Last week we highlighted a
ligand-detected NMR method to measure affinities of protein-ligand
interactions. That technique, R2KD, requires preparing multiple NMR samples
with the ligand at different concentrations. In a new open-access paper
published in J. Am. Chem. Soc., Serena Monaco and collaborators at University
of East Anglia and Universidad de Sevilla describe a method that can be done in
a single NMR tube.
The researchers have actually
combined two methods, chemical shift imaging (CSI) and Saturation Transfer
Difference (STD) NMR, to create imaging STD NMR. We’ve written previously about
STD NMR, which relies on the transfer of magnetization from an irradiated
protein to a bound ligand. In CSI, chemical shift information is recorded at
multiple slices along the length of an NMR tube. Normally the solution in an
NMR tube is homogenous and so the chemical shifts would be identical at the
bottom and top of the NMR tube. Here, though, the researchers create
concentration gradients by carefully pipetting a solution containing ligand on
top of a solution containing protein and allowing the ligand to diffuse the length
of the NMR tube.
Like all things NMR-related, the mathematics
get a bit complicated. One important factor is the rate of diffusion for a
given small molecule. This “diffusion coefficient” can be experimentally
measured by creating a concentration gradient in the absence of protein and
measuring the ligand concentration at various positions in an NMR tube after a
given length of time (typically more than 12 hours). Diffusion is dependent on
molecular weight, so it is also possible to calculate the diffusion coefficient,
and in fact the researchers found that the calculated values matched the experimental
values for three different small molecules.
Knowing the diffusion coefficient
helps establish the maximum ligand concentration to use and the ideal diffusion
time. The researchers examined three different protein-ligand pairs, all of which
had weak affinities, with KD values from 0.2 to 2 mM. Measuring STD
signals at different slices along the NMR tube effectively yields STD signals at
different concentrations of ligand, and fitting this to an equation allows calculation
of the dissociation constant. For the three model systems the affinities agreed
with literature values, which had been determined using ITC or WAC.
One nice feature of imaging STD
NMR is that it can identify non-specific binding. This is because STD signals
vary depending in part on how close a proton on the ligand is to the protein,
resulting in different STD signals for different protons for specific binders. If
this “epitope pattern” is lost at higher concentrations, this suggests
non-specific binding, where the ligand can bind in random orientations to multiple
sites on the protein. The researchers demonstrated this for one of their model
systems: tryptophan binds specifically to bovine serum albumin with a dissociation
constant of 0.2 mM, but above 1 mM or so the epitope disappears, suggesting
non-specific binding.
Imaging STD NMR does have some
limitations. For one thing, it requires a high initial concentration of ligand:
30 mM in the case of tryptophan, and even higher for the other two ligands. Most
small molecules are nowhere near this soluble in water. The researchers suggest
that ligands could be dissolved in DMSO and placed on the bottom of the NMR tube,
with the protein solution gently layered on top. They show that the concentration
gradients develop in a similar manner as a fully aqueous system, but acknowledge
that high DMSO concentrations may not play well with most proteins.
Also not stated is the
sensitivity of the method for higher affinity binders. Last week’s R2KD could measure affinities as tight as 10 µM, but it is unclear how much below 200 µM imaging
STD NMR can go.
Finally, as we noted in 2019, STD
effects are remarkably complex and not well-correlated with affinity. In
particular, binding kinetics can play a role in the strength of the signal. It
would have been nice to see more than three protein-ligand pairs tested.
All that said, this is an
intriguing approach. Laudably, the researchers provide extensive supporting information,
including mathematical derivation of the fitting equations, a spreadsheet, NMR pulse
sequences, and macros. I’ll be curious to see how it works for others.
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