Print

Print


Dear Randy,

thanks for your comment - a good point with the likelihood target 
estimated from E-values! So, in principle, there shouldn't be any 
difference in maximum-likelihood refinement using sharpened data or not. 
However, for curiosity, in one case at 4.3 A resolution and a sharpening 
B-factor of ~100 A**2, I compared ML refinement against the sharpened 
data with ML refinement against the original data and subsequent map 
sharpening: the R-factors were almost identical, and so were the 
electron density maps in most places. But in a some places, the maps 
were slightly different, with slightly less (!) model-bias and slightly 
clearer densities for the refinement against sharpened data. But those 
judgements were very subjective, and since a "true" structure at really 
high resolution is not available, I never could quantify this. Either, 
this was only anecdotal evidence, or there is still room for improvement 
in existing ML refinement programs.

Best regards,

Dirk.

Am 28.02.11 11:40, schrieb Randy Read:
> Hi,
>
> I'm on Garib's side here.  The way the maximum likelihood targets work, the variances are defined relative to the average intensity in a resolution shell, so if you change the falloff the variances will change in the same way.  In fact, one way to implement maximum likelihood refinement is in terms of E-values, from which the falloff has been removed.  If your B-factors didn't run into hard limits (which, as Garib points out, they will when you make the data non-physical) you would end up with the same model if you refined against sharpened data, except the B-factors would be lower.  The other thing that will change if you sharpen the data is that the R-factors will be higher, because the poorly-fit higher-resolution terms will contribute more to the sums.  And that's probably not what you want when you might already have a hard time getting a low resolution structure past the freeR police!
>
> This is a case where intuition can lead you astray.  Intuition might suggest that, if you sharpen the data, the refinement program should pay more attention to fitting the high resolution detail, but the likelihood target doesn't look at the data the same way you do when you look at a map.  The fact that you can define the target in terms of E-values means that, if your model and data are both good, the likelihood target can be thought of as sharpening the data anyway.
>
> Best wishes,
>
> Randy Read
>
> On 28 Feb 2011, at 09:02, Dirk Kostrewa wrote:
>
>> Dear CCP4ers,
>>
>> I really would sharpen the structure factors, not only the electron density maps. The simple reason is: if sharpening emphasizes enough information at higher resolution to help interpreting the electron density maps, refinement will also benefit from this information.
>> Of course, the mean B-factor of the refined structure will be lower by the sharpening B-factor, but since B-factor sharpening is usually done with lower resolution data, the Wilson B-factor is usually very high, and thus far, I didn't run into problems with B-factors crashing at the lower limit.
>> The sharpening B-factor can easily reach values in the -100s A**2, not only -10 to -50 A**2. Axel Brunger has published several papers about how to estimate a good sharpening B-factor (a recent one with references is Brunger et al. Acta Cryst D65, 128-133). He usually describes map sharpening, but B-factor sharpening of structure factors seems to be done routinely for virus structures in Steve Harrisons lab.
>>
>> One word of caution: the B-factor sharpening should be correctly described not only in the publication but also in the PDB deposition (if refinement was done against sharpened structure factors, the refinement statistics can only be reproduced using these structure factors). The original structure factors can be easily reproduced by applying back the negative sharpening B-factor.
>>
>> Best regards,
>>
>> Dirk.
>>
>> Am 26.02.11 01:09, schrieb Garib N Murshudov:
>>> I would not sharpen structure factors before refinement. It may cause problems with B value refinement (a lot of B values may stuck around 2 or minimum B). One must remember that not all atoms in crystal have same Bvalue. There is a distribution of Bvalues.
>>>
>>> However maps can be sharpened after refinement. It can be done directly in coot (I hope this version of coot is now widely available). Or if you are using refmac for refinement you can use:
>>>
>>> mapc sharpen   #  regularised map sharpening. Bvalues and regularisation parameters are calculated automatically
>>>
>>> or
>>>
>>> mapc sharpen<Bvalue>   # regularised map sharpening with specified Bvalue
>>>
>>> or
>>>
>>> mapc sharpen<Bvalue>
>>> mapc sharpen alpha<value=0.1>    #  regularisation paramater. alpha=0 is simple sharpening.
>>>
>>>
>>> I am sure other programs have similar options. (I know CNS has and it has been used successfully by many people)
>>>
>>> regards
>>> Garib
>>>
>>> P.S. These options available from refmac v5.6 available from; www.ysbl.york.ac.uk/refmac/data/refmac_experimental/refmac5.6_linux.tar.gz
>>>
>>>
>>>
>>> On 25 Feb 2011, at 23:57, Dima Klenchin wrote:
>>>
>>>> At 05:39 PM 2/25/2011, Pete Meyer wrote:
>>>>>> Or could anyone suggest a program that would be of help?
>>>>> CAD scaling with a scale factor of 1.0 and negative B-factor (isotropic or anisotropic) should do the trick.  I haven't had much luck with density sharpening (at least at ~4-5 Angstroms), but others have apparently had some success with it.
>>>> Alternatively, CCP4i task Run FFT does the job:
>>>>
>>>> 1. Take MTZ from Refmac output
>>>> 2. Run FFT to create simple map with SigmaA-weighted phases (i.e., PHWT label).
>>>> 3. In Infrequently used options, "Apply B-factor scaling to F1", specify negative B-factor scaling value, usually within -10 to -50.
>>>>
>>>> - Dima
>> -- 
>>
>> *******************************************************
>> Dirk Kostrewa
>> Gene Center Munich, A5.07
>> Department of Biochemistry
>> Ludwig-Maximilians-Universität München
>> Feodor-Lynen-Str. 25
>> D-81377 Munich
>> Germany
>> Phone: 	+49-89-2180-76845
>> Fax: 	+49-89-2180-76999
>> E-mail:	[log in to unmask]
>> WWW:	www.genzentrum.lmu.de
>> *******************************************************
> ------
> Randy J. Read
> Department of Haematology, University of Cambridge
> Cambridge Institute for Medical Research      Tel: + 44 1223 336500
> Wellcome Trust/MRC Building                   Fax: + 44 1223 336827
> Hills Road                                    E-mail: [log in to unmask]
> Cambridge CB2 0XY, U.K.                       www-structmed.cimr.cam.ac.uk

-- 

*******************************************************
Dirk Kostrewa
Gene Center Munich, A5.07
Department of Biochemistry
Ludwig-Maximilians-Universität München
Feodor-Lynen-Str. 25
D-81377 Munich
Germany
Phone: 	+49-89-2180-76845
Fax: 	+49-89-2180-76999
E-mail:	[log in to unmask]
WWW:	www.genzentrum.lmu.de
*******************************************************