Q-markers in Naoxintong Capsules by using multivariable statistical and "components-targets-diseases" network analysis / 中草药
Chinese Traditional and Herbal Drugs
; (24): 2775-2785, 2018.
Article
in Zh
| WPRIM
| ID: wpr-851894
Responsible library:
WPRO
ABSTRACT
Objective This study aimed to establish an integral quality control method for Naoxintong capsules based on the theory of quality markers (Q-marker) in traditional Chinese medicine via multivariable statistical calculation and "active compounds-targets" network construction. Methods Multi-statistical methods were firstly carried out to explore the specific components from different batches of Naoxintong Capsules. The "Q-markers-targets-pathways-diseases" network was constructed using the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) online analysis tool, and biological information annotations were made. Moreover, a simultaneously determination method for Q-markers was established by using ultra-high performance liquid chromatography (UPLC). Results Nine compounds were chose as the Naoxintong Q-markers capsules including mulberroside A, hydroxysafflor yellow A, paeoniflorin, ferulic acid, calycosin-7-glucoside, rosemary acid, salvianolic acid B, formononetin, and tanshinone IIA. To verify the prediction, target network construction analysis was performed and indicated that the nine Q-markers mainly targeted five proteins which were PTGIS, PTGS2, CHRNA10, ENPP1, and ADORA2A. Methodological validation showed that the established UPLC method had good linear relationship (r<0.999), and all RSD values were lower than 3% in the repeatability, stability, and precision test. Conclusion Based on the multivariate statistics, network pharmacology analysis, and UPLC multi-component quantitative analysis, a multi-angle analysis method for effective components can be established for the integral quality control of Naoxintong Capsules.
Full text:
1
Database:
WPRIM
Traditional Medicines:
Medicinas_tradicionales_de_asia
/
Medicina_china
Type of study:
Prognostic_studies
Language:
Zh
Journal:
Chinese Traditional and Herbal Drugs
Year:
2018
Type:
Article