Network pharmacology: a crucial approach in traditional Chinese medicine research

• Published in: Chinese medicine Vol. 20; no. 1; pp. 8 - 20
• Main Authors: Zhai, Yiyan, Liu, Liu, Zhang, Fanqin, Chen, Xiaodong, Wang, Haojia, Zhou, Jiying, Chai, Keyan, Liu, Jiangying, Lei, Huiling, Lu, Peiying, Guo, Meiling, Guo, Jincheng, Wu, Jiarui
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 12.01.2025; BioMed Central; BMC
• Subjects: Big Data; Bioinformatics; Cultural heritage; Current state of research; Disease; Drug development; Drugs; Herbs; Medicine, Chinese; Network pharmacology; Pharmacokinetics; Pharmacology; Precision network pharmacology; Review; Toxicity; Traditional Chinese medicine; China; Database; Traditional Chinese medicine; Network pharmacology; Precision network pharmacology; Current state of research
• ISSN: 1749-8546; 1749-8546
• DOI: 10.1186/s13020-024-01056-z

Network pharmacology plays a pivotal role in systems biology, bridging the gap between traditional Chinese medicine (TCM) theory and contemporary pharmacological research. Network pharmacology enables researchers to construct multilayered networks that systematically elucidate TCM’s multi-component, multi-target mechanisms of action. This review summarizes key databases commonly used in network pharmacology, including those focused on herbs, components, diseases, and dedicated platforms for network pharmacology analysis. Additionally, we explore the growing use of network pharmacology in TCM, citing literature from Web of Science, PubMed, and CNKI over the past two decades with keywords like “network pharmacology”, “TCM network pharmacology”, and “herb network pharmacology”. The application of network pharmacology in TCM is widespread, covering areas such as identifying the material basis of TCM efficacy, unraveling mechanisms of action, and evaluating toxicity, safety, and novel drug development. However, challenges remain, such as the lack of standardized data collection across databases and insufficient consideration of processed herbs in research. Questions also persist regarding the reliability of study outcomes. This review aims to offer valuable insights and reference points to guide future research in precision TCM network pharmacology.