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  4. Vol 5, Issue 3, 2023

Active Components and Mechanism of Dihuang Yinzi in Treatment of Vascular Dementia Based on Network Pharmacology and Molecular Docking Technology

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DOI: 10.23977/medcm.2023.050301 | Downloads: 19 | Views: 722

Author(s)

Tang Ju 1, Miao Feng 2, Ma Yilun 1, Ren Hui 1, Wei Peifeng 2

Affiliation(s)

1 Shaanxi University of Traditional Chinese Medicine, Xianyang, 712046, China
2 The Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, 712000, China

Corresponding Author

Miao Feng

ABSTRACT

The objective this study aims to look into the active ingredients and mechanism of Dihuang Yinzi in the treatment of vascular dementia (VaD) using network pharmacology and molecular docking technology. Methods Based on network pharmacology, screening of the chemical composition and its role of Dihuang Yinzi targets, disease targets, intersection targets, and other related information, and then based on bioinformatics technology, the key pathways related annotation, the active components of Dihuang Yinzi intervention vascular dementia and the underlying mechanisms, and then will get key components and key targets for molecular docking. Results According to network pharmacology, the active ingredients of Dihuang Yinzi in the treatment of VaD were Stigmasterol, beta-sitosterol, Erianin, and others. Dihuang Yinzi's signaling pathways in the treatment of VaD primarily include lipid and atherosclerosis, the PI3K-Akt signaling pathway, the TNF signaling pathway, apoptosis, and so on. Stable structures can be formed by docking key targets with key component molecules. Conclusion Dihuang Yinzi works by using several components, multiple targets, and multiple pathways to cure and prevent VaD.

KEYWORDS

Dihuang Yinzi, Vascular Dementia, Network Pharmacology, Molecular Docking Technology

CITE THIS PAPER

Tang Ju, Miao Feng, Ma Yilun, Ren Hui, Wei Peifeng, Active Components and Mechanism of Dihuang Yinzi in Treatment of Vascular Dementia Based on Network Pharmacology and Molecular Docking Technology. MEDS Chinese Medicine (2023) Vol. 5: 1-7. DOI: http://dx.doi.org/10.23977/medcm.2023.050301.

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