Applicability of linear and nonlinear retention‐time models for reversed‐phase liquid chromatography separations of small molecules,peptides, and intact proteins |
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| Authors: | Eva Tyteca Jelle De Vos Nikola Vankova Petr Cesla Gert Desmet Sebastiaan Eeltink |
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| Affiliation: | 1. Department of Chemical Engineering, Vrije Universiteit Brussel, Brussels, Belgium;2. Faculty of Chemical Technology, Department of Analytical Chemistry, University of Pardubice, Pardubice, Czech Republic |
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| Abstract: | The applicability and predictive properties of the linear solvent strength model and two nonlinear retention‐time models, i.e., the quadratic model and the Neue model, were assessed for the separation of small molecules (phenol derivatives), peptides, and intact proteins. Retention‐time measurements were conducted in isocratic mode and gradient mode applying different gradient times and elution‐strength combinations. The quadratic model provided the most accurate retention‐factor predictions for small molecules (average absolute prediction error of 1.5%) and peptides separations (with a prediction error of 2.3%). An advantage of the Neue model is that it can provide accurate predictions based on only three gradient scouting runs, making tedious isocratic retention‐time measurements obsolete. For peptides, the use of gradient scouting runs in combination with the Neue model resulted in better prediction errors (<2.2%) compared to the use of isocratic runs. The applicability of the quadratic model is limited due to a complex combination of error and exponential functions. For protein separations, only a small elution window could be applied, which is due to the strong effect of the content of organic modifier on retention. Hence, the linear retention‐time behavior of intact proteins is well described by the linear solvent strength model. Prediction errors using gradient scouting runs were significantly lower (2.2%) than when using isocratic scouting runs (3.2%). |
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| Keywords: | Linear solvent strength model Method development Neue– Kuss model Retention‐time prediction Selectivity |
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