Isothermal titration calorimetry (ITC) is a highly valuable technique that is used throughout drug discovery workflow to study the binding interactions of proteins and small molecules. It is an essential tool for both drug design and the study and regulation of protein interactions. The data yielded from a single experiment enable the simultaneous examination of a number of parameters. This article briefly examines the uses and challenges of ITC in drug discovery and looks at how intelligent new software enables even less experienced users to analyze complex data in order to understand binding results.
Uses and challenges of ITC
ITC has a number of important applications throughout early stage drug discovery, from assay optimization work and secondary screening to later stages involving lead optimization. It is used to measure the binding affinity and thermodynamic properties of any molecular-level change that may influence recognition between binding partners— usually between a protein and ligand. When also combined with structural information, ITC data can provide even deeper insights into structure-function relationships and the mechanisms of binding.
A particular advantage of ITC is the ability to measure multiple binding parameters in a single experiment offering comprehensive information about the protein and its behavior. The thermodynamic data reveal to users why interactions occur and what forces are driving complex formation at the molecular level.
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The ideal drug will bind to targets with high affinity and selectivity. Traditionally, lead optimization has been driven by studies of the affinity component. However, the thermodynamic variables of enthalpy and entropy are also fundamental to binding and can provide deeper insights into the interactions.
While a number of techniques are available for characterizing binding interactions, ITC has won favor in drug discovery research as it is a label free approach that can accommodate a broad dynamic range of affinities. The technique is relatively easy to run and generates information-rich data. New generation instruments (such as the MicroCal PEAQ-ITC, Malvern Instruments) are capable of delivering exceptional sensitivity and outstanding data quality at high speed. However, until recently, the complex data generated by ITC has been challenging and time-consuming to process.
It’s all in the data analysis
Intuitive new MicroCal PEAQ-ITC Analysis Software is making the benefits of ITC more accessible to a wider range of researchers, including non-specialists. User-friendly 
guided workflows are incorporated together with embedded help videos that give any level of user the ability to generate high quality binding data. Further, the software packages can simulate experiment design (reducing wasted time and resources), provide batch evaluation of large data sets and automate assessment of data quality. At the same time a streamlined interface improves workflow by guiding the user to final figures and presentation quality graphs quickly and easily.
Binding data generated by ITC can be complex to interpret and where inaccuracies in the concentration or heterogeneity of the reactants occur, this interpretation becomes more complicated still. New ITC data analysis software can identify and accommodate for such errors, still delivering meaningful results to the user. The following examples demonstrate such benefits in greater detail.
Identifying and accounting for incorrect concentration of reactants
During early and late stages of drug discovery, researchers will often test a set of compounds and also incorporate a well-established positive control. The periodic use of a positive control ligand enables protein quality to be monitored and active protein concentrations to be established and confirmed throughout a series of ITC experiments. With the right ITC analysis software, scatter plots of binding parameters may be generated for a series of consecutive titrations. These support the detection of possible trends and identification of potential issues with assay design and reagent quality.
Figure 1 demonstrates this in practice. Here, the 
stoichiometry (N value) is obtained for a series of ITC titrations and shows a trend in the apparent number of binding sites on the target protein. The N value gradually decreases over time suggesting stability issues with the target protein. Limited protein stability, batch-to-batch variation, and limited freeze-thaw stability of a target protein are all common challenges associated with studies of protein-ligand interactions.
ITC data can be used to assess lot-to-lot variation in terms of protein activity and to provide potential normalization criteria, which are useful across many assays run throughout the screening and characterization process.
With the concentration of the active protein established and used in the ITC data analysis, any remaining errors in the apparent stoichiometry (i.e. non integer values) would be assigned to incorrect concentration determination of the ligand.
Dealing with ligand concentration errors
During drug discovery it is not uncommon for specified compound concentrations to be significantly wrong due to inaccurate measurement, limited solubility, or potential 
chemical heterogeneity of the compounds such as the presence of enantiomers and isomers. Inaccurate binding parameter information to be returned as a result, particularly affecting the determination of enthalpy and entropy. Now, novel software can identify and account for such compound concentration inaccuracies, thus minimizing errors in thermodynamic measurement.
In this example from a recent drug discovery and development project, a target protein was shown interacting with a series of low molecular weight (LMW) hits. The stoichiometry (N values) determined by ITC varied from 0.2 to 1.8 and did not correlate with a fraction of inactive protein that had already been established using the method described above. A binding stoichiometry of 1:1 was anticipated for the compounds based on X-ray structures of the complexes, so it was clear that the differences in the apparent stoichiometry was actually due to incorrect determination of the ligand concentration.
This original error impacted on the enthalpy data generated by ITC making it difficult to interpret the thermodynamics of interactions between each ligand and the target protein. However, groundbreaking new software can overcome this by allowing the concentration of the LMW ligand in the sample syringe to be adjusted while setting the stoichiometry value to 1 during the fitting process. Figure 3 shows this in practice.
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Once ligand concentration errors were identified and factored into the analysis, the enthalpy data looked dramatically different. In turn, this had a significant impact on the interpretation of binding activity in this lead optimization study.
A further consequence of ligand concentration inaccuracy is demonstrated in figure 4. The incomplete nature of the binding isotherm means that, without the right software, experiments may prove difficult to analyze and may need repeating. However, new software solutions can fit these incomplete binding isotherms using a constant offset, representing the control heats. By including the control offset and the ligand concentration into the fitting process, difficult datasets can be analyzed automatically in a non-subjective manner.
In the example above, the ligand concentration was initially thought to be 200 µM instead of an actual concentration of just 126 µM. As a result, the calculated enthalpy was out by -2.8 kcal/M and the entropy by 2.28 kcal/M. Lastly, the apparent dissociation constant (KD) was changed from 241 nM to 122 nM.
Simultaneous affinity determination for isomers and enantiomers
During the later drug discovery process, compounds are frequently synthesized as mixtures of isomers and enantiomers. In some cases, these can be separated and 
tested, although this separation is often difficult and time consuming. The alternative is to test the mixtures directly and here ITC provides binding information about both strong and weak binding components simultaneously in a single experiment.
An example of such ITC data is shown in the biphasic isotherms in figures 5 where an enantiomeric ligand mixture is injected into a target protein in the cell.
Biphasic isotherms may also be observed when high affinity ligands are intentionally mixed with weaker ligands as a form of competition experiment to determine the dissociation constant outside the range of direct measurements.
These experiments demonstrate the level of resolution that can be achieved by using MicroCal PEAQ-ITC along with its sophisticated software, and the potential for quantitative characterization of the binding mixtures. The fitting of complex ITC data has been made simpler and more accessible than ever before.
Filed Under: Drug Discovery
