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Design of a new drug entity is usually preceded by analysis of quantitative structure activity (properties) relationships, QSA(P)R. Six newly synthesized succinimide derivatives have been determined for (i) in silico physico-chemical descriptors, pharmacokinetic and toxicity predictors, (ii) in vitro biological activity on four different carcinoma cell lines and on normal fetal lung cells and (iii) lipophilicity on liquid chromatography. All compounds observed were predicted for good permeability and solubility, good oral absorption rate and moderate volume of distribution as well as for modest blood brain permeation, followed by acceptable observed toxicity. In silico determined lipophilicity, permeability through jejunum and aqueous solubility were correlated with experimentally obtained lipophilic constants (by use of high pressure liquid chromatography) and linear correlations were obtained. Absorption rate and volume of distribution were predicted by chromatographic lipophilicity measurements while permeation through blood bran barrier was predicted dominantly by molecular size defined with molecular weight. Five compounds have demonstrated antiproliferative activity toward cervix carcinoma HeLa cell lines; three were cytotoxic against breast carcinoma MCF-7 cells, while one inhibited proliferation of colon carcinoma HT 29 cell lines. Only one compound was cytotoxic toward normal cell lines, while other compounds were proven as safe. Antiproliferative potential against HeLa cells was described as exponential function of lipophilicity. Based on obtained results, lead compounds were selected.

Aim: The purpose of this work was to develop and validate a rapid and robust LC–MS/MS method for the determination of dexmedetomidine (DEX) in plasma, suitable for analysis of a large number of samples. Method: Systematic approach, Design of Experiments, was applied to optimize ESI source parameters and to evaluate method robustness, therefore, a rapid, stable and cost-effective assay was developed. The method was validated according to US FDA guidelines. LLOQ was determined at 5 pg/ml. The assay was linear over the examined concentration range (5–2500 pg/ml), Results: Experimental design approach was applied for optimization of ESI source parameters and evaluation of method robustness. The method was validated according to the US FDA guidelines. LLOQ was determined at 5 pg/ml. The assay was linear over the examined concentration range (R2 > 0.98). The accuracies, intra- and interday precisions were less than 15%. The stability data confirmed reliable behavior of DEX under tested conditions. Conclusion: Application of Design of Experiments approach allowed for fast and efficient analytical method development and validation as well as for reduced usage of chemicals necessary for regular method optimization. The proposed technique was applied to determination of DEX pharmacokinetics in pediatric patients undergoing long-term sedation in the intensive care unit.

For the first time, stepwise pH gradient thin-layer chromatograms of biologically active substances with controlled developing solvent velocity are presented and described in the paper. Change in buffer pH of the mobile phase solution influences retardation, selectivity, and shape of the separated substances' spots. The conducted research has confirmed that the mobile phase's pH gradient could be an essential factor to optimize the conditions of the separation of substances in reversed-phase high-performance thin-layer chromatography. The reproducibility of the gradient retardation factor values of separated substance zones is satisfactory.

The present paper reports a comparison study of two data processing procedures in GC–MS metabolome components investigation based on two modern softwares: Automated Mass Spectral Deconvolution and Identification System (AMDIS) and GC–MS Solution Postrun Analysis (GC–MS SPA). GC–MS SPA is intended for manual integration and identification, while AMDIS is proposed as a fast, and automatic data analysis tool. Both methods are based on the same free-access library. In the present study, 12 compounds previously detected in a metabolomic fingerprint of grasshopper abdominal secretion, were tested at three concentration levels: 2.5, 5 and 10 μg/mL. The processing procedures were evaluated by comparison of peak area ratio for each tested concentration. The obtained results proved that processing with the use of AMDIS was more sensitive and enabled the identification of all compounds at the lowest selected concentration. Additionally, the differentiation of structurally similar compounds was possible with the use of AMDIS software.

The objective of this work was to develop a multilevel (hierarchical) model based on isocratic-reversed-phase-high-performance-chromatographic data collected in methanol and acetonitrile for 58 chemical compounds. Such a multilevel model is a regression model of the analyte-specific chromatographic measurements, in which all the regression parameters are given a probability model. It is a fundamentally different approach from the most common approach, where parameters are separately estimated for each analyte (without sharing information across analytes and different organic modifiers). The statistical analysis was done with Stan software implementing the Bayesian-statistics inference with Markov-chain Monte Carlo sampling. During the model-building process, a series of multilevel models of different complexity were obtained, such as (1) a model with no pooling (separate models were fitted for each analyte), (2) a model with partial pooling (a common distribution was used for analyte-specific parameters), and (3) a model with partial pooling as well as a regression model relating analyte-specific parameters and analyte-specific properties (QSRR equations). All the models were compared with each other using 10-fold cross-validation. The benefits of multilevel models in inference and predictions were shown. In particular the obtained models allowed us to (i) better understand the data and (ii) solve many routine analytical problems, such as obtaining well-calibrated predictions of retention factors for an analyte in acetonitrile-containing mobile phases given zero, one, or several measurements in methanol-containing mobile phases and vice versa.

Fast and reliable methods for the determination of hydrophobicity and acidity are desired in pre-clinical drug development phases to eliminate compounds with poor pharmacokinetic properties. Reversed-phase high-performance liquid chromatography (RP HPLC) coupled with time-of-flight mass spectrometry (RP HPLC-ESI-TOF-MS) is a convenient technique for that purpose. In this work we determined the chromatographic measure of hydrophobicity (logkw) and dissociation constant (pKa) simultaneously for a large and diverse group of 161 drugs. Retention times were determined by means of RP HPLC-ESI-TOF-MS for a series of pH and organic modifier gradients. We were able to measure retention times for 140 out of 161 (87%) compounds. For those analytes logkw and pKa parameters were calculated and compared with literature and ACD Labs-calculated data. The determined chromatographic measure of hydrophobicity and dissociation constant was closely related to literature and theoretically calculated values. Applied methodology achieved the medium-throughput screening rate of 100 compounds per day and proved to be a simple, fast and reliable approach of assessing important physicochemical properties of drugs. This technique has certain limitations as it is not applicable for very hydrophilic analytes (logP

In this review, we will firstly discuss the types and the general properties of silica, focusing on the silica support used in chromatography and capillary electrophoresis. Additionally, the characterization of functional groups (silanols and siloxanes) will be considered in terms of activity of the stationary phases. We will then discuss physical chemistry of the stationary phases applied in liquid chromatography and capillary electrophoresis. The use of ionic liquids as a silanols’ suppressors will be presented in the next parts of the study, along with the examples of specific applications. The review is completed with conclusions and an outlook for the future developments in the area of analytical applications of ionic liquids.

Trigonelline is a pyridine alkaloid found in fenugreek seeds and coffee beans. Most of the previous studies are concerned with the quantification of trigonelline along with other constituents in coffee herbs or beverages. Only a few have focused on its determination in animal or human tissues by applying different modes of HPLC with UV or MS detection. The aim of the study was to develop and validate a fast and simple method for trigonelline determination in serum by the use of hydrophilic interaction liquid chromatography (HILIC) with ESI-MS/MS detection. Separation of trigonelline was achieved on a Kinetex HILIC column operated at 35°C with acetonitrile-ammonium formate (10 mm, pH = 3) buffer mixture (55:45, v/v) as the mobile phase. The developed method was successfully applied to determine trigonelline concentration in mouse serum after intravenous administration of 10 mg/kg. The developed assay is sensitive (limit of detection = 1.5 ng/mL, limit of quantification = 5.0 ng/mL) and linear in a concentration range from 5.0 to 250.0 ng/mL. Sample preparation is limited to deproteinization, centrifugation and filtration. The application of the HILIC mode of chromatography with MS detection and selection of deuterated trigonelline as internal standard allowed a rapid and precise method of trigonelline quantification to be to developed.

This paper investigates correlations between the standard chromatographic parameter, log kw, obtained experimentally (classical thermodynamic) and obtained through the use of quantitative structure-retention relationships (QSRR) models (extrathermodynamic approach). QSRR models were created using descriptors from calculation chemistry, selected a priori on the basis of chemical intuition. Four modern analytical columns (packed with C18), often used in pharmaceutical analysis, were selected for the study. The simple extrathermodynamic model was demonstrated to be superior in terms of retention description with relation to rather complex models based on thermodynamic hermeneutics. However, all the QSRR equations derived are of limited predictive value as regards prediction of retention on the basis of the structure of the analyte. Nonetheless, they allow the differentiation of mechanism of separation operating on individual tested stationary phases. The descriptors, which are most significant in QSRR equati...

In recent years biologically active compounds isolated from insects call special interest of drug researchers. According to some Polish etnopharmacological observations, secretion from the grasshopper's abdomen ( Orthoptera family) is believed to speed up the process of wound healing. In the present work we focused on determination of main components of the lipid fraction of material from grasshopper abdomen using GC–MS/MS. Samples were qualitatively analyzed using gas chromatography coupled with mass spectrometry. Both liquid–liquid extraction and solid-phase extraction pretreatment methods were used to concentrate and fractionate the compounds from the insect. In the derivatized fractions ca. 350 compounds were identified, including substances of known biological activity. The potential agents affecting wound healing have been indicated. A set of compounds characteristic for all the studied Chorthippus spp., have been identified. Data analysis revealed different lipidomic profiles of grasshoppers depending on the insects origin and collection area.

This study describes application of liquid chromatography coupled with triple quadrupole mass spectrometry (LC-MS) for evaluation of vitamin C stability, the objective being prediction of the degradation products. Detection was performed with an UV detector (UV-Vis) in sequence with a triple-quad mass spectrometer in the multiple reaction mode. The negative ion mode of ESI and MS-MRM transitions of m/z 175→115 (quantifier) and 175→89 (qualifier) for ascorbic acid was used. All the validation parameters were within the range of acceptance proposed by the Food and Drug Administration. The method was fully validated in terms of linearity, LOD, LOQ, accuracy, and interday precision. Validation experiments revealed good linearity with R(2) = 0.999 within the established concentration range, and excellent repeatability (9.3%). The LOD of the method was 0.1524 ng/mL whereas the LOQ was 0.4679 ng/mL. LC-MS methodology proves to be an improved, simple, and fast approach to determining the content of vitamin C and its degradation products with high sensitivity, selectivity, and resolving power within 6 minutes of analysis.

In view of linear free-energy relationships (LFER) chromatographic systems are “free-energy transducers,” translating differences in the structure of analytes into quantitative differences in physicochemical properties, like retention parameters. Hence, quantitative structure property (retention) relationships (QSP(R)R) bear valuable information on analytes and the separation systems involved. We illustrate here what can be achieved from the statistically valid and physically meaningful quantitative structure-retention relationships, QSRR. In particular, one can predict retention data, confirm identification, and optimize conditions of separation of given structurally defined analytes. Also, QSPR can shed light on the molecular mechanism of separation operating on specific stationary phases. Additionally, one can assess such properties of drug analytes of pharmacokinetic importance, such as lipophilicity and acidity. Also, differences in interactions of xenobiotics with biomacromolecule components of chromatographic systems can conveniently be quantified. By means of QSRR, the chromatographic behavior of analytes in diverse separation systems can be related to their pharmacological properties. However, in context of recent warnings over misuse of P values in statistical data analyses, numerous reported and actually proposed QSP(R)R require critical reevaluation.

Fluoroquinolones are the drugs of choice in the prevention of bacterial infections after transrectal ultrasound guided prostate biopsy. In order to improve assessment of antibacterial efficacy in the target tissue a simple, selective, rapid and robust HPLC-ESI-MS/MS method for the determination of levofloxacin and ciprofloxacin concentrations in human prostate bioptates was developed and validated. Preparation procedure for prostate samples (10mg) was carried out using homogenization and filtration steps. Analyses were performed within 3.5min using RP C18 column in the isocratic elution mode with mobile phase composed of a mixture of 0.1% formic acid aqueous solution and 0.1% formic acid methanol solution (v/v; 79:21). The method was linear between 0.3μg/g and 15μg/g for levofloxacin and ciprofloxacin with coefficient of correlation (r) ≥0.999. The limit of detection and the limit of quantification for levofloxacin were 0.06μg/g and 0.2μg/g and for ciprofloxacin were 0.04μg/g and 0.13μg/g, respectively. Average concentrations (±SD) of levofloxacin and ciprofloxacin obtained from patients tissue were 5.4±2.2μg/g and 3.9±1.5μg/g, respectively. Additionally, during validation procedure a novel, experimental design approach was applied for the robustness study. For evaluation of analytical method robustness, Plackett-Burman design was employed and for sample preparation method robustness Fractional Factorial design was used. The developed and validated method was successfully applied to examine prostate tissue samples obtained from patients enrolled into a clinical study. Up to now, there has been no other HPLC-ESI-MS/MS method reported for the simultaneous determination of levofloxacin and ciprofloxacin in human prostatic tissue.

Fluoroquinolones are considered as gold standard for the prevention of bacterial infections after transrectal ultrasound guided prostate biopsy. However, recent studies reported that fluoroquinolone- resistant bacterial strains are responsible for gradually increasing number of infections after transrectal prostate biopsy. In daily clinical practice, antibacterial efficacy is evaluated only in vitro, by measuring the reaction of bacteria with an antimicrobial agent in culture media (i.e. calculation of minimal inhibitory concentration). Such approach, however, has no relation to the treated tissue characteristics and might be highly misleading. Thus, the objective of this study was to develop, with the use of Design of Experiments approach, a reliable, specific and sensitive ultra-high performance liquid chromatography- diode array detection method for the quantitative analysis of levofloxacin in plasma and prostate tissue samples obtained from patients undergoing prostate biopsy. Moreover, correlation study between concentrations observed in plasma samples vs prostatic tissue samples was performed, resulting in better understanding, evaluation and optimization of the fluoroquinolone-based antimicrobial prophylaxis during transrectal ultrasound guided prostate biopsy. Box-Behnken design was employed to optimize chromatographic conditions of the isocratic elution program in order to obtain desirable retention time, peak symmetry and resolution of levofloxacine and ciprofloxacine (internal standard) peaks. Fractional Factorial design 2(4-1) with four center points was used for screening of significant factors affecting levofloxacin extraction from the prostatic tissue. Due to the limited number of tissue samples the prostatic sample preparation procedure was further optimized using Central Composite design. Design of Experiments approach was also utilized for evaluation of parameter robustness. The method was found linear over the range of 0.030-10μg/mL for human plasma and 0.300-30μg/g for human prostate tissue samples. The intra-day and inter-day variability for levofloxacine from both plasma and prostate samples were less than 10%, with accuracies between 93 and 108% of the nominal values. The limit of detection and the limit of quantification for human plasma were 0.01μg/mL and 0.03μg/mL, respectively. For the prostate tissue, the limit of detection and the limit of quantification were 0.1μg/g and 0.3μg/g, respectively. The average recoveries of levofloxacin were in the range from 99 to 106%. Also, the method fulfills requirements of robustness what was determined and proved by Design of Experiments. The developed method was successfully applied to examine prostate tissue and plasma samples from 140 hospitalized patients enrolled into the clinical study, 12h after oral administration of LVF at a dose of 500mg. The mean (±SD) LVF concentration in prostate was 6.22±3.52μg/g and in plasma 2.54±1.14μg/mL. Due to simplicity of the method and relative small amount of sample needed for the assay, the method can be applied in clinical practice for monitoring of LVF concentrations in plasma and prostate gland.

Convenient drug candidates testing methods for lipophilicity and acidity are highly requested in modern pharmaceutical research and development strategy. Reversed-phase high-performance liquid chromatography (RP HPLC) might be particularly useful for the determination of both pKa and the apparent (pH-dependent) octanol–water partition coefficient, applicable in high-throughput analysis of multi-component mixtures. In this report the pH/organic modifier gradient RP HPLC is presented as a means of simultaneous determination of acidity and lipophilicity of a series of 26 imidazoline-like drugs. The previously theoretically elaborated approach has been applied consisting in retention measurements in a series of methanol gradient runs differing in pH range and duration of the gradient. The simultaneously determined lipophilicity and dissociation constants have been demonstrated to correlate to the respective parameters form calculation chemistry. The proposed approach can be applied to compound mixtures, it requires only minute amounts of substances, and pKa values can be determined in the range 3–10 units and lipophilicity log P parameter in the range 0–7 units.

This review highlights the basis of gradient reversed-phase high-performance liquid chromatography (RP-HPLC) of ionogenic analytes. We describe pH-gradient RP-HPLC in strict theoretical terms, with examples of experiments to provide improvements in analyte separations and peak shapes, and an original method of pK a determination. Finally, we present the concept of the combined pH/organic-modifier gradient mode of RP-HPLC and illustrate it with applications. It allows optimization of separation of ionogenic analytes, along with a method for determining their biorelevant physico-chemical parameters [e.g., hydrophobicity ( log k w ) and acidity ( pK a )]. The method is applicable to drugs and other xenobiotic mixtures, including individual analytes of interest assayed in biological fluids.

The properties relevant to pharmacokinetics of two series of newly synthesized succinimide derivatives have been studied. The properties under consideration have been either determined empirically, by reversed-phase liquid chromatography (TLC and HPLC technique), or calculated with the use of established theoretical medicinal chemistry/drug design software. Chromatographic techniques allowed determination of the retention constants R(M)⁰ and log k(w), which characterize lipophilicity of compounds. Considering potential pharmaceutical importance of succinimide derivatives, we (i) examined the retention behavior in the reversed-phase liquid chromatographic (RP LC) systems, in both planar and column LC, and (ii) determined the relationships between chromatographic data and selected structural features of analytes that are believed to markedly affect their processes of absorption, distribution, metabolism, excretion and toxicity (ADMETox). Significant relationships were found between the retention constants, R(M)⁰ and log k(w), and the in silico calculated bioactivity descriptors, in particular HIA (human intestinal absorption) and PPB (plasma protein binding) parameters. The R(M)⁰ and log k(w) values of the investigated compounds have been recommended for description of their lipophilicity and evaluating pharmacokinetic properties. In view of results of this study the newly synthesized succinimide agents meet pharmacokinetic criteria of preselection of drug candidates and hence qualify for pharmacodynamic phase of antiepileptic drug development. Best compromising human intestinal absorption and plasma protein binding features appear to be compounds A4, A5, A10 and A11.

Binding to melanin is considered to be a reason for several adverse effects of drugs and should be known to reduce the failure rate due to inappropriate pharmacokinetics in search for better pharmaceuticals. A new, reliable and convenient method of determination of affinity of drugs and drug candidates to melanin has been proposed employing magnetic beads. For that aim the reaction conditions to effectively covalently immobilize melanin on surface of superparamagnetic beads have been determined. Binding efficiency of melanin towards antipsychotic and other basic drugs has been determined and compared to that obtained in the affinity HPLC systems employing aminopropylsilica stationary phases with immobilized melanin. The magnetic beads method provided melanin binding data correlating well with the ability of agents to evoke extrapyramidal symptoms. Quantitative structure-property relationships have been derived describing the melanin binding efficiency in terms of structural descriptors of drugs from calculation chemistry. Thus, an approach has been proposed to evaluate a priori melanin binding potency of drug candidates based solely on their chemical formula.

At the current state of knowledge, the rational optimization of the chromatographic separation of peptides, as well as the identification of proteins in proteomics are challenges for analytical chemists. In this paper the generalized applicability of a recently derived descriptor log Sum(k+1)AA in a QSRR equation to model peptide retention in RP-LC systems was evaluated. For that purpose, two sets of peptides analyzed on dissimilar RP-LC systems were considered. A first set of 28 peptides was measured on 17 columns/systems, while a second of 70 peptides was eluted on four. The aim of this work was to confirm the usefulness of the partly experimental log Sum(k+1)AA descriptor for the prediction of peptides retention compared to the initially applied, fully experimental log SumAA descriptor. The verification of the predictive abilities of both QSRR models, applying either the initial or the alternative descriptor, was done by using the leave-one-out and leave-three-out cross-validation procedures. The results seem to demonstrate that the QSRR model with log Sum(k+1)AA, for which the retention measurement of only seven out of 20 existing amino acids is necessary, possesses similar or in some cases even better predictive abilities than that containing log SumAA.

The purpose of this work was to propose a theoretical model of the combined pH/organic modifier gradient in reversed-phase high-performance liquid chromatography (RP HPLC) with special emphasis on its applicability to polyprotic analytes. The model was developed and approximated to be useful for a data set comprising organic modifier gradients obtained at different pH changes and different gradient durations. It was evaluated regarding its ability to describe experimental data. The chromatographic pKa and lipophilicity parameter, log k w , were obtained by fitting to the proposed model and comparing to the literature values.

Previous studies demonstrated that quantitative structure-retention relationships (QSRR) combined with the linear solvent strength (LSS) model allow for prediction of gradient reversed-phase liquid chromatography retention time for any analyte of a known molecular structure under defined LC conditions. A QSRR model derived at the selected gradient time and at the same gradient time was tested. The aim the present study was to evaluate the accuracy of QSRR predictions used during the predictions of LC gradient retention times with variable gradient times. For this purpose, predictions of retention times at two gradient times were used to find the optimal, different gradient times. In the first step, experimental retention data for the model set of analytes were used to derive appropriate QSRR models at two gradient times. These QSRR models were further used to predict gradient retention times for another set of testing analytes at the two selected above gradient times. Then, applying linear solvent-strength (LSS) theory, the predicted retention times for test analytes were used to find other optimal gradient times for those analytes. Satisfactory predictions of gradient retention times for test analytes were obtained at gradient times different from those applied for model analytes.

Recent reports from our laboratory presented a comprehensive theory and demonstrated feasibility of reversed-phase liquid chromatography (RP-LC) employing the programmed gradient of pH of the mobile phase. The aim of that work was to explore the usefulness of the pH gradient-based approach in fractionation of peptides. The experiments were performed on a series of peptides separated at various LC conditions. Retention parameters of peptides in the pH gradient and in the simultaneous pH/organic modifier gradient RP-LC were compared. The best results were obtained with eluents comprising low but constant concentrations of organic modifier while gradient of pH in the mobile phase was developed several times during each chromatographic run. The elaborated LC conditions allowed controlling the elution of peptides not only according to their hydrophobic properties, but also taking into account their electronic properties, represented by isoelectric point (pI) values. The combination of isocratic (regarding organic modifier) LC mode with recurring eluent pH gradient is proposed as an effective fractionation method of peptide mixtures. Moreover, information on hydrophobicity and pI of the peptides, obtained by that approach, might be an additional peptides database matching constraint. Hence, a new tool for analytical and bioinformatics studies of peptides fractionation is proposed.

Interest in ionic liquids (ILs) for their potential application in analytical chemistry continues to grow. Their usefulness can be due to favourable physicochemical properties, like the lack of vapour pressure, good thermal and chemical stability as well as very good dissolution properties regarding both organic and inorganic compounds. A specific feature of ILs is that these compounds provide strong proton donor-acceptor intermolecular interactions. As a result, ILs are able to affect on the hydroxy groups of the silica supports the most popular stationary phases in liquid chromatography (LC). It is well known that the hydroxy groups, called free or isolated silanols cause serious problems in LC, especially when separating basic compounds. This review focuses on the application of ILs in LC and capillary electrophoresis (CE) and comparisons of their efficiency with standard silanol suppressing additives to mobile phases.

The pH of a mobile phase is one of the most important parameters affecting retention of ionic analytes in reversed phase high-performance liquid chromatography (RP-HPLC). RP-HPLC and hydrophilic interaction liquid chromatography (HILIC) can be used as a convenient tool for the analysis of ionizable analytes. The ionic analyte contains one or more acidic or basic functional groups in its molecular structure. Acidic compounds lose a proton as pH increases, whereas bases gain a proton as pH decreases The ionic analyte contains one or more acidic or basic functional groups in its molecular structure. for chromatographic retention, the presence of dissociated group(s) decreases analytes' hydrophobicity that leads to the lower retention of the dissociated form than that of the nondissociated form of an analyte. The chapter discusses effect of pH on Isocratic retention, pH effect on organic modifier gradients, pH gradient, and effect of pH in normal-phase mode. Keywords: chromatographic retention modes; hydrophilic interaction liquid chromatography; isocratic retention; isocratic retention; organic modifier gradients; pH effect; pH-gradient; reversed phase HPLC

The aim of this work was to develop a nonlinear mixed-effect chromatographic model able to describe the retention times of weak acids and bases in all possible combinations of organic modifier content and mobile-phase pH. Further, we aimed to identify the influence of basic covariates, like lipophilicity (log P), dissociation constant (pK(a)), and polar surface area (PSA), on the intercompound variability of chromatographic parameters. Lastly, we aimed to propose the optimal limited experimental design to the estimation process of parameters through a maximum a posteriori (MAP) Bayesian method to facilitate the method development process. The data set comprised retention times for two series of organic modifier content collected at different pH for a large series of acids and bases. The obtained typical parameters and their distribution were subsequently used as priors to improve the estimation process from reduced design with a variable number of preliminary experiments. The MAP Bayesian estimator was validated using two external-validation data sets. The common literature model was used to relate analyte retention time with mobile-phase pH and organic modifier content. A set of QSRR-based covariate relationships was established. It turned out that four preliminary experiments and prior information that includes analyte pK(a), log P, acid/base type, and PSA are sufficient to accurately predict analyte retention in virtually all combined changes of pH and organic modifier content. The MAP Bayesian estimator of all important chromatographic parameters controlling retention in pH/organic modifier gradient was developed. It can be used to improve parameter estimation using limited experimental design.

The objective of this study was to model the retention of nucleosides and pterins in hydrophilic interaction liquid chromatography (HILIC) via QSRR-based approach. Two home-made (Amino-P-C18, Amino-P-C10) and one commercial (IAM.PC.DD2) HILIC stationary phases were considered. Logarithm of retention factor at 5% of acetonitrile (log kACN) along with descriptors obtained for 16 nucleosides and 11 pterins were used to develop QSRR models. We used and compared the predictive performance of three regression techniques: partial least square (PLS), the least absolute shrinkage and selection operator (LASSO), and the LASSO followed by stepwise multiple linear regression. The highest predictive squared correlation coefficient ( Q L O O C V 2 ) in PLS analysis was found for Amino-P-C10 ( Q L O O C V 2 = 0.687 ) and IAM.PC.DD2 ( Q L O O C V 2 = 0.506 ) and the lowest for IAM.PC.DD2 ( Q L O O C V 2 = − 0.01 ). Much higher values were obtained for the LASSO model. The Q L O O C V 2 equaled 0.9 for Amino-P-C10, 0.66 for IAM.PC.DD2 and 0.59 for Amino-P-C18. The combination of LASSO with stepwise regression provided models with comparable predictive performance as the LASSO, however with possibility of calculating the standard error of estimates. The use of LASSO itself and in combination with classical stepwise regression may offer greater stability of the developed models thanks to more smooth change of coefficients and reduced susceptibility towards chance correlation. Application of QSRR-based approach, along with the computational methods proposed in this work, may offer a useful approach in the modeling of retention of nucleoside and pterin compounds in HILIC.

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 Horvath (J. Chromatogr. 1981, 203, 53-63). The binding constant, K A , 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.

The growing interest in application of ionic liquids (ILs) in analytical chemistry has been observed. The aim of presented investigation was to verify whether ILs would be a suitable modifier of the background electrolyte (BGE) for pharmaceutical analysis of the closely related drug analogues. The study demonstrates the use of 1-ethyl-3-methylimidazolium tetrafluoroborate (1E-3MI-TFB) ionic liquid as modifiers in the separation of nicotinic acid and its structural isomers by capillary electrophoresis. Dependences of the ionic liquid concentration in a BGE on the separation parameters like migration time, resolution factor and width at peak's baseline have been compared. The separation mechanism involves the free imidazolium ions, which can interact with inner surface of the capillary wall. Increased 1E-3MI-TFB concentration to 150 mmol/L caused decrease of migration times of analytes, improve peaks shape and increase of separation performances. At this ionic liquid concentration in a BGE resolution factor between nicotinic and isonicotinic acids increased to 1.86. The proposed CE separation procedure is highly reproducible and can be applied in qualitative and quantitative analysis of carboxylic acids.

A suppression of silanophilic interactions by the selected ionic liquids added to the mobile phase in thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC) is reported. Acetonitrile was used as the eluent, alone or with various concentrations of water and phosphoric buffer pH 3. Selectivity of the normal (NP) and the reversed (RP) stationary phase material was examined using a series of proton-acceptor basic drugs analytes. The ionic liquids studied appeared to significantly affect analyte retention in NP-TLC, RP-TLC and RP-HPLC systems tested. Consequently, the increased separation selectivity was attained. Due to ionic liquid additives to eluent even analytes could be chromatographed, which were not eluted from the silica-based stationary phase materials with 100% of acetonitrile in the mobile phase. Addition of ionic liquid already in very small concentration (0.5%, v/v) could reduce the amount of acetonitrile used during the optimization of basic analytes separations in TLC and HPLC systems. Moreover, the influence of temperature on the separation of basic analytes was demonstrated and considered in practical HPLC method development.

A combined pH/organic solvent linear gradient mode in high performance liquid chromatography (HPLC) is presented as a new approach to determination of low concentrations of ionogenic analytes in biological material. The approach consists in simultaneous development of linear gradients of pH and organic modifier in the mobile phase. Advantages of the method are illustrated in postmortem analysis of opipramol in material from suicide victims. Very narrow peaks without tailing were obtained and several times lower limits of analyte quantitation were achieved using ultraviolet detection as compared to a standard isocratic method. The double gradient HPLC method seems to be especially valuable in case of ionogenic analytes dispersed in complex biological matrices. That is due to a high selectivity of the double gradient method and the lack of peak tailing, which is commonly observed for basic analytes chromatographed at isocratic conditions.

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.

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.

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 tetrafluoroborate to the eluent in comparison to the system without the ionic liquid. Nonlinear dependence of the retention coefficient, RM, of peptides on the volume percentage of acetonitrile in the eluent was found in normal-phase TLC with and without immidazolium tetrafluoroborate in the mobile phase. In general, RM increased with increasing concentration of acetonitrile. In TLC systems without the ionic liquid, RM 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. Copyright © 2004 John Wiley & Sons, Ltd.

A new reversed-phase high-performance liquid chromatographic (RP HPLC) procedure has been theoretically and experimentally established. The approach consists of the simultaneous development of a gradient of pH and of the organic modifier in the mobile phase. The proposed theoretical model of the pH/organic solvent double-gradient RP HPLC allows determination of both pK(a) and the lipophilicity parameter of the ionized and the nonionized form of the analyte and prediction of the retention times at specific separation conditions as well as bandwidth for all analytes. The model provides a rational basis for optimization of separation of ionizable analytes at any given chromatographic mode and analysis conditions. In addition, in the case of pH/organic solvent double-gradient RP HPLC, a compression of analyte peak and its reduced tailing can be expected.

pH gradient reversed-phase HPLC consists of a programmed increase during the chromatographic run of the eluting power of the mobile phase with regard to ionizable analytes. On the analogy of the conventional organic modifier gradient RP HPLC, in the pH gradient mode, the eluting strength of the mobile phase increases due to its increasing (with acid analytes) or decreasing (with basic analytes) pH, whereas the content of organic modifier is kept constant. We have shown previously that the pH gradient separations are technically possible using standard chromatographic equipment. Here we demonstrate that the method is uniquely suitable to determine pK(a) values of analytes. A strict theoretical model is proposed to determine pK(a) values based on the retention data from a pH gradient RP HPLC run. The pK(a) data so obtained are discussed in relation to the concentration of methanol in the mobile phase, the type of stationary phase, and the duration of the gradient. The pK(a) values determined by the pH gradient method are related to the respective data obtained conventionally in a series of isocratic experiments. A close similarity of the two types of chromatographically determined pK(a) data is demonstrated. The HPLC-derived pK(a) parameters correlate to the literature pK(a) values determined by titrations in water. The chromatographically derived and the reference pK(a) values are not identical, however. That is probably due to the effects on the chromatographic pK(a) of the specific sites of interactions with analytes on the surfaces of the HPLC stationary phases. Nonetheless, the proposed pH gradient HPLC method may supply in a fast and convenient manner comparable acidity parameters for larger series of drug candidates, including those available in only minute amounts, without need of their purification, and also when the compounds are provided as complex mixtures, like those produced by combinatorial chemistry.

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.

pH gradient HPLC is reported, which is a new original mode of reversed-phase high-performance liquid chromatography applicable to ionogenic analytes. The method consists of programmed increase during the chromatographic run of the eluting strength of the mobile phase with respect to the acid/base analytes separated. Unlike the well-established conventional gradient HPLC, where the eluting power of the mobile phase is increased with time due to the increasing content of organic modifier, in the pH gradient HPLC that is realized by linearly increasing (in the case of acids) or decreasing (in the case of bases) the pH of the eluent of a fixed organic modifier content, thus providing functional increase in the degree of analyte dissociation and, hence, a decrease in its retention. The pH gradient mode has typical features of gradient HPLC, such as reduced peak width and minimized peak-tailing due to peak compression, which is especially advantageous in the case of organic base analytes. It may be of special value for separation of those analytes which are susceptible to the higher concentrations of organic solvents, as many bioanalytes are. A theory of the pH gradient HPLC has been elaborated, and its full mathematical formalistic is presented step by step in a comprehensive manner. Although fundamental relationships at the basis of pH gradient HPLC are more complex than in the case of the organic gradient variant, the resulting mathematical model is easily manageable. Its applicability to predict changes in retention and separation of test mixtures of analytes accompanying the changes in chromatographic conditions has been demonstrated experimentally in both gradient and isocratic HPLC. The proposed model supplies a rational basis for modifications of eluent pH aimed at optimization of separations and for convenient assessment of chromatographically relevant physicochemical parameters of analytes, such as pK(a).

Liquid chromatography and capillary electrophoresis are unique tools for fast and efficient modeling of pharmacokinetic properties of drug candidates. Therefore numerous new separation methods and procedures have very recently been introduced to facilitate the high-throughput screening of biopartitioning features of xenobiotics. This report is a concise, up-to-date review of progress in the chromatographic assessments of data of importance for medicinal chemistry and molecular pharmacology.

The importance of lipophilicity for pharmacological and toxicological potency of xenobiotics has been recognized for a century. The reference lipophilicity scale is defined by the logarithm of partition coefficient, log P, determined in the l-octanol-water partition system. The tediousness of determinations and limited interlaboratory reproducibility of log P, on one hand, and the observations of linear relationship between log P and chromatographic retention parameters, on the other hand, gave rise to the substitution of the former by the readily available chromatographic data. Since its introduction, the reversed-phase high - performance liquid chromatography (HPLC), which has been viewed in terms of partition of a solute between a polar, aqueous mobile phase and a nonpolar stationary phase appeared especially suitable for lipophilicity (hydrophobicity) determination. The method got wide acceptance and has officially been recommended by the OECD. Fundamental relationships between chromatographic parameters are reviewed from the point of view of convenient and reliable lipophilicity measurements. The advantages and disadvantages of the stationary phase materials, which are presently employed for the determination of lipophilicity as well as those of specific HPLC systems and procedures, are critically reported. The literature on the application of chromatographic and electrochromatographic methods for assessment of lipophilicity of xenobiotics is reviewed. A separate paragraph is devoted to interpretation of retention parameters from HPLC systems comprising biomacromolecules. Role of lipophilicity in drug-biomacromolecule interactions is discussed in terms of quantitative structure-retention relationships (QSRR). Finally, reports are analyzed on systemic information which can be extracted by multivariate methods of data processing, like principal component analysis (PCA), from sets of lipophilicity parameters determined in diverse HPLC systems.

The linear solvent strength (LSS) model combined with quantitative structure-retention relationships (QSRR) and artificial neural network (ANN) analysis has been shown to permit approximate prediction of the gradient high-performance liquid chromatography (HPLC) retention time for any analyte on a once-characterized column. The approach applies well to the reversed-phase HPLC mode with a methanol-water (buffer) eluent of linearly changing composition. Its suitability was tested for a representative series of structurally diverse analytes. In this approach the determination of retention times, t R , in two gradient runs for a predesigned model series of 15 analytes is first needed. Next, model QSRR equations describing t R in terms of analyte structure are derived to characterize the HPLC systems of interest. To quantitatively characterize the structure of the analytes the following three structural descriptors from molecular modeling are employed: total dipole moment; electron excess charge of the most negatively charged atom; and water-accessible molecular surface area. Using these data a general QSRR equation is derived which is valid for a given column/eluent system. Next, having the structural descriptors for any analyte to be chromatographed in such a characterized HPLC system, one employs the previously derived general QSRR equation to calculate the analyte's retention time. The expected gradient retention time for any gradient conditions can be calculated by means of appropriate LSS equations. Independent of the standard QSRR calculation procedure based on multiple regression analysis (MRA), predictions of gradient retention times were performed by means of artificial neural networks (ANN). It has been found that the predictive power of ANN is similar to that of MRA. The combined LSS/QSRR approach has been demonstrated to provide approximate, yet otherwise unattainable, a priori predictions of gradient retention of analytes based solely on their chemical formulae. That way a rational chemometric basis for a systematic optimization of chromatographic separations has been elaborated as an alternative to the trial-and-error method normally applied at present.

Quantitative Structure-Retention Relationships (QSRRs) have been employed to study retention mechanism of Reversed-Phase Liquid Chromatography (RPLC). Two C 18 and two C 8 columns were used with mobile phases containing methanol, acetonitrile, and tetrahydrofuran in concentrations ranging from 40 to 90 (v/v)% in water. QSRR equations derived are generally characterized by a satisfactory quality of fit, although missing data or a low average retention can decrease the goodness-of-fit. In agreement with literature the most important retention descriptors appeared to be the analyte's molecular volume and its hydrogen-bond accepting basicity, but also the polarity/polarizability, hydrogen-bond donating acidity, and excess molar refraction showed statistical significance in several cases. Relatively small, but significant differences between the two C 18 stationary phases were observed. The differences between C 8 and C 18 column types were more pronounced. The influence of the mobile phase on regression coefficients is more difficult to interpret, because of adsorption of mobile phase constituents by the stationary phase. However, the importance of this partitioning of water and modifier is illustrated by the practically identical trends in b values for the three modifiers studied, while the trends in v values are significantly different. Principal component analysis of the QSRR regression coefficients demonstrated the prevailing role of the mobile phase for chromatographic properties of the RPLC systems studied as compared to the stationary phase.

Retention parameters reflect free-energy changes of analytes, associated with their chromatographic distribution. The linear free-energy relationships are at the base of the quantitative structure–retention relationships (QSRRs). To obtain statistically significant QSRRs, reliable input parameters are necessary and stringent chemometric analysis must be carried out. Chromatography can provide a large amount of precise and reproducible data on analytes. By means of experimental and computational chemistry methods, the structure of analytes can be described in terms of numerical descriptors. Advanced data processing methods, like multiple linear regression, principal component analysis, partial least squares methods, discriminant analysis, and neural networks method, allow derivation of QSRR. Good QSRR can be applied to predict retention and confirm identification of analytes in proteomics and in doping control, to explain molecular mechanism of separation on given stationary phases, to classify stationary phase materials, and to evaluate ‘druglikeness’ features of analytes, in particular their lipophilicity.

Quantitative structure-retention relationships (QSRR) have been employed in studying the molecular mechanism of chromatographic separations under pressure- (HPLC) and electro-driven (CEC) conditions. Logarithms of retention factors corresponding to zero percent of organic modifier in aqueous eluent, log k(w), were determined on eight reversed-phase stationary phases under both HPLC and CEC conditions at similar eluent flow velocities. QSRR equations describing log k(w) in terms of linear solvation energy relationship (LSER) parameters of analytes, in terms of simple structural descriptors acquired by calculation chemistry, and in terms of logarithms of n-octanol-water partition coefficients, were derived. Parameters of corresponding QSRR equations for individual stationary phases were compared for both HPLC andCEC modes and the resulting similarities and differences in retention mechanisms were discussed. It has been concluded that at least in the case of regular neutral analytes the specific inputs to separation mechanism due to the electric field in CEC are of secondary importance.

It has been assumed that systematic information on the behavior of a series of analytes in a number of chromatographic systems can be exploited to evaluate their biological activity. Computerized methods of multivariate data processing, such as principal component analysis (PCA), allow the extraction of systematic information from large sets of diverse and mutually interrelated retention parameters. High-performance liquid chromatography (HPLC) is a unique method that can readily produce a great amount of retention data on large sets of drug analytes. A group of 65 new buspirone analogues were chromatographed in 9 carefully designed HPLC systems. A matrix of 65 x 9 HPLC data was subjected to statistical analysis by PCA. A grouping of analytes was obtained which was exclusively due to a systematic similarity of their behavior in the HPLC systems studied. That grouping was related to the affinity of the agents to 5-HT 1A serotonin receptors. It has been demonstrated that chemometrically processed HPLC parameters may help to segregate drugs and drug candidates according to differences in their pharmacological properties. That, in turn, may help to guide the biotesting strategy and limit the number of biological assays in the search for new drugs.

Prostate cancer (CaP) is a leading cause of cancer deaths in men worldwide. The alarming statistics, the currently applied biomarkers are still not enough specific and selective. In addition, pathogenesis of CaP development is not totally understood. Therefore, in the present work, metabolomics study related to urinary metabolic fingerprinting analyses has been performed in order to scrutinize potential biomarkers that could help in explaining the pathomechanism of the disease and be potentially useful in its diagnosis and prognosis. Urine samples from CaP patients and healthy volunteers were analyzed with the use of high performance liquid chromatography coupled with time of flight mass spectrometry detection (HPLC-TOF/MS) in positive and negative polarity as well as gas chromatography hyphenated with triple quadruple mass spectrometry detection (GC-QqQ/MS) in a scan mode. The obtained data sets were statistically analyzed using univariate and multivariate statistical analyses. The Principal Component Analysis (PCA) was used to check systems' stability and possible outliers, whereas Partial Least Squares Discriminant Analysis (PLS-DA) was performed for evaluation of quality of the model as well as its predictive ability using statistically significant metabolites. The subsequent identification of selected metabolites using NIST library and commonly available databases allows for creation of a list of putative biomarkers and related biochemical pathways they are involved in. The selected pathways, like urea and tricarboxylic acid cycle, amino acid and purine metabolism, can play crucial role in pathogenesis of prostate cancer disease.

The extrapyramidal side effect parameters of typical and atypical antypsychotics were correlated with affinity chromatographic data determined on the melanin-based column. The chromatographic study was performed according to the hypothesis that extrapyramidal symptoms (EPS) as side effects of the use of antipsychotic drugs at clinically effective doses are correlated to the affinity of these drugs to neuromelanin. For that aim the polymerization product of L-DOPA (melanin) was immobilized onto aminopropyl silica and the binding efficiency of melanin towards antipsychotics has been determined. The results indicate that melanin based-column can be used to evaluate the risk of EPS of drug candi- dates to antipsychotic drug therapy.

The automated mass spectral deconvolution and identification system (AMDIS) is a modern analytical tool, mostly used as a data processing method in environmental studies. The most attractive feature of that software is a fast, automatic data processing, which includes removal of interferences from the overlapping peaks and purification of the obtained mass spectra. The identification of analytes is based on their retention time and retention index and on comparison of the spectra obtained in GC/MS analysis with the spectra from the library of the National Institute of Standards and Technology (NIST). The main aim of the study reported was to elaborate and test a new data processing method with the use of AMDIS software for identification of lipidomic compounds present in the grasshopper's abdominal secretion. For the first time to the best of our knowledge, we have demonstrated the usage of AMDIS in a lipidomic study concerning a complex insect matrix. The samples processed with AMDIS software were analyzed with the use of GC/MS in order to determine the main fatty components of grasshoppers' abdominal secretion. The purification, concentration and fractionation of compounds present in a complex insect matrix were investigated with the use of liquid-liquid extraction as a pretreatment procedure. Moreover, a double-step derivatization process was carried out in order to obtain more volatile and stable derivatives of polar, non-volatile components of insects' secretion. This process, necessary for GC/MS analysis, was performed with the use of methoxyamine hydrochloride dissolved in pyridine and a mixture of bis-N-O-trimethylsilyl trifluoroacetamide (BSTFA) and chlorotrimethylsilane (TMCS). As a result, we obtained a fast, automatic method based on the use of AMDIS software, which enabled identification of 28 analytes, mainly fatty compounds. Moreover, 10 compounds out of 28 were determined to appear with 100% frequency in the tested samples, namely: seven fatty acids, one sterol, one organic acid and one alkaloid. The last part of our study was statistical analysis of average intensities of signals of compounds identified in grasshopper's abdominal secretion in order to differentiate insects collected at two distant locations in Poland: Starogard Gdanski and Łubianka meadows.