What if you have one domain with many B-factors aroun 70 and above, and another
domain with B-factors around 20? The atoms with high B-factor will make
essentially no contribution to the intensty of spots beyond 3 A, and so have no
effect on the slope of the Wilson plot byond that. But they will contribute
mightily to the average atomic B. Or so it seems to me.
eab
On 03/12/2019 04:39 PM, DUMAS Philippe (IGBMC) wrote:
Le Mardi 12 Mars 2019 19:55 CET, Dale Tronrud <de...@daletronrud.com> a écrit:
Dale
Good to have the opportunity of going back to the crystallography of the
fifties in these post-modern times...
There is an essential argumentation that should be recalled. The only reason
for the fact that one ignores low-resolution data in a Wilson plot is that a
Wilson plot is based precisely upon Wilson statistics, which assumes that the
atoms are cast randomly in the unit cell.
This assumption obviously does not hold at low resolution and there is no
reason to obtain a straight line that stems from the latter assumption.
Therefore, I do not think one may say that a Wilson plot tends to ignore atoms
with high B values.
Consequence: if one has data at rather low resolution, a Wilson plot is
inherently inaccurate, but if one has data at very high resolution, the Wilson
plot should give a very decent estimate of the average B and any significant
discrepancy should ring the bell.
Philippe Dumas
The numeric average of the B factors of the atoms in your model only
roughly corresponds to the calculation of the Wilson B. While I always
expect the average B to be larger than the Wilson B, how much larger
depends on many factors, making it a fairly useless criteria for judging
the correctness of a model.
While it is pretty easy to understand the average of the B factors in
your model, the Wilson B is more difficult. Since it is calculated by
drawing a line though the (Log of) the intensity of your structure
factors as a function of the square of sin theta over lambda, it is
rather removed from the atomic B factors. When drawing the line the low
resolution data are ignored because those data don't fall on a straight
line, and this means that the large B factor atoms in your model are
ignored in the Wilson B calculation.
The Wilson B is (sort of) a weighted average of the B factors of your
model, with the smallest B's given the largest weight. The actually
weighting factor is a little obscure so I don't know how to simulate it
to adjust the averaging of atomic B's to come out a match. The easiest
way to compare your model to the Wilson B is to calculate structure
factors from it and calculate the Calculated Wilson B. No one does this
because it will always come out as a match. If your calculated Wilson B
doesn't match the observed Wilson B your R values are guaranteed to be
unacceptable and your refinement program will have to be malfunctioning
to create such a model.
If all the B factors in your model are equal to each other, your
refined model will have an average B that matches the Wilson B, because
weighting doesn't matter in that situation. If you allow the B's to
vary, the difference between the average and the Wilson B will depend on
how high of an individual B factor you are willing to tolerate. If you
are a person who likes to build chain into weak loops of density, or
build side chains where there is little to no density, then your average
B will be much larger than the Wilson B. This does not mean there is an
error, it is simply a reflection of the Wilson B's insensitivity to
atoms with large B.
I do not believe comparing the average B to the Wilson B has any
utility at all.
Dale Tronrud
On 3/12/2019 11:34 AM, Eze Chivi wrote:
Dear CCP4bb community,
The average B-factor (calculated from model) of my protein is 65,
whereas the Wilson B is 52. I have read in this BB that "it is expected
that average B does not deviate strongly from the Wilson B". How I can
evaluate if the difference calculated for my data is razonable or not?
Thank you in advance
Ezequiel
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