On 11/25/2014 01:41 PM, Tim Gruene wrote:
Hi Ed,

it is an easy excercise to show that theory (according to "by
definition") and reality greatly diverge - refinement is too complex to
get back to exactly the same structure. Maybe because one often does not
reach convergence, no matter how  many cycles of refinement you run.

Yes- i was able to convince myself of this.

I took a structure which I considered was refined to convergencee.
I didn't see any way to refine with no free set in phenix, even with
least-squares target function, so I refined against a newly chosen free set,
should test the same principle. Turned off HQN flips and real space refinement.
After 2 rounds of 3 macrocycles each of individual ADP and XYZ refinement,
comparing the structure with the original gave all-atom RMSD of 0.0540 A,
maximum displacement 1.0161 A. Should be within radius of convergence, right?

So then I returned to the original free set in order to let it refine back
to the original position. R-free started out equal to R but soon increased to
approximately the original value., 0.2011 0.2256 vs original 0.2036 0.2278
(this is a 1.8A structure). So far so good.

But looking at RMSD compared to original, the numbers never decreased,
they continue to increase with every cycle. The structure is not returning to 
the
original but finding equally good solutions in the neighborhood. I guess it is
meandering about an essentially flat plateau (or better, flat-bottomed valley).
Does not reach convergence, no matter how  many cycles of refinement you run.
eab



Best,
Tim

On 11/25/2014 07:29 PM, Edward A. Berry wrote:
provided the jiggling keeps the structure inside the convergence
radius of refinement, then by definition the refinement will produce
the same result irrespective of the starting point (i.e. jiggled or
not).  If the jiggling takes the structure outside the radius of
convergence then the original structure will not be retrievable
without manual rebuilding: I'm assuming that's not the goal here.


I actually agree with this, but an R-free purist might argue that you
have to get outside of radius of convergence to eliminate R-free bias.
Otherwise, by definition, "you will just refine back to the same old
biased structure!".
   (but you have shown that the conventional .2A rms is within radius of
convergence)

In fact Dale's concern about low-res reflections could be put in terms
of radius of convergence and false minima.
Moving a lot of atoms by .2 A will have a significant effect on the
phase of a 2A reflection, but almost no effect on a 20A reflection. Say
you have refined against all the low resolution reflections, and got a
structure that fits better than it should because it is fitting the
noise in the free reflections. Now take away the free reflections and
continue to refine. It will drop into the nearest local minimum, which
since it is near the solution with all reflections, will still give
artificially low R-free.  Jiggling by 0.2 A will have no effect because
the local minima are are extremely broad and shallow, as far as the
low-res reflections go.

But then you could say that since any local minima are so broad, all
structures that are even slightly reasonable, (including the correct
one) will be within radius of convergence of the same minimum as far as
the low-res reflections are concerned. The nearest false minimum
involves moving atoms by 5-10 A, so within reason the convergence point
will be completely independent of the starting structure. Presumably
this is why Phenix rigid body refinement starts out at ultra-low
resolution: to increase the radius of convergence. From that
perspective, rather than being the worrisome part, the low-resolution is
the region where we can assume Ian's assumption is correct.

What about another experiment, which I think we've discussed before.
Take a structure refined to convergence with a pristine free set. Now
refine to convergence against all the data. The purist will say that the
free set is hopelessly corrupted. And sure enough when we take that
structure and calculate free-R with the original set, R-free is same as
R-work within statistical significance.  But- I guess adding the extra
5% reflections will not change any atomic position by more than 0.2 A
(maybe 0.02A), and so we are still well within radius of convergence of
the original unbiased structure. Refining against the original working
set will give back that unbiased structure, and Rfree will return to it
original value.

This suggest, if the only purpose of Rfree is to get a number to deposit
with the pdb (which it is not), you should first solve your structure
using all the data, fitting the noise; then exclude a free set and back
off on fitting the noise of it to get the R-free.  The only problem
would be that during the refinement without guidance of R-free, you may
have engaged in some practice that hurt the structure so much that it
ends up out of RoC of the well-refined structure. Not because you were
fitting the noise (anyway you are fitting the noise in your 95% working
set) but because you would not have been warned that some procedure was
not helping.

Very provocative discussion!
eab


On 11/25/2014 11:03 AM, Ian Tickle wrote:
Dear All

I'd like to raise the question again of whether any of this 'jiggling'
(i.e. addition of random noise to the co-ordinates) is really
necessary anyway, notwithstanding Dale's valid point that even if it
were necessary, jiggling in its present incarnation is unlikely to
work because it's unlikely to erase the influence of low res. reflexions.

My claim is that jiggling is completely unnecessary, because I
maintain that refinement to convergence is alI that is required to
remove the bias when an alternate test set is selected.  In fact I
claim that it's the refinement, not the jiggling, that's wholly
responsible for removing the bias.  I know we thrashed this out a
while back and I recall that the discussion ended with a challenge to
me to prove my claim that the refine-only Rfrees are indeed unbiased.
I couldn't see an easy way of doing this which didn't involve
rebuilding and re-refining the same structure 20 times over, without
introducing any observer bias.

The present discussion prompted me to think again about this and I
believe I can prove part of my claim quite easily, that jiggling has
no effect on the results.  Proving that the resulting Rfrees are
unbiased is much harder, since as we've seen there's no proof that
jiggling actually removes the bias as claimed by its proponents.
However given that said proponents of jiggling+refinement have been
happy to accept for many years that their results are unbiased, then
they must be equally happy now to accept that the refinement-only
results are also unbiased, provided I can demonstrate that the
difference between the results is insignificant.

The experimental proof rests on comparison between the Rfrees and
RMSDs of the jiggled+refined and the refined-only structures for the
19 possible alternate test sets (assuming 5% test-set size).  If
jiggling makes no difference as I claim then there should be no
significant difference between the Rfrees and insignificant RMSDs for
all pairs of alternate test sets.

However, first we must be careful to establish what is a suitable
value for the noise magnitude to add to the co-ordinates.  If it's too
small it won't remove the bias (again notwithstanding Dale's point
that it's unlikely to have any effect anyway on the low res. data);
too large and you push it beyond the convergence radius of the
refinement and end up damaging the structure irretrievably (at least
unless you're prepared to do significant rebuilding of the model).

For the record here's the crystal info for the test data I selected:

Nres: 96   SG: P41212   Vm: 1.99   Solvent: 0.377
Resol: 40-1.58 A.
Working set size: 11563   Test set size: 611 (5%)   Test set: 0
Refinement program:     BUSTER.
Noise addition program: PDBSET.

It's wise to choose a small protein since you need to run lots of
refinements!  However feel free to try the same thing with your own data.

First I took care that the starting model was refined to convergence
using the original test set 0, and I performed 2 sequential runs of
refinement with BUSTER (the deviations are relative to the input
co-ordinates in each case):

Ncyc  Rwork   Rfree   RMSD MaxDev
    82     0.181  0.230     0.005   0.072
    51     0.181  0.231     0.002   0.015

The advantage of using BUSTER is that it has its own convergence test;
with REFMAC you have to guess.

Then I tried a range of input noise values (0.20, 0.25. 0.30, 0.35,
0.40, 0.50 A) on the refined starting model.  Note that these are
RMSDs, not maximum shifts as claimed by the PDBSET documentation.  In
each case I did 4 sequential runs of BUSTER on the jiggled
co-ordinates and by looking at the RMSDs and max. shifts I decided
that 0.25 A RMSD was all the structure could stand without risking
permanent damage (note that the default noise value in PDBSET is 0.2):

Initial RMSD: 0.248  MaxDev: 0.407

Ncyc  Rwork   Rfree   RMSD  MaxDev
   358    0.183   0.230    0.052    0.454
   126    0.181   0.232    0.041    0.383
     65    0.181   0.232    0.040    0.368
     50    0.181   0.232    0.040    0.360

The only purpose of the above refinements is to establish the most
suitable noise value; the resulting refined PDB files were not used.

So then I took the co-ordinates with 0.25 A noise added and for each
test set 1-19 did 2 sequential runs of BUSTER.

Finally I took the original refined starting model (i.e. without noise
addition) and again refined to convergence using all 19 alternate test
sets.

The results are attached.  The correlation coefficient between the 2
sets of Rfrees is 0.992 and the mean RMSD between the sets is 0.04 A,
so the difference between the 2 sets is indeed insignificant.

I don't find this result surprising at all: provided the jiggling
keeps the structure inside the convergence radius of refinement, then
by definition the refinement will produce the same result irrespective
of the starting point (i.e. jiggled or not).  If the jiggling takes
the structure outside the radius of convergence then the original
structure will not be retrievable without manual rebuilding: I'm
assuming that's not the goal here.

I suspect that the idea of jiggling may have come about because
refinements have not always been carried through to convergence:
clearly if you don't do a proper job of refinement then you must
expect some of the original bias to remain.  Also to head off the
suggestion that simulated annealing refinement would fix this I would
suggest that any kind of SA refinement is only of value for initial MR
models when there may be significant systematic error in the model;
it's not generally advisable to perform it on final refined models
(jiggled or not) when there is no such systematic error present.

Cheers

-- Ian


On 21 November 2014 18:56, Dale Tronrud <de...@daletronrud.com
<mailto:de...@daletronrud.com>> wrote:



On 11/21/2014 12:35 AM, "F.Xavier Gomis-Rüth" wrote:
  > <snip...>

As to the convenience of carrying over a test set to another
dataset, Eleanor made a suggestion to circumvent this necessity
some time ago: pass your coordinates through pdbset and add some
noise before refinement:

pdbset xyzin xx.pdb xyzout yy.pdb <<eof noise 0.4 eof


     I've heard this "debiasing" procedure proposed before, but I've
never seen a proper test showing that it works.  I'm concerned that
this will not erase the influence of low resolution reflections that
were in the old working set but are now in the new test set.  While
adding 0.4 A gaussian noise to a model would cause large changes to
the 2 A structure factors I doubt it would do much to those at 10 A.

     It seems to me that one would have to have random, but
correlated,
shifts in atomic parameters to affect the low resolution data - waves
of displacements, sometimes to the left and other times to the right.
   You would need, of course, a superposition of such waves that span
all the scales of resolution in the data set.

     Has anyone looked at the pdbset jiggling results and shown
that the
low resolution data are scrambled?

Dale Tronrud

Xavier

On 20/11/14 11:43 PM, Keller, Jacob wrote:
Dear Crystallographers,

I thought that for reliable values for Rfree, one needs only to
satisfy counting statistics, and therefore using at most a couple
thousand reflections should always be sufficient. Almost always,
however, some seemingly-arbitrary percentage of reflections is
used, say 5%. Is there any rationale for using a percentage
rather than some absolute number like 1000?

All the best,

Jacob

******************************************* Jacob Pearson Keller,
PhD Looger Lab/HHMI Janelia Research Campus 19700 Helix Dr,
Ashburn, VA 20147 email:kell...@janelia.hhmi.org
<mailto:kell...@janelia.hhmi.org>
******************************************* .


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