TY - JOUR
T1 - Quantifying non-specific interactions via liquid chromatography
AU - Shimizu, Seishi
AU - Abbott, Steven
AU - Adamska, Katarzyna
AU - Voelkel, Adam
N1 - © The Royal Society of Chemistry 2019. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.
PY - 2019/3/7
Y1 - 2019/3/7
N2 - 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.
AB - 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.
U2 - 10.1039/C8AN02244E
DO - 10.1039/C8AN02244E
M3 - Article
SN - 0003-2654
VL - 144
SP - 1632
EP - 1641
JO - Analyst
JF - Analyst
IS - 5
ER -