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题名: Quantitative structure-retention relationship studies for taxanes including epimers and isomeric metabolites in ultra fast liquid chromatography
作者: Dong, Pei-Pei1, 2;  Ge, Guang-Bo1, 2;  Zhang, Yan-Yan1, 2;  Ai, Chun-Zhi1, 2;  Li, Guo-Hui3;  Zhu, Liang-Liang1, 2;  Luan, Hong-Wei1;  Liu, Xing-Bao1;  Yang, Ling1
通讯作者: 李国辉 ;  杨凌
关键词: QSRR ;  Taxanes ;  Isomers identification ;  Ultra fast liquid chromatography ;  Monte Carlo variable selection ;  Artificial neural network
刊名: JOURNAL OF CHROMATOGRAPHY A
发表日期: 2009-10-16
DOI: 10.1016/j.chroma.2009.08.079
卷: 1216, 期:42, 页:7055-7062
收录类别: SCI
文章类型: Article
部门归属: 18
项目归属: 1806
产权排名: 1.1
WOS标题词: Science & Technology ;  Life Sciences & Biomedicine ;  Physical Sciences
类目[WOS]: Biochemical Research Methods ;  Chemistry, Analytical
研究领域[WOS]: Biochemistry & Molecular Biology ;  Chemistry
英文摘要: Seven pairs of epimers and one pair of isomeric metabolites of taxanes, each pair of which have similar structures but different retention behaviors, together with additional 13 taxanes with different substitutions were chosen to investigate the quantitative structure-retention relationship (QSRR) of taxanes in ultra fast liquid chromatography (UFLC). Monte Carlo variable selection (MCVS) method was adopted to choose descriptors. The selected four descriptors were used to build QSRR model with multi-linear regression (MLR) and artificial neural network (ANN) modeling techniques. Both linear and nonlinear models show good predictive ability, of which ANN model was better with the determination coefficient R(2) for training, validation and test set being 0.9892, 0.9747 and 0.9840. respectively. The results of l 00 times' leave-12-out cross validation showed the robustness of this model. All the isomers can be correctly differentiated by this model. According to the selected descriptors, the three dimensional structural information was critical for recognition of epimers. Hydrophobic interaction was the uppermost factor for retention in UFLC. Molecules' polarizability and polarity properties were also closely correlated with retention behaviors. This QSRR model will be useful for separation and identification of taxanes including epimers and metabolites from botanical or biological samples. (C) 2009 Elsevier B.V. All rights reserved.
关键词[WOS]: ARTIFICIAL NEURAL-NETWORKS ;  CARLO CROSS-VALIDATION ;  MASS-SPECTROMETRY ;  MOLECULAR DESCRIPTORS ;  QSAR MODELS ;  PACLITAXEL ;  TAXOL ;  PHASE ;  CEPHALOMANNINE ;  CHEMISTRY
语种: 英语
原文出处: 查看原文
WOS记录号: WOS:000270750900011
Citation statistics: 
内容类型: 期刊论文
URI标识: http://cas-ir.dicp.ac.cn/handle/321008/102689
Appears in Collections:中国科学院大连化学物理研究所_期刊论文

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作者单位: 1.Chinese Acad Sci, Dalian Inst Chem Phys, Lab Pharmaceut Resource Discovery, Dalian 116023, Peoples R China
2.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Dalian Inst Chem Phys, Lab Mol Modeling & Design, Dalian 116023, Peoples R China

Recommended Citation:
Dong, Pei-Pei,Ge, Guang-Bo,Zhang, Yan-Yan,et al. Quantitative structure-retention relationship studies for taxanes including epimers and isomeric metabolites in ultra fast liquid chromatography[J]. JOURNAL OF CHROMATOGRAPHY A,2009,1216(42):7055-7062.
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