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Omics combined with network pharmacology reveal the neuroprotective mechanism of Sophora tonkinensis based on the biolabel research pattern: The treatment of Parkinson's disease against oxidative stress and neuroexcitatory toxicity.
- Source :
- Biomedical Chromatography; Mar2023, Vol. 37 Issue 3, p1-9, 9p
- Publication Year :
- 2023
-
Abstract
- Based on the biolabel research pattern, omics and network pharmacology were used for exploring the neuroprotection of Sophora tonkinensis (ST) in the treatment of brain diseases. Multi‐omics were applied to investigate biolabels for ST intervention in brain tissue. Based on biolabels, the therapeutic potential, mechanism and material basis of ST for treating brain diseases were topologically analyzed by network pharmacology. A Parkinson's disease (PD) mouse model was used to validate biolabel analysis results. Four proteins and three metabolites were involved in two key pathways (alanine, aspartate and glutamate metabolism and arginine biosynthesis) and considered as biolabels. Network pharmacology showed that ST has the potential to treat some brain diseases, especially PD. Eight compounds (including caffeic acid, gallic acid and cinnamic acid) may serve as the material basis of ST treating brain diseases via the mediation of three biolabels. In the PD model, ST and its active compounds (caffeic acid and gallic acid) may protect dopaminergic neurons (maximum recovery rate for dopamine, 49.5%) from oxidative stress (E3 ubiquitin‐protein ligase parkin, reactive oxygen species, nitric oxide, etc.) and neuroexcitatory toxicity (glutamate dehydrogenase, glutamine, glutamic acid, etc.). These findings indicated that omics and network pharmacology may contribute to the achievement of the objectives of this study based on the biolabel research pattern. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02693879
- Volume :
- 37
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Biomedical Chromatography
- Publication Type :
- Academic Journal
- Accession number :
- 161827224
- Full Text :
- https://doi.org/10.1002/bmc.5557