Applications of artificial intelligence in the research of molecular mechanisms of traditional Chinese medicine formulas.
10.1016/S1875-5364(25)60903-4
- Author:
Hongyu CHEN
1
;
Ruotian TANG
1
;
Mei HONG
1
;
Jing ZHAO
1
;
Dong LU
1
;
Xin LUAN
2
;
Guangyong ZHENG
3
;
Weidong ZHANG
4
Author Information
1. Shanghai Frontiers Science Center for Chinese Medicine Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
2. Shanghai Frontiers Science Center for Chinese Medicine Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China. Electronic address: luanxin@shutcm.edu.cn.
3. Shanghai Frontiers Science Center for Chinese Medicine Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China. Electronic address: gyzheng@shutcm.edu.cn.
4. Shanghai Frontiers Science Center for Chinese Medicine Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China; Department of Phytochemistry, School of Pharmacy, Second Military Medical University, Shanghai 200433, China; Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China. Electronic address: wdzhangy@hotmail.com.
- Publication Type:Review
- Keywords:
Artificial intelligence;
Knowledge graph;
Machine learning;
Molecular Mechanism;
Traditional Chinese Medicine Formula
- MeSH:
Artificial Intelligence;
Drugs, Chinese Herbal/pharmacokinetics*;
Humans;
Medicine, Chinese Traditional;
Animals
- From:
Chinese Journal of Natural Medicines (English Ed.)
2025;23(11):1329-1341
- CountryChina
- Language:English
-
Abstract:
Traditional Chinese medicine formula (TCMF) represents a fundamental component of Chinese medical practice, incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities, while providing comprehensive insights into health and disease. The foundation of TCMF lies in its holistic approach, manifested through herbal compatibility theory, which has emerged from extensive clinical experience and evolved into a highly refined knowledge system. Within this framework, Chinese herbal medicines exhibit intricated characteristics, including multi-component interactions, diverse target sites, and varied biological pathways. These complexities pose significant challenges for understanding their molecular mechanisms. Contemporary advances in artificial intelligence (AI) are reshaping research in traditional Chinese medicine (TCM), offering immense potential to transform our understanding of the molecular mechanisms underlying TCMFs. This review explores the application of AI in uncovering these mechanisms, highlighting its role in compound absorption, distribution, metabolism, and excretion (ADME) prediction, molecular target identification, compound and target synergy recognition, pharmacological mechanisms exploration, and herbal formula optimization. Furthermore, the review discusses the challenges and opportunities in AI-assisted research on TCMF molecular mechanisms, promoting the modernization and globalization of TCM.
