Modeling of retention of adrenoreceptor agonists and antagonists on polar stationary phases in hydrophilic interaction chromatography: a review

In depth investigation of the retention behavior of structurally related β-blockers on RP-HPLC column: Quality by design and quantitative structure-property relationship complementary approaches for optimization and validation

The persistent introduction of new β-blockers motivates the demand for optimizing RP-HPLC well-designed analytical procedures that could be applied to this structurally related and commonly prescribed pharmacological group in order to reduce time and chemicals consumption in quality control units. Betoxolol HCl (BEX) and Carvidolol (CAR) were selected as representative examples to conduct predictive studies based on two complementary approaches, Quality by design (QBD) and Quantitative structure property relationship (QSPR). In concern QBD, a Box-Behnken design was adopted at variable chromatographic parameters to achieve the most proper conditions that might be applied for efficient analysis of the majority of group members. On the other hand, the retention time was chosen as the target property in the QSPR study that was conducted onto seven β. blockers (the two investigated drugs in addition to five other β. blockers) to find the best correlated molecular descriptors to the retention behavior. Both external and internal validation studies have comparable quality with training levels. Hence a simple selection algorithm of conventional features provides robust confirmatory predictive QBD and QSPR models. Derringer's desirability function as as a multi-criteria approach was applied for getting the optimum chromatographic analysis conditions. Efficient analysis of BET and CAR was achieved at column temperatures of 26.00 and 27.50 °C, respectively using acetonitrile and phosphate buffer (pH 4.55) 70:30 v/v as a mobile phase with a flow rate of 1.00 mL/min, and UV detection at 220 nm. The method was validated in accordance to ICH guidelines, and had exhibited acceptable precision, accuracy, linearity, and robustness.

Novel computational approaches to retention modeling in dual hydrophilic interactions/reversed phase chromatography

The mixed-mode chromatographic behavior was estimated for imidazoline and serotonin receptor ligands, and their related compounds on dual hydrophilic/reversed phase stationary phase. The Box-Cox transformation was used to obtain the most suitable mathematical equations which describe the mixed-mode retention. Optimal equations were found for the optimization parameter (λ): λ = -1, λ = -0.5, λ = 0, λ = 0.5, and λ = 1. The proposed equations show satisfactory characteristics compared to standard multimodal and quadratic approaches. For a wide range of volume fractions of the mobile phase modifier, crossing between hydrophilic and reversed phase interactions (the turning point) was defined in terms of the minimal retention and the minimum value of the volume fraction of the aqueous eluent in the mobile phase. The cubic spline interpolation was used as a reference method for estimation of the turning point. It was found out that the newly proposed equations can be used as alternative mathematical forms for the description of the dual retention mechanism and for the evaluation of the turning point. Three new experimental descriptors of the mixed-mode retention were proposed. Two descriptors quantitatively characterize hydrophilic (log k_H) and reversed phase (log k_R) interactions, while the third one (log k_A) refers to the average retention for the whole HILIC/RP range. It was established that the main factors which control dual nature of the mixed-mode retention are lipophilicity, dipol-dipol, van der Waals and hydrogen bonding interactions. It was concluded that the newly proposed estimations of the retention data reliably characterize the mixed-mode chromatographic behavior.

Chemometric-assisted method development in hydrophilic interaction liquid chromatography: A review

With an enormous growth in the application of hydrophilic interaction liquid chromatography (HILIC), there has also been significant progress in HILIC method development. HILIC is a chromatographic method that utilises hydro-organic mobile phases with a high organic content, and a hydrophilic stationary phase. It has been applied predominantly in the determination of small polar compounds. Theoretical studies in computer-aided modelling tools, most importantly the predictive, quantitative structure retention relationship (QSRR) modelling methods, have attracted the attention of researchers and these approaches greatly assist the method development process. This review focuses on the application of computer-aided modelling tools in understanding the retention mechanism, the classification of HILIC stationary phases, prediction of retention times in HILIC systems, optimisation of chromatographic conditions, and description of the interaction effects of the chromatographic factors in HILIC separations. Additionally, what has been achieved in the potential application of QSRR methodology in combination with experimental design philosophy in the optimisation of chromatographic separation conditions in the HILIC method development process is communicated. Developing robust predictive QSRR models will undoubtedly facilitate more application of this chromatographic mode in a broader variety of research areas, significantly minimising cost and time of the experimental work.

Recent progress in the fundamental understanding of hydrophilic interaction chromatography (HILIC)

With the exponential growth in the application of the HILIC technique, there has been a significant progress in understanding the fundamental aspects of hydrophilic interaction chromatography.

Stationary phases for the enrichment of glycoproteins and glycopeptides

The analysis of protein glycosylation is important for biomedical and biopharmaceutical research. Recent advances in LC-MS analysis have enabled the identification of glycosylation sites, the characterisation of glycan structures and the identification and quantification of glycoproteins and glycopeptides. However, this type of analysis remains challenging due to the low abundance of glycopeptides in complex protein digests, the microheterogeneity at glycosylation sites, ion suppression effects and the competition for ionisation by co-eluting peptides. Specific sample preparation is necessary for comprehensive and site-specific glycosylation analyses using MS. Therefore, researchers continue to pursue new columns to broaden their applications. The current manuscript covers recent literature published from 2008 to 2013. The stationary phases containing various chemical bonding methods or ligands immobilisation strategies on solid supports that selectively enrich N-linked or sialylated N-glycopeptides are categorised with either physical or chemical modes of binding. These categories include lectin affinity, hydrophilic interactions, boronate affinity, titanium dioxide affinity, hydrazide chemistry and other separation techniques. This review should aid in better understanding the syntheses and physicochemical properties of each type of stationary phases for enriching glycoproteins and glycopeptides.

Quantitative structure-retention relationships models for prediction of high performance liquid chromatography retention time of small molecules: endogenous metabolites and banned compounds

Quantitative structure-retention relationship (QSRR) is a technique capable of improving the identification of analytes by predicting their retention time on a liquid chromatography column (LC) and/or their properties. This approach is particularly useful when LC is coupled with a high-resolution mass spectrometry (HRMS) platform. The main aim of the present study was to develop and describe appropriate QSRR models that provide usable predictive capability, allowing false positive identification to be removed during the interpretation of metabolomics data, while additionally increasing confidence of experimental results in doping control area. For this purpose, a dataset consisting of 146 drugs, metabolites and banned compounds from World Anti-Doping Agency (WADA) lists, was used. A QSRR study was carried out separately on high quality retention data determined by reversed-phase (RP-LC-HRMS) and hydrophilic interaction chromatography (HILIC-LC-HRMS) systems, employing a single protocol for each system. Multiple linear regression (MLR) was applied to construct the linear QSRR models based on a variety of theoretical molecular descriptors. The regression equations included a set of three descriptors for each model: ALogP, BELe6, R2p and ALogP(2), FDI, BLTA96, were used in the analysis of reversed-phase and HILIC column models, respectively. Statistically significant QSRR models (squared correlation coefficient for model fitting, R(2)=0.95 for RP and R(2)=0.84 for HILIC) indicate a strong correlation between retention time and the molecular descriptors. An evaluation of the best correlation models, performed by validation of each model using three tests (leave-one-out, leave-many-out, external tests), demonstrated the reliability of the models. This paper provides a practical and effective method for analytical chemists working with LC/HRMS platforms to improve predictive confidence of studies that seek to identify small molecules.

Hydrophilic interaction ultra performance liquid chromatography retention prediction under gradient elution

The development and application of new separation mechanisms such as hydrophilic interaction chromatography (HILIC) is of high importance for the simultaneous analysis of polar molecules such as primary metabolites. However the retention mechanism in HILIC is not fully understood and as a result retention prediction tools are not at hand for this chromatographic approach. In the present report we study the utility of a simple algorithm, based on a simple linear and/or a simple logarithmic retention model, for retention prediction in HILIC gradient separation of a mixture of 23 selected compounds including (poly)amines, amino acids, saccharides, and other molecules. Utilizing two types of gradient elution programs with or without an isocratic part, retention data were collected in order to build prediction models. Starting from at least three gradient runs the prediction of analyte retention was very satisfactory for all gradient programs tested, providing useful evidence of the value of such retention time prediction methodologies.

Evaluation of the Electrostatic Contribution to the Retention of Modified Nucleosides and Nucleobases by Zwitterionic Hydrophilic Interaction Chromatography

This work explores the benefits and limitations, on a quantitative basis, of using zwitterionic hydrophilic interaction chromatography (ZIC-HILIC) for the separation of several modified nucleosides and nucleobases of clinical interest. The target compounds were hydroxylated and methylated derivatives: 8-hydroxy-guanine, 8-hydroxy-guanosine, 8-hydroxy-2′-deoxyguanosine, 1-methyl-guanine, 7-methyl-guanine, and 9-methyl-guanine. A quantitative evaluation of the electrostatic interaction based on a systematic study of the nature and concentration of the salts in the mobile phase has been carried out. From the obtained results, it may be concluded that separation is based on a mechanism of partition and interaction through weak electrostatic forces: the contribution of the electrostatic interaction to the retention of the charged analytes reaching values between 25 and 52% at low salt concentration. However, the electrostatic contribution decreased progressively as the salt concentration rose.

Hydrophilic interaction liquid chromatography (HILIC)--a powerful separation technique

Hydrophilic interaction liquid chromatography (HILIC) provides an alternative approach to effectively separate small polar compounds on polar stationary phases. The purpose of this work was to review the options for the characterization of HILIC stationary phases and their applications for separations of polar compounds in complex matrices. The characteristics of the hydrophilic stationary phase may affect and in some cases limit the choices of mobile phase composition, ion strength or buffer pH value available, since mechanisms other than hydrophilic partitioning could potentially occur. Enhancing our understanding of retention behavior in HILIC increases the scope of possible applications of liquid chromatography. One interesting option may also be to use HILIC in orthogonal and/or two-dimensional separations. Bioapplications of HILIC systems are also presented.

Evolving neural network optimization of cholesteryl ester separation by reversed-phase HPLC

Cholesteryl esters have antimicrobial activity and likely contribute to the innate immunity system. Improved separation techniques are needed to characterize these compounds. In this study, optimization of the reversed-phase high-performance liquid chromatography separation of six analyte standards (four cholesteryl esters plus cholesterol and tri-palmitin) was accomplished by modeling with an artificial neural network–genetic algorithm (ANN-GA) approach. A fractional factorial design was employed to examine the significance of four experimental factors: organic component in the mobile phase (ethanol and methanol), column temperature, and flow rate. Three separation parameters were then merged into geometric means using Derringer’s desirability function and used as input sources for model training and testing. The use of genetic operators proved valuable for the determination of an effective neural network structure. Implementation of the optimized method resulted in complete separation of all six analytes, including the resolution of two previously co-eluting peaks. Model validation was performed with experimental responses in good agreement with model-predicted responses. Improved separation was also realized in a complex biological fluid, human milk. Thus, the first known use of ANN-GA modeling for improving the chromatographic separation of cholesteryl esters in biological fluids is presented and will likely prove valuable for future investigators involved in studying complex biological samples.

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