中医药
传统医学
药物发现
计算生物学
计算机科学
数据科学
医学
生物
生物信息学
替代医学
病理
作者
Meng Ding,Wen Tan,Xiao Zhang,Pengfei Tu,Yong Jiang
出处
期刊:PubMed
日期:2025-07-01
卷期号:50 (13): 3645-3656
标识
DOI:10.19540/j.cnki.cjcmm.20250511.601
摘要
Traditional Chinese medicine(TCM), with diverse structural types of active components and remarkable clinical efficacy, holds a significant position in the pharmacological research. As the key substances, active components of TCM are of great importance in revealing the material basis of TCM efficacy and mechanism of action. However, the conventional approaches of discovering active components in TCM are characterized by tedious procedures, lengthy cycles, and unclear mechanisms, which struggle to meet the current demands for drug development. In recent years, major breakthroughs have been made in target discovery technologies, and new drug targets are constantly being discovered, which has facilitated the development of target-driven approaches. The target-guided active component discovery strategy provides a new paradigm for discovering active components in TCM. This article systematically summarizes two mainstream target-based technologies-virtual screening and ligand fishing-for TCM active component discovery. By analyzing relevant application cases, this article evaluates the strengths and limitations of each technology. The review aims to provide frameworks for expediting bioactive component discovery in complex systems like TCM, so as to accelerate the development of innovative drugs based on the active components of TCM and promote the modernization and internationalization of TCM.
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