首页> 外文期刊>Talanta: The International Journal of Pure and Applied Analytical Chemistry >Determination of enantiomeric composition of samples by multivariate regression modeling of spectral data obtained with cyclodextrin guest-host complexes - Effect of an achiral surfactant and use of mixed cyclodextrins
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Determination of enantiomeric composition of samples by multivariate regression modeling of spectral data obtained with cyclodextrin guest-host complexes - Effect of an achiral surfactant and use of mixed cyclodextrins

机译:通过使用环糊精客体-主体配合物获得的光谱数据进行多元回归建模确定样品的对映体组成-非手性表面活性剂的作用和混合环糊精的使用

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摘要

The determination of the enantiomeric composition of samples by chemometric modeling of spectral data was investigated for samples of N,N'-bis-(alpha-methylbenzyl) sulfamide and tryptophan methyl ester hydrochloride. Multivariate regression models (PLS-1) were developed from spectral data obtained on solutions containing N,N'-bis-(alpha-methylbenzyl)sulfamide or tryptophan methyl ester hydrochloride in the presence of sodium dodecyl sulfate and mixed cycloolextrin host molecules. The regression models were subsequently used to predict the enantiomeric composition of laboratory-prepared test samples of NAP-bis(alpha-methylbenzyl)sulfamide or tryptophan methyl ester hydrochloride. The capability of the models to accurately predict the enantiomeric composition was evaluated in terms of the root-mean-square percent relative error (RMS %R.E.) as calculated from the results obtained with independently prepared validation sets of samples. It was found that the presence of SDS in most cases either had little effect on the predictive ability of the model or it actually reduced the predictive ability of the model. Moreover, it was found that the use of mixed CDs, either in the presence or absence of SDS, reduced the predictive ability of the regression model when compared with results obtained with individual CDs. (c) 2005 Elsevier B.V. All rights reserved.
机译:研究了N,N'-双-(α-甲基苄基)磺酰胺和色氨酸甲酯盐酸盐样品的光谱数据化学计量模型测定样品的对映体组成。从在十二烷基硫酸钠和混合的环糊精主体分子存在下含有N,N'-双-(α-甲基苄基)磺酰胺或色氨酸甲酯盐酸盐的溶液中获得的光谱数据,开发了多元回归模型(PLS-1)。随后将回归模型用于预测实验室制备的NAP-双(α-甲基苄基)磺酰胺或色氨酸甲酯盐酸盐的测试样品的对映体组成。根据由独立准备的验证样本集获得的结果计算出的均方根相对误差(RMS%R.E。)评估模型准确预测对映体组成的能力。发现在大多数情况下SDS的存在对模型的预测能力几乎没有影响,或者实际上降低了模型的预测能力。此外,发现与单独CD所获得的结果相比,在存在或不存在SDS的情况下使用混合CD都会降低回归模型的预测能力。 (c)2005 Elsevier B.V.保留所有权利。

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