Differentiation of Closely Related Isomers: Application of Data Mining Techniques in Conjunction with Variable Wavelength Infrared Multiple Photon Dissociation Mass Spectrometry for Identification of

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• 作者：Sarah E. Stefan ; Mohammad Ehsan ; Wright L. Pearson ; Alexander Aksenov ; Vladimir Boginski ; Brad Bendiak ; John R. Eyler
• 刊名：Analytical Chemistry
• 出版年：2011
• 出版时间：November 15, 2011
• 年：2011
• 卷：83
• 期：22
• 页码：8468-8476
• 全文大小：862K
• 年卷期：v.83,no.22(November 15, 2011)
• ISSN：1520-6882

文摘

Data mining algorithms have been used to analyze the infrared multiple photon dissociation (IRMPD) patterns of gas-phase lithiated disaccharide isomers irradiated with either a line-tunable CO₂ laser or a free electron laser (FEL). The IR fragmentation patterns over the wavelength range of 9.2鈥?0.6 渭m have been shown in earlier work to correlate uniquely with the asymmetry at the anomeric carbon in each disaccharide. Application of data mining approaches for data analysis allowed unambiguous determination of the anomeric carbon configurations for each disaccharide isomer pair using fragmentation data at a single wavelength. In addition, the linkage positions were easily assigned. This combination of wavelength-selective IRMPD and data mining offers a powerful and convenient tool for differentiation of structurally closely related isomers, including those of gas-phase carbohydrate complexes.