Exploring artificial intelligence approaches for predicting synergistic effects of active compounds in traditional Chinese medicine based on molecular compatibility theory.
10.1016/S1875-5364(25)60967-8
- Author:
Yiwen WANG
1
;
Tong WU
1
;
Xingyu LI
1
;
Qilan XU
1
;
Heshui YU
2
;
Shixin CEN
2
;
Yi WANG
3
;
Zheng LI
4
Author Information
1. College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
2. College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China; State Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China.
3. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address: zjuwangyi@zju.edu.cn.
4. College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; State Key Laboratory of Component-Based Chinese Medicine, Tianjin 301617, China; State Key Laboratory of Chinese Medicine Modernization, Tianjin 301617, China; Tianjin Key Laboratory of Intelligent and Green Pharmaceuticals for Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin, 301617, China. Electronic address: lizheng@tjutcm.edu.cn.
- Publication Type:Review
- Keywords:
Artificial intelligence;
Molecular compatibility theory;
Molecular drugs combination prediction;
Synergy prediction of TCM compounds
- MeSH:
Artificial Intelligence;
Medicine, Chinese Traditional/methods*;
Drugs, Chinese Herbal/pharmacology*;
Humans;
Drug Synergism
- From:
Chinese Journal of Natural Medicines (English Ed.)
2025;23(11):1409-1424
- CountryChina
- Language:English
-
Abstract:
Due to its synergistic effects and reduced side effects, combination therapy has become an important strategy for treating complex diseases. In traditional Chinese medicine (TCM), the "monarch, minister, assistant, envoy" compatibilities theory provides a systematic framework for drug compatibility and has guided the formation of a large number of classic formulas. However, due to the complex compositions and diverse mechanisms of action of TCM, it is difficult to comprehensively reveal its potential synergistic patterns using traditional methods. Synergistic prediction based on molecular compatibility theory provides new ideas for identifying combinations of active compounds in TCM. Compared to resource-intensive traditional experimental methods, artificial intelligence possesses the ability to mine synergistic patterns from multi-omics and structural data, providing an efficient means for modeling and optimizing TCM combinations. This paper systematically reviews the application progress of AI in the synergistic prediction of TCM active compounds and explores the challenges and prospects of its application in modeling combination relationships, thereby contributing to the modernization of TCM theory and methodological innovation.
