Isothermal titration calorimetry in drug discovery
- PMID: 11774798
- DOI: 10.1016/s0079-6468(08)70097-3
Isothermal titration calorimetry in drug discovery
Abstract
Isothermal titration calorimetry (ITC) follows the heat change when a test compound binds to a target protein. It allows precise measurement of affinity. The method is direct, making interpretation facile, because there is no requirement for competing molecules. Titration in the presence of other ligands rapidly provides information on the mechanism of action of the test compound, identifying the intermolecular complexes that are relevant for structure-based design. Calorimetry allows measurement of stoichiometry and so evaluation of the proportion of the sample that is functional. ITC can characterize protein fragments and catalytically inactive mutant enzymes. It is the only technique which directly measures the enthalpy of binding (delta H degree). Interpretation of delta H degree and its temperature dependence (delta Cp) is usually qualitative, not quantitative. This is because of complicated contributions from linked equilibria and a single change in structure giving modification of several physicochemical properties. Measured delta H degree values allow characterization of proton movement linked to the association of protein and ligand, giving information on the ionization of groups involved in binding. Biochemical systems characteristically exhibit enthalpy-entropy compensation where increased bonding is offset by an entropic penalty, reducing the magnitude of change in affinity. This also causes a lack of correlation between the free energy of binding (delta G degree) and delta H degree. When characterizing structure-activity relationships (SAR), most groups involved in binding can be detected as contributing to delta H degree, but not to affinity. Large enthalpy changes may reflect a modified binding mode, or protein conformation changes. Thus, delta H degree values may highlight a potential discontinuity in SAR, so that experimental structural data are likely to be particularly valuable in molecular design.
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