Applicability of predictive models to the peptide mobility analysis by capillary electrophoresis–electrospray mass spectrometry

CE-ESI-MS for bottom-up proteomics: Advances in separation, interfacing and applications

With the development of more sensitive hyphenation strategies for capillary electrophoresis-electrospray-mass spectrometry the technique has reemerged as technique with high separation power combined with high sensitivity in the analysis of peptides and protein digests. This review will discuss the newly developed hyphenation strategies for CE-ESI-MS and their application in bottom-up proteomics as well as the applications in the same time span, 2009 to present, using co-axial sheathliquid. Subsequently all separate aspects in the development of a CE-ESI-MS method for bottom-up proteomics shall be discussed, highlighting certain applications and discussing pros and cons of the various choices. The separation of peptides in a capillary electrophoresis system is discussed including the great potential for modeling of this migration of peptides due to the simple electrophoretic separation process. Furthermore, the technical aspects of method development are discussed, namely; background electrolyte choice, coating of the separation capillary and chosen loading method. Finally, conclusions and an outlook on future developments in the field of bottom-up proteomics by CE-ESI-MS will be provided.

Prediction of metabolite identity from accurate mass, migration time prediction and isotopic pattern information in CE-TOFMS data

CE-TOFMS is a powerful method for profiling charged metabolites. However, the limited availability of metabolite standards hinders the process of identifying compounds from detected features in CE-TOFMS data sets. To overcome this problem, we developed a method to identify unknown peaks based on the predicted migration time (t(m)) and accurate m/z values. We developed a predictive model using 375 standard cationic metabolites and support vector regression. The model yielded good correlations between the predicted and measured t(m) (R=0.952 and 0.905 using complete and cross-validation data sets, respectively). Using the trained model, we subsequently predicted the t(m) for 2938 metabolites available from the public databases and assigned tentative identities to noise-filtered features in human urine samples. While 38.9% of the peaks were assigned metabolite names by matching with the standard library alone, the proportion increased to 52.2%. The proposed methodology increases the value of metabolomic data sets obtained from CE-TOFMS profiling.

The design and synthesis of alanine-based indolicidin derivatives with identical physicochemical properties and their separation using capillary electrophoresis

Four novel alanine-based indolicidin peptide derivatives were designed containing one WPW motif and two alanine residues, resulting in peptides of similar sequence. The separation of these peptides with identical physicochemical properties including molar mass, charge, and secondary structure as characterized by circular dichroism spectroscopy is very difficult; and the separation of peptides with differing physicochemical properties has only previously been reported. Capillary electrophoresis parameters such as separation buffer concentration, separation buffer pH, capillary length, and separation voltage were investigated to optimize the analysis. Using optimized conditions of a background electrolyte containing 5 mM formic acid of pH 2.0, total capillary length of 51 cm and a voltage of 10 kV enabled a baseline separation of the four peptides. The relative standard deviation of the peak areas and migration times for method repeatability (n = 3) were found to be lower than 8% and 3%, respectively. In addition, reasoning for the separation of these peptides is proposed based on the acidity of the formic acid buffer and the hydrophobic grouping of the tryptophan residues in the peptide primary sequence.

Modelling migration behavior of peptide hormones in capillary electrophoresis-electrospray mass spectrometry

The applicability in capillary electrophoresis-electrospray mass spectrometry (CE-ESI-MS) of the classical semiempirical relationships between electrophoretic mobility and charge-to-mass ratio (me versus q/Malpha) has been investigated in order to describe the migration behavior of a series of bioactive peptide hormones. The influence upon the models of the separation electrolyte pH and the accuracy of the pK values of these compounds were studied first by capillary electrophoresis with ultraviolet detection (CE-UV). The classical polymer model, alpha = 1/2, resulted in slightly better correlations at any of the studied pH. Furthermore, a general linear equation can be adjusted combining all the experimental data pairs, which suggests that correlation in the whole pH range is independent of the ionic form of the studied peptide hormones. The plots of q/M1/2 against separation electrolyte pH were used to predict their electrophoretic separations, using the accurate pK values obtained in a previous work by CE-UV for charge calculations. A volatile separation electrolyte containing 50 mM of acetic acid and 50 mM of formic acid at pH 2.85 was selected for optimum CE-UV and CE-ESI-MS analysis of the peptide mixture. At this pH and taking into account the specific features of the coupling, the correlation using the classical polymer law was excellent and its parameters were similar to the ones of the general linear equation previously obtained by CE-UV. This confirmed the applicability in CE-ESI-MS of the semiempirical relationship originally established by CE-UV.

Recent developments in capillary electrophoresis and capillary electrochromatography of peptides

The article gives a comprehensive review on the recent developments in the applications of high-performance capillary electromigration methods, zone electrophoresis, isotachophoresis, isoelectric focusing, affinity electrophoresis, electrokinetic chromatography, and electrochromatography, to analysis, preparation, and physicochemical characterization of peptides. The article presents new approaches to the theoretical description and experimental verification of electromigration behavior of peptides, covers the methodological aspects of capillary electroseparations of peptides, such as rational selection of separation conditions, sample preparation, suppression of peptide adsorption, new developments in individual separation modes, and new designs of detection systems. Several types of applications of capillary electromigration methods to peptide analysis are presented: conventional qualitative and quantitative analysis, purity control, determination in biomatrices, monitoring of chemical and enzymatical reactions and physical changes, amino acid and sequence analysis, and peptide mapping of proteins. Some examples of micropreparative peptide separations are given and capabilities of capillary electromigration techniques to provide important physicochemical characteristics of peptides are demonstrated.

Capillary electrophoresis of proteins 2003-2005

This review article with 304 references describes recent developments in CE of proteins, and covers the two years since the previous review (Hutterer, K., Dolník, V., Electrophoresis 2003, 24, 3998-4012) through Spring 2005. It covers topics related to CE of proteins, including modeling of the electrophoretic migration of proteins, sample pretreatment, wall coatings, improving separation, various forms of detection, special electrophoretic techniques such as affinity CE, CIEF, and applications of CE to the analysis of proteins in real-world samples including human body fluids, food and agricultural samples, protein pharmaceuticals, and recombinant protein preparations.

Accurate quantitative structure–property relationship model of mobilities of peptides in capillary zone electrophoresis

The aim of this work was to predict electrophoretic mobilities of peptides in capillary zone electrophoresis (CZE) using the linear heuristic method (HM) and a nonlinear radial basis function neural network (RBFNN). Two data sets, consisting of 125 peptides ranging in size between 2 and 14 amino acids and 58 peptides ranging in size between 2 and 39 amino acids, are researched to test applicability of the QSPR methods. In this study, the root mean squared (RMS) errors of the training set, the test set and the whole set of data set 1 are 1.3766, 1.5608 and 1.4157 and the correlation coefficients (R2) are 0.9740, 0.9671 and 0.9724 predicted by RBFNN, respectively. While the RMS errors of the training set, the test set and the whole set of data set 2 are 0.6279, 0.8145 and 0.6673 and the correlation coefficients (R2) are 0.9773, 0.9489 and 0.9732, respectively. So the Offord charge-over-mass term (Q/M(2/3)) combined with descriptors calculated by CODESSA represents the structural features of the peptides appropriately. The electrophoretic mobilities of peptides can be accurately predicted by the linear and nonlinear model. Furthermore, the results of nonlinear model are closer to the experimental data than those of linear model.

Capillary electrophoresis - mass spectrometry: survey on developments and applications 2003-2004

The major developments and applications related to CE-MS over the last two years (2003-2004) and most of the reviews and applications found in the ISI Web of Science and publisher data bases are presented in a tabulated way. This article complements our previous review "Capillary electrophoresis - mass spectrometry: 15 years of developments and applications", Electrophoresis, 2003, 24, 3837-3867 for the last two years 2003-2004. All cited articles were analyzed in a way to illustrate (i) in which journals CE-MS-related papers were mostly found over the last decades and (ii) which commercial CE-, MS-instrumentations or CE-MS combinations were mostly used in the European, Asian, and American continent. Additionally, like it was done in our last review, the reader will rapidly find applications classified as forensics, environment, bioanalytics, pharmaceutics, and metabolites.

Capillary electrophoresis-mass spectrometry: recent advances to the analysis of small achiral and chiral solutes

We describe here the state-of-the-art development of on-line capillary electrophoresis-mass spectrometry (CE-MS) over the last two years. Technological developments included are novel designs of new interfaces and ionization sources, new capillary coatings, buffers, and micelles as well as application of various modes of CE-MS published in the recent literature. The areas of CE-MS application in analysis of small achiral and chiral solutes are covered in sections that highlight the recent advances and possibilities of each mode of CE-MS. Application areas reviewed in this paper include achiral and chiral pharmaceuticals, agrochemicals, carbohydrates, and small peptides. The separation of enantiomers using micellar electrokinetic chromatography (MEKC)-MS with molecular micelles and capillary electrochromatography (CEC)-MS using pack tapered columns appears to provide good tolerance to electrospray stability for routine on-line CE-MS. These two modes seem to be very suitable for sensitive detection of chiral pharmaceuticals in biological samples, but their use will probably increase in the near future. Overall, it seems that one mode of CE-MS, in particular capillary zone electrophoresis (CZE)-MS, is now recognized as established technique for analysis of small charged solutes, but other modes, such as MEKC-MS and CEC-MS, are still within a period of development in terms of both MS-compatible pseudostationary phases and columns as well as applications.

Large-Scale Prediction of Cationic Metabolite Identity and Migration Time in Capillary Electrophoresis Mass Spectrometry Using Artificial Neural Networks

We developed a computational technique to assist in the large-scale identification of charged metabolites. The electrophoretic mobility of metabolites in capillary electrophoresis-mass spectrometry (CE-MS) was predicted from their structure, using an ensemble of artificial neural networks (ANNs). Comparison between relative migration times of 241 various cations measured by CE-MS and predicted by a trained ANN ensemble produced a correlation coefficient of 0.931. When we used our technique to characterize all metabolites listed in the KEGG ligand database, the correct compounds among the top three candidates were predicted in 78.0% of cases. We suggest that this approach can be used for the prediction of the migration time of any cation and that it represents a powerful method for the identification of uncharacterized CE-MS peaks in metabolome analysis.