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首页> 外文期刊>Journal of chromatography, A: Including electrophoresis and other separation methods >Global retention models and their application to the prediction of chromatographic fingerprints
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Global retention models and their application to the prediction of chromatographic fingerprints

机译:全局保留模型及其在色谱指纹预测中的应用

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摘要

The resolution of samples containing unknown compounds of different nature, or without standards available, as is the case of chromatographic fingerprints, is still a challenge. Possibly, the most problematic aspect that prevents systematic method development is finding models that describe without bias the retention behaviour of the compounds in the samples. In this work, the use of global models (able to describe the whole sample) is proposed as an alternative to the use of individual models for each solute. Global models contain parameters that are specific for each solute, while other parameters -related to the column and solvent- are common for all solutes. A special regression procedure is presented for the construction of global models, which are applied to predict highly complex chromatograms, such as chromatographic fingerprints, for diverse experimental conditions in isocratic and gradient elution. Another interesting application is the prediction of molecular properties, such as log P-o/w from the specific solute parameters of the global models. The examined adapted models are based on the equations proposed by Snyder, Schoenmakers, Neue and Kuss, Jandera, and Bosch Roses to describe the retention. In all cases, the predictive capability was very satisfactory. Two cases of study were considered: chromatograms of camomile extracts analysed using acetonitrile gradients, and a set of 145 known compounds in a wide range of structures and functionalities, eluted isocratically with acetonitrile/water mobile phases. (C) 2020 Elsevier B.V. All rights reserved.
机译:对于含有不同性质未知化合物的样品,或没有可用标准的样品,如色谱指纹,其分辨率仍然是一个挑战。可能,阻碍系统方法开发的最有问题的方面是找到无偏见地描述化合物在样品中保留行为的模型。在这项工作中,建议使用全局模型(能够描述整个样本)来替代使用每个溶质的单个模型。全局模型包含特定于每种溶质的参数,而与色谱柱和溶剂相关的其他参数则适用于所有溶质。本文提出了一种用于构建全局模型的特殊回归程序,该程序可用于预测高度复杂的色谱图,例如在等度和梯度洗脱的不同实验条件下的色谱指纹图。另一个有趣的应用是预测分子性质,例如根据全局模型的特定溶质参数预测对数P-o/w。所研究的适应模型基于Snyder、Schoenmakers、Neue和Kuss、Jandera和Bosch Roses提出的描述保留的方程。在所有情况下,预测能力都非常令人满意。考虑了两个研究案例:使用乙腈梯度分析甘菊提取物的色谱图,以及使用乙腈/水流动相等比例洗脱的一组具有广泛结构和功能的145种已知化合物。(C) 2020爱思唯尔B.V.版权所有。

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