PDF
Full
Outline
OBJECTIVE To establish HPLC fingerprints of Centellae Herba and study the spectrum-effect relationship between its fingerprints and antioxidant activity, screen the quality markers of Centellae Herba and provide a basis for its quality evaluation. METHODS To establish the HPLC fingerprint of Centellae Herba and study the results of common peak area by combining cluster analysis and principal component analysis (PCA). The antioxidant activity of 16 batches of Centellae Herba samples was evaluated by the DPPH and ABTS radical scavenging methods and apply gray correlation analysis (GCA) and partial least squares regression (PLSR) to analyze the spectrum-effect relationship between Centellae Herba fingerprint and antioxidant activity. Network pharmacology technology was introduced to analyze the core targets and construct the network relationship, the compound and core target were verified based on molecular docking to comprehensively screen the active ingredients. RESULTS The similarity range of the fingerprints spectrum was 0.819-0.982, and a total of 9 common peaks were calibrated, 7 chemical components were identified. The 16 batches of Centellae Herba were divided into four categories, all of which had antioxidant capacity and were concentration-dependent. The results of spectral correlation analysis showed that the total peaks 1 (asiaticoside B), 2 (madecassoside) and 5 (kaempferol) were closely related to the antioxidant activity of Centellae Herba, among which asiaticoside B, madecassoside and kaempferol acted on 127 targets, and the key targets were SRC, ESR1 and HSP90AB1. Based on the five principles of Q-Marker, asiaticoside B, madecassoside, kaempferol and asiaticoside were finally determined as the evaluation indexes for quality control. CONCLUSION The spectral correlation analysis between different batches of Centellae Herba and antioxidant activity can provide a reference for the excavation and overall quality control of Centellae Herba.
PDF
233
114
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
