Qiu Ling-Ling, Chen Long-Hu, Yan Dan, Zhang Ping, Tan Man-Rong, Li Zheng-Ming, Xiao Xiao-He
China Military Institute of Chinese Meteria Medica, Intergrative Medicine Centre, 302 Military Hospital, Beijing 100039, China.
Yao Xue Xue Bao. 2012 Apr;47(4):466-71.
This study aimed to establish a novel method to screen out the combined components of multi-fractions traditional Chinese medicine (TCM), so that the internal relationship between multi-ingredients could be objectively assessed and the proportioning ratio could be optimized. Taking antiviral effect on neuraminidase activity of influenza virus as the evaluating indicator and using Box-Behnken response surface methodology, the main effective ingredients of Shuanghuanglian injection (SHL) were screened. Meanwhile, the relationship between active ingredients was discussed. Taking SHL as a comparison, the optimum proportioning ratio was predicted. The results indicated that chlorogenic acid, cryptochlorogenic acid, caffeic acid and baicalin have comparatively strong antiviral activity against influenza virus. Moreover, antagonistic action existed between chlorogenic acid and cryptochlorogenic acid, whereas synergistic action between caffeic acid and other components. The optimum proportioning ratio resulted from fitted model is: chlorogenic acid, cryptochlorogenic acid, caffeic acid and baicalin (107 microg x mL(-1) : 279 microg x mL(-1) : 7.99 microg x mL(-1) : 92 microg x mL(-1)). The antiviral activity of the recombined components is stronger than that of SHL, which was consistent with the experiment results (P < 0.05). Box-Behnken response surface methodology has the advantages of general-screening, high-performance and accurate-prediction etc, which is appropriate for screening the combined components of multi-fractions TCM and the optimization of the proportioning ratio. The proposed method can serve as a technological support for the development of modern multi-fractions TCM.
本研究旨在建立一种筛选多组分中药复方成分的新方法,以便客观评估多成分之间的内在关系并优化配比。以对流感病毒神经氨酸酶活性的抗病毒作用为评价指标,采用Box-Behnken响应面法筛选双黄连注射液(SHL)的主要有效成分。同时,探讨活性成分之间的关系。以SHL作为对照,预测最佳配比。结果表明,绿原酸、隐绿原酸、咖啡酸和黄芩苷对流感病毒具有较强的抗病毒活性。此外,绿原酸和隐绿原酸之间存在拮抗作用,而咖啡酸与其他成分之间存在协同作用。拟合模型得到的最佳配比为:绿原酸、隐绿原酸、咖啡酸和黄芩苷(107μg·mL-1 : 279μg·mL-1 : 7.99μg·mL-1 : 92μg·mL-1)。重组成分的抗病毒活性强于SHL,与实验结果一致(P < 0.05)。Box-Behnken响应面法具有全筛选、高性能和预测准确等优点,适用于多组分中药复方成分的筛选和配比优化。该方法可为现代多组分中药的开发提供技术支持。