It all will depend on the resolution. At low
resolution, relaxing the geometric restraints will allow the refinement program
to tweak the model such that the difference between Fobs and Fcalc is minimized,
but not that the model gets closer to the "truth". I once struggled for a long
time with a 3.5Åish data set with a protein where the most important
feature was a rather flexible loop. It was before maximum
likelyhood methods and Rfrees and the only way I could get rid of
the model bias was to use extremely tight geometric restraints.
The Rfactor would go up, but suddenly the electron density maps would
no longer accept incorrectly placed side chains and new features, not present in
the model, would appear.
So my advice: at low resolution use as tight restraints
as possible and monitor with Rfree if you are going in the right direction. At
high or very high resolution, you can follow what your diffraction data tells
you. In fact many very high resolution structures (< 1.5 Å) have higher
rmsd's for bond lenghts and angles as medium resolution structures. However, at
medium or low resolution there is not enough data to justify to relax the
geometric restraints too much.
Best regards,
Herman
Hi Uma,
Altering sigma affects the strength of geometry restraints throughout the
model - bonds, angles, etc. Choosing a very low sigma will cause geometry to
be more tightly restrained towards "ideal" values, which is why you
observe improvements in Coot validation. Note that strengthening the
geometry weight causes the observations (data) to be less influential in
refinement. The "risk" of this is that your model may no longer
appropriately/optimally describe your data. You can assess this locally by
manual inspection of the electron density, and globally by considering overall
refinement statistics (as reported at the bottom of the Refmac5 log file).
Ideally, you want your model to both describe the data and have reasonable
geometry.
Regards
Rob
On 26 Apr 2012, at 21:26, Uma Ratu wrote:
On Thu, Apr 26, 2012 at 4:08 PM, aaleshin
<[log in to unmask]> wrote:
Hi Uma,
Which sigma do you mean? The one for
Jelly-body refinement?
J-B sigma=0.01 means very small fraction of the
gradient will be used in each step. It is used usually with very low
resolution (less then 3A)
Alex
On Apr 26, 2012, at 11:38 AM, Uma Ratu
wrote:
>
> Dear All:
>
> I use Refmac5 to
refine my structure model.
>
> When I set the sigma value to
0.3 (as recommended from tutorial), the resulted model has many red-bars
by coot validation (geometry, rotamer, especially, Temp
Facotr).
>
> I then lower the sigma value to 0.1, the resulted
model is much improved by coot validation.
>
> I then lower
the sigma value to 0.01, the resulted model is almost perfect, by coot
validation and Molprobity.
>
> My question is: what is the
risk for very low value sigma value?
>
> Thank you for your
advice
>
> Ros
