Retention prediction of analytes in reversed-phase high-performance liquid chromatography based on molecular structure

Revisiting the dependence of retention factor on the content of organic component in the mobile phase in reversed-phase HPLC

In high-performance liquid chromatography, the dependence of retention factor k on volumetric fraction ϕ of organic phase is expressed by log k = F(ϕ) with F(ϕ) obtained by measuring log k at different ϕ values. From F(ϕ), a value kw is calculated by taking ϕ = 0. The equation log k = F(ϕ) is applied for predicting k, and kw is a descriptor of hydrophobic character of solutes and stationary phases. Calculated kw should not depend on the nature of organic component of mobile phase but extrapolation procedure leads to different kw for different organic components. The present study shows that the expression of F(ϕ) changes depending on the range of ϕ and the same function F(ϕ) cannot be used for the full range of ϕ from 0 to 1. Consequently, kw obtained by extrapolation of ϕ to zero is not correct because the expression of F(ϕ) was generated by fitting the data using ϕ with higher values. The present study shows the proper way to obtain the value of kw .

Global retention models and their application to the prediction of chromatographic fingerprints

The resolution of samples containing unknown compounds of different nature, or without standards available, as is the case of chromatographic fingerprints, is still a challenge. Possibly, the most problematic aspect that prevents systematic method development is finding models that describe without bias the retention behaviour of the compounds in the samples. In this work, the use of global models (able to describe the whole sample) is proposed as an alternative to the use of individual models for each solute. Global models contain parameters that are specific for each solute, while other parameters ‒related to the column and solvent‒ are common for all solutes. A special regression procedure is presented for the construction of global models, which are applied to predict highly complex chromatograms, such as chromatographic fingerprints, for diverse experimental conditions in isocratic and gradient elution. Another interesting application is the prediction of molecular properties, such as log P_o/w, from the specific solute parameters of the global models. The examined adapted models are based on the equations proposed by Snyder, Schoenmakers, Neue and Kuss, Jandera, and Bosch Rosés to describe the retention. In all cases, the predictive capability was very satisfactory. Two cases of study were considered: chromatograms of camomile extracts analysed using acetonitrile gradients, and a set of 145 known compounds in a wide range of structures and functionalities, eluted isocratically with acetonitrile/water mobile phases.

On the Enantioselective HPLC Separation Ability of Sub-2 µm Columns: Chiralpak® IG-U and ID-U

Silica with a particle size of 3-5 µm has been widely used as selector backbone material in 10-25 cm HPLC chiral columns. Yet, with the availability of 1.6 µm particles, shorter, high-efficiency columns practical for minute chiral separations are possible to fabricate. Herein, we investigate the use of two recently commercialized sub-2 µm columns with different substituents. Thus, Chiralpak® IG-U and ID-U were used in HPLC for the fast enantioseparation of a set of drugs. Chiralpak® IG-U [amylose tris (3-chloro-5-methylphenylcarbamate)] has two substituents on the phenyl ring, namely, a withdrawing chlorine group in the third position and a donating group in the fifth position. Chiralpak® ID-U [amylose tris (3-chlorophenylcarbamate)] has only one substituent on the phenyl ring, namely a withdrawing chlorine group. Their applications in three liquid chromatography modes, namely, normal phase, polar organic mode, and reversed phase, were demonstrated. Both columns have similar column parameters (50 mm length, 3 mm internal diameter, and 1.6 µm particle size) with the chiral stationary phase as the only variable. Improved chromatographic enantioresolution was obtained with Chiralpak® ID-U. Amino acids partially separated were reported for the first time under an amylose-based sub-2-micron column.

Carbamazepine and its metabolites in wastewater: Analytical pitfalls and occurrence in Germany and Portugal

The occurrence of carbamazepine (CBZ) and its metabolites in German and Portuguese wastewater was investigated. A total of 46 samples from influent and effluent wastewater were analyzed by liquid-chromatography (LC) tandem mass spectrometry. The five metabolites 10,11-dihydro-10,11-dihydroxy-CBZ (DiOH-CBZ), 10,11-dihydro-10-hydroxy-CBZ (10-OH-CBZ), 10,11-epoxy-10,11-dihydro-CBZ, 2-hydroxy-CBZ and 3-hydroxy-CBZ were very persistent with little to no removal during wastewater treatment. The highest concentrations were found for CBZ, DiOH-CBZ, and 10-OH-CBZ, with up to 5.0, 4.8 and 1.1 μg/L, respectively. Furthermore, the related pharmaceutical oxcarbazepine and the metabolites 9-hydroxymethyl-10-carbamoylacridan, 1-hydroxy-CBZ (1-OH-CBZ) and 4-hydroxy-CBZ (4-OH-CBZ) were detected. Explicit care was taken to achieve a good chromatographic separation of the numerous isomers that were difficult to distinguish by mass spectrometry alone. A phenylether stationary phase provided the best separation. In combination with high resolution mass spectrometry and hydrogen-deuterium exchange, this LC column enabled us to identify 1-OH-CBZ and 4-OH-CBZ in wastewater for the first time.

Comparative study of solvation parameter models accounting the effects of mobile phase composition in reversed-phase liquid chromatography

Solvation parameter models relate linearly compound properties with five fundamental solute descriptors (excess molar refraction, dipolarity/polarizability, effective hydrogen-bond acidity and basicity, and McGowan volume). These models are widely used, due to the availability of protocols to obtain the descriptors, good performance, and general applicability. Several approaches to predict retention in reversed-phase liquid chromatography (RPLC) as a function of these descriptors and mobile phase composition are compared, assaying the performance with a set of 146 organic compounds of diverse nature, eluted with acetonitrile and methanol. The approaches are classified in two groups: those that only allow predictions of retention for the mobile phases used to build the models, and those valid at any other mobile phase composition. The first group includes the use of ratios between the regressed coefficients of the solvation models that are assumed to be characteristic for a column/solvent system, and the application of offsets to transfer the retention from a reference mobile phase to any other. Maximal accuracy in predictions corresponded, however, to the approaches in the second group, which were based on models that describe the retention as a function of mobile phase composition (expressed as the solvent volume fraction or a normalised polarity measurement), where the coefficients were made dependent on the solvent descriptors. The study revealed the properties that influence the retention and distinguish the particular behaviour of acetonitrile and methanol in RPLC.

Polarity parameters of the Symmetry C18 and Chromolith Performance RP-18 monolithic chromatographic columns

A set of 12 compounds of different chemical nature has been established to characterise RPLC columns on the basis of a polarity retention model previously developed: log k=(log k)(0)+p(P(m)(N)-P(s)(N)). This model allows the calculation of the retention factor (k) of any non-ionized compound using one parameter which describes the polarity of the solute (p), another one for the polarity of the mobile phase (P(m)(N)) and two more parameters for the characterisation of the stationary phase ((log k)(0) and P(s)(N)). The selected set of compounds allows the determination of (log k)(0) and P(s)(N) of stationary phases and it has been used to characterise two commercial columns (Symmetry C18 from Waters and Chromolith Performance RP-18 monolithic from Merck). Column parameters, together with those of the mobile phase permit successful transfer of retention data between chromatographic systems. Prediction of retention of a variety of non-ionized analytes has been also successfully achieved using the column descriptors and p values of solutes from a previously established p data base.

A QSPR study of the p solute polarity parameter to estimate retention in HPLC

A Quantitative Structure-Property Relationship (QSPR) model is developed to calculate the solute polarity parameter p of a set of 233 compounds of a very different chemical nature. The proposed model, derived from multiple linear regression, contains four descriptors calculated from the molecular structure and the well-known hydrophobicity parameter log P(o/w). According to the statistics obtained with the prediction set, the model has a very good prediction capacity (R(2) = 0.954, F = 889, n = 45, and SD = 0.27). The study shows that log P(o/w) and hydrogen bond acidity of the solutes are the most relevant descriptors to predict p values. This p parameter is embodied in a general equation to predict retention in reversed-phase liquid chromatography (RP-HPLC). It describes analyte retention exclusively on the basis of mobile phase/analyte/stationary phase polar interactions. Equations and procedures to determine polarity of both chromatographic phases had been successfully developed previously. Therefore, the proposed QSPR model for p estimation becomes a very useful tool in RP-HPLC optimization of procedures and methods in the everyday analytical work.

Effect of molecular interactions on retention and selectivity in reversed-phase liquid chromatography

The linear solvation energy relationships (LSERs) have been applied in the last years for description and prediction of retention and selectivity in reversed-phase liquid chromatography with good results. Widely different stationary phases have been compared and characterized by LSERs. In recent publications the influence of the type of the organic moderator and the composition of the mobile phase have also been described. However, the influence of the molecular properties of the solutes to be separated has never been discussed. According to the LSER model variation in retention factors (log k) with solute structure can be related to their potential for various intermolecular interactions. The retention factor is given as the sum of the terms of the LSER equation representing various types of molecular interactions. For this reason the influence of the structure and molecular properties of the solutes to be separated can also be investigated using the LSER equation. In this study we shall demonstrate how the specific molecular interactions influence chromatographic retention and selectivity. We intend to show that retention and selectivity depend on all participants of the system. In addition to the structure and properties of the stationary phase and the type and composition of the mobile phase the molecular properties of the solutes, characterized by the solvation parameters, will also influence the type and extent of the various molecular interactions governing retention and selectivity.

Prediction of the retention in reversed-phase liquid chromatography using solute-mobile phase-stationary phase polarity parameters

A previously reported algorithm, based on the equation: log k = (log k)o + p(PN(m) - PN(s)), that relates the retention in reversed-phase liquid chromatography with solute (p), mobile phase (PN(m)) and stationary phase (PN(s)) relative polarity parameters, is improved. The retention data reported by several authors for different sets of compounds, eluted with acetonitrile-water and methanol-water mixtures, are used to test the algorithm and elaborate a database of p values. The methodology is successfully applied to predict the retention using PN(m), values calculated as PN(m) = 1.00 - (2.13phi)/(1+1.4phi) for acetonitrile-water and PN(m) = 1.00 - (1.33phi)/(l1 + 0.47phi) for methanol-water, phi being the organic solvent volumetric fraction. The polarity parameters are demonstrated to be useful to transfer retention data between solvent systems and between columns. Accordingly, the retention in a solvent system is predicted by characterising the working column with a small training set of compounds having diverse polarities, and using the p values known for another solvent system or column. The p polarity parameter is found to be a good descriptor of the retention, allowing the prediction of the expected elution order and peak overlaps.