- phenixbb - phenix-online.org

secondary structure restraints helices/helixes proline
by Morten Groftehauge 04 May '12

04 May '12

Hi guys, How does phenix.refine handle prolines in helices? When I look in high resolution structures it seems that the carbonyl of the residue four positions before the proline (also in the helix) should be more perpendicular than parallel to the helix. This makes sense since there isn't any nitrogen for it to hydrogen bond to. But when I refine my structure it seems as if phenix.refine is trying to push the carbonyl into parallel position. Am I imagining things? It's not the best data and this is a troublesome region. Cheers, Morten -- Morten K Grøftehauge, PhD Pohl Group Durham University

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Re: [phenixbb] Geometry Restraints - Anisotropic truncation
by Terwilliger, Thomas C 03 May '12

03 May '12

Hi Kendall, Yes, I think you could use this kind of approach to make overall decisions of any kind, including those you suggest. I would not use Rsleep for anything at all, other than calculating a final number. I would use a fixed Rfree set (which could be a subset of the total free set or the whole set) for all such decision making. If a lot of such decisions are made with Rfree...then yes it would be good to have an Rsleep to make sure that everything is ok. All the best, Tom T ________________________________ From: Kendall Nettles [knettles(a)scripps.edu] Sent: Thursday, May 03, 2012 9:05 AM To: Terwilliger, Thomas C; PHENIX user mailing list Subject: Fwd: [phenixbb] Geometry Restraints - Anisotropic truncation Hi Tom, Do you think something like this could be used during refinement to identify the "best" resolution limits? If you have an Rsleep set would Rfree be sufficient for this? I imagine collecting data with a ring of noise and then let the optimal resolution be determined during refinement. My understanding of this is that the modern refinement algorithms can handle some noise in the reflections, but maybe this could be a way to optimize how much signal is needed to contribute in a positive fashion? Kendall

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Re: [phenixbb] Geometry Restraints - Anisotropic truncation
by Leonid Sazanov 03 May '12

03 May '12

Hi, so will we see now the possibility to apply anisotropic resolution limits truncation in Phenix? Despite the fact that a lot of people use UCLA server, there is still no possibility to do this in any major crystallographic software, AFAIK. Phaser does the scaling, but no truncation, and noise sitting in those regions where there is no signal, is a real culprit. Large SIGFs there do not resolve the problem completely. Thanks. >>>>>> Message: 4 Date: Wed, 25 Apr 2012 09:05:57 -0400 From: Mario Sanches <mariosan(a)gmail.com> To: PHENIX user mailing list <phenixbb(a)phenix-online.org> Subject: [phenixbb] Geometry Restraints - UPDATE .......... It turns out that the reason to my nightmares was a highly anisotropic dataset. When I tried to fix geometry related problems in coot, phenix.refine was twisting the geometry back again, probably because it was trying to fit a lot of noise due to the anisotropy. Everything was getting worst, geometry, clashscore, and Ramachandran. Pavel finally corrected it by using this server: http://services.mbi.ucla.edu/anisoscale/ ............ -- Dr. Leonid A. Sazanov Research group leader Medical Research Council Mitochondrial Biology Unit Wellcome Trust / MRC Building Hills Road Cambridge CB2 0XY WEB: www.mrc-mbu.cam.ac.uk Tel: +44-1223-252910 Fax: +44-1223-252915

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Secondary Structure Definitions
by Antony Oliver 03 May '12

03 May '12

Dear all, Is there a phenix jiffy to assign (and write!) secondary structure definitions to a pdb file? I'm currently using MacPyMOL to put together some figures, and I can see that some of the secondary structure elements in the cartoon representation aren't being drawn correctly. Being slightly old-school, I used to use DSSP and the little program dssp2pdb to extract the information and put it into the PDB header. Is there a simpler / easier way to do this? (NB: I'm aware that CCP4MG copes better with SS assignment, but I prefer to use PyMOL in this instance). With thanks, Tony. --- Dr Antony W Oliver Senior Research Fellow CR-UK DNA Repair Enzymes Group Genome Damage and Stability Centre Science Park Road University of Sussex Falmer, Brighton, BN1 9RQ email: antony.oliver(a)sussex.ac.uk<mailto:[email protected]> tel (office): +44 (0)1273 678349 tel (lab): +44 (0)1273 677512

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Fwd: Geometry Restraints - Anisotropic truncation
by Kendall Nettles 03 May '12

03 May '12

Hi Tom, Do you think something like this could be used during refinement to identify the "best" resolution limits? If you have an Rsleep set would Rfree be sufficient for this? I imagine collecting data with a ring of noise and then let the optimal resolution be determined during refinement. My understanding of this is that the modern refinement algorithms can handle some noise in the reflections, but maybe this could be a way to optimize how much signal is needed to contribute in a positive fashion? Kendall From: "Terwilliger, Thomas C" <terwilliger(a)lanl.gov<mailto:[email protected]>> Date: May 3, 2012 10:23:29 AM EDT To: PHENIX user mailing list <phenixbb(a)phenix-online.org<mailto:[email protected]>> Subject: Re: [phenixbb] Geometry Restraints - Anisotropic truncation Reply-To: PHENIX user mailing list <phenixbb(a)phenix-online.org<mailto:[email protected]>> Hi Kendall, This could work. You could define a fixed set of test reflections, and never touch these, and never include them in refinement, and always use this fixed set to calculate a free R. Then you could do whatever you want, throw away some work reflections, etc, refine, and evaluate how things are working with the fixed free R set. All the best, Tom T ________________________________________ From: phenixbb-bounces(a)phenix-online.org<mailto:[email protected]> [phenixbb-bounces(a)phenix-online.org<mailto:[email protected]>] on behalf of Kendall Nettles [knettles(a)scripps.edu<mailto:[email protected]>] Sent: Thursday, May 03, 2012 7:05 AM To: PHENIX user mailing list Subject: Re: [phenixbb] Geometry Restraints - Anisotropic truncation Hi Pavel, Could you use a similar approach to figuring out where to cut your data in general? Could you compare the effects of throwing out reflections in different bins, based on I/sigma, for example, and use this to determine what is truly noise? I might predict that as you throw out "noise" reflections you will see a larger drop in Rfree than from throwing out "signal" reflections, which should converge as you approach the "true" resolution. While we don't use I/sigma exclusively, we do to tend towards cutting most of our data sets at the same i/sigma, around 1.5. It would be great if there was a more scientific approach. Best, Kendall On May 3, 2012, at 7:45 AM, Pavel Afonine wrote: Hi Kendall, removing same amount of data randomly gives Rwork/Rfree ~ 30/35%. Pavel On 5/3/12 4:13 AM, Kendall Nettles wrote: Hi Pavel, What happens if you throw out that many reflections that have signal? Can you take out a random set of the same size? Best, Kendall On May 3, 2012, at 2:41 AM, "Pavel Afonine"<pafonine(a)lbl.gov<mailto:[email protected]>> wrote: Hi Kendall, I just did this quick test: calculated R-factors using original and anisotropy-corrected Mike Sawaya's data (*) Original: r_work : 0.3026 r_free : 0.3591 number of reflections: 26944 Truncated: r_work : 0.2640 r_free : 0.3178 number of reflections: 18176 The difference in R-factors is not too surprising given how many reflections was removed (about 33%). Pavel (*) Note, the data available in PDB is anisotropy corrected. The original data set was kindly provided to me by the author. On 5/2/12 5:25 AM, Kendall Nettles wrote: I didnt think the structure was publishable with Rfree of 33% because I was expecting the reviewers to complain. We have tested a number of data sets on the UCLA server and it usually doesn't make much difference. I wouldn't expect truncation alone to change Rfree by 5%, and it usually doesn't. The two times I have seen dramatic impacts on the maps ( and Rfree ), the highly anisotrophic sets showed strong waves of difference density as well, which was fixed by throwing out the noise. We have moved to using loose data cutoffs for most structures, but I do think anisotropic truncation can be helpful in rare cases. Kendall On May 1, 2012, at 3:07 PM, "Dale Tronrud"<det102(a)uoxray.uoregon.edu<mailto:[email protected]>> wrote: While philosophically I see no difference between a spherical resolution cutoff and an elliptical one, a drop in the free R can't be the justification for the switch. A model cannot be made more "publishable" simply by discarding data. We have a whole bunch of empirical guides for judging the quality of this and that in our field. We determine the resolution limit of a data set (and imposing a "limit" is another empirical choice made) based on Rmrg, or Rmes, or Rpim getting too big or I/sigI getting too small and there is no agreement on how "too big/small" is too "too big/small". We then have other empirical guides for judging the quality of the models we produce (e.g. Rwork, Rfree, rmsds of various sorts). Most people seem to recognize that the these criteria need to be applied differently for different resolutions. A lower resolution model is allowed a higher Rfree, for example. Isn't is also true that a model refined to data with a cutoff of I/sigI of 1 would be expected to have a free R higher than a model refined to data with a cutoff of 2? Surely we cannot say that the decrease in free R that results from changing the cutoff criteria from 1 to 2 reflects an improved model. It is the same model after all. Sometimes this shifting application of empirical criteria enhances the adoption of new technology. Certainly the TLS parametrization of atomic motion has been widely accepted because it results in lower working and free Rs. I've seen it knock 3 to 5 percent off, and while that certainly means that the model fits the data better, I'm not sure that the quality of the hydrogen bond distances, van der Waals distances, or maps are any better. The latter details are what I really look for in a model. On the other hand, there has been good evidence through the years that there is useful information in the data beyond an I/sigI of 2 or an Rmeas> 100% but getting people to use this data has been a hard slog. The reason for this reluctance is that the R values of the resulting models are higher. Of course they are higher! That does not mean the models are of poorer quality, only that data with lower signal/noise has been used that was discarded in the models you used to develop your "gut feeling" for the meaning of R. When you change your criteria for selecting data you have to discard your old notions about the acceptable values of empirical quality measures. You either have to normalize your measure, as Phil Jeffrey recommends, by ensuring that you calculate your R's with the same reflections, or by making objective measures of map quality. Dale Tronrud P.S. It is entirely possible that refining a model to a very optimistic resolution cutoff and calculating the map to a lower resolution might be better than throwing out the data altogether. On 5/1/2012 10:34 AM, Kendall Nettles wrote: I have seen dramatic improvements in maps and behavior during refinement following use of the UCLA anisotropy server in two different cases. For one of them the Rfree went from 33% to 28%. I don't think it would have been publishable otherwise. Kendall On May 1, 2012, at 11:10 AM, Bryan Lepore wrote: On Mon, Apr 30, 2012 at 4:22 AM, Phil Evans<pre(a)mrc-lmb.cam.ac.uk<mailto:[email protected]>> wrote: Are anisotropic cutoff desirable? is there a peer-reviewed publication - perhaps from Acta Crystallographica - which describes precisely why scaling or refinement programs are inadequate to ameliorate the problem of anisotropy, and argues why the method applied in Strong, et. al. 2006 satisfies this need? -Bryan _______________________________________________ phenixbb mailing list phenixbb(a)phenix-online.org<mailto:[email protected]> http://phenix-online.org/mailman/listinfo/phenixbb _______________________________________________ phenixbb mailing list phenixbb(a)phenix-online.org<mailto:[email protected]> http://phenix-online.org/mailman/listinfo/phenixbb _______________________________________________ phenixbb mailing list phenixbb(a)phenix-online.org<mailto:[email protected]> http://phenix-online.org/mailman/listinfo/phenixbb _______________________________________________ phenixbb mailing list phenixbb(a)phenix-online.org<mailto:[email protected]> http://phenix-online.org/mailman/listinfo/phenixbb _______________________________________________ phenixbb mailing list phenixbb(a)phenix-online.org<mailto:[email protected]> http://phenix-online.org/mailman/listinfo/phenixbb

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How to include restraints when refining DNA?
by Xun Lu 03 May '12

03 May '12

Dear all, I am refining a protein-DNA complex structure at 2.9A resolution. The R/Rfree is 0.2181/0.2501, which is pretty good, but I can tell that the DNA is not well refined. Some sugar puckers are not right. The distances between some base-paired bases are kind of short (~2.5A). I've tried including a reference model for the DNA, or including a cif file, and I've also tried to turn on the secondary_structure_restraints.... nothing worked. I must have not done it in a correct way. But how to do it? And how to deal with sugar puckers? In refmac, I can set the distances between bases during the refinement, so there must be a way to do it in phenix as well? Any advice is welcome. Thanks! Xun -- Department of Molecular and Structural Biochemistry North Carolina State University

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anisotropic induced noise amplification
by James Thompson 02 May '12

02 May '12

Anyone willing to summarize Xtriage's algorithm that determines whether "anisotropic induced noise amplification" is present in diffraction data? What is this noise amplification? Is it anisotropic correction factors that over-fit the data thereby inducing noise? Many thanks, Jim T ---------------- Anisotropy analyses ---------------- Anisotropy ( [MaxAnisoB-MinAnisoB]/[MaxAnisoB] ) : 3.596e-01 Anisotropic ratio p-value : 0.000e+00 The p-value is a measure of the severity of anisotropy as observed in the PDB. The p-value of 0.000e+00 indicates that roughly 100.0 % of datasets available in the PDB have an anisotropy equal to or worse than this dataset. For the resolution shell spanning between 2.36 - 2.20 Angstrom, the mean I/sigI is equal to 3.37. 42.2 % of these intensities have an I/sigI > 3. When sorting these intensities by their anisotropic correction factor and analysing the I/sigI behavior for this ordered list, we can gauge the presence of 'anisotropy induced noise amplification' in reciprocal space. The quarter of Intensities *least* affected by the anisotropy correction show <I/sigI> : 3.82e+00 Fraction of I/sigI > 3 : 5.01e-01 ( Z = 3.59 ) The quarter of Intensities *most* affected by the anisotropy correction show <I/sigI> : 2.02e+00 Fraction of I/sigI > 3 : 1.84e-01 ( Z = 10.78 ) The combined Z-score of 11.36 indicates that there probably is significant systematic noise amplification that could possibly lead to artefacts in the maps or difficulties in refinement

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Re: [phenixbb] Scaling of diffraction data
by jens j birktoft 02 May '12

02 May '12

Hi Everybody, Is there a protocol for re-scaling several sets of diffraction data against a common reference set, either native or based on a Fcalc set computed from a common input model. The are from a number of derivatives, are all isomorphus, and are anomalous data . We want to compare the relative peak heights in Fo-Fc and Anom. difference maps Cheers Jens +++++++++++++++++++++++++++++++++++++++++++++++++++ Jens J. Birktoft e-mail: birktoft @ nyu.edu <jens.knold(a)gmail.com> ; Phone: 212-749-5057 +++++++++++++++++++++++++++++++++++++++++++++++++++

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Xtriage problem
by Abhinav Kumar 02 May '12

02 May '12

Hi, When I try to do R vs R analysis for calculated data using xtriage, it has a problem accepting calc labels. source /home/sw/rhel5/x86_64/phenix/phenix-1.7.3-928/phenix_env phenix.xtriage_1.7.3-928 junk.mtz calc_labels=FC ==> Sorry: No matching array: scaling.input.xray_data.calc_labels=FC Howevere, it works fine with an earlier version: source /home/sw/rhel5/x86_64/phenix/phenix-1.6.4-486/phenix_env phenix.xtriage_1.6.4-486 junk.mtz calc_labels=FC Thanks, Abhinav JCSG@SSRL, SLAC (650) 926-2992 -------- Original Message -------- Subject: RE: SP16569N-180314 Date: Tue, 1 May 2012 15:09:00 -0700 From: Miller, Mitchell D. <mmiller(a)slac.stanford.edu> To: Kumar, Abhinav <abhinavk(a)slac.stanford.edu> Hmm, it seems like it may be a bug introduced into phenix. (or else they changed they syntax and did not update the documentation) Can you report it? I get it to do the RvR analysis for calculated data if I use source /home/sw/rhel5/x86_64/phenix/phenix-1.6.4-486/phenix_env phenix.xtriage_1.6.4-486 junk.mtz calc_labels=FC but if I use source /home/sw/rhel5/x86_64/phenix/phenix-1.7.1-743/phenix_env phenix.xtriage_1.7.1-743 junk.mtz calc_labels=FC or source /home/sw/rhel5/x86_64/phenix/phenix-1.7.3-928/phenix_env phenix.xtriage_1.7.3-928 junk.mtz calc_labels=FC then I get the error Sorry: No matching array: scaling.input.xray_data.calc_labels=FC Thanks, Mitch P.S. the results I got were: R vs R statistic: R_abs_twin =<|I1-I2|>/<|I1+I2|> Lebedev, Vagin, Murshudov. Acta Cryst. (2006). D62, 83-95 R_abs_twin observed data : 0.451 R_abs_twin calculated data : 0.502 R_sq_twin =<(I1-I2)^2>/<(I1+I2)^2> R_sq_twin observed data : 0.279 R_sq_twin calculated data : 0.335 The analyses of the Patterson function reveals a significant off-origin peak that is 44.82 % of the origin peak, indicating pseudo translational symmetry. The chance of finding a peak of this or larger height by random in a structure without pseudo translational symmetry is equal to the 1.4447e-04. See the relevant section of the logfile for more details. The results of the L-test indicate that the intensity statistics behave as expected. No twinning is suspected. Even though no twinning is suspected, it might be worthwhile carrying out a refinement using a dedicated twin target anyway, as twinned structures with low twin fractions are difficult to distinguish from non-twinned structures. -----Original Message----- From: Kumar, Abhinav Sent: Tuesday, May 01, 2012 1:30 PM To: Miller, Mitchell D. Subject: Re: SP16569N-180314 I am having trouble inputting Calc labels to xtriage: My mtz file has the following columns: FreeR_flag FP SIGFP FC PHIC FC_ALL PHIC_ALL FWT PHWT DELFWT PHDELWT FOM PHCOMB I tried "FC,PHIC" and "FC" for calc labels but xtriage does not like it. It writes: No matching array: scaling.input.xray_data.calc_labels=FC Possible choices: /mnt/exdsstaff/abhinavk/Refine/SP16569N-180314/RESULTS/current.mtz:FP,SIGFP /mnt/exdsstaff/abhinavk/Refine/SP16569N-180314/RESULTS/current.mtz:FOM /mnt/exdsstaff/abhinavk/Refine/SP16569N-180314/RESULTS/current.mtz:PHCOMB Thanks, Abhinav JCSG@SSRL, SLAC (650) 926-2992 On 05/01/2012 12:51 PM, Miller, Mitchell D. wrote: Also, you could try running xtriage with FC's from the untwined refinement to look at the R vs R stats for Fc vs Fobs.

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Re: [phenixbb] Geometry Restraints - Anisotropic truncation
by Frank von Delft 02 May '12

02 May '12

Hi Pavel > we discussed this with Randy the other day.. A couple of copy-pasts from > that discussion: > > In general, given highly anisotropic data set: > > 1) maps calculated using all (unmodified) data by phenix.refine, > phenix.maps and similar tools are better than maps calculated using > anisotropy truncated data. So, yes, for the purpose of map calculation > there is no need to do anything: Phenix map calculation tools deal with > anisotropy very well. How did you define "better"? If there are a lot of reflections without signal, that makes them essentially missing, so by including them, you're effectively filling in for those reflections with only DFc. If anisotropy is very strong (i.e. many missing reflections), does that not introduce very significant model bias? The maps would look cleaner, though. (I haven't tested myself, btw; I'm genuinely wondering.) > 2) phenix.refine refinement may fail if one uses original anisotropic > data set. This is probably because the ML target does not use > experimental sigmas (and anisotropy correction by UCLA server is nothing > but Miller index dependent removing the data by sigma criterion - yeah, > that old well criticized practice of throwing away the data that you > worked hard to measure!). May be using sigmas in ML calculation could > solve the problem but that has to be proved. If there are large swathes of reciprocal space without signal - I don't see why shouldn't that be excluded? Tossing out individual reflections is of course silly, but what's wrong with trimming down the edges of the elipsoid? Cheers phx

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