Application of the Solvatic Model for Prediction of Retention in RP-LC for Multi-Step Gradient Profiles

Abstract

of mobile-phase (B %) does not change during the separation. Isocratic elution is suitable for analysis of compounds with a relatively narrow range of polarity and hydrophobicity. In gradient elution, mobile phase strength (B %) increases during the separation. This means that sample retention is measured by k value decrease for each band as it migrates through the column [1-3]. Chromatographers are cautioned to avoid gradient elution when isocratic elution is possible to use. It is common knowledge that development and optimization of HPLC gradient methods can be time consuming and require many experiments [1,2]. Moreover, the transfer of a gradient elution method between columns, instruments and laboratories is notoriously more difficult than the transfer of an isocratic elution method [4,5]. Despite that gradient elution is a powerful method for separation and peak identification of many branches of chromatography provided that the optimum gradient profile, the profile that yields the best separation of the chromatographic peaks of a mixture of analytes can be easily determined [1-3, 6] The principal reason for using a gradient elution approach is a necessity to analyze samples containing solutes with a wide range of hydrophobicity [1-3, 6].As we mentioned before, optimization of gradient elution is a substantially more difficult task than optimization of isocratic conditions and can require many experiments, especially for multi-component samples [7][8][9][10]. Prediction of retention in gradient elution from structural formulae of analytes can potentially save time in method development, however, only a limited number of studies in this field have been published [11][12][13]. An approach described earlier requires many preliminary experiments to "train a column" and values of molecular descriptors which are mainly not known. Such an approach can be considered as theoretically interesting but without practical value [14][15][16]. The solvatic Abstract Application of the solvatic retention model of reversed-phase liquid chromatography was studied to predict retention of phenylisothiocyanate derivatives of amino acids from structural formulae and stationary and mobile phase properties. The gradient elution mode with methanol and acetonitrile aqueous mobile phases was used. It was shown that practically acceptable prediction or retention time values can be achieved after the first approximation step when experimental data of one run are used. The zero approximation level predictions-from structural formulae, column and mobile phase properties can be used as a "first guess" method from which further optimization can begin.

Application of Solvatic Model for Prediction of Retention at Gradient Elution in Reversed-Phase Liquid Chromatography

“…4 Presumably methods developed using computer-assisted procedures are expected to be more robust than those, developed by the traditional »trial and error« approach. [5][6][7] Three main factors affect analyte partition between the stationary and the mobile phase. Those are the chemical structure of analyte, characteristics of the stationary phase and physico-chemical properties of the mobile phase at the constant temperature.…”

“…9-15 Optimization of gradient elution is more complex compared to isocratic one and requires more experiments. 5,[16][17][18] In the literature successful prediction of isocratic retention parameters is reported. 16 In 2003, Baczek and Kaliszan applied quantitative structure retention relationships (QSRRs) to predict retention in reversed-phase HPLC with linear gradient.…”

“…Thus, in the Galushko's model the molecular interactions of analytes with the stationary and mobile phase are assumed to be accounted by the partial molar surface, S (S = V 2/3 ) that determines the energy to create a cavity in the phases. 5 The partial molar volume parameter (V) appears to be a reasonably reliable parameter of structurally nonspecific determination of analyte retention. Another molecular parameter ΔG, energy of interaction, reflects differences in the so-called electrostatic intermolecular interactions of analytes with a surrounding mobile phase.…”

“…Another molecular parameter ΔG, energy of interaction, reflects differences in the so-called electrostatic intermolecular interactions of analytes with a surrounding mobile phase. 5 The main limitation for retention prediction of chemical compounds from their structure is the inadequacy of the translation of structural formulas into sets of numerical descriptors. 19 Kaliszan's approach needs three molecular descriptors and four regression coefficients, Abraham's approach needs five molecular descriptors, constant log k 0, and five regression coefficients and Galushko's approach needs only two molecular parameters and three regression coefficients.…”

“…2,20,[24][25] It should be noted that Kaliszan's approach can be used only for prediction on selected stationary phase and only for the same gradient that was used for deriving the model, 16 while Galushko's approach enables prediction of retention also for other stationary phases and multistep gradients. 5 Other practical important point to be considered is that in QSRR modelling retention behaviour is usually performed in one software, and different software is used to calculate the molecular descriptors. 26 ChromSword ® enables all operations -structures drawing, molecular parameters calculation, chromatogram simulation for different columns and gradients in one software platform.…”