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[ccp4bb]: Re: [o-info] refinement problem
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"Yoder, Marilyn" wrote:
>
> Dear All,
>
> I'm having a refinement problem and would appreciate any suggestions.
>
> I have a well-refined, well-behaved 2.2 A MAD data set that the structure was
> solved with Se atoms to a crystallographic R of 21.2% and a free R of 25.2%
> (269 of a possible 271 amino acids, one phospholipid, 55 waters). The crystals
> are P21, a = 43.914 Å, b = 73.773 Å, c = 48.185 Å, b = 114.732º.
>
> My problem is in refining a higher resolution native data set, to 1.9 A. The
> data is fairly isomorphous with the MAD data set, P21, a = 43.718 Å, b = 73.184
> Å, c = 47.427 Å, b = help analysis data quality.
º. All data has been processed with denzo/scalepack
> (including the MAD data). For the high resolution refinement, I took the model
> from the MAD data, did a rigid body refinement, simulated annealing, and a
> B-individual refinement, manually rebuilt a little, ran a conjugate gradient
> minimization -- but my crystallographic R is stuck at about 27%, and the free R
> is about 31%. The 2fomfc maps calculated after this refinement are beautiful.
> Truly, without exaggeration. I can contour to about 2 sig and see holes in my
> aromatic residues, and water molecules are clearly visible. Carbonyl oxygen
> bulges are readily apparent throughout the molecule. I can automatically add
> about 100 water molecules, and my crystallographic R drops to 25.0% and a free R
> of 28.8%.
>
> I have tried numerous refinement strategies, including refining with and without
> the MAD data set, cutting the resolution to 50-2.2A, cutting the resolution to
> 10-1.9A, and nothing seems to get me beyond this 25% crystallographic R. The
> maps look, to me at least, way to good to have this high of an R. The B's
> refined with the MAD data and the native data are very comparable. OMIT maps
> showed no obvious problem with the model.
>
> My gut feeling is there is a problem with the data, but it looks good to me.
> I'm including the end two tables from the final scalepack run. The only thing I
> can think of with this data, is that it is a synchrotron data set, and during
> that data collection run there were considerable problems with the beam (it kept
> dumping prematurely).
>
> I would appreciate any comments or suggestions.
>
> Shell I/Sigma in resolution shells:
> Lower Upper % of reflections with I / Sigma less than
> limit limit 0 1 2 3 5 10 20 >20 total
> 50.00 4.09 2.7 4.3 5.1 5.5 6.0 7.9 12.8 85.6 98.4
> 4.09 3.25 0.2 0.6 1.1 2.4 4.2 8.6 19.1 80.8 99.9
> 3.25 2.84 1.2 2.5 4.8 6.6 11.4 21.2 46.5 53.4 100.0
> 2.84 2.58 2.2 4.8 7.8 11.1 18.7 36.8 100.0 0.0 100.0
> 2.58 2.39 3.2 7.3 11.9 17.3 26.4 51.5 99.9 0.0 99.9
> 2.39 2.25 4.3 10.3 18.1 24.4 35.5 70.0 99.8 0.0 99.8
> 2.25 2.14 4.6 11.6 21.8 31.5 48.8 99.6 99.6 0.0 99.6
> 2.14 2.05 7.2 16.2 27.5 37.6 56.2 97.9 97.9 0.0 97.9
> 2.05 1.97 9.5 19.2 29.5 40.4 58.3 94.5 94.5 0.0 94.5
> 1.97 1.90 8.2 20.7 33.3 44.5 66.3 88.4 88.4 0.0 88.4
> All hkl 4.3 9.7 16.0 22.0 33.0 57.4 75.6 22.3 97.9
>
> Summary of reflections intensities and R-factors by shells
> R linear = SUM ( ABS(I - <I>)) / SUM (I)
> R square = SUM ( (I - <I>) ** 2) / SUM (I ** 2)
> Chi**2 = SUM ( (I - <I>) ** 2) / (Error ** 2 * N / (N-1) ) )
> In all sums single measurements are excluded
>
> Shell Lower Upper Average Average Norm. Linear Square
> limit Angstrom I error stat. Chi**2 R-fac R-fac
> 50.00 4.09 2614.5 72.3 36.3 0.981 0.028 0.033
> 4.09 3.25 2132.1 61.3 34.0 1.295 0.037 0.040
> 3.25 2.84 935.9 42.2 23.6 1.243 0.056 0.055
> 2.84 2.58 565.2 40.9 20.0 0.991 0.075 0.071
> 2.58 2.39 382.9 35.8 19.4 1.008 0.102 0.093
> 2.39 2.25 305.4 36.2 20.9 1.106 0.134 0.121
> 2.25 2.14 253.9 41.8 22.6 1.011 0.193 0.000
> 2.14 2.05 199.1 38.8 23.7 1.027 0.196 0.170
> 2.05 1.97 174.9 37.4 24.4 1.024 0.207 0.177
> 1.97 1.90 138.4 37.9 24.0 0.979 0.243 0.221
> All reflections 787.7 44.7 24.9 1.072 0.062 0.044
>
> Thanks,
> Marilyn Yoder
>
> Marilyn D. Yoder yoderm@umkc.edu
> Division of Cell Biology and Biophysics phone: 816-235-1986
> School of Biological Sciences fax: 816-235-1503
> University of Missouri-Kansas City
> 5007 Rockhill Rd.
> Kansas City, MO 64110-2499
>
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IT is hard to say without more information.
And harder still as I dont know CNS diagnostics..
If you import scalepack data via the GUI you get some very useful plots
which help analyse data qualitty. Look at wilson plot ; cumulative
intensities, fall off of <F> and anisotropic falloff..
Again with REFMAC5 you get plots which might help diagnose scaling
problems etc.
Do you have 2 molecules in the asymmetric unit? Pseudo translation NCS
can increase R values greatly
And did you transfer the FreeR set from the first data set to the
second?
Maybe not essential but can help..
Eleanor