Advancing HIC method development: Retention-time modeling and tuning selectivity with ternary mobile-phase systems

Raphael Ewonde Ewonde, Stef R.A. Molenaar, Ken Broeckhoven, Sebastiaan Eeltink*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Abstract

The use of a ternary mobile-phase system comprising ammonium sulphate, sodium chloride, and phosphate buffer was explored to tune retention and enhance selectivity in hydrophobic interaction chromatography. The accuracy of the linear solvent-strength model to predict protein retention with the ternary mobile-phase system based on isocratic scouting runs is limited, as the extrapolated retention factor at aqueous buffer conditions (k0) cannot be reliably established. The Jandera retention model utilizing a salt concentration averaged retention factor (k¯0) in aqueous buffer for ternary systems overcomes this bottleneck. Gradient retention factors were derived based on isocratic scouting runs after numerical integration of the isocratic Jandera model, leading to retention-time prediction errors below 11 % for linear gradients. Furthermore, an analytical expression was formulated to predict HIC retention for both linear and segmented linear gradients, considering the linear solvent-strength (LSS) model within ternary salt systems, relying on a fixed k0. The approach involved conducting two gradient scouting runs for each of the two binary salt systems to determine model parameters. Retention-time prediction errors for linear gradients were below 12 % for lysozyme and 3 % for trypsinogen and α-chymotrypsinogen A. Finally, the analytical expression for a ternary mobile-phase system was used in combination with a genetic algorithm to tune the HIC selectivity. With an optimized segmented ternary gradient, a critical-pair separation for a mixture of 7 proteins was achieved within 15 min with retention-time prediction errors ranging between 0.7 and 15.7 %.

Original languageEnglish
Article number465133
Pages (from-to)1-10
Number of pages10
JournalJournal of Chromatography A
Volume1730
Early online date30 Jun 2024
DOIs
Publication statusPublished - 16 Aug 2024

Bibliographical note

Publisher Copyright:
© 2024

Funding

FundersFunder number
BASF
Ministry of Economic Affairs
Fonds Wetenschappelijk OnderzoekG026522N, 30897864
Nederlandse Organisatie voor Wetenschappelijk Onderzoek731.017.303

    Keywords

    • Genetic algorithm
    • Gradient prediction
    • Hydrophobic interaction chromatography
    • Protein analysis

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