[phenixbb] Global metrics for Ramachandran quality beyond %outliers?
nechols at lbl.gov
Thu Feb 5 10:56:39 PST 2015
The %favored is also important - if you only have 1% outliers but 20% are
"allowed", that's still not a very realistic structure. On the other hand,
it is entirely possible to generate a model that has 98% favored but an
equally unrealistic distribution, if you try to make the plot too "tight"
(i.e. forcing residues into particular sub-regions of favored). But there
isn't any metric for this that I'm aware of - it's very qualitative and
based entirely on visual intuition.
On Thu, Feb 5, 2015 at 10:46 AM, Shane Caldwell <shane.caldwell17 at gmail.com>
> I'm making a new thread because it's off the topic, but I have a question
> in response to this point
> > [Doggy structure improved, as shown by how] The Ramachandran plot
> This is interesting to me - other than eyeballing the plot, are there any
> quantitative metrics of Ramachandran distribution quality? At low-res or
> when refining a bunch of structures side-by-side it could be an additional
> indicator of quality of the model, without requiring having to inspect the
> plot. Of course manual inspection is always important in the end, but in
> early stages a global measure of spread could help guide refinement.
> I've seen %outliers used for this purpose, but that ignores that while a
> residue can be "allowed" it can still be far from a statistically likely
> conformation. From what I've seen, some users only consult Ramachandran to
> tweak residues until they pop into the "allowed" regions and stop there,
> which isn't the same as globally improving the geometry.
> Interested to hear thoughts (or it it's already in use, pointing me in the
> right direction!),
> Shane Caldwell
> McGill University
> On Thu, Feb 5, 2015 at 5:06 AM, Andreas Förster <docandreas at gmail.com>
>> Dear Almudena,
>> I promise not to make a habit of advertising other programs on the Phenix
>> mailing list, but just once I would like to encourage you (and the
>> community) to try all the tools at your disposal.
>> Different refinement programs have different strength and weaknesses.
>> Secondary-structure restraints in Phenix are great for low-resolution data,
>> but so is jelly-body refinement in Refmac. A dodgy 3.2 Å structure I'm
>> currently working on was improved dramatically by Buster-TNT. The
>> Ramachandran plot tightened, and R free plunged by four percentage points.
>> On 05/02/2015 10:44, Almudena Ponce Salvatierra wrote:
>>> Dear all,
>>> I am refining my structure (data at 3 A), with a model that is complete.
>>> However the Rs values are: R work= 0.25 and Rfree= 0.32. I have read
>>> "Improved target weight optimization in phenix.refine" (In the
>>> computational crystallographic newsletter 2011) and what I understand is
>>> that just by marking the boxes "improve xray/stereochemistry weight" and
>>> "improve xray/adp weight" it should work... giving me the best possible
>>> I'm refining individual coordinates, occupancies, b-factors (isotropic
>>> for all atoms), TLS, and using secondary structure restraints, automatic
>>> ligand linking and experimental phases restraints. Also, I chose this
>>> strategy because I have finished building the structure and according to
>>> some of the suggestions in "towards automated crystallographic structure
>>> refinement with phenix.refine".
>>> I am actually quite confused and don't know what to think... is it a
>>> matter of the weights? is it only that this is as good as it gets?
>>> Any suggestions and comments are welcome.
>>> Thanks a lot in advance,
>>> Almudena Ponce-Salvatierra
>>> Macromolecular crystallography and Nucleic acid chemistry
>>> Max Planck Institute for Biophysical Chemistry
>>> Am Fassberg 11 37077 Göttingen
>>> phenixbb mailing list
>>> phenixbb at phenix-online.org
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