How about this one:
Can't
Refine
Your
Structure
To
Acceptable
Likelihood
Typical error bars on crystallographic data are ~5% (R_sym), but with
very few exceptions the models in the PDB do not fit their corresponding
observations to better than ~40% error (R_cryst for intensities).
Gerard? What is the "likelihood" that such a model is correct?
Jokes and jabs aside, how much can we trust conclusions based on a model
with such a large amount of systematic error? I have been looking for
the answer to this question for many years now. So far, no luck.
DePriso et al. (2004) Structure 12, 831-8 framed this problem much
better than I just did. In my experience, pretty much everyone has a
hypothesis of why crystallographic R factors are so high: multiple
conformers is a popular one, as is semi-ordered solvent, local minima in
refinement space, etc. but I have yet to find convincing experimental
evidence (in the form of a 5% R_cryst with observations/parameters > 1
as is generally required of small molecule structures), or even a
controlled experiment to verify or reject any of these hypotheses. For
example, Vitkup et al. showed that fitting a single model to
MD-simulation derived "data" gave ~20% R, which means multiple
conformers are sufficient to explain the "R-Factor Gap", but the
converse has never been shown. The best results I have seen modeling
multiple conformers (such as the seminal Burling et al. 1996) get a few
percent decrease in R, but nothing close to the 15% needed to close the
"R-Factor Gap". Anybody got an idea for a necessary AND sufficient test?
I know that the core reason why we believe that our models are correct
is because they visually agree with the "1-sigma" contour of
experimentally-phased electron density maps. But, when it comes to
comparing NMR and MX, I am reminded of a certain idiom ... involving
glass houses.
-James Holton
MAD Scientist (who has also done a little NMR).
Gerard Bricogne wrote:
Dear Tassos, Bernhard and David,
If I may push this humourous response (obviously tainted with
crystallographic bias) a little further, I would say that my favourite
mnemonic for the acronym "NMR" is
N eeds
M ore
R esolution
Joking apart, of course, it is a devilishly clever method.
With best wishes,
Gerard.
--
On Fri, Nov 14, 2008 at 11:28:25AM +0100, Anastassis Perrakis wrote:
Since I don't like attachments, I will first iterate the title of the
attached publication:
"Traditional Biomolecular Structure Determination by NMR Spectroscopy
Allows for Major Errors "
It immediately reminded me of an older one (ehm .. one author in common!),
addressed at that time mostly to crystallographers:
"Errors in protein structures." (Nature 1996)
... and I am afraid that the authors were right in both cases (they did not
make many friends publishing these though)
Crystallographers learned from that paper back then. And the participation
of NMR spectroscopists on the 2006 paper
implies they are also learning ;-)
A.
On Nov 14, 2008, at 6:34, Bernhard Rupp wrote:
wondering what people think of this.
Very funny.
But no kidding, Richard Dickerson, the pioneer of DNA crystallography,
comes from your institution. For DNA, NMR has the benefit of readily
identifying intercalations in short oligomers etc w/o agony of
crystallizing.
For others, pls see attached. As a physical principle, spectroscopic
methods do not deliver atomic resolution structures, but a set of
inferences that may or may no be compatible with a molecular model.
BR
<Nabuurs_2006_PLOS_biomolecular_structure_NMR_errors.pdf>
