Abstract
For a conscientious interpretation of thermodynamic parameters (Gibbs free energy, enthalpy and entropy) obtained by isothermal titration calorimetry (ITC), it is necessary to first evaluate the experimental setup and conditions at which the data were measured. The data quality must be assessed and the precision and accuracy of the measured parameters must be estimated. This information provides the basis at which level discussion of the data is appropriate, and allows insight into the significance of comparisons with other data. The aim of this article is to provide the reader with basic understanding of the ITC technique and the experimental practices commonly applied, in order to foster an appreciation for how much measured thermodynamic parameters can deviate from ideal, error-free values. Particular attention is paid to the shape of the recorded isotherm (c-value), the influence of the applied buffer used for the reaction (protonation reactions, pH), the chosen experimental settings (temperature), impurities of protein and ligand, sources of systematic errors (solution concentration, solution activity, and device calibration) and to the applied analysis software. Furthermore, we comment on enthalpy–entropy compensation, heat capacities and van’t Hoff enthalpies.
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Acknowledgments
SK was kindly supported by the European Research Council (ERC) Advanced Grant No. 268145-DrugProfilBind awarded to GK. We want to thank Mahalia Lepage for thorough proof-reading of the manuscript.
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Experimental details are given for the ITC titrations of the analysis of the heat of ionization (Fig. 3), for the titration at different salt concentrations (Fig. 4) and for the titrations applying different protein concentrations (Fig. 5). All raw ITC thermograms and their resulting isotherms as well as the extracted parameters are listed. (PDF 969 kb)
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Krimmer, S.G., Klebe, G. Thermodynamics of protein–ligand interactions as a reference for computational analysis: how to assess accuracy, reliability and relevance of experimental data. J Comput Aided Mol Des 29, 867–883 (2015). https://doi.org/10.1007/s10822-015-9867-y
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DOI: https://doi.org/10.1007/s10822-015-9867-y