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Multidimensional statistical analysis applied to electron ionization mass spectra to determine steroid stereochemistry

机译:多维统计分析应用于电子电离质谱以确定类固醇立体化学

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The differentiation of stereoisomers on the basis of their mass spectra only is usually a difficult challenge even when an informative ionization technique such as electron ionization is used; this is particularly the case for steroids. In this study, multivariate statistical techniques have been applied to the mass spectra of derivatized 5xi-androstane-3xi,17xi-diols (xi = alpha,beta) in order to investigate the possibility of discrimination among the different isomers. After collection of the data from the mass spectra (20 replicates for each of the 8 isomers), each ion was considered as a statistical variable and each mass spectrum as an observation. The more discriminative variables (42 out of the 160 initial ones) were selected using the analysis of variance technique (ANOVA). Thereafter, a linear discriminant analysis (LDA) allowed us to set up a predictive model for stereochemistry determination. The two-dimensional graphical display of the 160 observations on the basis of the canonical variables derived from LDA made it possible to separate the eight isomers. The discrimination of 5alpha and 5beta isomers as well as 3alpha and 3beta was unambiguous, whereas, the discrimination of 17alpha and 17beta epimers was less obvious. The robustness of the model was checked with 40 mass spectra recorded over a 6-month period on different quadrupole mass spectrometers and under different signal acquisition conditions. The percentage of correct assignment of these 'unknown' stereoisomers, was 92%; only three 17alpha and 17beta epimers were not correctly plotted in the expected zone. Nevertheless, the performance score was better than those observed with traditional mass spectral libraries. Furthermore, this statistical approach allowed us to identify the main fragment ions involved in the discrimination between isomers: m/z 256 and 421 for isomers 5a-5b; m/z 241 and 331 for isomers 5alpha3alpha-5alpha3beta; m/z 143 and 162 for isomers 5beta3alpha-5beta3beta; and m/z 255 for epimers 17alpha-17beta. Copyright (C) 2005 John Wiley Sons, Ltd.
机译:即使仅使用信息性电离技术(例如电子电离),仅根据其质谱区分立体异构体通常也是一个难题。对于类固醇尤其如此。在这项研究中,多元统计技术已应用于衍生化的5xi-androstane-3xi,17xi-diols(xi = alpha,beta)的质谱中,以研究在不同异构体之间进行区分的可能性。从质谱收集数据后(对于8个异构体,每个重复20个),每个离子被视为统计变量,每个质谱被视为观察值。使用方差分析技术(ANOVA)选择更具区别性的变量(在160个初始变量中选择了42个)。此后,线性判别分析(LDA)使我们能够建立用于立体化学测定的预测模型。基于LDA的标准变量对160个观测值进行二维图形显示,可以分离8种异构体。 5alpha和5beta异构体以及3alpha和3beta的区别是明确的,而17alpha和17beta差向异构体的区别则不太明显。通过在不同的四极质谱仪上和在不同的信号采集条件下,在6个月的时间内记录的40个质谱图,检查了模型的鲁棒性。这些“未知”立体异构体的正确分配百分比为92%;只有三个17alpha和17beta差向异构体未正确绘制在预期区域中。然而,性能得分比传统质谱库更好。此外,这种统计方法使我们能够确定参与异构体区分的主要碎片离子:异构体5a-5b的m / z 256和421;异构体5a-5b的m / z 256和421。对于异构体5alpha3alpha-5alpha3beta,m / z 241和331; m / z 143和162异构体5beta3alpha-5beta3beta;差向异构体17alpha-17beta的m / z 255。版权所有(C)2005 John Wiley Sons,Ltd.

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