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 <[email protected]> wrote: > -----BEGIN PGP SIGNED MESSAGE----- > Hash: SHA1 > > > > 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: [email protected] > >> ******************************************* . > >> > > > > -- > -----BEGIN PGP SIGNATURE----- > Version: GnuPG v2.0.22 (MingW32) > > iEYEARECAAYFAlRviu4ACgkQU5C0gGfAG12TMwCfTT0Q4yfCCOxJlRXtsCXmmp1n > 9lEAn2Ir57+Y16fh02VcsvDxwu6KYRGK > =68gK > -----END PGP SIGNATURE----- >
