Application of fluorescence spectroscopy combined with interval partial least squares to the determination of enantiomeric composition of tryptophan

Abstract The application of interval partial least squares (iPLS) method to the fluorescence spectroscopy analysis was investigated. The practicability of spectral region selection in the fluorescence spectroscopy analysis was studied. A method which combines fluorescence spectroscopy and iPLS was proposed for determining the enantiomeric composition of tryptophan (Trp). Fluorescence spectroscopy was used to measure the diastereomeric interaction between the enantiomers of Trp and bovine serum albumin, which plays the role of chiral selector. iPLS was used to select the spectral region and build the calibration model between the fluorescence spectral data and enantiomeric composition of Trp. The spectral region from 300 nm to 356 nm was selected and used to build the calibration model. Leave-one-out cross validation and external test validation were used to validate the obtained models. By selecting the spectral region, iPLS provided better prediction performance, in comparison to the full-spectrum PLS model. The root mean square relative error (RMSRE) of leave-one-out validation has decreased from 10.24 to 7.17, and the RMSRE of external test validation has decreased from 8.59 to 7.06. In addition, four local-spectrum PLS models were developed in order to make a comparison to the iPLS model. The result demonstrates the iPLS model is superior to the four local-spectrum PLS models. The result of this work demonstrates the proposed method is practicable for determining the enantiomeric composition of Trp at trace level. When there is 2.50 μmol·L− 1 Trp in the samples, the enantiomeric composition can be accurately determined. Moreover, the result demonstrates the selection of spectral region has significant influence on the fluorescence spectroscopy analysis and iPLS is a practicable method for spectral region selection.

[1]  Cuirong Sun,et al.  Qualitative and quantitative analysis of enantiomers by mass spectrometry: application of a simple chiral chloride probe via rapid in-situ reaction. , 2014, Analytica chimica acta.

[2]  C. Tran,et al.  Chiral ionic liquid that functions as both solvent and chiral selector for the determination of enantiomeric compositions of pharmaceutical products. , 2006, Analytical chemistry.

[3]  Marco Flôres Ferrão,et al.  Simultaneous determination of quality parameters of biodiesel/diesel blends using HATR-FTIR spectra and PLS, iPLS or siPLS regressions , 2011 .

[4]  I. Swamidoss,et al.  Determination of the enantiomeric composition of some molecules of pharmaceutical interest by chemometric analysis of the UV spectra of guest-host complexes formed with modified cyclodextrins. , 2005, Talanta.

[5]  Tahir Mehmood,et al.  A review of variable selection methods in Partial Least Squares Regression , 2012 .

[6]  S. Engelsen,et al.  Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .

[7]  Long Jiao,et al.  QSPR study on the relative retention time of polybrominated diphenyl ethers (PBDEs) by using molecular distance-edge vector index , 2014 .

[8]  Jiewen Zhao,et al.  Selection of the efficient wavelength regions in FT-NIR spectroscopy for determination of SSC of ‘Fuji’ apple based on BiPLS and FiPLS models , 2007 .

[9]  I. Delfino,et al.  Visible micro-Raman spectroscopy for determining glucose content in beverage industry. , 2011, Food chemistry.

[10]  K. W. Busch,et al.  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. , 2006, Talanta.

[11]  M. Jalali-Heravi,et al.  Prediction of electrophoretic mobilities of alkyl- and alkenylpyridines in capillary electrophoresis using artificial neural networks. , 2002, Journal of chromatography. A.

[12]  Roman M. Balabin,et al.  Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data. , 2011, Analytica chimica acta.

[13]  Søren Balling Engelsen,et al.  Multivariate near-infrared and Raman spectroscopic quantifications of the crystallinity of lactose in whey permeate powder. , 2005 .

[14]  Zou Xiaobo,et al.  Variables selection methods in near-infrared spectroscopy. , 2010, Analytica chimica acta.

[15]  Ryan Gosselin,et al.  A Bootstrap-VIP approach for selecting wavelength intervals in spectral imaging applications , 2010 .

[16]  T. Ward,et al.  Chiral separations: a review of current topics and trends. , 2012, Analytical chemistry.

[17]  Pierre Dardenne,et al.  Validation and verification of regression in small data sets , 1998 .

[18]  Paola Gramatica,et al.  Principles of QSAR models validation: internal and external , 2007 .

[19]  Susan L. Rose-Pehrsson,et al.  Automated wavelength selection for spectroscopic fuel models by symmetrically contracting repeated unmoving window partial least squares , 2008 .

[20]  C. Spiegelman,et al.  Theoretical Justification of Wavelength Selection in PLS Calibration:  Development of a New Algorithm. , 1998, Analytical Chemistry.

[21]  Long Jiao.  QSPR studies on soot-water partition coefficients of persistent organic pollutants by using artificial neural network. , 2010, Chemosphere.

[23]  C. Tran,et al.  Fluorescence determination of enantiomeric composition of pharmaceuticals via use of ionic liquid that serves as both solvent and chiral selector. , 2006, Analytical biochemistry.

[24]  Alejandro C. Olivieri,et al.  Wavelength Selection for Multivariate Calibration Using a Genetic Algorithm: A Novel Initialization Strategy , 2002, J. Chem. Inf. Comput. Sci..

[25]  Patrícia Valderrama,et al.  Bilinear least squares (BLLS) and molecular fluorescence in the quantification of the propranolol enantiomers. , 2008, Analytica chimica acta.

[26]  Marcelo Blanco,et al.  Use of circular dichroism and artificial neural networks for the kinetic-spectrophotometric resolution of enantiomers , 2001 .

[27]  I. Swamidoss,et al.  Determination of the enantiomeric composition of guest molecules by chemometric analysis of the UV-visible spectra of cyclodextrin guest-host complexes. , 2003, Journal of the American Chemical Society.

[28]  T. Næs,et al.  Canonical partial least squares—a unified PLS approach to classification and regression problems , 2009 .

[29]  S. Engelsen,et al.  Quantification of blockiness in pectins-A comparative study using vibrational spectroscopy and chemometrics. , 2009, Carbohydrate research.

[30]  B. Hemmateenejad,et al.  A comparative study between PCR and PLS in simultaneous spectrophotometric determination of diphenylamine, aniline, and phenol: Effect of wavelength selection. , 2007, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[31]  S. Wold,et al.  Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data. , 2002, Analytical chemistry.

[32]  C. Tran,et al.  Determination of enantiomeric compositions of amino acids by near-infrared spectrometry through complexation with carbohydrate. , 2003, Analytical chemistry.

[33]  J. Kong,et al.  A novel strategy for the determination of enantiomeric compositions of chiral compounds by chemometric analysis of the UV-vis spectra of bovine serum albumin receptor-ligand mixtures. , 2007, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[34]  Ronei J. Poppi,et al.  Application of mid infrared spectroscopy and iPLS for the quantification of contaminants in lubricating oil , 2005 .

[35]  C. Jun,et al.  Performance of some variable selection methods when multicollinearity is present , 2005 .

[36]  Jiewen Zhao,et al.  Measurement of total flavone content in snow lotus (Saussurea involucrate) using near infrared spectroscopy combined with interval PLS and genetic algorithm. , 2010, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[37]  C. P. Winlove,et al.  Feasibility study using surface-enhanced Raman spectroscopy for the quantitative detection of tyrosine and serine phosphorylation. , 2007, Biochimica et biophysica acta.

[38]  S. Fakayode,et al.  Determination of the enantiomeric composition of some molecules of pharmaceutical interest by chemometric analysis of the UV spectra of cyclodextrin guest–host complexes , 2004 .

[39]  D. Bellert,et al.  Determination of the enantiomeric composition of phenylalanine samples by chemometric analysis of the fluorescence spectra of cyclodextrin guest-host complexes. , 2005, The Analyst.

[40]  Roberto Kawakami Harrop Galvão,et al.  NIR spectrometric determination of quality parameters in vegetable oils using iPLS and variable selection , 2008 .