Biomedical subjects

Tomasz Baczek

Publications and source records attributed to Tomasz Baczek.

14 recordsLinked to original sources

PubMed2006

Chemometric evaluation of relationships between retention and physicochemical parameters in terms of multidimensional liquid chromatography of peptides.

Statistical evaluation of relationships between chromatographic retention and physicochemical descriptors of peptides was performed. The relationships describing retention were derived for a set of 98 structurally diversified peptides chromatographed on HPLC columns using acetonitrile and water with the addition of 0.1% trifluoroacetic acid as the mobile phase. It was found with the aid of multivariate principal component analysis (PCA) and factor analysis that the retention contributions of the amino acids comprising the individual peptide and the physicochemical parameters describing the bulkiness properties of peptides have the greatest influence on the retention of peptides, independent of the stationary phase used. Retention data were determined on six physicochemically different HPLC columns with the aid of experiments performed with various gradient times and column temperatures. Moreover, PCA permitted differentiation of the RP-HPLC columns used in terms of their similarities and dissimilarities in respect of peptide separations.

Amino Acid Sequence↗

PubMed2006

Evaluation of the silanol-suppressing potency of ionic liquids.

Recently, increasing attention has been paid to the use of ionic liquids for high-performance liquid chromatography (HPLC) and capillary electrophoresis. In the present study, the silanol-suppressing potency of ionic liquids was evaluated by HPLC using the two-retention site model proposed previously by Nahum and Horváth (J. Chromatogr. 1981, 203, 53-63). The binding constant, KA, in that approach has been demonstrated to reliably reflect the ability of the ionic liquids to block the silanols of the silica support material of the stationary phase. The determinations were carried out for ionic liquids of the 1-alkyl-3-methylimidazolium group with the use of a series of basic drugs as the test analytes. Comparison of ionic liquids with standard mobile phase additives such as triethylamine showed the former to possess advantages as silanol suppressors in HPLC. The main advantage of the method is that it provides a simple and fast determination of the silanol complex stability, which allowed comparison of the suppressing efficiency of several ionic liquids.

Chromatography, High Pressure Liquid↗

PubMed2005

Comparative characteristics of HPLC columns based on quantitative structure-retention relationships (QSRR) and hydrophobic-subtraction model.

The study was aimed at quantitative comparison of retention properties of modern stationary phases for reversed-phase HPLC. Three approaches, the calculated logarithm of octanol/water partition coefficient (clogP)-based model, the molecular modeling descriptors-based model and the hydrophobic-subtraction model, were compared and discussed. Gradient retention time, tR, of a series of test analytes was a dependent variable in the quantitative structure-retention relationship (QSRR) equations describing retention in terms of analytes' structure descriptors. The QSRRs derived were used to characterize in quantitative manner the specific retention properties of nine representative reversed-phase HPLC. Either the theoretically calculated logarithm of octanol/water partition coefficient, or the structural descriptors from molecular modeling were employed to quantitatively characterize the structure of the analytes. The three molecular modeling-derived structural descriptors considered were: the total dipole moment, the electron excess charge of the most negatively charged atom and the water-accessible molecular surface area. In addition to the above standard QSRR approaches, a recently developed parameterization of reversed-phase column selectivity based on the hydrophobic-subtraction model of Snyder et al. [L.R. Snyder, J.W. Dolan, J.W. Carr, The hydrophobic-subtraction model of reversed-phase column selectivity, J. Chromatogr. A 1060 (2004) 77] was considered. According to the hydrophobic-subtraction model, reversed-phase columns are characterized by five selectivity parameters derived from the linear solvation energy relationships (LSER) theory. Values of these parameters are available for more than 300 different columns. It has been demonstrated that the clogP-based model, the molecular modeling descriptors-based model and the hydrophobic-subtraction model provide generally similar classification of the HPLC columns studied. Some differences in column classification by the three approaches considered are discussed in terms of specific properties of individual stationary phases. All the approaches allow a quantitative, although multidimensional, characteristic of HPLC columns, however, the nonempirical QSRR-based approach is simpler and require less labor.

Chromatography, High Pressure Liquid↗

PubMed2005

Behavior of peptides and computer-assisted optimization of peptides separations in a normal-phase thin-layer chromatography system with and without the addition of ionic liquid in the eluent.

The addition of an ionic liquid into the mobile phase appeared to be useful in optimization of chromatographic separation of peptides. Different behavior of peptides in thin-layer chromatography (TLC) was observed after addition of 1-ethyl-3-methylimidazolium tetra fluoroborate to the eluent in comparison to the system without the ionic liquid. Nonlinear dependence of the retention coefficient, R(M), of peptides on the volume percentage of acetonitrile in the eluent was found in normal-phase TLC with and without immidazolium tetra fluoroborate in the mobile phase. In general, R(M) increased with increasing concentration of acetonitrile. In TLC systems without the ionic liquid, R(M) can be described well with a quadratic function. On the other hand, in a TLC system with an ionic liquid as the additive to the mobile phase, the retention behavior is better described with a third-degree polynomial function. The potential usefulness of ionic liquids for optimization of separation of peptides was demonstrated. Optimization of the separation conditions was supported by a commercially available computer program.

Acetonitriles↗

PubMed2005

Prediction of high-performance liquid chromatography retention of peptides with the use of quantitative structure-retention relationships.

Quantitative structure retention relationships (QSRR) were derived allowing prediction of reversed-phase high-performance liquid chromatography (HPLC) retention of peptides. To quantitatively characterize the structure of a peptide, and then to predict its gradient retention time under given HPLC conditions, the following descriptors are employed: logarithm of the sum of retention times of the amino acids composing the peptide, log Sum(AA), logarithm of Van der Waals volume of the peptide, log VDW(Vol), and logarithm of its calculated n-octanol-water partition coefficient, clog P. The first descriptor is based on a set of empirical data for 20 natural amino acids. The next two descriptors are easily calculated from a structural formula. The predicted gradient retention times are in excellent agreement with the experimental data, determined for a structurally diversified series of 101 peptides. The QSRR equation obtained predicts in a convenient and reliable manner the retention times for any peptide in a once characterized HPLC system.

Amino Acid Sequence↗

PubMed2004

Fractionation of peptides and identification of proteins from Saccharomyces cerevisiae in proteomics with the use of reversed-phase capillary liquid chromatography and pI-based approach.

The aim of the work was to explore the identification of proteins from Saccharomyces cerevisiae using combined capillary reversed-phase liquid chromatography (RPLC) and in-solution isoelectric focusing (sIEF) for fractionation of peptides prior to mass spectrometry analysis. That method was proved to be the alternative separation method for complex mixtures of protein tryptic digests in proteomics. Analysis of the identification of peptides was performed with the use of electrospray ionization-ion trap tandem mass spectrometry (ESI-IT-MS/MS). First, the sIEF fractionation was carried out prior to separation and mass spectrometry identification by nano-LC/ESI-MS/MS instrument. The proposed approach based on sIEF and nano-LC/ESI-MS/MS analysis was proved to be an efficient and accurate alternative fractionation method of complex protein digests and can be considered as the useful tool for identification of proteins. Moreover, analytical information from that approach can be considered as the additional source of database matching constraint and can be valuable tool for analytical and bioinformatics studies of peptides fractionation in proteomics. Based on the MS/MS results obtained with ESI-IT-MS/MS instrument, 851 proteins from S. cerevisiae were identified. However, after careful analysis of the data reduction in number of proteins to 126 was obtained. Those results are discussed and interpreted in the view of the evaluation method used.

Animals↗

PubMed2004

Suppression of deleterious effects of free silanols in liquid chromatography by imidazolium tetrafluoroborate ionic liquids.

Silica-based stationary phases are commonly used in liquid chromatography, but their surface acidity causes known problems, especially when separating basic compounds. Deleterious effects of free silanols are not fully removed by standard prevention procedures consisting in adding alkylamines or other amino quenchers to the eluents. We found that ionic liquids of the imidazolium tetrafluoroborate class, added to mobile phases at concentrations of 0.5-1.5% (v/v), blocked silanols and provided excellent thin-layer chromatographic separations of strongly basic drugs which were otherwise not eluted, even with neat acetonitrile as the mobile phase. The silanol suppressing potency of imidazolium tetrafluoroborates was demonstrated to markedly exceed that of the standard mobile phase additives, like triethylamine, dimethyloctylamine and ammonia. The proposed new mobile phase additives were also demonstrated to provide reliable lipophilicity parameters of base drug analytes as determined by gradient mode of high-performance liquid chromatography. By applying the readily available and environmentally friendly imidazolium tetrafluoroborate ionic liquids, simple and efficient means of improvement of liquid chromatographic analysis of organic bases were elaborated.

Borates↗

PubMed2004

Artificial neural network analysis for evaluation of peptide MS/MS spectra in proteomics.

The aim of the work was to explore usefulness of artificial neural network (ANN) analysis for the evaluation of proteomics data. The analysis was applied to the data generated by the widely used protein identification program Sequest, completed with several structural parameters readily calculated from peptide molecular formulas. Proteins from yeast cells were identified based on the MS/MS spectra of peptides. The constructed ANN was demonstrated to classify automatically as either "good" or "bad" the peptide MS/MS spectra otherwise classified manually. An appropriately trained ANN proves to be a high-throughput tool facilitating examination of Sequest's results. ANNs are recommended as a means of automatic processing of large amounts of MS/MS data, which normally must be considered in the analysis of complex mixtures of proteins in proteomics.

Artificial Intelligence↗

PubMed2004

Fractionation of peptides in proteomics with the use of pI-based approach and ZipTip pipette tips.

The aim of the work was to explore the utility of the in-solution isoelectric focusing (sIEF) fractionation method. That method was proved to be the alternative separation method of mixtures of protein tryptic digests in proteomics. Analysis of the identification of peptides was performed with the use of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS). For that research, previously designed the miniaturized multi-chamber fractionation sIEF device (75 microl volume for each chamber) based on polyacrylamide gel membranes with immobilines technology was utilized. To evaluate the efficiency and accuracy of sIEF fractionation combined with MS/MS peptides identification, bovine serum albumin (BSA) digest and mixture of five proteins digest were used. First, fractionation of bovine serum albumin digest sample was performed using sIEF method. Studies performed for that simple mixture of peptides proved the ability of the sIEF device to focus peptides mostly in one chamber. Additionally performed the correlation analysis between pI(calc) and pI(exp) values for identified peptides proved the possibility to obtain experimentally useful high correlation. That information was found to have a potential value for construction of additional constraint during false positives evaluation process among identified proteins. Next, studies on the sIEF fractionation were combined with the evaluation of practical use of ZipTip pipette tips to fractionate peptides in the case of simple mixture of proteins. For this, five proteins digest samples were used. The analysis without prior any fractionation enabled to identify very limited number of proteins. The significant improvement was obtained when one used sIEF alone or with combination with ZipTips fractionation prior to MS analysis. The proposed approach based on in-solution isoelectric focusing proved to be an efficient and accurate alternative fractionation method of protein digests and can be considered as the first useful dimension in two-dimensional proteomics separations. Moreover, analytical information from that pI-based fractionation method can be considered as the additional source of database matching constraint. It can also be a valuable tool for analytical and bioinformatic studies of peptides fractionation in proteomics.

Amino Acid Sequence↗

PubMed2004

Prediction of the affinity of the newly synthesised azapirone derivatives for 5-HT1A receptors based on artificial neural network analysis of chromatographic retention data and calculation chemistry parameters.

The performance of artificial neural network (ANN) in predicting the affinity of a series of 65 new azapirone derivatives for rat brain serotonin 5-HT1A receptors based on high-performance liquid chromatography (HPLC) retention data and on non-empirical structural parameters of the compounds' was studied. Affinity of the agents for rat brain 5-HT1A receptors were assessed in vitro and expressed as inhibitor constant values, Ki. The retention parameters determined in 14 HPLC systems along with compounds' structural descriptors from calculation chemistry were considered in ANN analysis. Supervised method of ANN learning with back-propagation strategy was used in ANN calculations. Two models of ANN of similar architecture were designed: the first one for the data based on chromatographic retention data and the second based on structural parameters of the agents. Each ANN model was trained with the data of training set. It was next used to classify the agents from the testing set into two groups: active (Ki < 50 nM) and inactive compounds (Ki > 50 nM). A high prediction performance of both ANN models considered as regards the affinity of new azapirone derivatives for the serotonin 5-HT1A receptors was demonstrated. However, the percent of correctly classified compounds was higher in the case of the ANN processing of the non-empirical structural descriptors of azapirone derivatives. Since the ANN analysis of the retention data and of the structural parameters originating from calculation chemistry allows to segregate drug candidates according to their pharmacological properties that, in consequence, may be of help to limit the number of biological assays in the search for new drugs.

Aza Compounds↗

PubMed2003

Predictive approaches to gradient retention based on analyte structural descriptors from calculation chemistry.

Quantitative structure retention relationships (QSRRs) were applied to predict reversed-phase HPLC gradient retention. The performance of the recently recommended QSRR models was compared. One tested model is based on structural descriptors from molecular modeling. To quantitatively characterize the structure of analytes the following three structural descriptors are employed: total dipole moment, electron excess charge of the most negatively charged atom and water-accessible molecular surface area. Reliability of the resulting gradient retention time predictions was compared to that provided by the models relating retention to the theoretically calculated logarithm of n-octanol-water partition coefficient, log P. The requested values of log P were obtained using three commercially available softwares. The predicted retention parameters were compared for a series of structurally diversified small molecular mass analytes. It has been demonstrated that the retention predictions from both the molecular modeling descriptors-based and the log P-based QSRR are characterized by similar errors. It has been hypothesized that the optimization of separation based on QSRRs and the linear solvent strength theory might be of practical analytical value.

Chromatography, High Pressure Liquid↗

PubMed2002

Lipophilicity and pKa estimates from gradient high-performance liquid chromatography.

The linear-solvent strength (LSS) model of gradient elution has been applied to estimate parameters of lipophilicity and acidity of a series of drugs and model chemicals. Apparent pKa values and log kw values for individual analytes were determined in 2-3 gradient runs. The first experiment (or first two experiments) uses a wide-range organic modifier gradient with pH chosen for suppressed ionization of the analyte. The result of this experiment allows an estimate of contents of organic modifier of the mobile phase (%B) providing the required retention coefficient, k, for the non-ionized analyte. The following experiment is carried out with the latter %B and a pH-gradient of the aqueous component of the eluent that is sufficient to overlap the possible pKa-value of the analyte. The initial pH of the buffer used to make the mobile phase is selected to insure that the analyte is in non-ionized form. The resulting retention time allows an estimate of PKa in a solvent of the selected %B. At the same time, estimates of log kw can also be obtained. The log kw parameter obtained from gradient HPLC by the approach proposed correlated well with the corresponding value obtained by standard procedure of extrapolation of retention data determined in a series of isocratic measurements. Correlation between log kw and the reference parameter of lipophilicity, log P, was very good for a series of test analytes and satisfactory for a structurally diverse series of drugs. The approach supported with specific detection procedures can be recommended for fast screening of lipophilicity of individual components of complex mixtures like those produced by combinatorial chemistry. The values of pKa obtained in a study were found to correlate with the literature pKa data determined in water for a set of aniline derivatives studied. In case of a series of drugs the correlation was less than moderate if the general procedure of pKa determination was applied.

Chromatography, High Pressure Liquid↗

PubMed2002

Combination of linear solvent strength model and quantitative structure-retention relationships as a comprehensive procedure of approximate prediction of retention in gradient liquid chromatography.

Quantitative structure-retention relationships (QSRR) combined with the linear solvent strength (LSS) model are demonstrated to provide approximate predictions of gradient reversed-phase high-performance liquid chromatography (HPLC) retention time for any structurally defined analyte on a once characterized column. The approach requires at first the determination of retention times for a predesigned model series of 15 analytes in two gradient runs. Then by employing the LSS theory a given HPLC system of interest is quantitatively characterized. Structure of the model analytes is next described quantitatively by means of three structural descriptors from standard molecular modeling: total dipole moment, electron excess charge of the most negatively charged atom and water-accessible molecular surface area. With those data the general QSRR equations are derived which describe gradient retention times of the model analytes in the specific column/eluent system. Having now the structural descriptors for any analyte to be chromatographed in such a characterized HPLC system, one employs respective general QSRR equations to calculate its expected gradient retention time at given gradient conditions by means of appropriate LSS equations. Additionally, the chromatographic parameters log kw and S can be calculated and retention coefficients corresponding to chosen isocratic conditions evaluated. The approach provides retention predictions which can be treated as a first approximation of actual data. Predictions are not yet precise enough for practical separation purposes but can be of use in rational modification of analytical conditions aimed at optimization of separations.

Chromatography, High Pressure Liquid↗

PubMedDate not supplied

Prediction of peptide retention at different HPLC conditions from multiple linear regression models.

To quantitatively characterize the structure of a peptide and to predict its gradient retention time at given HPLC conditions three structural descriptors are used: (i) logarithm of the sum of retention times of the amino acids composing the peptide, log SumAA, (ii) logarithm of the van der Waals volume of the peptide, log VDW(Vol), (iii) and the logarithm of the peptide's calculated n-octanol-water partition coefficient, clog P. The log SumAA descriptor is obtained from empirical data for 20 natural amino acids, determined in a given HPLC system. The two other descriptors are calculated from the peptides' structural formulas using molecular modeling methods. The quantitative structure-retention relationships (QSRR), build by multiple linear regression, describe HPLC retention of peptide on a given chromatographic system on which the retention of the 20 amino acids was predetermined. A structurally diversified series of 98 peptides was employed. The predicted gradient retention times on several chromatographic systems were in good agreement with the experimental data. The QSRR equations, derived for a given system operated at variable gradient times and temperatures allowed for the prediction of peptide retention in that system. Matching the experimental HPLC retention to the theoretically predicted for a presumed peptide could facilitate original protein identification in proteomics. In conjunction with MS data, prediction of the retention time for a given peptide might be used to improve the confidence of peptide identifications and to increase the number of correctly identified peptides.

Amino Acid Sequence↗