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
________________________________
From: CCP4 bulletin board [mailto:CCP4BB@JISCMAIL.AC.UK] On Behalf Of
Robert Nicholls
Sent: Friday, April 27, 2012 9:25 AM
To: CCP4BB@JISCMAIL.AC.UK
Subject: Re: [ccp4bb] Refmac and sigma value
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:
Hi, Alex:
> Which sigma do you mean?
The one for automatic weight, not for Jelly-body refinement.
I did not turn the "Jelly-body refinement" on.
Thanks
Ros
On Thu, Apr 26, 2012 at 4:08 PM, aaleshin
<aales...@burnham.org> 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
