its application in the West. In the present study, a stepwise causal adjacent relationship discovery algorithm has been developed to study correlation between composition and bioactivity of herbal medicine and identify active components from the complex mixture. This approach was successfully applied in discovering active constituents from mixed extracts of Radix Salviae miltiorrhizae and Cortex Moutan. Moreover, advantage of the present approach compared with bioassay-guided isolation was demonstrated by its application on a typical herbal drug. The current work offers a new way to virtually screen active components of herbal medicine, and it might be helpful to accelerate the process of new drug discovery from natural products.

摘要

草药在东亚和其他国家被广泛应用于临床。然而，其复杂的化学成分与生物活性之间不明确的相关性阻碍了它在西方的应用。在本研究中，已开发出一种逐步因果邻接关系发现算法，以研究草药成分与生物活性之间的相关性，并从复杂混合物中鉴定出活性成分。该方法已成功应用于从丹参和牡丹皮混合提取物中发现活性成分。此外，通过将该方法应用于一种典型草药，证明了其与生物测定导向分离相比的优势。当前的工作为虚拟筛选草药活性成分提供了一种新方法，可能有助于加速从天然产物中发现新药的进程。