基于黄嘌呤氧化酶半数抑制率的中草药提取配方的筛选
Optimization of Chinese herbal medicine water extract formula based on the half inhibition rate of xanthine oxidase
代建刚 1谭婷婷 1傅勇围 2汪程远1
作者信息
- 1. 重庆工商大学环境与资源学院,重庆 400067
- 2. 重庆市计量质量检测研究院,重庆 401519
- 折叠
摘要
目的 以中草药水提取物为原料,研究不同配比对黄嘌呤氧化酶的抑制作用.方法 以黄嘌呤氧化酶半数抑制率为评价指标,筛选中草药水提取物;用正交t值法和加权综合分析法对筛选的中草药进行主辅药分析及辅药交互作用分析;利用响应面混料设计模型优化配方比例.结果 槐花、菊花、桑葚、金银花对黄嘌呤氧化酶具有较强的抑制效果,且菊花和桑葚是配方中的主药,槐花和金银花为辅药.配方最佳配比为槐花水、菊花、桑葚、金银花提取物浓度为50％、30％、11％、9％,对黄嘌呤氧化酶的抑制率为66.21％±0.82％.结论 以中草药水提取物为主要原料组成的配方可防治高尿酸血症.
Abstract
OBJECTIVE To study the inhibitory effect of different ratios on xanthine oxidase using aqueous extracts of Chinese herbal medicines as raw materials.METHODS Using the half inhibition rate of xanthine oxidase as the evaluation index,the liquid extracts of Chinese herbal medicines were screened.The main and auxiliary drugs and the interaction of auxiliary drugs of the selected Chinese herbal medicines were analyzed by Orthogonal t-value method and weighted comprehensive analysis.The formula proportion was optimized by the response surface mixture design model.RESULTS Sophora japonica,chrysanthemum,mulberry and honeysuckle had a strong inhibitory effect on xanthine oxidase.Chrysanthemum and mulberry are the main drugs in the formula,and Sophora japonica and honeysuckle were auxiliary drugs.The optimal formula for inhibiting xanthine oxidase involves a mass concentration of water extract of Sophora japonica chrysanthemum mulberry and honeysuckle were 50％,30％,11％,and 9％,respectivily.This inhibition rate of xanthine oxidase reached of 66.21±0.82％.CONCLUSION The use of a formula containing water extract of Chinese herbal medicine as the primary ingradient can be considered a novel approach for prerenting and treating hypeuricemia.
关键词
中草药水提物/黄嘌呤氧化酶/黄嘌呤氧化酶抑制剂/半数抑制率/正交t值法/响应面混料设计/配方优化Key words
Aqueous extracts of Chinese herbs/Xanthine oxidase/Xanthine oxidase inhibitor/IC50/Orthogonal t-value method/Response surface mixing design/Formulation Optimization引用本文复制引用
基金项目
重庆市科技攻关项目(cstc2016zdcyztzx10001)
重庆工商大学重点项目(950219077)
重庆工商大学重点项目(930517004)
出版年
2024
NETL
NSTL
万方数据