On Tue, Apr 5, 2011 at 5:22 PM, Pavel Afonine <pafonine@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.

_______________________________________________
phenixbb mailing list
phenixbb@phenix-online.org
http://phenix-online.org/mailman/listinfo/phenixbb

_______________________________________________
phenixbb mailing list
phenixbb@phenix-online.org
http://phenix-online.org/mailman/listinfo/phenixbb

_______________________________________________
phenixbb mailing list
phenixbb@phenix-online.org
http://phenix-online.org/mailman/listinfo/phenixbb

======================

Jason

Structural Biology Department

University of Pittsburgh

======================