以药效成分群-活性-功效关联作用筛选当归质量标志物

目的基于质量标志物(quality markers,Q-Marker)概念,通过构建当归的药效成分群-生物活性关联网络,确定影响当归药材质量的Q-Marker,建立当归药材的整体质控方法。方法以当归药材表征成分结合主成分分析结果,对15批次不同产地当归药材差异显著的活性成分进行筛选,将初步选定的差异成分作为当归质控的药效成分群。基于关联规则,建立体外、体内活性成分筛选评价模型,通过挖掘组分间关系,以此确定当归药材的Q-Marker,并建立了Q-Marker同时定量的测定方法。结果经UPLC-TOF/MS技术及药动学参数预测,找到当归中11个具有潜在药效活性的药效成分群。经药效成分群-生物活性关联网络分析,将阿魏酸、Z-藁本内酯和欧当归内酯A作为当归质控的Q-Marker,其方法学结果显示,3种化合物线性关系良好,r0.990,精密度、重复性和稳定性良好,平均加样回收率范围为99.18%～100.25%。结论基于药效成分群-生物活性关联概念,采用多元统计结合液质联用分析技术的当归药材Q-Marker辨析方法,可以初步明确与当归药效紧密联系的化学成分来源,为当归的整体质量控制提供相关数据。

Q-Marker screening method for Angelicae Sinensis Radix depending on effective components-bioactivity-efficacy network integration analysis

Objective According to quality markers (Q-Marker) theory, to establish a whole set of quality control methods for Danggui (Angelica Sinensis Radix, ASR) on the basis of effective components-bioactivity-efficacy network correlation analysis and determine Q-marker affecting the quality of ASR. Methods Combined ASR components characterization with principal component analysis (PCA), the differential active components among 15 various habitats materials were directly evaluated, regarding the initially-selected components as the bio-efficacy components for quality control of ASR. Based on correlation analysis principle, the screening and evaluation models of active ingredients in vitro and in vivo were established by digging inter-relationship of components to determine the Q-marker of ASR. Meanwhile, the simultaneous determination methodology for the Q-Marker was established. Results With UPLC-TOF/MS technique and pharmacokinetic parameter prediction, 11 bio-efficacy components with potential drug effect activity were found. After being analyzed by the bio-efficacy components-bioactivity network integration analysis, ferulic acid, Z-ligustilide, and levistilide A were chosen as the Q-Marker for quality control of ASR. By using the established quantification method, the linearity coefficients of three Q-Marker were over 0.99. With a highly precision, repeatability and stability results, the average recoveries of three Q-Marker in the samples were ranged from 99.18% to 100.25%. Conclusion Based on the concept of bio-efficacy components-bioactivity network correlation, UPLC-TOF/MS was used to discriminate the Q-Marker of ASR, in order to preliminarily identify the source of chemical constituents closely related to the efficacy of ASR, which can provide relevant statistics for the overall quality control of ASR.