> (2). Why RMS-Z(bonds) should be lower than that for low resolution data
and higher for high resolution? Or why high-resolution can allows more
outliers?
Imagine torsion angle refinement only, at low resolution: The bond
lengths are fixed to target values, their rmsd will be zero.
Imagine free refinement at atomic resolution: the rmsd will approach the
established variance/sigma for the (small molecule/peptide) target values.
In between it depends on the restraint weights (or overall: matrix weight)
that are needed to keep the model within bounds of plausible
stereochemistry.
The less data, the more restraint weight, almost always.
REFMAC to my knowledge uses(ed) the same rmsd target values (close to
target variance or somewhat less) for all resolutions. Garib?
The LLfree or Rfree minimization as Ian mentioned is the correct way to go,
and I
found that - at least until recently - the REFMAC default B restraints
are too tight (Garib?), at least for my structures and around 2A (depends on
molecule).
So there is no fixed recipe or target - one needs to try and find values
appropriate to the specific structure. At convergence of the refinement
of course.
Now, whether the differences between differently restrained
models are *significant* is an entire story in itself...
BR
Thanks again for that!
Best Regards, Hailiang
> To give credit where it is due I should perhaps have explained that
> the formula for RMS-Z(bonds) that I quoted was derived from an
> analysis of re-refinements from the PDB-REDO project
> (http://www.cmbi.ru.nl/pdb_redo), not from the PDB itself. PDB-REDO
> itself uses the LLfree optimisation method that I referred to briefly.
>
> Cheers
>
> -- Ian
>
> On Tue, Sep 21, 2010 at 9:42 PM, Ian Tickle <[log in to unmask]> wrote:
>> Hi Hailiang
>>
>> The short answer is that the optimal X-ray weighting factor minimises
>> Rfree, or better -LLfree.
>>
>> However this is tricky to carry out in practice since it means you
>> have to run several jobs adjusting the weight manually each time to
>> find the optimum. Also, ideally the same procedure should be
>> performed for the B weighting factor, but this adds yet another
>> dimension to the problem, and I suspect most people just go with the
>> default B weighting factor (though strictly speaking its optimum value
>> is resolution-dependent).
>>
>> Another somewhat easier way in practice is to adjust the weight to get
>> a particular target value for RMS-Z(bonds), however you still have the
>> problem of choosing that optimal target value. The median value of
>> RMS-Z(bonds) over the whole PDB is about 0.5 so you could use that for
>> everything, though ideally the value should be lower than that for low
>> resolution data and higher for high resolution. I use this
>> empirically-derived formula obtained by fitting the RMS-Z(bonds)
>> values in the PDB to a straight line with resolution:
>>
>> RMS-Z(bonds) = 0.85 - 0.146*resolution
>>
>> though this is probably valid only in the resolution range 3.5 to 1
>> Ang, since the number of structures outside that range is too small to
>> get a meaningful fit. I'm sure others have different opinions on
>> this.
>>
>> One problem with the 'WEIGHT MATRIX' value is that the optimum is
>> resolution-dependent, i.e. the optimum value for a low-resolution
>> dataset is quite different from that for a high-resolution one. The
>> 'WEIGHT AUTO' option is much better in this respect as the optimum
>> value is much less resolution-independent. The default weight value
>> for 'WEIGHT AUTO' is 10 but I find this much too high, and I always
>> reset it to 'WEIGHT AUTO 2.5' as a first attempt.
>>
>> Cheers
>>
>> -- Ian
>>
>> On Tue, Sep 21, 2010 at 8:54 PM, Hailiang Zhang <[log in to unmask]>
>> wrote:
>>> Hi all:
>>>
>>> I have a question about deciding an ideal "Weight matrix" value in
>>> REFMAC.
>>> When I change it from 0.1 to 0.001, the bond distance rmsd changes from
>>> 0.075 to 0.008, while the R changes from 0.26 to 0.33 (resolution
>>> 3.2A).
>>> Now I am not sure what is the best balance based on these numbers. Are
>>> there any references or empirical values? Thanks!
>>>
>>> Best Regards, Hailiang
>>>
>>
>
>
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