Re: [ccp4bb] Phenix composite omit map
Hi Chen, I will answer you on the phenix mailing list! All the best, Tom T On Apr 21, 2014, at 10:53 AM, Chen Zhao wrote: Dear all, Hello! I am now running into a simple technical problem but I just cannot figure it out. I am trying to create a composite omit map by phenix, but when I typed in the command phenix.composite_omit_map XXX.eff based on the instructions on http://www.phenix-online.org/version_docs/dev-1579/composite_omit_map.htm, I got the error message command not found. Could anybody help me out? Thank you so much in advance! Sincerely, Chen
Re: [ccp4bb] Ligandfit - problem with ligand_start
Hi Danilo, I'll answer you on the Phenix mailing list! All the best, Tom T On Nov 25, 2013, at 8:14 AM, Danilo Belviso wrote: Dear all, I am working on a membrane protein covalently bound to a molecular antanna: it is known that this molecule binds to lysine residue but I do not know how many and which lysine residues it binds. 20 diffraction datasets of this protein-ligand complex have been obtained and now, I would quickly localize the ligand using the Fo-Fc map of each data set and using the information on the covalent bound protein-ligand. Ligandfit tool (PHENIX) seems to be indicated to do this; to use the information on the covalent bound, I am using the ligand_start keyword with a pdb containing a ghost atom (however present in ligand model) perfectly superposed to the lysine atom that should bind the ligand. The command used is: phenix.ligandfit data=prot.mtz model=prot.pdb ligand=lig.pdb ligand_start=lig_start.pdb input_labels=FOFCWT PHFOFCWT \ refine_ligand=True \ nproc=32 \ cif_def_file_list=lig.cif description: - prot.mtz (data) - prot.pdb (protein without ligand) - lig.pdb(ligand containing ghost atom) - lig_start.pdb (ghost atom superpose to NZ of a lysine) - lig.cif (restrain of lig.pdb) Strangely, no ligand is found at the end of the process even reducing ligand_cc_min to 0.01. I have run the same command by using an other protein where an other ligand has been correctly fitted but, also in this case, no ligand has been detected. Conversely, without the use of ligand_start, ligandfit properly localizes the ligand. I'm doing some mistake in the use of ligand_start? Do you know an other tool to perform a ligand fitting in these conditions? Thanks for your answers. Danilo
Re: [ccp4bb] ctruncate bug?
Implementing refinement against images will be pretty challenging. As far as I know the problem isn't in saying what has to happen, but rather in the enormous amount of bookkeeping necessary to relate a model of a structure and a model of the entire experiment (including such details as parameters defining spot shape, absorption etc) to a very long list of counts on pixels...and to calculate derivatives so as to optimize likelihood. As you suggest, there could be payoff in modeling diffuse scattering. Also I imagine that the structure factors could be estimated more accurately by refining against the raw images. One question will be whether all this would make a lot of difference with today's models. My guess is it won't make a substantial difference in most cases because our biggest problem is the inadequacy of these models and not deficiencies in our analysis of the data. However there might be some cases where it could help. The bigger question is whether it will make a difference in the future when we have more advanced models that have the potential to explain the data better. I think that yes, at that point all the effort will be worth it. Tom T From: Jrh [jrhelliw...@gmail.com] Sent: Monday, June 24, 2013 12:13 AM To: Terwilliger, Thomas C Cc: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] ctruncate bug? Dear Tom, I find this suggestion of using the full images an excellent and visionary one. So, how to implement it? We are part way along the path with James Holton's reverse Mosflm. The computer memory challenge could be ameliorated by simple pixel averaging at least initially. The diffuse scattering would be the ultimate gold at the end of the rainbow. Peter Moore's new book, inter alia, carries many splendid insights into the diffuse scattering in our diffraction patterns. Fullprof analyses have become a firm trend in other fields, admittedly with simpler computing overheads. Greetings, John Prof John R Helliwell DSc FInstP On 21 Jun 2013, at 23:16, Terwilliger, Thomas C terwilli...@lanl.gov wrote: I hope I am not duplicating too much of this fascinating discussion with these comments: perhaps the main reason there is confusion about what to do is that neither F nor I is really the most suitable thing to use in refinement. As pointed out several times in different ways, we don't measure F or I, we only measure counts on a detector. As a convenience, we process our diffraction images to estimate I or F and their uncertainties and model these uncertainties as simple functions (e.g., a Gaussian). There is no need in principle to do that, and if we were to refine instead against the raw image data these issues about positivity would disappear and our structures might even be a little better. Our standard procedure is to estimate F or I from counts on the detector, then to use these estimates of F or I in refinement. This is not so easy to do right because F or I contain many terms coming from many pixels and it is hard to model their statistics in detail. Further, attempts we make to estimate either F or I as physically plausible values (e.g., using the fact that they are not negative) will generally be biased (the values after correction will generally be systematically low or systematically high, as is true for the French and Wilson correction and as would be true for the truncation of I at zero or above). Randy's method for intensity refinement is an improvement because the statistics are treated more fully than just using an estimate of F or I and assuming its uncertainty has a simple distribution. So why not avoid all the problems with modeling the statistics of processed data and instead refine against the raw data. From the structural model you calculate F, from F and a detailed model of the experiment (the same model that is currently used in data processing) you calculate the counts expected on each pixel. Then you calculate the likelihood of the data given your models of the structure and of the experiment. This would have lots of benefits because it would allow improved descriptions of the experiment (decay, absorption, detector sensitivity, diffuse scattering and other background on the images,on and on) that could lead to more accurate structures in the end. Of course there are some minor issues about putting all this in computer memory for refinement -Tom T From: CCP4 bulletin board [CCP4BB@JISCMAIL.AC.UK] on behalf of Phil [p...@mrc-lmb.cam.ac.uk] Sent: Friday, June 21, 2013 2:50 PM To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] ctruncate bug? However you decide to argue the point, you must consider _all_ the observations of a reflection (replicates and symmetry related) together when you infer Itrue or F etc, otherwise you will bias the result even more. Thus you cannot
Re: [ccp4bb] ctruncate bug?
I hope I am not duplicating too much of this fascinating discussion with these comments: perhaps the main reason there is confusion about what to do is that neither F nor I is really the most suitable thing to use in refinement. As pointed out several times in different ways, we don't measure F or I, we only measure counts on a detector. As a convenience, we process our diffraction images to estimate I or F and their uncertainties and model these uncertainties as simple functions (e.g., a Gaussian). There is no need in principle to do that, and if we were to refine instead against the raw image data these issues about positivity would disappear and our structures might even be a little better. Our standard procedure is to estimate F or I from counts on the detector, then to use these estimates of F or I in refinement. This is not so easy to do right because F or I contain many terms coming from many pixels and it is hard to model their statistics in detail. Further, attempts we make to estimate either F or I as physically plausible values (e.g., using the fact that they are not negative) will generally be biased (the values after correction will generally be systematically low or systematically high, as is true for the French and Wilson correction and as would be true for the truncation of I at zero or above). Randy's method for intensity refinement is an improvement because the statistics are treated more fully than just using an estimate of F or I and assuming its uncertainty has a simple distribution. So why not avoid all the problems with modeling the statistics of processed data and instead refine against the raw data. From the structural model you calculate F, from F and a detailed model of the experiment (the same model that is currently used in data processing) you calculate the counts expected on each pixel. Then you calculate the likelihood of the data given your models of the structure and of the experiment. This would have lots of benefits because it would allow improved descriptions of the experiment (decay, absorption, detector sensitivity, diffuse scattering and other background on the images,on and on) that could lead to more accurate structures in the end. Of course there are some minor issues about putting all this in computer memory for refinement -Tom T From: CCP4 bulletin board [CCP4BB@JISCMAIL.AC.UK] on behalf of Phil [p...@mrc-lmb.cam.ac.uk] Sent: Friday, June 21, 2013 2:50 PM To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] ctruncate bug? However you decide to argue the point, you must consider _all_ the observations of a reflection (replicates and symmetry related) together when you infer Itrue or F etc, otherwise you will bias the result even more. Thus you cannot (easily) do it during integration Phil Sent from my iPad On 21 Jun 2013, at 20:30, Douglas Theobald dtheob...@brandeis.edu wrote: On Jun 21, 2013, at 2:48 PM, Ed Pozharski epozh...@umaryland.edu wrote: Douglas, Observed intensities are the best estimates that we can come up with in an experiment. I also agree with this, and this is the clincher. You are arguing that Ispot-Iback=Iobs is the best estimate we can come up with. I claim that is absurd. How are you quantifying best? Usually we have some sort of discrepancy measure between true and estimate, like RMSD, mean absolute distance, log distance, or somesuch. Here is the important point --- by any measure of discrepancy you care to use, the person who estimates Iobs as 0 when IbackIspot will *always*, in *every case*, beat the person who estimates Iobs with a negative value. This is an indisputable fact. First off, you may find it useful to avoid such words as absurd and indisputable fact. I know political correctness may be sometimes overrated, but if you actually plan to have meaningful discussion, let's assume that everyone responding to your posts is just trying to help figure this out. I apologize for offending and using the strong words --- my intention was not to offend. This is just how I talk when brainstorming with my colleagues around a blackboard, but of course then you can see that I smile when I say it. To address your point, you are right that J=0 is closer to true intensity then a negative value. The problem is that we are not after a single intensity, but rather all of them, as they all contribute to electron density reconstruction. If you replace negative Iobs with E(J), you would systematically inflate the averages, which may turn problematic in some cases. So, I get the point. But even then, using any reasonable criterion, the whole estimated dataset will be closer to the true data if you set all negative intensity estimates to 0. It is probably better to stick with raw intensities and construct theoretical predictions properly to account for their properties. What I was trying
[ccp4bb] ICSG 2013 Abstract Deadline April 30, 2013: International Conference on Structural Genomics - Structural Life Science
Dear Colleagues, We hope that you are planning to attend the International Conference on Structural Genomics 2013, which will be held in Sapporo, Hokkaido, Japan, July 29th – August 1st, 2013. ICSG2013-SLS is intended to provide an overview for the most recent developments in Structural Genomics and its impact on research in biology, medicine and disease, and to foster international collaboration among researchers. Five oral presentations will be chosen from the posters, and three poster prizes will also be awarded! Please submit your abstracts by April 30, 2013. You can see all the details of the conference at: http://www.c-linkage.co.jp/ICSG2013 The scientific topics covered in ICSG2013-SLS include the wider life science research fields with particular attention to drug discovery (small molecules and biopharmaceuticals), biotechnology and industrial issues while keeping strength in the high-throughput technologies and integration of hybrid methods. These technologies are now leading to the new field of “Structural Life Science”. In order to widen the opportunity to young and enthusiastic fellows to study more, we have organized several satellite workshops before ICSG2013- SLS (during the day on July 29, 2013). The topics will include “Small molecule screening”, “Automation of X-ray Structure Determination”, “Cell-free Protein Production”, “Automated NMR methods”, Eukaryotic expression, “Interaction analyses and Bioinformatics”. We hope you also find the satellite workshops are informative and productive. The conference will be held in Keio Plaza Hotel Sapporo, in walking distance of Hokkaido University's main campus and Sapporo station. The summer in Sapporo is a great time to stay and enjoy the cool summer night of Japan. ICSG2-13-SLS is partially supported by the Grant-in-Aid for Scientific Research on Innovative Areas; “Structural Cell Biology”, “Intrinsically Disordered Protein” and “Transient Macromolecular Complexes”, from Ministry of Education, Culture, Sports, Science and Technology (MEXT) . We are looking forward to welcoming you to Sapporo in the summer of 2013. Sincerely yours, Katsumi Maenaka, Ph.D. Chair, International Conference on Structural Genomics 2013 -Structural Life Science- (ICSG2013-SLS) Laboratory of Biomolecular Science and Center for Research and Education on Drug Discovery, Faculty of Pharmaceutical Sciences, Hokkaido University, Japan Soichi Wakatsuki Chair of Program Committee, ICSG2013-SLS Photon Science, SLAC National Accelerator Laboratory Department of Structural Biology School of Medicine Stanford University The International Structural Genomics Organization Executive Committee Shigeyuki Yokoyama Dino Moras Joel Sussman Jennifer Martin Aled Edwards Tom Terwilliger
[ccp4bb] International Conference on Structural Genomics - Structural Life Science, Sapporo, Japan, July 29-Aug 1, 2013
Dear Colleagues: On behalf of the organizing committee of the International Conference on Structural Genomics 2013 – Structural Life Science – (ICSG2013-SLS), we cordially welcome you to the conference, to be held in Sapporo, Hokkaido, Japan, July 29th – August 1st, 2013. ICSG2013-SLS is intended to provide an overview for the most recent developments in Structural Genomics and its impact on research in biology, medicine and disease, and to foster international collaboration among researchers. You can see all the details of the conference at: http://www.c-linkage.co.jp/ICSG2013 . Registration for the conference is now open. The scientific topics covered in ICSG2013-SLS include the wider life science research fields with particular attention to drug discovery (small molecules and biopharmaceuticals), biotechnology and industrial issues while keeping strength in the high-throughput technologies and integration of hybrid methods. These technologies are now leading to the new field of “Structural Life Science”. ICSG2-13-SLS is partially supported by the Grant-in-Aid for Scientific Research on Innovative Areas; “Structural Cell Biology”, “Intrinsically Disordered Protein” and “Transient Macromolecular Complexes”, from Ministry of Education, Culture, Sports, Science and Technology (MEXT) . In order to widen the opportunity to young and enthusiastic fellows to study more, we have organized several satellite workshops before ICSG2013- SLS. The topics will include “Small molecule screening”, “Automation of X-ray Structure Determination”, “Cell-free Protein Production”, “Automated NMR methods”, Eukaryotic expression, “Interaction analyses and Bioinformatics”. We hope you also find the satellite workshops are informative and productive. The conference will be held in Keio Plaza Hotel Sapporo, in walking distance of Hokkaido University's main campus and Sapporo station. The summer in Sapporo is a great time to stay and enjoy the cool summer night of Japan. We are looking forward to welcoming you to Sapporo in the summer of 2013. Sincerely yours, Katsumi Maenaka, Ph.D. Chair, International Conference on Structural Genomics 2013 -Structural Life Science- (ICSG2013-SLS) Laboratory of Biomolecular Science and Center for Research and Education on Drug Discovery, Faculty of Pharmaceutical Sciences, Hokkaido University, Japan Soichi Wakatsuki Chair of Program Committee, ICSG2013-SLS Photon Science, SLAC National Accelerator Laboratory Department of Structural Biology School of Medicine Stanford University
Re: [ccp4bb] a challenge
Hi James, As an aside (as your point is looking for a John Henry, not investigating automated model-building) I would point out that it is not uncommon at all to find cases where a very small difference in starting parameters or starting phases leads to a very different final result in automated model-building. I suspect that this comes from the discrete nature of model-building: an atom goes either here or there and every time you put in something you have branched the search...then when this model is used in calculating a map you get a new map that depends on the exact branching...so that small starting perturbations can become amplified. As you have found a way to automatically build possible.mtz I would expect that some small change in parameters or software would solve the impossible one too (not that one could necessarily find this change easily). All the best, Tom T On Jan 11, 2013, at 12:13 PM, James Holton wrote: I have a challenge for all those expert model-builders out there: can you beat the machine? It seems these days that everything is automated, and the only decision left for a crystallographer to make is which automation package to use. But has crystallography really been solved? Is looking at maps now no more interesting than playing chess, or any of the other once noble pursuits of human beings that we no longer see as challenging because someone built a machine that can do the job better than any of us? I think not. But I need your help to prove it. Specifically, the phases in this file: http://bl831.als.lbl.gov/~jamesh/challenge/possible.mtz when fed with the right set of parameters into the best model building package I have available to me actually does converge to the correct structure, with nice low R/Rfree. However, THIS file: http://bl831.als.lbl.gov/~jamesh/challenge/impossible.mtz contains the same amplitudes but very slightly different phases from those in possible.mtz above, and this file invariably leads to abysmal failure of every model-building package I have tried. Short of cheating (aka using molecular replacement with the right ansswer: 3dko), I don't think there is any automated way to arrive at a solved structure from impossible.mtz. What is interesting about this is how remarkably similar these two maps are. In fact, the correlation coefficient between them is 0.92. And yet, one can be solved automatically, and the other can't. More details can be found on the web page: http://bl831.als.lbl.gov/~jamesh/challenge/ But, my question for the CCP4BB is: Are there any John Henrys left out there who can still beat the machine? Anyone? -James Holton MAD Scientist
[ccp4bb] Postdoctoral position at Los Alamos in crystallization engineering
Dear all, A postdoctoral position is available in Geoff Waldo's group at Los Alamos working on a program project to create new protein reagents that can enhance macromolecular crystallization. The project leaders are Geoff Waldo, Todd Yeates, David Eisenberg, Andrew Bradbury and myself. If you are interested, please contact Geoff Waldo at gfpg...@gmail.com! All the best, Tom T Postdoctoral Fellow at Los Alamos National Laboratory We are seeking an outstanding postdoctoral candidate (background in molecular biology, protein chemistry, protein structure modeling) who will create new protein reagents to assist crystallization of macromolecules. This position will support a multi-investigator NIH P01 interdisciplinary project to overcome barriers to crystallization, the major bottleneck in structure determination of macromolecules and their complexes. This position is available immediately. Required Skills: A strong background in one or more of the following areas. Biology: molecular biology, protein expression and purification, or phage/yeast display, making and using protein expression libraries in E. coli or yeast. Highly desirable: protein design structural modeling and a strong foundation in protein molecular biology, with experience working closely with experimental teams. Other general requirements include: demonstrated record of scientific achievement through publications and presentations, strong problem-solving skills, and ability to conduct research independently. Education: A Ph.D. Biology, Biophysics, Biochemistry, or equivalent completed within the last five years or soon to be completed. Notes to Applicants: For further information about the position and project, please contact Dr. Geoffrey S. Waldo (gfpg...@gmail.commailto:gfpg...@gmail.com). Other investigators on the project include Drs. Thomas Terwilliger, Todd Yeates, Andrew R. M. Bradbury, David Eisenberg.
Re: [ccp4bb] IUCr committees, depositing images
For those who may not have made it through all the CCP4bb postings in October-December 2011 on archiving raw images, I have posted a summary at the IUCR Diffraction Data Deposition Working Group forum page http://forums.iucr.org/viewforum.php?f=21 in which I have attempted to list the unique points made during the discussion, along with links to some of the original postings. All the best, Tom T Tom Terwilliger terwilli...@lanl.gov
