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CC BY 4.0 · Planta Med 2025; 91(05): 226-237
DOI: 10.1055/a-2512-8928
DOI: 10.1055/a-2512-8928
Reviews
Application of Network Pharmacology in the Treatment of Neurodegenerative Diseases with Traditional Chinese Medicine
Authors
The authors are thankful for the support provided by the Natural Science Foundation of Hubei Province (Grant Nos. 2023AFB677, 2024AFB578) and the Intramural Research Program of Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology (Grant Nos. 2023LYYYSZRP0001,2023LYYYGZRP0003). We confirm that the funding sources had no role in the study design, data collection, analysis, interpretation, or manuscript preparation.
Abstract
In recent years, the incidence of neurodegenerative diseases, including Alzheimerʼs disease, Parkinsonʼs disease, Huntingtonʼs disease, and amyotrophic lateral sclerosis, has exhibited a steadily rising trend, which has posed a major challenge to the global public health. Traditional Chinese medicine, with its multicomponent and multitarget characteristics, offers a promising approach to treating neurodegenerative diseases. However, comprehensively elucidating the complex mechanisms underlying traditional Chinese medicine formulations remains challenging. As an emerging systems biology method, network pharmacology has provided a vital tool for revealing the multitarget mechanisms of traditional Chinese medicine through high-throughput technologies, molecular docking, and network analysis. This paper reviews the advancements in the application of network pharmacology in treating neurodegenerative diseases using traditional Chinese medicine, analyzes the current status of relevant databases and technological methods, discusses the limitations, and proposes future directions to promote the modernization of traditional Chinese medicine and the development of precision medicine.
Keywords
neurodegenerative diseases - traditional Chinese medicine - network pharmacology - therapeutic targetsPublication History
Received: 20 October 2024
Accepted after revision: 06 January 2025
Accepted Manuscript online:
08 January 2025
Article published online:
18 February 2025
© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
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