The Study Of Development And Application Of Multivariate Curve Resolution And Other Chemometric Methods In Analytical Chemistry

In traditional separation experiment, searching optimal separation conditions, in order to analysis each compound in a mixture respectively, is more often than not a time-consuming and tedious procedure. However, such kind of condition is difficult to find because of complexity and limitation of separation technique. When the physical separation of components is not accomplished, 'soft separation' of these compounds is still possible by using multivariate curve resolution. Multivariate curve resolution (MCR) methods are a group of techniques which intend the recovery of the response profiles of more than one component in an unresolved and unknown mixture obtained from evolutionary processes when no prior or little information is available about the nature and composition of these mixtures. In this paper, the application of MCR in capillary electrophoresis (CE) overlapping peaks resolution and quantification and in the qualitative evaluation of chromatographic fingerprint of herbal, is studied. Factors that affect resolution are discussed, including spectra similarities of components, type of overlapping peaks, internal standard, iteration optimization initials and data pretreatment. Quantification of uncompleted separated compounds is accomplished, and comparison among several MCR methods is performed.Chiral analysis has become increasing important in recent years because chirality is a central factor in biological phenomena, and chiral recognition is the basic aspect of the bio-system in nature. For example, the behavior of the enantiomers of a chiral drug may show striking differences in terms of biological activity, potency, toxicity, transport mechanisms, and routes of metabolism. Therefore, the pervasiveness of chiral drug development and the rapid development of combinatorial synthesis demand simple, fast, reliable and sensitive methods for chiral analysis.There are three main sections in this research work:1 The application of multivariate curve resolution in resolution and quantification of capillary electrophoresis overlapping peaks 1) Resolution of overlapping capillary electrophoresis peaks by using chemometric analysis: quantification of the components in compound reserpine tabletsThis paper is concerned with application of multivariate curve resolution with alternating least squares (MCR-ALS) methods to second order data from capillary electrophoresis with diode array detector (CE-DAD). Initial qualitative solutions obtained by evolving factor analysis (EFA) and pure-variable-detection method can be further optimized by a simultaneous analysis of multiple electrophoresis run data with ALS regression. While unknown samples are analyzed simultaneously against the corresponding standards in different composition ratios, the exact amounts of common components in different capillary electrophoresis (CE) runs can be determined by traditional calibration curve method, and quantification can thus be achieved. The above methods are applied to the determination of the components in compound reserpine tablets in overlapping peaks from CE. The quantification results are compared with those of the first derivative of electrophoretogram method and artificial neural networks (ANN) method.2) Application of MCR-ALS on Analysis of Hyphenated-Instrument DataThis paper is concerned with application of multivariate curve resolution with alternating least squares (MCR-ALS) methods to simulated and experimental data. The experimental data are from capillary electrophoresis with diode array detector (CE-DAD). Factors that affect resolution when MCR-ALS is applied to single matrix are discussed, including spectra similarities of components, type of overlapping peaks and initials from EFA analysis. MCR-ALS is also used when several matrices are analyzed simultaneously and in this case the problem, such as rank-deficiency can be overcome.3) Resolution of overlapping capillary electrophoresis peaks by using chemometric analysis: improved quantification by using internal standardDiscussed in this paper is the application of internal standard for quantification of compounds in overlapping peaks from capillary electrophoresis diode array detection, which has not often been studied. A strategy is proposed to calculate the calibration coefficient in this case. The resolution of overlapping capillary electrophoresis peaks is achieved by using second order multivariate curve resolution method. Before resolution, the signals are baseline corrected by automation baseline correction, in which a smoothed signal is used for both baseline recognition and modeling. An evolving routine is used to determine the peak shift and improve the repeatability of migration times. The quantification results are compared with those of generalized rank annihilation method. For multivariate curve resolution method, improved quantification-precision results from using internal standard,but further research is expected in the case of generalized rank annihilation method.4) Application of MCR-ALS methods on the resolution of overlapping CE peaks from different separation conditionsDiscussed in this paper is the development of a new strategy to improve resolution of overlapping capillary electrophoresis (CE) peaks by using second-order multivariate curve resolution with alternating least square (second-order MCR-ALS) methods. Several kinds of organic reagents are added respectively in buffers and sets of overlapping peaks with different separations are obtained. Augmented matrix is formed by the corresponding matrices of the overlapping peaks and is then analyzed by the second-order MCR-ALS method in order to use all data information to improve the precision of the resolution. Similarity between the resolved unit spectrum and the true one is used to assess the quality of the solutions provided by the above method. 3, 4-dihydropyrimidin-2-one derivatives (DHPOs) are used as model components and mixed artificially in order to obtain overlapping peaks. Three different impurity levels, 100, 20, 10 % relative to the main component, are used. With this strategy, the concentration profiles and spectra of impurities, which are no more than 10% of the main component, can be resolved from the overlapping peaks without pure standards participant in the analysis. The effects of the changes in the components spectra in the buffer with different organic reagents on the resolution are also evaluated, which are slight and can thus be ignored in the analysis. Individual data matrices (two-way data) are also analyzed by using MCR-ALS and heuristic evolving latent projections (HELP) methods and their results are compared with those when MCR-ALS is applied to augmented data matrix (three- way data) analysis. 2 The application of multivariate curve resolution in evaluation of chromatographic fingerprint of herbal1) Resolution of overlapping chromatographic peaks by using MCR-ALS: resolution and quantification of the components in rhizoma corydalisThe application of chemmometrics on the resolution of overlapping peaks from chromatographic fingerprint of herbal. Multivariate curve resolution with alternating least square is used to analyze the overlapping peaks from chromatographic fingerprint of Rhizoma Corydalis. The results are compared with those from traditional methods. MCR-ALS can detect the presence of impurity which interfere the quantification of analytes. Chemmometrics can evaluate the quality of herbal more accurate than traditional methods.3 The application of chemometric tools in chiral discrimination1) Quantitative chiral analysis in capillary electrophoresis from unresolved peaks using derivative electropherograms, experimental design and artificial neural networks.Quantitative capillary electrophoretic analysis of chiral compounds might be difficult or even impossible when baseline separation is not reached. In this work, the use of n-th derivative of the electropherogram was studied and examined on model and experimental data. The electropherograms should be first smoothed using Savitzky-Golay method and then the quantitative analysis is then possible using either a graphical method or multivariate calibration applying a combination of experimental design (ED) and artificial neural networks (ANNs). The best results were obtained for the first derivative, higher derivatives are not suitable because of noise accumulation. The method was applied to quantify chiral amino acids from unresolved peaks, but it is applicable for quantitative analysis of any other chiral analytes from poorly resolved peaks. Precision of analysis from partially resolved peaks is about±3.2 % rel.2) A novel strategy for the determination of enantiomeric compositions of chiral compounds by chemometric analysis of the UV-Visible spectra of bovine serum albumin receptor-ligand mixtures In this work, a novel strategy was constructed to determine the enantiomericcomposition of chiral substances discriminated by bovine serum albumin (BSA) based on the UV-Vis spectra of the receptor-ligand mixtures coupled with partial least squares (PLS-1) analysis. Taking tryptophan (Trp) enantiomer as an example, when 20μM BSA was used, the enantiomeric composition was accurately determined with concentration of only 100 nM and the corresponding enantiomeric excess as high as 98% (or - 98%),-which is relatively more sensitive than that reported. Furthermore, the BSA-based approach was also used to predict the enantiomeric composition of other chiral compounds, such as phenylalanine (Phe), tyrosine (Tyr), alanine (Ala), cysteine (Cys), DOPA, and propranolol (Prop). The results fully demonstrate that BSA is effective in determination of enantiomeric composition of some chiral compounds.3) Quantitative chiral analysis in UV-Vis spectrum by using artificial neural networksA new method based on bovine serum albumin (BSA) was demonstrated to determine the enantiomeric composition of chiral substances. In this method, the quantitative determination of enantiomeric compounds is achieved by combining UV-Vis spectra, BSA guest-host complexion, and artificial neural network modeling. Seven chiral compounds, tryptophan, phenylalanine, tyrosine, alanine, cysteine, DOPA, and propranolol are separately determined by this method. The results show that this method is effective in determination of tryptophan, DOPA and propranolol. The average quantitative errors are 7.14%, 2.92% and 4.30%, respectively.4) Bovine serum albumin used for determination of the enantiomeric concentration of chiral compounds by chemometric analysis of the fluorescence spectra of receptor-ligand mixturesIn this chapter, a new method based on fluorescence spectra was demonstrated to determine the enantiomeric composition of chiral substances with relatively higher sensitivity. In this method, the quantitative determination of enantiomeric compounds is achieved by combining fluorescence spectra, BSA guest-host complexion, and PLS-1 and artificial neural network modeling. The composition of tryptophan in relatively lower concentration is separately determined by this method, and the prediction results show that the method is not only effective but also relatively sensitive in determination of enantiomeric compositions. When 5.00μM BSA is used, the enantiomeric composition is accurately determined with only 0.03μM concentration by using both PLS and ANNs.