Quantifying non-specific interactions via liquid chromatography

Seishi Shimizu, Steven Abbott, Katarzyna Adamska, Adam Voelkel

Research output: Contribution to journalArticlepeer-review

Abstract

Determinations of solute-cosolute interactions from chromatography have often resulted in problems, such as the “antibinding” (or a negative binding constant) between the solute and micelle in micellar liquid chromatography (MLC) or indeterminacy of salt-ligand binding strength in high-performance affinity chromatography (HPAC). This shows that the stoichiometric binding models adopted in many chromatographic analyses cannot capture the non-specific nature of solvation interactions. In contrast, an approach using statistical thermodynamics handles these complexities without such problems and directly links chromatographic data to, for example, solubility data via a universal framework based on Kirkwood-Buff integrals (KBI) of the radial distribution functions. The chromatographic measurements can now be interpreted within this universal theoretical framework that has been used to rationalize small solute solubility, biomolecular stability, binding, aggregation and gelation. In particular, KBI analysis identifies key solute-cosolute interactions, including excluded volume effects. We present (i) how KBI can be obtained directly from the cosolute concentration dependence of the distribution coefficient, (ii) how the classical binding model, when used solely as a fitting model, can yield the KBIs directly from the literature data, and (iii) how chromatography and solubility measurements can be compared in the unified theoretical framework provided via KBIs without any arbitrary assumptions about the stationary phase. To perform our own analyses on multiple datasets we have used an “app”. To aid readers’ understanding and to allow analyses of their own datasets, the app is provided with many datasets and is freely available on-line as an open-source resource.
Original languageEnglish
Pages (from-to)1632-1641
Number of pages10
JournalAnalyst
Volume144
Issue number5
Early online date15 Jan 2019
DOIs
Publication statusPublished - 7 Mar 2019

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