Collecting Variable-concentration Isothermal Titration Calorimetry Datasets in Order to Determine Binding Mechanisms

Summary

ITC is a powerful tool for studying the binding of a ligand to its host. In complex systems however, several models may fit the data equally well. The method described here provides a means to elucidate the appropriate binding model for complex systems and extract the corresponding thermodynamic parameters.

Abstract

Isothermal titration calorimetry (ITC) is commonly used to determine the thermodynamic parameters associated with the binding of a ligand to a host macromolecule. ITC has some advantages over common spectroscopic approaches for studying host/ligand interactions. For example, the heat released or absorbed when the two components interact is directly measured and does not require any exogenous reporters. Thus the binding enthalpy and the association constant (Ka) are directly obtained from ITC data, and can be used to compute the entropic contribution. Moreover, the shape of the isotherm is dependent on the c-value and the mechanistic model involved. The c-value is defined as c = n[P]tKa, where [P]t is the protein concentration, and n is the number of ligand binding sites within the host. In many cases, multiple binding sites for a given ligand are non-equivalent and ITC allows the characterization of the thermodynamic binding parameters for each individual binding site. This however requires that the correct binding model be used. This choice can be problematic if different models can fit the same experimental data. We have previously shown that this problem can be circumvented by performing experiments at several c-values. The multiple isotherms obtained at different c-values are fit simultaneously to separate models. The correct model is next identified based on the goodness of fit across the entire variable-c dataset. This process is applied here to the aminoglycoside resistance-causing enzyme aminoglycoside N-6'-acetyltransferase-Ii (AAC(6')-Ii). Although our methodology is applicable to any system, the necessity of this strategy is better demonstrated with a macromolecule-ligand system showing allostery or cooperativity, and when different binding models provide essentially identical fits to the same data. To our knowledge, there are no such systems commercially available. AAC(6')-Ii, is a homo-dimer containing two active sites, showing cooperativity between the two subunits. However ITC data obtained at a single c-value can be fit equally well to at least two different models a two-sets-of-sites independent model and a two-site sequential (cooperative) model. Through varying the c-value as explained above, it was established that the correct binding model for AAC(6')-Ii is a two-site sequential binding model. Herein, we describe the steps that must be taken when performing ITC experiments in order to obtain datasets suitable for variable-c analyses.

Protocol

1. Preparing stock solutions

1. Purify the macromolecule of interest. (In this case, aminoglycoside N-6'-acetyltransferase-Ii (AAC6'-Ii), is isolated as reported elsewhere.¹³)
2. Prepare 4 litres of dialysis buffer. (In this case we used 25 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES, MW 238.3 g/mol), containing 2 mM ethylenediaminetetraacetic acid (EDTA, MW 292.2), at pH 7.5.)
3. Dialyze the protein The AAC(6')-Ii sample (5 mL at 400 μM) used must be dialyzed in dialysis buffer (3 x 1.3 L). The final dialysis solution is kept to rinse the machine and to dilute samples.
4. Filter the final dialysis solutio....

Discussion

This analytical portion of variable-c fitting has been previously described in detail¹⁰. Here we report practical aspects of collecting variable-c datasets suitable for this approach. It is essential that all protein and ligand samples are drawn from the same stock solutions. Therefore it is important that sufficient stock solution is prepared initially to complete the entire series of experiments. This ensures the ratio of AAC(6')-Ii and AcCoA is constant among all experiments, and reduces random fluctuation.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Acetyl c–nzyme A (AcCoA)	Sigma-Aldrich	A2056
4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES)	Fisher Scientific	7365-45-9
ethylenediaminetetraacetic acid (EDTA)	Sigma-Aldrich	431788
Spectra/Por 2 Dialysis Tubing	Spectrum Labs	132678
Sterile Syringe Filter (0.2 μm)	VWR international	281445-477
Cellulos Nitrate Membrane Filters (0.45 μm)	Whatman, GE Healthcare	7184-004
VP-ITC	MicroCal	VP-ITC	Microcalorimeter used for measurements
ThermoVac	MicroCal	USB Thermo Vac	Temperature Controlled Degassing Station