Multicomponent analyses of chiral samples by use of regression analysis of UV-visible spectra of cyclodextrin guest-host complexes.

We report the first combined use of analytical spectroscopy, guest-host chemistry, and multivariate regression analysis for determination of enantiometric composition of multicomponent samples of chiral analytes. Sample solutions containing multicomponent analytes of ephedrine, tryptophan, propranolol, and proline of varying enantiomeric composition with beta-cyclodextrin (BCD) or methyl-beta-cyclodextrin (Me-BCD) as chiral host molecules were investigated using ultraviolet (UV)-visible spectroscopy. The interactions of enantiomers of chiral analytes with chiral hosts resulted in the formation of transient diastereomeric inclusion complexes with varying spectral properties. Multivariate analysis using partial-least-square (PLS) regression was used to correlate subtle changes in the UV-visible spectra of the guest-host complexes with the enantiomeric composition of the calibration samples. These PLS regressions were carefully optimized and then used to predict the enantiomeric composition of multicomponent chiral analytes of validation samples. The results of these validation studies demonstrate the predictive ability of the regression models for determination of future enantiomeric composition of samples. The accuracy of the models to correctly predict the enantiomeric composition of samples, evaluated by use of the root mean square percent relative error (RMS%RE) was analyte and chiral host dependent. In general, better prediction of enantiomeric composition of samples and low RMS%RE values were obtained when Me-BCD was used as the chiral host. The analyses procedure reported here is simple, rapid, and inexpensive. In addition, this approach does not require prior separation of chiral analytes, thus reducing analysis time and eliminating the need for expensive chiral columns.