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Network-based identification and mechanism exploration of active ingredients against Alzheimer's disease via targeting endoplasmic reticulum stress from traditional chinese medicine.
- Source :
-
Computational and structural biotechnology journal [Comput Struct Biotechnol J] 2023 Dec 20; Vol. 23, pp. 506-519. Date of Electronic Publication: 2023 Dec 20 (Print Publication: 2024). - Publication Year :
- 2023
-
Abstract
- Alzheimer's disease is a neurodegenerative disease that leads to dementia and poses a serious threat to the health of the elderly. Traditional Chinese medicine (TCM) presents as a promising novel therapeutic therapy for preventing and treating dementia. Studies have shown that natural products derived from kidney-tonifying herbs can effectively inhibit AD. Furthermore, endoplasmic reticulum (ER) stress is a critical factor in the pathology of AD. Regulation of ER stress is a crucial approach to prevent and treat AD. Thus, in this study, we first collected kidney-tonifying herbs, integrated chemical ingredients from multiple TCM databases, and constructed a comprehensive drug-target network. Subsequently, we employed the endophenotype network (network proximity) method to identify potential active ingredients in kidney-tonifying herbs that prevented AD via regulating ER stress. By combining the predicted outcomes, we discovered that 32 natural products could ameliorate AD pathology via regulating ER stress. After a comprehensive evaluation of the multi-network model and systematic pharmacological analyses, we further selected several promising compounds for in vitro testing in the APP-SH-SY5Y cell model. Experimental results showed that echinacoside and danthron were able to effectively reduce ER stress-mediated neuronal apoptosis by inhibiting the expression levels of BIP, p-PERK, ATF6, and CHOP in APP-SH-SY5Y cells. Overall, this study utilized the endophenotype network to preliminarily decipher the effective material basis and potential molecular mechanism of kidney-tonifying Chinese medicine for prevention and treatment of AD.<br />Competing Interests: The authors do not have any potential conflicts of interest.The authors declare that they have no competing interests.<br /> (© 2024 The Authors.)
Details
- Language :
- English
- ISSN :
- 2001-0370
- Volume :
- 23
- Database :
- MEDLINE
- Journal :
- Computational and structural biotechnology journal
- Publication Type :
- Academic Journal
- Accession number :
- 38261917
- Full Text :
- https://doi.org/10.1016/j.csbj.2023.12.017