Determination of the enantiomeric composition of guest molecules by chemometric analysis of the UV-visible spectra of cyclodextrin guest-host complexes

Multivariate statistical techniques were applied to the UV spectra of a series of solutions at pH 12 containing a fixed concentration (30 mM) of beta-cyclodextrin (beta-CD) and a fixed concentration (15 mM) of 2-phenylglycine (phi-Gly) with various known enantiomeric compositions. Multivariate correlation of the spectral data for the solutions containing the phi-Gly/beta-CD guest-host complexes with the known enantiomeric composition of the phi-Gly samples was accomplished by partial-least-squares regression. When the multivariate model was used to predict the enantiomeric purity of a test set of samples over the mol fraction range of 0.5-0.9 R-phi-Gly, the average magnitude of the relative errors in the mol fraction determination of enantiomeric composition was 3%. A plot of the enantiomeric composition predicted by the model versus the known enantiomeric composition of the calibration set gave a straight line with a correlation coefficient of 0.955, a slope of 1.05, and an offset of 5.61 x 10-4.     

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

The determination of the enantiomeric composition of samples by chemometric modeling of spectral data was investigated for samples of N,N′-bis-(-methylbenzyl) sulfamide and tryptophan methyl ester hydrochloride. Multivariate regression models (PLS-1) were developed from spectral data obtained on solutions containing N,N′-bis-(-methylbenzyl)sulfamide or tryptophan methyl ester hydrochloride in the presence of sodium dodecyl sulfate and mixed cyclodextrin host molecules. The regression models were subsequently used to predict the enantiomeric composition of laboratory-prepared test samples of N,N′-bis(-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.     

Determination of the enantiomeric composition of phenylalanine samples by chemometric analysis of the fluorescence spectra of cyclodextrin guest-host complexes

A novel strategy for determining the enantiomeric composition of phenylalanine samples that combines ordinary fluorescence spectroscopy, guest-host cyclodextrin chemistry, and multivariate regression modeling is investigated. Partial-least-squares regression (PLS-1) models were developed from fluorescence spectral data obtained with a series of samples containing cyclodextrin guest-host complexes of phenylalanine with different known enantiomeric compositions. The regression models were subsequently validated by determining the enantiomeric composition of a set of independently prepared phenylalanine samples. The ability of the models to correctly predict the enantiomeric compositions of future samples was evaluated in terms of the root-mean-square percent relative error (RMS%RE). The RMS%RE in the mol fraction of D-phenylalanine ranged from 1.3% to 3.0% when beta-cyclodextrin was used as the host molecule for different guest-host concentrations. The RMS%RE in the mol fraction of D-phenylalanine obtained in a similar validation study conducted with gamma-cyclodextrin ranged between 1.8% and 4.0% for different guest-host concentrations. Compared with previous studies done in absorption, fluorescence data were found to be more sensitive and the spectral differences observed as a function of enantiomeric composition were more uniformly spaced, making regression modeling more reliable. As a result, good regression models could be made at lower concentrations than were possible previously when absorption measurements were used.     

Enantiopurity analysis of new types of acyclic nucleoside phosphonates by capillary electrophoresis with cyclodextrins as chiral selectors

CE methods have been developed for the chiral analysis of new types of six acyclic nucleoside phosphonates, nucleotide analogs bearing [(3‐hydroxypropan‐2‐yl)‐1H‐1,2,3‐triazol‐4‐yl]phosphonic acid, 2‐[(diisopropoxyphosphonyl)methoxy]propanoic acid, or 2?(phosphonomethoxy)propanoic acid moieties attached to adenine, guanine, 2,6‐diaminopurine, uracil, and 5‐bromouracil nucleobases, using neutral and cationic cyclodextrins as chiral selectors. With the exception of the 5‐bromouracil‐derived acyclic nucleoside phosphonate with a 2‐(phosphonomethoxy)propanoic acid side chain, the R and S enantiomers of the other five acyclic nucleoside phosphonates were successfully separated with sufficient resolutions, 1.51–2.94, within a reasonable time, 13–28 min, by CE in alkaline BGEs (50 mM sodium tetraborate adjusted with NaOH to pH 9.60, 9.85, and 10.30, respectively) containing 20 mg/mL β‐cyclodextrin as the chiral selector. A baseline separation of the R and S enantiomers of the 5‐bromouracil‐derived acyclic nucleoside phosphonate with 2‐(phosphonomethoxy)propanoic acid side chain was achieved within a short time of 7 min by CE in an acidic BGE (20:40 mM Tris/phosphate, pH 2.20) using 60 mg/mL quaternary ammonium β‐cyclodextrin chiral selector. The developed methods were applied for the assessment of the enantiomeric purity of the above acyclic nucleoside phosphonates. The preparations of all these compounds were found to be synthesized in pure enantiomeric forms. Using UV absorption detection at 206 nm, their concentration detection limits were in the low micromolar range.     

Determination of lithium in pharmaceutical formulations used in the treatment of bipolar disorder by flow injection analysis with spectrophotometric detection

In this work, a flow injection system with spectrophotometric detection was developed for the determination of lithium in pharmaceutical formulations used in the treatment of bipolar disorder. Reaction between Quinizarine (1,4-dihydroxyanthraquinone) and Li(I) ion in alkaline medium containing dimethylsulfoxide (DMSO) was explored for this purpose. The flow system was optimized regarding to its chemical (DMSO, Quinizarine and NaOH concentrations and sample pH) and physical parameters (sample loop volume, carrier flow rate and reactor length) in order to establish better conditions in terms of sensitivity and sampling frequency. The results obtained showed that the concentration of DMSO in the reagent solution presents remarkable influence on the magnitude of analytical signal. Chemical species that could be found in the formulations such as Na(I), K(I), Mg(II), Ca(II), Ti(IV), Cl⁻, CO₃²⁻ e sodium dodecylsulfate were tested as possible interfering ions. Among them, only non-monovalent cations presented noticeable interference on lithium signal. However, they were not found in concentrations high enough to cause interference in the determination of lithium in the samples. Sample preparation was performed by sonicating a slurry prepared by dispersing 100 mg of powdered sample in 15 mL of 0.10 mol L⁻¹ HCl solution. Results obtained by developed methodology were not statistically different from those obtained by flame emission spectrometry. In the optimized conditions the method presented a linear range of 5-40 mg L⁻¹ and a relative standard deviation of 3.6% at 5 mg L⁻¹ Li concentration. Detection and quantification limits were 0.54 and 1.8 mg L⁻¹, respectively. Sampling frequency, calculated as the time interval passed between two consecutive injections, was 60 samples per hour. The methodology was successfully applied in the determination of lithium in three commercial samples.