Dear Yu,
in the CORRECT.LP,
The I/Sig is very low for the resolution higher than 4.17 . If i were
you i probably cut the resolution around 4 Å not 2.8 Å. Because of the
I/sig and CC.
This explain probably the bad electron density. Because, you have not
strong information for the resolution higher than 4 Å.
Hope to help
Nicolas
Le 30/08/13 10:59, Yu Longjiang a écrit :
> Dear all,
>
> I recently collected a dataset of a membrane protein. I first
> processed the data with HKL2000 to 2.8A ( the diffraction limit) at
> the beamline, and then treated the data again with XDS, although I am
> not familiar with this program. the quality of this data seemed not
> good compared with the other data we have collected before , and the
> electron density was worse after molecular replacement and refinement.
>
>
> the log file of HKL2000 is too large, so I just paste last statistics
> as below, the CORRECT.LP is also attached.
>
>
>
> Shell Lower Upper Average Average Norm. Linear Square
> limit Angstrom I error stat. Chi**2 R-fac R-fac
> 50.00 7.59 526.8 6.8 4.4 2.442 0.047 0.048
> 7.59 6.03 54.4 2.5 2.4 1.727 0.112 0.104
> 6.03 5.27 26.6 3.5 3.5 1.289 0.197 0.183
> 5.27 4.79 27.4 4.9 4.9 1.201 0.231 0.228
> 4.79 4.44 28.2 6.6 6.6 1.083 0.265 0.282
> 4.44 4.18 28.2 8.0 8.0 0.939 0.304 0.357
> 4.18 3.97 28.1 9.3 9.3 0.835 0.343 0.454
> 3.97 3.80 28.6 10.4 10.4 0.802 0.366 0.501
> 3.80 3.65 29.9 11.1 11.1 0.815 0.374 0.529
> 3.65 3.53 30.0 11.7 11.6 0.824 0.384 0.550
> 3.53 3.42 30.2 12.1 12.0 0.812 0.386 0.557
> 3.42 3.32 29.8 12.2 12.2 0.817 0.389 0.565
> 3.32 3.23 29.3 12.3 12.3 0.797 0.387 0.558
> 3.23 3.15 28.4 12.3 12.3 0.802 0.387 0.559
> 3.15 3.08 27.5 12.2 12.2 0.777 0.383 0.556
> 3.08 3.02 26.7 12.0 12.0 0.762 0.383 0.551
> 3.02 2.96 25.6 11.8 11.7 0.773 0.387 0.562
> 2.96 2.90 25.1 11.7 11.6 0.734 0.379 0.543
> 2.90 2.85 24.0 11.5 11.5 0.731 0.384 0.548
> 2.85 2.80 23.7 11.5 11.5 0.754 0.383 0.551
> All reflections 56.0 9.5 9.4 1.364 0.100 0.056
>
>
>
> Any suggestion and comment about this dataset is greatly appreciated.
> Thanks a lot!
>
>
>
> YU
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