- phenixbb - phenix-online.org

discrepancy in MolProbity statistics
by Michael Thompson 15 May '12

15 May '12

Hello All, I recently ran into a discrepancy between the MolProbity statistics reported by phenix.refine and the MolProbity statistics reported by the actual MolProbity webserver. I was hoping someone could comment on this and let me know if this is a warning sign that something is amiss. The structure (resolution=2.0A) seems to be correct and well refined, based on R-factors (0.1591/0.1774) and geometry reports from the various validation tools. Remark 3, which was written out to the pdb file by phenix.refine, contains the following: REMARK 3 MOLPROBITY STATISTICS. REMARK 3 ALL-ATOM CLASHSCORE : 4.14 REMARK 3 RAMACHANDRAN PLOT: REMARK 3 OUTLIERS : 0.00 % REMARK 3 ALLOWED : 2.32 % REMARK 3 FAVORED : 97.68 % REMARK 3 ROTAMER OUTLIERS : 1.83 % REMARK 3 CBETA DEVIATIONS : 0 Remark 40, which was created by and downloaded from the MolProbity web server, contains slightly different statistics: REMARK 40 MOLPROBITY OUTPUT SCORES: REMARK 40 ALL-ATOM CLASHSCORE : 0.83 REMARK 40 BAD ROTAMERS : 1.6% 8/510 (TARGET 0-1%) REMARK 40 RAMACHANDRAN OUTLIERS : 0.0% 0/657 (TARGET 0.2%) REMARK 40 RAMACHANDRAN FAVORED : 97.7% 642/657 (TARGET 98.0%) I am mainly concerned about the values of the ALL-ATOM CLASHSCORE, as they are significantly different according to the two calculations. Thanks in advance for any information/answers! Mike -- Michael C. Thompson Graduate Student Biochemistry & Molecular Biology Division Department of Chemistry & Biochemistry University of California, Los Angeles miket(a)chem.ucla.edu

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phenix.model
by r n 14 May '12

14 May '12

Hi I did get different values in phenix.model_vs_data, after the refinement gave me R and Rfree as 24 and 29% and phenix.model_vs_data gave me R_compute and Rfree-compute as 22 and 26%. Thought that both R-compute and refinement values should be more or less same? any suggestions R

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CASP 10: Call for targets to assess the state of the art in protein structure modeling
by Torsten Schwede 11 May '12

11 May '12

*CASP 10: Call for targets to assess the state of the art in protein structure modeling* As many of you know, CASP (Critical Assessment of Structure prediction) has been assessing the state of the art in modeling protein structure from sequence since 1994, running a community experiment once every two years. In these experiments, information on soon to be solved structures is collected from the experimental community, and the sequence data are passed to the structure modeling community so that blind predictions of structure and can collected and assessed (1). Over that period CASP has seen enormous progress in the quality of modeled structures (2), but many problems remain. CASP is only possible because of the generous participation of the experimental community in providing the modeling targets (3). We recently appealed for your help in providing novel fold and membrane protein targets for the ongoing CASP ROLL process. That is very successful, with 57 prediction teams participating and 26 targets already released, thanks to all of you who have contributed. The prediction season for the next full biannual experiment, CASP 10, begins May 1, and so we are now asking for your help again, this time in reaching our goal of releasing at least varied 100 targets in a the three-month period. We need all sorts of targets, spanning the categories below: 1. (More than ever) novel folds and membrane protein targets -- even with the extended collection season provided by CASP ROLL, there will be still a shortage. There are some interesting methods developments for ab initio modeling, and it is important to be able to decisively evaluate their effectiveness. 2. A diversity of comparative modeling targets. Cases where the there is fairly high sequence identity (30-50%) between the target structure and an available template are valuable for testing the degree to which model accuracy can approach that of experiment, particularly in functionally critical regions. Cases with lower sequence identity to template, right down to undetectable, are valuable for testing the ability of the methods to detect remote homologs, to overcome challenging alignment difficulties, to make use of multiple templates, and to build regions of the structure not obviously available from a template. 3. Targets containing significant amounts of disordered structure, so as to test the ability of methods to identify these regions. Disorder identified by absence of density in crystallography is current the main source and very useful, but its important to have cases where the nature of the disorder has been established by other means, such as NMR. 4. Some targets will also be used to test methods of structure refinement. In these cases, the best model received for a target will be released to the refinement community, who will subsequently submit new models. This too is an area where there have been some exciting developments in the last year, so we are hoping for significant progress. Refinement targets are selected based on the nature of the errors in the initial models. Because of the extended process, these targets need to be available for longer before release of the experimental structure. For those of you who have not provided targets to CASP before, the procedure is simple. There are three ways to submit targets: (1) Go the target submission web page and fill in the easy form; (2) When you submit your co-ordinates to the PDB, tick the 'CASP HOLD' box, automatically setting up a target entry; (3) Send an email the prediction center with details. If you have queries, there is a very experienced prediction center staff to deal with them. The key thing is timing: We need a window of at least four weeks between receiving information about a target and the release of your experimental structure. A longer window -- up to eight weeks - is often useful, for example so that a target can be used to test refinement methods, but is not essential (note that using the PDB target submission route automatically selects eight weeks). We don't need your experimental structure in advance of its release by the PDB, provided that will happen by the end of August. Please consult the target submission page for more details: http://www.predictioncenter.org/casp10/targets_submission.cgi There are already over 200 prediction teams signed for CASP 10, and so any targets provided will receive plenty of attention. If you have a suitable target now, we are ready to receive it. If new targets come up before July 17, we would also love to have them. (After July 17, we will continue with CASP ROLL for novel folds and membrane proteins). So please get in touch whenever a suitable opportunity arises, and help improve modeling methods. Thanks, CASP organizing committee John Moult, IBBR, University of Maryland, USA Krzysztof Fidelis, University of California, Davis, USA Andriy Kryshtafovych, University of California, Davis, USA Torsten Schwede, SIB & Biozentrum University of Basel, Switzerland Anna Tramontano, University of Rome, Italy Get in touch: casp(a)predictioncenter.org More information: http://www.predictioncenter.org/casp10/index.cgi CASP Roll targets so far: http://www.predictioncenter.org/casprol/targetlist.cgi Submit a target: http://www.predictioncenter.org/casp10/targets_submission.cgi 1. Critical assessment of methods of protein structure prediction (CASP)--round IX. <http://www.ncbi.nlm.nih.gov/pubmed/21997831> Moult J, Fidelis K, Kryshtafovych A, Tramontano A. Proteins. 2011;79 Suppl 10:1-5. doi: 10.1002/prot.23200. Epub 2011 Oct 14. 2. CASP9 results compared to those of previous CASP experiments. <http://www.ncbi.nlm.nih.gov/pubmed/21997643> Kryshtafovych A, Fidelis K, Moult J. Proteins. 2011;79 Suppl 10:196-207. doi: 10.1002/prot.23182. Epub 2011 Oct 14 3.Target highlights in CASP9: Experimental target structures for the critical assessment of techniques for protein structure prediction. <http://www.ncbi.nlm.nih.gov/pubmed/22020785> Kryshtafovych A et al. Proteins 2011;79 Suppl 10:6-20. doi: 10.1002/prot.23196. Epub 2011 Oct 21.

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Fwd: Re: anisotropic induced noise amplification
by Pavel Afonine 11 May '12

11 May '12

Hi, I realized Randy's reply did not go to the mailing list, so I'm forwarding it now. Pavel -------- Original Message -------- Subject: Re: [phenixbb] anisotropic induced noise amplification Date: Mon, 7 May 2012 09:49:57 +0100 From: Randy Read <rjr27(a)cam.ac.uk> To: Pavel Afonine <pafonine(a)lbl.gov> CC: developers(a)phenix-online.org <developers(a)phenix-online.org>, Peter Zwart <PHZwart(a)lbl.gov> In the absence of an answer from Peter (who implemented this and therefore ought to know best), I'm pretty sure that the idea is to measure how much difference there is in the amount of signal in the data that have received the biggest anisotropy corrections, compared to the ones that have received the smallest anisotropy corrections. If there's very little signal in the data that have been scaled up the most, then the noise is being amplified (nearly-random amplitudes have gone from being relatively small to the same size on average as the well-measured amplitudes). But what the Z-scores mean is not at all clear from that output, and I'm not aware that Peter has written anything describing this. This amplified noise is what I suspect is creating problems in phenix.refine refinement with highly anisotropic data, because if the experimental sigmas are ignored then the program doesn't know (after anisotropic scaling) which amplitudes of a comparable size contain signal and which are essentially noise. Anisotropic truncation gets rid of it, which would explain why refinement works better with anisotropically-truncated data. Randy On 6 May 2012, at 20:21, Pavel Afonine wrote: > Hi, > > did anyone address this post? I'm interested to know the answer > myself: I have absolutely no idea what is this. > > Pavel > > -------- Original Message -------- > Subject: [phenixbb] anisotropic induced noise amplification > Date: Wed, 2 May 2012 16:06:55 -0500 > From: James Thompson <Thompson.James(a)mayo.edu> > Reply-To: PHENIX user mailing list <phenixbb(a)phenix-online.org> > To: phenixbb(a)phenix-online.org > > > > 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* > > <Attached Message Part.txt> ------ Randy J. Read Department of Haematology, University of Cambridge Cambridge Institute for Medical Research Tel: + 44 1223 336500 Wellcome Trust/MRC Building Fax: + 44 1223 336827 Hills Road E-mail: rjr27(a)cam.ac.uk <mailto:[email protected]> Cambridge CB2 0XY, U.K. www-structmed.cimr.cam.ac.uk

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lastest phenix.refine reproducible problem
by 周文昌 09 May '12

09 May '12

Dear all, I've been learning phenix refinement on a MAD dataset which is already deposited in PDB. There are something I can not get through. Basically I had two steps refinement: 1->phenix.refine data.mtz model.pdb xray_data.high_resolution=3 fix_rotamers=true strategy=individual+adp+individual_sites+tls 2->phenix.refine data.mtz model-refined.pdb xray_data.high_resolution=3 fix_rotamers=false strategy=none main.number_of_macro_cycles=1 model-refined.pdb is actually from the 1st step, so in principle the R/R-free values should be the same for 1 and 2. However in my case, I had 0.2506/0.2996 for the 1st step but 0.2503/0.2998 for the second. I compared the resulting pdb and mtz files from the two steps. PDB model were exactly the same but there were little difference in the mtz file. Why there is difference in mtz file and would it be the reason for the difference of R factors? I use the latest version of phenix, phenix-dev-1009. thanks, Wenchang

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Installation on a POWER 7 system
by Rajagopalan, Senapathy 09 May '12

09 May '12

Hi Everyone, I was wondering if its possible to install PHENIX on a POWER 7 system. The cluster for which we have access runs on a power 7 system and at least my initial try to install the FC3 version failed. 'uname –rm' gives me '2.6.32-220.13.1.el6.ppc64 ppc64'. If only re-compilation is required, I would appreciate if you can point me in the right direction. Thanks Sena Methodist. Leading Medicine. Recognized by U.S.News & World Report as one of America's "Best Hospitals" in 13 specialties. Named to FORTUNE® Magazine's "100 Best Companies to Work For®" list seven years in a row. Designated as a Magnet hospital for excellence in nursing. Visit us at methodisthealth.com. Follow us at twitter.com/MethodistHosp and www.facebook.com/MethodistHospital. ***CONFIDENTIALITY NOTICE*** This e-mail is the property of The Methodist Hospital and/or its relevant affiliates and may contain restricted and privileged material for the sole use of the intended recipient(s). Any review, use, distribution or disclosure by others is strictly prohibited. If you are not the intended recipient (or authorized to receive for the recipient), please contact the sender and delete all copies of the message. Thank you.

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NCS, TLS and anisotropic b-factors
by Morten Groftehauge 08 May '12

08 May '12

Hi Phenixbb, Just one more stupid question: On the phenix website it says under *current limitations of phenix.refine*"Atoms with anisotropic ADP in NCS groups". I take this to mean that phenix.refine doesn't handle the combination of TLS and NCS well, is this correct? So what is the correct way of handling TLS and NCS? Do one run where individual, isotropic ADP+xyz and NCS are refined and then another where individual, isotropic ADP+xyz and TLS are refined? Or one run where individual, isotropic ADP+xyz and NCS are refined and then another where individual, isotropic ADP and TLS are refined? Or does the issues go away if you only use torsional NCS? Or adjusting the B-factor weight of NCS selections? Should B-factor weight then be set up or down? Okay, that was more than one question but at least they're all on the same topic. Cheers, Morten -- Morten K Grøftehauge, PhD Pohl Group Durham University

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UPDATE-- Difficult dataset and refinement--P422? I422?Twinning?
by Zhou, Tongqing (NIH/VRC) [E] 08 May '12

08 May '12

Hi Jürgen, Kelly and Nat, I tried XDS and MosFilm, they simply cannot index the data. I reprocessed the data yesterday with HKL2000 starting from frame #30 (splitting 1-29, 30-360), I did get it indexed to I4 and refined to very nice x/y chi^2 and covering most spots, I then used the index/refinement numbers for the whole data set. it seems that other spots were from a "nicely" positioned secondary crystal which fooled the program to pick P4 space group. I scaled the data as I4 and I422 to see which one is better. The I4 data set, ~95% complete overall, 9.2% R-sym. Xtriage suggested it should have higher symmetry I422 or twin (-k, -h, -l, almost 50%). MR sent well and best SG is I4, 2 mol/ASU, r and r-free went to about 27% and 32%, but if I used the twin-law in phenix.refine and ask phenix to generate r-free-flags with twinning in mind, the numbers went to ~22% and 27%. Shell Lower Upper Average Average Norm. Linear Square limit Angstrom I error stat. Chi**2 R-fac R-fac 50.00 7.32 440.7 8.8 5.1 1.481 0.027 0.030 7.32 5.81 167.2 4.2 3.2 1.868 0.045 0.048 5.81 5.08 196.3 5.1 3.9 2.130 0.053 0.058 5.08 4.62 243.1 6.2 4.7 2.264 0.056 0.061 4.62 4.29 236.7 6.4 4.9 2.057 0.055 0.055 4.29 4.03 167.6 5.6 4.7 1.819 0.067 0.066 4.03 3.83 139.5 5.6 5.0 1.740 0.083 0.075 3.83 3.66 110.2 5.5 5.1 1.645 0.102 0.091 3.66 3.52 92.5 5.6 5.3 1.459 0.117 0.101 3.52 3.40 76.5 5.7 5.4 1.372 0.143 0.124 3.40 3.30 59.3 5.7 5.5 1.278 0.179 0.146 3.30 3.20 47.3 5.7 5.6 1.161 0.212 0.179 3.20 3.12 40.7 5.8 5.7 1.103 0.241 0.201 3.12 3.04 31.6 5.8 5.8 1.057 0.298 0.254 3.04 2.97 28.9 5.9 5.9 1.031 0.331 0.271 2.97 2.91 22.6 5.9 5.9 0.985 0.400 0.340 2.91 2.85 19.0 6.0 6.0 0.991 0.484 0.405 2.85 2.80 17.1 6.1 6.1 0.957 0.518 0.437 2.80 2.75 14.6 6.2 6.2 0.908 0.577 0.485 2.75 2.70 13.0 6.4 6.3 0.931 0.645 0.550 All reflections 112.9 5.9 5.3 1.455 0.092 0.066 The I422 data (below), 1 mol/ASU, r and r-free were about 27% and 32%. Shell Lower Upper Average Average Norm. Linear Square limit Angstrom I error stat. Chi**2 R-fac R-fac 50.00 7.32 430.0 8.4 5.0 1.344 0.025 0.028 7.32 5.81 163.4 4.0 3.0 1.489 0.040 0.042 5.81 5.08 192.4 4.8 3.6 1.694 0.046 0.052 5.08 4.62 231.6 5.6 4.3 1.790 0.049 0.053 4.62 4.29 227.8 5.8 4.5 1.534 0.045 0.043 4.29 4.03 161.3 5.0 4.2 1.401 0.055 0.052 4.03 3.83 135.3 5.0 4.4 1.367 0.066 0.059 3.83 3.66 106.2 4.9 4.4 1.302 0.082 0.071 3.66 3.52 88.1 4.8 4.5 1.253 0.097 0.082 3.52 3.40 75.0 4.9 4.6 1.193 0.113 0.096 3.40 3.30 56.7 4.8 4.6 1.121 0.144 0.115 3.30 3.20 44.8 4.8 4.7 1.061 0.172 0.141 3.20 3.12 38.0 4.8 4.7 1.011 0.203 0.166 3.12 3.04 29.1 4.7 4.7 1.029 0.253 0.209 3.04 2.97 27.7 4.8 4.8 0.985 0.261 0.209 2.97 2.91 21.4 4.9 4.8 0.917 0.320 0.266 2.91 2.85 18.3 4.9 4.8 0.949 0.380 0.316 2.85 2.80 16.1 4.9 4.9 0.955 0.431 0.358 2.80 2.75 14.2 5.0 5.0 0.940 0.483 0.399 2.75 2.70 12.6 5.2 5.2 0.886 0.536 0.462 All reflections 110.9 5.1 4.5 1.236 0.076 0.054 So my questions are: 1. Is it really twinned since including twin-law in refinment gave much better numbers? 2. When refining with twin-law, Are the maps by phenix.refine output already "corrected" mtz/map? 3. If I use xray_data.r_free_flags.generate=True, can I write the data mtz out with the generated r-free-flags so that each round of refinement uses the same CV set? Thnaks, Tongqing Tongqing Zhou, Ph.D. Staff Scientist Structural Biology Section Vaccine Research Center, NIAID/NIH Building 40, Room 4609B 40 Convent Drive, MSC3027 Bethesda, MD 20892 (301) 594-8710 (Tel) (301) 793-0794 (Cell) (301) 480-2658 (Fax) ****************************************************************************** The information in this e-mail and any of its attachments is confidential and may contain sensitive information. It should not be used by anyone who is not the original intended recipient. If you have received this e-mail in error please inform the sender and delete it from your mailbox or any other storage devices. National Institute of Allergy and Infectious Diseases shall not accept liability for any statements made that are sender's own and not expressly made on behalf of the NIAID by one of its representatives. ****************************************************************** From: Bosch, Juergen [mailto:[email protected]] Sent: Monday, May 07, 2012 1:34 PM To: PHENIX user mailing list Subject: Re: [phenixbb] Difficult dataset and refinement--P422? I422?Twinning? Why don't you index over the whole dataset (XDS) ? Or at least over a couple of images (Mosflm) Jürgen On May 7, 2012, at 12:50 PM, Kelly Daughtry wrote: I agree. The fact that two "crystals forms" appear, with related unit cells: P422 data: unit_cell = 191.6999969 191.6999969 311.0539856 90 90 90 space_group = "P 4 2 2" I422 data: unit_cell = 191.783 191.783 103.775 90 90 90 space_group = "I 4 2 2" indicated to me you have mis-indexed the P422 data. It is likely I422. Kelly ******************************************************* Kelly Daughtry, Ph.D. Post-Doctoral Fellow, Raetz Lab Biochemistry Department Duke University Alex H. Sands, Jr. Building 303 Research Drive RM 250 Durham, NC 27710 P: 919-684-5178 ******************************************************* On Mon, May 7, 2012 at 12:18 PM, Nathaniel Echols <nechols(a)lbl.gov<mailto:[email protected]>> wrote: On Mon, May 7, 2012 at 8:46 AM, Kelly Daughtry <kddaught(a)bu.edu<mailto:[email protected]>> wrote: Looking at the P422 data, it look like you have pseudo translational symmetry. Did you try processing this data as I422? >From the P422_xtriage.log: The full list of Patterson peaks is: x y z height p-value(height) ( 0.500, 0.500, 0.165 ) : 78.635 (6.634e-07) ( 0.000, 0.000, 0.330 ) : 56.292 (2.795e-05) ( 0.500, 0.500, 0.497 ) : 30.920 (1.207e-03) One word of caution: an exceptionally high off-origin peak can mean that the unit cell was measured too large, and you've integrated extra reflections that are really non-existent. (I'm not sure what the threshold for this is, but 80% seems pretty large.) Splitting and various indexing artifacts can sometimes lead to this. I'd recommend running labelit.index on the images and seeing what it thinks the lattice should be. -Nat _______________________________________________ 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 ...................... Jürgen Bosch Johns Hopkins University Bloomberg School of Public Health Department of Biochemistry & Molecular Biology Johns Hopkins Malaria Research Institute 615 North Wolfe Street, W8708 Baltimore, MD 21205 Office: +1-410-614-4742 Lab: +1-410-614-4894 Fax: +1-410-955-2926 http://web.mac.com/bosch_lab/

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redundancy of merged multiple datasets
by CPMAS Chen 08 May '12

08 May '12

Dear all, I have merged multiple datasets obtained from the same crystals, different spots of course, it certainly increases the signal/noise ratio and makes the resolution go higher a little bitter. But, the con is, the redundancy is increased to ~20 after I merged 6 datasets. Whereas the individual dataset has the redundancy around 3~5. Is this acceptable? Thanks! *************************************************** CPMAS Chen Research Associate University of Pittsburgh School of Medicine Department of Anesthesiology ******************************************************

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Re: [phenixbb] UPDATE-- Difficult dataset and refinement--P422? I422?Twinning?
by Kay Diederichs 08 May '12

08 May '12

> On May 8, 2012, at 11:11 AM, Zhou, Tongqing (NIH/VRC) [E] wrote: > > Hi J?rgen, Kelly and Nat, > > I tried XDS and MosFilm, they simply cannot index the data. > Hi, "simply cannot index" is hard to believe. 90% of indexing failures are due to wrong header values, 9% to the spindle rotating in the "wrong" direction, and the last 1% has other causes. I have yet to see a single-crystal dataset that cannot be indexed. If you are willing to confidentially share (at least some of) your data, I could try to process them with XDS - at least you get another opionion. Easiest way: copy them into a Dropbox or Wuala folder and share that. best, Kay

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