[phenixbb] Advice on final refinement of twinned R3 structure: DETWIN and ML-target vs twin_lsq_sq target

Bjørn Panyella Pedersen bjopp at msg.ucsf.edu
Mon Sep 10 10:44:58 PDT 2012

Dear list
I would like some advice on how to do the final refinement of a twinned 
I have a 3.0A structure (sg R3) which is twinned. I have collected ~50 
datasets and the estimated twin-fraction varies from 0.2 to 0.45 based 
on phenix.xtriage analysis (britton plot etc). The structure could only 
be solved by experimental phasing using _detwinned_ datasets (detwinned 
by the ccp4 program DETWIN).
Refinement of the model was initially done using my highest resolution 
_detwinned_ dataset (3.0A, britton_alpha:0.21) and a ML target in 
phenix.refine. Lately I have switched to th twin_lsq_f target and 
refined using the 'unmodified'/twinned dataset.

1. I have tried systematically to detwin the dataset with different 
twin-fractions and then refine using the ML-target and my best 
refinements comes using an alpha of 0.2 (see attached figure). This fits 
the Britton plot etc.

2. xtriage estimated the twin-fraction to by ~0.21, but using 
twin_lsq_f, phenix.refine now gets alpha to be 0.31. This seems like a 
large increase to me?

3. Using the manually detwinned dataset and a ML-target gives better 
R-factors than using the twin_lsq_f target (see attached figure).

Bottom line:
How should I report/deposit this structure:
A. Should I use the manually detwinned data and an ML-target to get a 
model that explains the data best (lowest R-factors). And deposit my 
structure with modified (i.e DETWINNED) structure factors.
I fear that people would react strongly to the deposition of modified 
F_obs in the pdb. I could deposit both twinned and detwinned 
structure-factores but this might also confuse?

B. Should I use the twin_lsq_f target and accept that my deposited model 
is not as good as I know it could be. And deposit my structure with the 
real (i.e TWINNED) structure factors.

C. Something I'm not aware of means that refinement using the ML-target 
is not allowed on detwinned datasets, causing me to have artificially 
low R-factors.

I hope I'm not missing something basic here.:)
Thank for any advice, pointers and ideas!


Bjørn Panyella Pedersen, PhD

Macromolecular Structure Group
Dept. of Biochemistry and Biophysics
University of California, San Francisco
MC2240, 600 - 16th Street S414
San Francisco, CA 94158-2517

Phone: +1 415-476-3937
E-mail: bjopp at msg.ucsf.edu
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