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. 

Poll Results: Do you Need Structure

The poll question, Do you Need Structure To Prosecute Fragments is closed. We had 27 votes. 6 (22%) people voted for "Absolutely. No X-ray, no fragments." 6 (22%) voted for "Nope". And the majority 55% (15/27) voted for "Yes, but I am flexible as to what structure is." So, ~80% of the people who voted (self-selection?) think you do not need a X-ray structure to move forward.

So, what kind of methods can we put in the "structure" bin that is not X-ray? I think we need to define structure to get to that first question. In my eyes (and I hope this generates some dialog in the comments), structural information is data that informs on how the ligand and target interact. In my eyes, non-structural structural information is SAR without the guessing. Typical SAR: let's walk this methyl (hopefully its a magic methyl) around this ring, then ethyl, propyl, butyl, futile. Change the ring from phenyl to pyridyl...and so on.

Epitope mapping is one well established method to establish interactions between ligand and target. I am partial to this, but I am an NMR jock. To me, this is as instructive as a crystal structure. It tell you which part of the molecule is in closest contact with the target, which aren't. It leads to imminently testable medchem hypotheses.

Hydrogen-deuterium exchange (HDX) is another method which could inform on the target side of the ligand-target interaction. HDX is most robustly performed by Mass spectrometry, but can also be done by NMR (if the protein is amenable, blah^3). Is this a robust (and SENSITIVE!!!) enough method for routine mapping of ligand-protein interactions?

I ask this out of ignorance, not out of general gadfly-ness, but what methods do those people who are "flexible to structure" use to generate non-structure structural information?