On 10-10-28 04:09 PM, Ethan Merritt wrote:
This I can answer based on experience.  One can take the coordinates from a 
structure
refined at near atomic resolution (~1.0A), including multiple conformations,
partial occupancy waters, etc, and use it to calculate R factors against a lower
resolution (say 2.5A) data set collected from an isomorphous crystal.  The
R factors from this total-rigid-body replacement will be better than anything 
you
could get from refinement against the lower resolution data.  In fact, 
refinement
from this starting point will just make the R factors worse.

What this tells us is that the crystallographic residuals can recognize a
better model when they see one. But our refinement programs are not good
enough to produce such a better model in the first place. Worsr, they are not
even good enough to avoid degrading the model.

That's essentially the same thing Bart said, perhaps a little more pessimistic 
:-)

        cheers,

                Ethan

Not pessimistic at all, just realistic and perhaps even optimistic for methods developers as apparently there is still quite a bit of progress that can be made by improving the "search strategy" during refinement.

During manual refinement I normally tell students not to bother about translating/rotating/torsioning atoms by just a tiny bit to make it fit better. Likewise there is no point in moving atoms a little bit to correct a distorted bond or bond length. If it needed to move that little bit the refinement program would have done it for you. Look for discreet errors in the problematic residue or its neighbors: peptide flips, 120 degree changes in side chain dihedrals, etc. If you can find and fix one of those errors a lot of the stereochemical distortions and non-ideal fit to density surrounding that residue will suddenly disappear as well.

The benefit of high resolution is that it is much easier to pick up and fix such errors (or not make them in the first place)

Bart

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Bart Hazes (Associate Professor)
Dept. of Medical Microbiology&  Immunology
University of Alberta
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