ITC analysis of polydisperse systems: Unravelling the impact of sample heterogeneity

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

ITC analysis of polydisperse systems : Unravelling the impact of sample heterogeneity. / Schönbeck, Christian; Kari, Jeppe; Westh, Peter.

In: Analytical Biochemistry, Vol. 687, 115446, 2024.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Schönbeck, C, Kari, J & Westh, P 2024, 'ITC analysis of polydisperse systems: Unravelling the impact of sample heterogeneity', Analytical Biochemistry, vol. 687, 115446. https://doi.org/10.1016/j.ab.2023.115446

APA

Schönbeck, C., Kari, J., & Westh, P. (2024). ITC analysis of polydisperse systems: Unravelling the impact of sample heterogeneity. Analytical Biochemistry, 687, [115446]. https://doi.org/10.1016/j.ab.2023.115446

Vancouver

Schönbeck C, Kari J, Westh P. ITC analysis of polydisperse systems: Unravelling the impact of sample heterogeneity. Analytical Biochemistry. 2024;687. 115446. https://doi.org/10.1016/j.ab.2023.115446

Author

Schönbeck, Christian ; Kari, Jeppe ; Westh, Peter. / ITC analysis of polydisperse systems : Unravelling the impact of sample heterogeneity. In: Analytical Biochemistry. 2024 ; Vol. 687.

Bibtex

@article{71fca918249a41edad62e0e217aec925,
title = "ITC analysis of polydisperse systems: Unravelling the impact of sample heterogeneity",
abstract = "Binding interactions often involve heterogeneous samples displaying a distribution of binding sites that vary in affinity and binding enthalpy. Examples include biological samples like proteins and chemically produced samples like modified cyclodextrins. Experimental studies often ignore sample heterogeneity and treat the system as an interaction of two homogeneous species, i.e. a chemically well-defined ligand binding to one type of site. The present study explores, by simulations and experiments, the impact of heterogeneity in isothermal titration calorimetry (ITC) setups where one of the binding components is heterogeneous. It is found that the standard single-site model, based on the assumption of two homogeneous binding components, provides excellent fits to simulated ITC data when the binding free energy is normally distributed and all sites have similar binding enthalpies. In such cases, heterogeneity can easily go undetected but leads to underestimated binding constants. Heterogeneity in the binding enthalpy is a bigger problem and may result in enthalpograms of increased complexity that are likely to be misinterpreted as two-site binding or other complex binding models. Finally, it is shown that heterogeneity can account for previously observed experimental anomalies. All simulations are accessible in Google Colab for readers to experiment with the simulation parameters.",
author = "Christian Sch{\"o}nbeck and Jeppe Kari and Peter Westh",
note = "Publisher Copyright: {\textcopyright} 2023 The Authors",
year = "2024",
doi = "10.1016/j.ab.2023.115446",
language = "English",
volume = "687",
journal = "Analytical Biochemistry",
issn = "0003-2697",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - ITC analysis of polydisperse systems

T2 - Unravelling the impact of sample heterogeneity

AU - Schönbeck, Christian

AU - Kari, Jeppe

AU - Westh, Peter

N1 - Publisher Copyright: © 2023 The Authors

PY - 2024

Y1 - 2024

N2 - Binding interactions often involve heterogeneous samples displaying a distribution of binding sites that vary in affinity and binding enthalpy. Examples include biological samples like proteins and chemically produced samples like modified cyclodextrins. Experimental studies often ignore sample heterogeneity and treat the system as an interaction of two homogeneous species, i.e. a chemically well-defined ligand binding to one type of site. The present study explores, by simulations and experiments, the impact of heterogeneity in isothermal titration calorimetry (ITC) setups where one of the binding components is heterogeneous. It is found that the standard single-site model, based on the assumption of two homogeneous binding components, provides excellent fits to simulated ITC data when the binding free energy is normally distributed and all sites have similar binding enthalpies. In such cases, heterogeneity can easily go undetected but leads to underestimated binding constants. Heterogeneity in the binding enthalpy is a bigger problem and may result in enthalpograms of increased complexity that are likely to be misinterpreted as two-site binding or other complex binding models. Finally, it is shown that heterogeneity can account for previously observed experimental anomalies. All simulations are accessible in Google Colab for readers to experiment with the simulation parameters.

AB - Binding interactions often involve heterogeneous samples displaying a distribution of binding sites that vary in affinity and binding enthalpy. Examples include biological samples like proteins and chemically produced samples like modified cyclodextrins. Experimental studies often ignore sample heterogeneity and treat the system as an interaction of two homogeneous species, i.e. a chemically well-defined ligand binding to one type of site. The present study explores, by simulations and experiments, the impact of heterogeneity in isothermal titration calorimetry (ITC) setups where one of the binding components is heterogeneous. It is found that the standard single-site model, based on the assumption of two homogeneous binding components, provides excellent fits to simulated ITC data when the binding free energy is normally distributed and all sites have similar binding enthalpies. In such cases, heterogeneity can easily go undetected but leads to underestimated binding constants. Heterogeneity in the binding enthalpy is a bigger problem and may result in enthalpograms of increased complexity that are likely to be misinterpreted as two-site binding or other complex binding models. Finally, it is shown that heterogeneity can account for previously observed experimental anomalies. All simulations are accessible in Google Colab for readers to experiment with the simulation parameters.

U2 - 10.1016/j.ab.2023.115446

DO - 10.1016/j.ab.2023.115446

M3 - Journal article

C2 - 38147946

AN - SCOPUS:85181763210

VL - 687

JO - Analytical Biochemistry

JF - Analytical Biochemistry

SN - 0003-2697

M1 - 115446

ER -

ID: 380200614