NMR has a checkered history in drug discovery. In the 90s, it promised to deliver structures just like X-ray. Strike 1! After that, especially after the advent of SAR by NMR, it promised to deliver boatloads of hits from screening. Strike 2! After that, pharmaceutical NMR worked hard to make sure that it was impactful and value-added. It found niches in which it thrives, e.g. a variety of -omics. In drug discovery, NMR still needs to realize it is living with two strikes. How can NMR survive and even thrive? Quite simply. NMR needs to provide rapid, robust, and easily understandable data to medchemists that leads to decisions. Data that results in no action has no value.
In this paper, Salvia et al. present a ligand-based NMR screening method using "long-lived states (LLS)" of the ligand to boost the sensitivity of ligand-based screening. This new method provides 25x better signal-to-noise than established (T1rho) methods and uses less protein. One of the benefits of this method is it allows NMR to study interactions as tight as 100nM and up to 1 mM.
The graphical abstract (above) shows that while this method is very similar in concept to other ligand-based methods (TOP: equilibrium between NMR differentiated states) it requires much more work than these other methods (Bottom: titrations of ligands). The data (Below) does generate quite satisfying curves, and as noted by the authors, are in agreement with previously published values.
I think this work, while an interesting application of Long Lived States, has really no practical value to the screening world. The strength of the binding can be too strong, making the bound lifetime too long, and thus there is a practical floor for Kd. Of course, because it is based upon kinetics, it can be very different for every system.
If you want to determine Kds for a complex < 10uM there are better, far more robust methods (SPR, for one). The amount of time and effort required to generate Kds from this method seems to run contrary to the tenets I described above (rapid, robust, and (most importantly) easily understandable). To me, the title of the paper simply does not deliver. This method is NOT a screening application. A screening application is one experiment (NMR or otherwise) from which you can determine whether a compound is binding or not, ideally from a mixture of compounds.
I would be curious to see in the comments if anyone (especially our NMR savvy readers, you know who you are) think that this method has practical applications.
In this paper, Salvia et al. present a ligand-based NMR screening method using "long-lived states (LLS)" of the ligand to boost the sensitivity of ligand-based screening. This new method provides 25x better signal-to-noise than established (T1rho) methods and uses less protein. One of the benefits of this method is it allows NMR to study interactions as tight as 100nM and up to 1 mM.
The graphical abstract (above) shows that while this method is very similar in concept to other ligand-based methods (TOP: equilibrium between NMR differentiated states) it requires much more work than these other methods (Bottom: titrations of ligands). The data (Below) does generate quite satisfying curves, and as noted by the authors, are in agreement with previously published values.
I think this work, while an interesting application of Long Lived States, has really no practical value to the screening world. The strength of the binding can be too strong, making the bound lifetime too long, and thus there is a practical floor for Kd. Of course, because it is based upon kinetics, it can be very different for every system.If you want to determine Kds for a complex < 10uM there are better, far more robust methods (SPR, for one). The amount of time and effort required to generate Kds from this method seems to run contrary to the tenets I described above (rapid, robust, and (most importantly) easily understandable). To me, the title of the paper simply does not deliver. This method is NOT a screening application. A screening application is one experiment (NMR or otherwise) from which you can determine whether a compound is binding or not, ideally from a mixture of compounds.
I would be curious to see in the comments if anyone (especially our NMR savvy readers, you know who you are) think that this method has practical applications.
Firstly, I'd argue with your 'two strikes' for NMR in pharma. While NMR structures were never able to match crystallography for speed and resolution, I don't think there's a more robust way of identifying ligand/receptor interactions than solution phase NMR. The interaction that you're looking at is reduced to a simple two-component experiment, where both components can be monitored directly and without the need for any labelling or indirect read-out. With this, NMR can (and does) deliver boat-load of screening hits which, if you design your screening experiment correctly, have a very high validation rate in follow-up techniques.
ReplyDeleteHaving said that, you should always use the correct tool for the job. I'd use NMR for screening if the system lends itself to it; I'd use crystallography for getting the structure of the bound state, and I'd use ITC or SPR for getting the Kd. Although you can do all of these by NMR, unless you have to there's no reason to do so.
Anyway, the LLS paper. Interesting technique, but as you say it's of limited practical application. The biggest limitation, as far as I'm concerned, is that the technique requires a two-spin system with which the LLS state can be set up. This immediately means that you can't apply it to a screening library, unless you specifically tailor the chemical matter to contain two-spin systems. And if you're going to set up a tailor made library, you might as well go for 19F labeling.
Ben, I agree that receptor-ligand interactions are best done by solution NMR methods, like STD or waterlogsy, diffusion mapping, etc. I don't think labeled protein studies (what I term the first strike) is the way. I think we agree there from your later comments.
ReplyDeleteI also agree that if you need to tailor your library, 19F is the way to go.
Hi there, just a comment on LLS paper. This is a relaxation filtered ligand based method (like T1rho or selective T1). You therefore may consider using it in competition mode if you find one suitable "spy" molecule: this would allow with a single point experiment screening mixtures and/or ranking for low affinity hits(especially if solubility is limiting). I would actually give it a try.
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