[phenixbb] refinement question
PAfonine at lbl.gov
Fri Jun 26 14:44:59 PDT 2009
yes, we discussed it with Engin a few months ago, agreeing that
automatic NCS detection in phenix.refine should be enhanced by making
use of maps (for example), and automatic taking care of outliers.
On 6/26/09 2:38 PM, Maia Cherney wrote:
> Hi Pavel,
> Thank you for your letter. You mentioned "unless it is highly systematic
> and consistent observation .."
> Yes, it is highly systematic and consistent for these data. I continue
> to refine this structure with both strategies (with and without ncs).
> Weights optimization keeps the same difference between Rfee factors
> (improves both). I liked the suggestion by Engin to keep the ncs, but
> remove some offending residues from the ncs restraints. (There are such
> residues that have slightly different conformations and they get moved
> out of density by the ncs restraints).
> Pavel Afonine wrote:
>> Hi Maia,
>> I would add a couple of comments too:
>>> I am wondering why the ncs refinement gives me a better Rfree (21.0%)
>> Because by using NCS you added some "observations", therefore you
>> improved the data-to-parameters ratio, which in turn reduced degree of
>> The fact that the R-factor dropped (and not increased) probably suggests
>> that you selected NCS groups correctly.
>>> the ncs refinement gives me a better Rfree (21.0%)
>>> than without ncs (21.7%).
>> Here is another stream of thought...
>> The target for restrained coordinate (and similarly for B-factor)
>> refinement looks like this (in phenix.refine):
>> T_total = wxc_scale * wxc * T_xray + wc * T_geometry
>> where the relative target weight wxc is determined as wxc ~ ratio of
>> gradient's norms:
>> Brünger, A.T., Karplus, M. & Petsko, G.A. (1989). Acta Cryst. A45,
>> 50-61. "Crystallographic refinement by simulated annealing: application
>> to crambin"
>> Brünger, A.T. (1992). Nature (London), 355, 472-474. "The free R value:
>> a novel statistical quantity for assessing the accuracy of crystal
>> Adams, P.D., Pannu, N.S., Read, R.J. & Brünger, A.T. (1997). Proc. Natl.
>> Acad. Sci. 94, 5018-5023. "Cross-validated maximum likelihood enhances
>> crystallographic simulated annealing refinement"
>> Before wxc scale is computed, the structure is subject of a short
>> molecular dynamics run - this is where the random component comes into
>> Now, having said this, we know that if you run, for example, 100
>> identical phenix.refine runs, where the only difference between each run
>> is the random seed, you will get 100 slightly different refinement
>> results. The spread in R-factors depends on resolution, and if I
>> remember correctly, for a structure at ~2A resolution I was getting
>> delta_R~ from 0.1 to 2%. It can be higher at lower resolution, and
>> smaller at higher resolution.
>> The NCS term goes into T_geometry, which in turn means that it changes
>> (somehow) the weight. This may explain the difference in R-factors and,
>> I would say, the one less then 1% I would consider insignificant (unless
>> it is highly systematic and consistent observation, and unless it is not
>> made weight independent).
>> To make it less arbitrary I would suggest to run two refinement jobs
>> using "optimize_wxc=true optimize_wxu=true", one with NCS and the other
>> one without using NCS. I'm sure I suggested this a month or two ago.
>> phenixbb mailing list
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