[phenixbb] Question about structure quality

Pavel Afonine pafonine at lbl.gov
Tue Apr 5 14:22:48 PDT 2011

I agree with Ed - it's a matter of balance!

Also, it's good to realize that at low resolution even if your starting 
model has zero Ramachandran outliers it will most likely has a lot of 
outliers after a quick refinement without Ramachandran restrains - I've 
done this test for all low resolution structures in PDB. This is simply 
because the density at that resolution is not informative enough to keep 
the residues within the allowed Ramachgandran plot areas, and the other 
geometry restraints do not have that information either. So I guess at 
that low resolution the Ramachandran plot is rather the tool to get your 
model physically correct, rather than a validation tool (simply because 
you don't have much choice). Of course, keeping eye on the map and model 
never hurts, especially in this case.


On 4/5/11 2:11 PM, Edward A. Berry wrote:
> After fixing the Ramachandran with restraints, I would recommend refining
> several cycles without restraints before depositing to see how many
> outliers stay in the allowed region.  The ramachandran is often used
> as a measure of model quality, and you might just fool the end user
> into using your structure instead of a better model which
> has slightly worse ramachandran but much better than yours would be
> without restraints.
> eab
> Pavel Afonine wrote:
>> Hi Jason,
>>> The Ramachandran statistics are poor; I've seen worse published, but
>>> it would be wise to fix these. I'm assuming you don't have a
>>> high-resolution structure that you can use as a reference model - this
>>> is usually the best option. Otherwise, adding Ramachandran restraints
>>> will probably help a lot, but you should first fix all outliers
>>> manually in Coot (also applying real-space refinement with Coot's
>>> Ramachandran restraints turned on), as the default potential is very
>>> tight and can pull residues the wrong way if they're starting from a
>>> very bad position.
>> - Often using Ramachandran restraints fixes the problem right away, so I
>> would probably do it first, and then walk through the list of outliers
>> that you had before refinement run with Ramachandran restraints, and see
>> *how* these outliers were fixed. Nat's suggestion should work too but
>> might require more up-front work.
>> - Run refinement with weights optimization (optimize_wxc=true);
>> - Use NCS if available;
>> - Secondary structure restraints should definitely help, but:
>> -- you need to have secondary structure well defined in your input
>> model if you want phenix.refine to pick it up automatically (and
>> correctly), or alternatively
>> -- define it manually in a parameter file and supply to phenix.refine.
>> Pavel.
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