Total ion chromatographic fingerprints combined with chemometrics and mass defect filter to predict antitumor components of Picrasma quassioids
Total ion chromatographic fingerprints combined with chemometrics and mass defect filter to predict antitumor components of Picrasma quassioids
复制标题
总离子色谱指纹图谱结合化学计量学和质量缺陷过滤器预测苦味苦素的抗肿瘤成分
DOI：
10.1002/jssc.201501410
复制
发表时间：
2016-07-01
影响因子：
3.1
通讯作者：
Xie, Ning
中科院分区：
文献类型：
--
作者：
Shi, Yuanyuan;Zhan, Hao;Xie, Ning
A method of total ion chromatogram combined with chemometrics and mass defect filter was established for the prediction of active ingredients in Picrasma quassioides samples. The total ion chromatogram data of 28 batches were pretreated with wavelet transformation and correlation optimized warping to correct baseline drifts and retention time shifts. Then partial least squares regression was applied to construct a regression model to bridge the total ion chromatogram fingerprints and the antitumor activity of P. quassioides. Finally, the regression coefficients were used to predict the active peaks in total ion chromatogram fingerprints. In this strategy, mass defect filter was employed to classify and characterize the active peaks from a chemical point of view. A total of 17 constituents were predicted as the potential active compounds, 16 of which were identified as alkaloids by this developed approach. The results showed that the established method was not only simple and easy to operate, but also suitable to predict ultraviolet undetectable compounds and provide chemical information for the prediction of active compounds in herbs.
