[phenixbb] Question about structure quality

Jason phenix.upitt at gmail.com
Tue Apr 5 17:20:05 PDT 2011


Thanks everyone, ramachandran restrain does bring the ramachandran favored
to 91%. However, it does does improve the rotamer outlier (even a little
worse). After manually adjust the outliers in coot, which took me ~4hours
for one round, the rotamer outlier decreases to ~9%, which is much better. I
will keep working to see if there is more room for such improvement.


On Tue, Apr 5, 2011 at 5:22 PM, Pavel Afonine <pafonine at lbl.gov> wrote:

> 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.
>
> Pavel.
>
>
>
> 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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>>>
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-- 
======================
Jason
Structural Biology Department
University of Pittsburgh
======================
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