井冈山大学学报（自然科学版）2026，Vol.47Issue(5)：69-80,12.DOI:10.3969/j.issn.1674-8085.2026.05.008
基于HPLC指纹图谱与多成分定量及网络药理学的十全大补酒质量特征及潜在作用靶点预测研究
Study on quality characteristics and potential action target prediction of Shiquandabu wine based on HPLC fingerprint,multi-component quantification and network pharmacology
摘要
Abstract
This study aimed to establish an HPLC fingerprint and multi-component quantification method for Shiquandabu wine,and to preliminarily reveal its potential material basis and mechanism of action against oxidative stress by integrating network pharmacology and molecular docking.HPLC was used to establish the fingerprints of 15 batches of Shiquandabu wine and simultaneously determine the contents of nine active components.Network pharmacology and molecular docking were applied to predict the potential targets and pathways related to antioxidant and immunomodulatory activities.The results showed that twenty-four common peaks were identified in the fingerprint,and the similarity of the 15 batches was>0.95.The nine components showed good linear relationships(r≥0.999 6),and the average recoveries ranged from 98.96%to 100.84%(RSD<2.0%,n=6).Network pharmacology identified 262 overlapping targets related to oxidative stress,with core genes including SRC,EGFR,STAT3,and PIK3R1.GO and KEGG enrichment analyses indicated that these targets were mainly involved in oxidative stress response,inflammatory signaling,and energy metabolism-related pathways.Molecular docking showed that liquiritin,ammonium glycyrrhizinate,and albiflorin exhibited good binding stability with SRC(2SRC)and EGFR(1M17).This study established HPLC fingerprint profiles and quantitative determination methods for Shiquandabu wine.It is preliminarily revealed that the wine may exert antioxidative stress effects through components such as liquiritin and ammonium glycyrrhizate by regulating SRC/EGFR-related pathways,providing a basis for subsequent biological verification.关键词
十全大补酒/指纹图谱/高效液相色谱法/网络药理学/分子对接Key words
Shiquandabu wine/fingerprint spectrum/HPLC/network pharmacology/molecular docking分类
化学化工引用本文复制引用
徐敏,眭荣春,商杰雅,郭俊勇,严全明,谢春菲,宋明霞..基于HPLC指纹图谱与多成分定量及网络药理学的十全大补酒质量特征及潜在作用靶点预测研究[J].井冈山大学学报（自然科学版）,2026,47(5):69-80,12.基金项目
国家自然科学基金项目(22467014) （22467014）
吉安市科技局重点科技计划项目(2024H-090155) （2024H-090155）
