I think the relevant point in this discussion is that the original paper
discussed the apo and substrate complexes of the protein. For the
structure with lower resolution data you may indeed get a better model
by taking the high resolution model and just applying rigid body
refinement to it. After that step you would like to find and model the
differences between the two structures. This includes the bound
substrate (or the lack thereof) and any significant structural changes
that accompany substrate binding. Significant meaning those changes that
can be reliably determined at the lower resolution. For most of the
structure that may mean you are best off by simply taking the
rigid-body-refined coordinates of the higher resolution structure
without further refinement. I see no problem in doing so and as long as
interesting differences between the structures can be clearly defined
and the procedure is explicity described in publications this should be
perfectly reasonable.
Bart
Edward A Berry wrote:
You have a good point there and I would be interested in hearing
some other opinions, so I take the liberty of reposting-
My instinctive preference is that each structure should be
supported solely by the data that is deposited with it -
(one dataset one structure) but in terms of good science
we want to produce the best model we can, and that might be
the rigid-body-located structure from another dataset.
In particular the density for the ligand might be clearer
before overfitting with the low resolution data.
Even if the free-R set is not preserved for the new crystal,
R and R-free tend to diverge rapidly once any kind of
fitting with a low data/param is performed, so I think
the new structure must not have been refined much beyond
rigid body (and over-all B which is included in any kind
of refinement). And that choice may be well justified.
Ed
cdekker wrote:
Hi,
Your reply to the ccp4bb has confused me a bit. I am currently
refining a low res structure and realise that I don't know what to
expect for final R and Rfree - it is definitely not what most people
would publish. So the absolute values of R and Rfree are not telling
me much, the only gauge I have is that as long as both R and Rfree are
decreasing I am improving the model (and yes, at the moment that is
only rigid body refinement).
In your email reply you suggest that even though a refinement to
convergence that will lead to an increased Rfree (and lower R? - a
classic case of overfitting!) would be a better model than the
rigid-body-refined only model. This is what confuses me.
I can see your reasoning that starting with an atomic model to solve
low-res data can lead to this behaviour, but then should the solution
not be a modification of the starting model (maybe high B-factors?) to
compensate for the difference in resolution of model and data?
Carien
On 4 Jun 2007, at 19:38, Edward A Berry wrote:
Ibrahim M. Moustafa wrote:
The last question: In the same paper, for the complex structure R
and Rfree are equal (30%) is that an indication for improper
refinement in these published structure? I'd love to hear your
comments on that too.
Several times I solved low resolution structures using high resolution
models, and noticed that R-free increased during atomic positional
refinement. This could be expected from the assertion that after
refinement to convergence, the final values should not depend on
the starting point: If I had started with a crude model and refined
against low resolution data, Rfree would not have gone as low as the
high-resolution model, so if I start with the high resolution model
and refine, Rfree should worsen to the same value as the structure
converges to the same point.
Thinking about the main purpose of the Rfree statistic, in a very
real way this tells me that the model was better before this step
of refinement, and it would be better to omit the minimization step.
Perhaps this is what the authors did.
On the other hand it does not seem quite right submit a model that
has simply been rigid-body-refined against the data- I would prefer to
refine to convergence and submit the best model that can be supported
by the data alone, rather than a better model which is really the model
from a better dataset repositioned in the new crystal.
Ed
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