08 November 2012

Not to get too meta on you

If you read this blog, you should be aware that I  think you do not need structure to prosecute fragments.  So, when a paper comes along titled "Toward Rational Fragment-Based Lead Design without 3D Structures" you would think I would plotz.  After reading it, plotz I did, but not from excitement.  

Henen and colleagues (in Robert Konrat's lab in Vienna) present their vision for a structureless future of FBDD.  This future (dystopian for many, utopian for me) is predicated on their meta-structural analysis.  Meta-structural analysis relies on "higher level of abstraction" and "incorporating 3D structural information."  This seems like unfocusing the lens to get a sharper image.  I won't go into the fine details I am sure Peter Kenney has already or would do a much better job if he hasn't.  The general gist is (and trust me I may be misunderstanding this) for a target you predict its secondary structure (because the primary sequence has too low homology to build a reasonable model) and then search for proteins (in DRUGBANK) with known structure and similar secondary structure motifs.  You then get a list of "meta-structurally" similar targets and you make sure they have experimentally-verified ligands. To demonstrate this, the authors show the results of the meta-structure search for lipocalin Q83.

Red structure shows similarity from Q83 while orange shows similarity from the homologs, in this case the beta-barrel structure (A)Strepavidin; (B) FABP, (C) chorismate lyase.  The authors note that chorismate lyase only shares half of the beta-barrel structure.  The further demonstrate this approach, they then chose to go with chorismate lyase and its ligand vanillic acid.  It shares structural similarity with the known Q83 ligand enterobactin.  

A comparison of the solution structure of Q83 (where is my utopian strucutureless future?) and chorismate lyase shows that the two proteins bind their ligands in similar fashion.  From this they concluded that Q83 binds vanillic acid in a 2:1 stoichiometry.  They then used 1H-15N HSQC and ITC to verify the binding of vanillic acid to Q83.  Not surprisingly, it binds. And because they have the assignments (and structure) they found that it binds in the enterobactin binding site.  ITC confirmed that it binds in a 2:1 ratio.  Using the plethora of structural information they have, they wanted to test their ability to link two vanillic acid moieties and went with a "Analog by Catalog"  using the structural insights they have from the meta-structure (and NMR structure) approach with this beast ->.   [To their credit, the authors admit this is not in anyway a reasonable molecule.  I think its most appealing property is that it was available from Sigma-Aldrich.]  They confirmed that this bound to Q83, showing similar chemical shift perturbations as vanillic acid and confirmed by fluorescence quenching.  As their conclusion to this part of the paper, the authors state
Most importantly, it demonstrates that the information needed to rationally improve molecular fragments, found in a first iteration of an FBLD program, is eventually solely provided by meta-structural data without the requirement of a highly resolved crystal structure.
To quote the greatest movie ever, "Opinions vary." [Warning VERY NSFW and very potentially offensive].  As far as I can tell, they didn't have a crystal structure, but a NMR structure.  In my, admittedly biased eyes, that is still structural data. 

In the second part of this paper, the authors repeat this approach with beta-catenin.  But here, they want to show the AFP-NOESY (adiabatic fast passage-NOESY) method they developed can be used for epitope mapping.  The concept here is that:
sizable spin diffusion effects, as a result of the existence of dense hydrogen networks or hydrophobic clusters, lead to measurable shifts of the zero passage toward larger tilt angles.
This seems like "Another (impractical) NMR Method".  STD can deliver the exact same data, has been accepted in the hit discovery  community for a long time, and so on.  I don't see why AFP-NOESY is better.  Anybody care to change my mind?  They end with an example of dynamic combinatorial chemistry to select for a combination of two fragments with improved binding. 

So, did the authors deliver on the promise of their title?  Not in the least.  This is homology modeling by another name.  They still are using structures, just not of the target of interest.  Could it be useful?  Maybe. 


Dan Erlanson said...

I agree with this assessment, but I actually have some more fundamental concerns about this paper: specifically, it is not clear that the molecules described are legitimate binders.

Let me start by noting that the researchers’ “known ligands” for one of the targets consist largely of PAINS. These molecules are likely to react covalently with the target or generate hydrogen peroxide under typical assay conditions. I’m afraid that this may be a cautionary tale of GIGO.

There are also several other red flags. First, the fluorescence quenching assay contains no detergent, so it is very possible that their molecules are simply aggregating, a classic and insidious false positive. I’m also not convinced by the NMR and ITC data. In the case of the ITC data shown, millimolar amounts of a fairly acidic fragment are added to a protein in 20 mM phosphate buffer. This has low buffer capacity, especially at pH 6.5, so it seems likely that many of the perturbations observed are simply due to acidification of the solution.

There are examples of advancing fragments without structures, but I’m not convinced this is one of them. At best, this technique may be prone to picking up promiscuous binders that hit lots of proteins. At worst, many or most of the molecules described here are simply assay artifacts.

Dr. Teddy Z said...

I concur Dan. But, I wanted someone else to point that out. ;-)