Automated Author Profile

LILU

tianjin hospital

Current S-Index

0.2

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.2

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

15.4%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

ZSS alkaloids (Version: V1)

This study aimed to investigate the antidepressant mechanism of the alkaloid fraction of Ziziphi Spinosae Semen (AZSS) on depressed mice using network pharmacology and pharmacodynamics. Data on the active ingredients and targets were retrieved from TCMSP Platform, and the therapeutic targets for depression were retrieved using GeneCards database; Venn diagrams determined the intersecting targets. STRING platform constructed an AZSS-antidepressant network. With Cluster Profiler R, the common targets were analyzed using GO analysis. The nitric oxide (NO) content in the brain was determined by fluorescence spectrophotometry, and the molecular docking of AZSS-NO synthase (NOS) was performed by Autodock. Nine active components and nine intersecting targets were analyzed, exerting 57 molecular functions. NOS binding was found to be one of the main biological processes targeted by AZSS, and AZSS containing the SLC6A4 segment, that is, (S)-coclaurine, sanjoinine E, dl-nuciferine, and n-methylasimilobine, exhibited this property. NO levels were lower in the venlafaxine and AZSS groups than in the model group (P<0.01). The four SLC6A4-containing AZSS components had high molecular docking energy with NOS. The results suggest that the SLC6A4-containing AZSS components exert antidepressant effects by binding to NOS and interfering with the elevation of NO levels in brain tissue of depressed mice.

Authors

  • LILU ;
  • Lu, Wang ;
  • Yan, Sun ;
  • Wei, Qiao
0 Citations0 Mentions15% FAIR0.2 Dataset Index
10.57760/sciencedb.015202022