DICP OpenIR
学科主题物理化学
A QSRR Model for Identification of Taxanes and Their Metabolites By Prediction Retention Time on UFLC
Dong PP(董佩佩); Ge GB(葛广波); Zhang YY(张延延); Zhang JW(张江伟); Ai CZ(艾纯芝); Yang L(杨凌)
会议名称2nd ASIAN PACIFIC REGIONAL ISSX MEETING
会议日期2008-5-11
2008-05-11
会议地点中国
页码120/2
部门归属十八室
主办者DRUG METABOLISM REVIEWS
英文摘要Ultra-flow liquid chromatography (UFLC) is one of the most promising devices in separation as for its high throughput, good chromatographic performance and high speediness. We intended to build a QSRR model to predict the gradient retention time of taxanes on UFLC, so as to aid in the identification of the metabolites and optimization of separation conditions. We obtained the retention data of 28 taxanes under the same gradient elution, and a large set of molecular descriptors including the semi-empirical descriptors and the E-dragon descriptors were computed to characterize the structures. Genetic algorithm-partial least square (GA-PLS) was adopted to choose variables, then the chosen variables were used to build models for prediction of retention time by multi-linear regression (MLR), artificial neural network (ANN), and support vector machine (SVM) separately. At last, we build a good model by SVM with the statistical results of R2=0.94, the absolute error between calculated and real retention time less than 1 minutes for external test set. In order to test the generalization of this model, the retention time of metabolites about paclitaxel and cephalomannie were also predicted, through the predicted retention time, we can discriminate metabolites at different sites. Our QSRR model is not only useful in identification of metabolites; but also will help in separation and identification of new compounds.
语种中文
WOS记录号WOS:000265257500179
引用统计
文献类型会议论文
条目标识符http://cas-ir.dicp.ac.cn/handle/321008/113476
专题中国科学院大连化学物理研究所
通讯作者Yang L(杨凌)
推荐引用方式
GB/T 7714
Dong PP,Ge GB,Zhang YY,et al. A QSRR Model for Identification of Taxanes and Their Metabolites By Prediction Retention Time on UFLC[C],2008:120/2.
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