Network pharmacology approaches for research of Traditional Chinese Medicines.
10.1016/S1875-5364(23)60429-7
- Author:
Xiang LI
1
,
2
,
3
;
Ziqi LIU
4
;
Jie LIAO
5
,
6
,
7
;
Qian CHEN
5
,
6
,
7
;
Xiaoyan LU
5
,
6
,
7
;
Xiaohui FAN
5
,
6
,
8
Author Information
1. School of Basic Medical Sciences and Forensic Medicine, Hangzhou Medical College, Hangzhou 311399, China
2. Department of Chinese Medicine Science & Engineering, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
3. Innovation Center in Zhejiang University, State Key Laboratory of Component-based Chinese Medicine, Hangzhou 310058, China.
4. Department of Chinese Medicine Science & Engineering, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
5. Department of Chinese Medicine Science & Engineering, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
6. Innovation Center in Zhejiang University, State Key Laboratory of Component-based Chinese Medicine, Hangzhou 310058, China
7. Future Health Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China.
8. Future Health Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China. Electronic address: fanxh@zju.edu.cn.
- Publication Type:Journal Article
- Keywords:
Artificial Intelligence;
Drug Repurposing;
Effective Mechanism;
Herbal Medicine;
Network Pharmacology;
Pharmacodynamics Material Basis;
Single-Cell omics;
Traditional Chinese Medicine
- MeSH:
Drugs, Chinese Herbal/pharmacology*;
Network Pharmacology;
Artificial Intelligence;
Medicine, Chinese Traditional;
Metabolomics
- From:
Chinese Journal of Natural Medicines (English Ed.)
2023;21(5):323-332
- CountryChina
- Language:English
-
Abstract:
Pharmacodynamics material basis and effective mechanisms are the two main issues to decipher the mechnisms of action of Traditional Chinese medicines (TCMs) for the treatment of diseases. TCMs, in "multi-component, multi-target, multi-pathway" paradigm, show satisfactory clinical results in complex diseases. New ideas and methods are urgently needed to explain the complex interactions between TCMs and diseases. Network pharmacology (NP) provides a novel paradigm to uncover and visualize the underlying interaction networks of TCMs against multifactorial diseases. The development and application of NP has promoted the safety, efficacy, and mechanism investigations of TCMs, which then reinforces the credibility and popularity of TCMs. The current organ-centricity of medicine and the "one disease-one target-one drug" dogma obstruct the understanding of complex diseases and the development of effective drugs. Therefore, more attentions should be paid to shift from "phenotype and symptom" to "endotype and cause" in understanding and redefining current diseases. In the past two decades, with the advent of advanced and intelligent technologies (such as metabolomics, proteomics, transcriptomics, single-cell omics, and artificial intelligence), NP has been improved and deeply implemented, and presented its great value and potential as the next drug-discovery paradigm. NP is developed to cure causal mechanisms instead of treating symptoms. This review briefly summarizes the recent research progress on NP application in TCMs for efficacy research, mechanism elucidation, target prediction, safety evaluation, drug repurposing, and drug design.
