Dissociation constant (Kd) - what is it, how is it measured and why does it matter?

‍What is the Dissociation Constant (Kd)?

The dissociation constant (Kd) is a measurement of affinity betweentwo biomolecules – in general terms, a ligand and a receptor – driven by chemical and biophysical attractions. As a value, Kd reports the extent of binding that occurs naturally between the ligand and receptor. A low Kd value indicates that the two molecules are highly attracted to each other, and that only a low concentration of the ligand is needed to saturate the receptor. A highKd value indicates that the binding between the ligand and the receptor is weak and that a high concentration of the ligand is needed to enable receptor-ligand interaction.

Why is Kd important to measure?

Binding affinity is a vital parameter in all industries that work with biomolecules. Specificity and selectivity of binding defines how the biomolecule will interact with its surroundings. For example, novel immunotherapy drugs for cancer must both be tested for their ability to bind and neutralise cancer cells as well as their potential to bind to healthy cells and cause side effects. Thus, Kd must be carefully and thoroughly studied to understand the impact of biomolecules on their environment.

How can you measure the Kd?

Several methods exist to quantitatively measure binding affinity, including spectroscopic assays, titration calorimetry, or optical biosensors. However, these methods are disadvantaged with high sample volume needs, low-throughput, and failure to deal with complex matrices. Additionally, these methods require dedicated instruments and trained staff to operate, reducing their applicability in experimental workflows.

An innovative approach to measuring Kd is possible with FIDA (FlowInduced Dispersion Analysis), which uses the absolute measurement of molecular size (hydrodynamic radius) to determine the binding affinity between two or more biomolecules alongside a host of other crucial biophysical and quality control parameters.

How are size-based Kd measurements made?

In solution, molecules have a specific geometry that can be measured as the hydrodynamic radius (Rh). FIDA measures Rh directly from the diffusivity of the molecule as it passes through a capillary. As a biomolecule binds its ligand(s), the complex increases in size. FIDA software reports this binding and complex formation as an increase in Rh. By measuring the change in Rh of the biomolecule under increasing concentrations of the ligand, FIDA software calculates the dissociation constant (Kd).

In more detail

Considering the following system,

The 1-1 interaction between the analyte A and the indicator I is analysed using mathematical models in FIDA software. The indicator is a fluorescently labelled, or intrinsically fluorescent species and analyte is the unlabelled binding partner. It is assumed that the total concentration of A is equal to the free concentration of A. In praxis this approximation is valid when the indicator concentration is less than the Kd. Binding isotherm based on hydrodynamic radius (R):

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Here, Rapp is the apparent hydrodynamic radius measured by the Fida 1,Kd is the equilibrium dissociation constant defined in eq 1, RI is the hydrodynamic radius of the unbound indicator, RIA is the hydrodynamic radius ofthe 1-1 complex and [A] is the analyte concentration.

What makes size-based Kd measurements superior to other methods?

An absolute measurement of molecular size by FIDA uses no assumptions or models to determine the size of a biomolecule. That means that the disassociation constant is calculated from direct measurements of the interactions between biomolecules. First principle thinking reveals the true state of affinity between ligand and receptor: in solution, label-free, and independent of the buffer used. Additionally, FIDA’s low-input, high-throughput set up allows for fast testing of novel biomolecules from small volumes, reducing time to first data and conserving precious sample material. With FIDA, Kd is reachable for all biomolecules without the need for complex experiments, so time and resources can be used for future scientific discoveries, not assay optimization.