4.6 Article

Enantiomeric separation of isochromene derivatives by high-performance liquid chromatography using cyclodextrin based stationary phases and principal component analysis of the separation data

期刊

JOURNAL OF CHROMATOGRAPHY A
卷 1305, 期 -, 页码 94-101

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2013.06.044

关键词

Isochromene; Chiral HPLC; Principal component analysis; Cyclodextrin phases

资金

  1. Robert A. Welch Foundation [Y-0026]

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Isochromene derivatives are very important precursors in the natural products industry. Hence the enantiomeric separations of chiral isochromenes are important in the pharmaceutical industry and for organic asymmetric synthesis. Here we report enantiomeric separations of 21 different chiral isochromene derivatives, which were synthesized using alkynylbenzaldehyde cyclization catalyzed by chiral gold(I) acyclic diaminocarbene complexes. All separations were achieved by high-performance liquid chromatography with cyclodextrin based (Cyclobond) chiral stationary phases. Retention data of 21 chiral compounds and 14 other previously separated isochromene derivatives were analyzed using principal component analysis. The effect of the structure of the substituents on the isochromene ring on enantiomeric resolution as well as the other separation properties was analyzed in detail. Using principal component analysis it can be shown that the structural features that contribute to increased retention are different from those that enhance enantiomeric resolution. In addition, principal component analysis is useful for eliminating redundant factors from consideration when analyzing the effect of various chromatographic parameters. It was found that the chiral recognition mechanism is different for the larger gamma-cyclodextrin as compared to the smaller beta-cyclodextrin derivatives. Finally this specific system of chiral analytes and cyclodextrin based chiral selectors provides an effective format to examine the application of principal component analysis to enantiomeric separations using basic retention data and structural features. (C) 2013 Elsevier B.V. All rights reserved.

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