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Faculty Positions in Structural Biology at Purdue University
by Noinaj, Nicholas 27 Jan '16

27 Jan '16

PHENIXbb, I wanted to bring to your attention that our Structural Biology group here at Purdue University is looking to hire three new faculty members at the Assistant (tenure-track), Associate, and Full Professor ranks, as outlined in the job ad. The official ad from Science can be accessed via this link (copied below as well): http://jobs.sciencecareers.org/job/391248/faculty-positions-in-structural-b… It is important to also add that Purdue University has just made a HUGE investment of more than $250 million to life sciences over the next five years to advance research. http://www.purdue.edu/newsroom/releases/2016/Q1/purdue-to-invest-more-than-… As a new faculty member myself, I can attest that Purdue is an amazing place to do research! We have all the resources needed to do cutting-edge studies in structural biology on many types of projects including drug discovery, enzymes, viruses, protein assemblies and complexes, membrane proteins, and more. Please forward this email to others who may be interested and/or actively looking for a faculty position, but not on PHENIXbb or CCP4bb. Thanks in advance! Cheers, Nick ------------------------------- Nicholas Noinaj 240 S. Martin Jischke Dr. Hockmeyer Building of Structural Biology, Rm 333 Dept. of Biological Sciences, Purdue Univ. West Lafayette, IN 47907 765-496-0061 (office) 765-496-0059 (wetlab) +++++++++++++++++ Faculty Positions in Structural Biology Markey Center for Structural Biology Department of Biological Sciences The Department of Biological Sciences, Purdue University, is initiating a major effort to expand its investment in Structural Biology and invites applicants at all academic professorial levels to fill multiple new tenure-track faculty positions in this accelerating area. The Structural Biology Group at Purdue is recognized worldwide for its leadership in structural biology of viruses, membrane proteins, and technical approaches to crystallographic and electron microscopy challenges. Creative investigators in a variety of research approaches, X-ray crystallography, NMR spectroscopy and electron microscopy, are sought to enhance these current structural investigations. Potential areas of research interest include but are not limited to studies of viruses and other pathogens, membrane proteins, cancer biology, target molecules for structure-based drug discovery and development of new technologies in structural biology. This position is aligned with major campus-wide investments in the life sciences including the Center for Drug Discovery (https://www.purdue.edu/research/pcdd/), the Center for Integrative Neurosciences and the Institute for Inflammation, Immunology and Infectious Disease (https://www.purdue.edu/research/life-sciences/). Applicants for senior positions in Structural Biology must have a Ph.D. or equivalent in an appropriate discipline and currently hold a position equivalent to an Associate or Full Professor. Structural biologists with a clear cancer focus in their research will also be considered by the Purdue Center for Cancer Research as a Walther Cancer Professor (https://www.cancerresearch.purdue.edu). Applicants at the junior rank in Structural Biology must have a Ph.D. or equivalent in an appropriate discipline and at least 2 years of postdoctoral experience. There is particular interest in researchers trained in single particle cryo-electron microscopy or whole cell electron tomography. Successful applicants for these positions are expected to direct a dynamic and collaborative research program in structural biology to address fundamental questions in the area of human disease, to excel at teaching at the undergraduate and/or graduate level and participate in ongoing programs at Purdue. Extensive opportunities for collaboration exist within the Department, which has over 50 faculty members conducting research in neurobiology, virology, microbiology, molecular and cell biology, bioinformatics, evolutionary biology and ecology (http://www.bio.purdue.edu/). These opportunities are enhanced by a highly interactive community of scientists within the Colleges of Science, Pharmacy, Veterinary Medicine and Engineering and existing and emerging interdisciplinary centers in the life sciences. Abundant infrastructure support for structural biology exists, including advanced imaging analysis and biophysical instrumentation available in established core facilities at the Bindley Bioscience Center and the Birck Nanotechnology Center in Discovery Park (http://www.purdue.edu/discoverypark/). Applications should be submitted electronically to https://hiring.science.purdue.edu/ as a single PDF file containing a letter of interest, a detailed curriculum vitae, contact information for three references, a two to three page summary of research interests, and a one-page teaching statement. The Department of Biological Sciences is committed to advancing diversity in all areas of faculty effort - scholarship, instruction and engagement. Candidates should address at least one of these areas in their cover letter, including past experience, current activity and/or future goals to promote a climate that values diversity and inclusion. As an ADVANCE institution, Purdue University is dedicated to the recruitment, retention and advancement of women in the STEM disciplines. Inquiries should be directed to Cynthia Stauffacher, Chair, Structural Biology Search Committee StructureSearch(a)bio.purdue.edu<mailto:[email protected]> Structural Biology Search Committee Department of Biological Sciences Purdue University, 915 W. State St., West Lafayette, IN 47907-2054. Review of applications will begin December 15, 2015 and continue until these positions are filled. A background check is required for employment in this position. Purdue University is an EOE/Affirmative Action Employer. All qualified applicants, including minorities, women, individuals with disabilities and veterans are encouraged to apply. +++++++

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postdoctoral position MRC Laboratory of Molecular Biology
by Roger Williams 27 Jan '16

27 Jan '16

A three-year postdoctoral position is available with the group of Roger Williams at the MRC Laboratory of Molecular Biology in Cambridge, UK. The project, which is funded by Cancer Research UK is aimed at understanding structural mechanisms of regulation of the target of rapamycin complexes. Specifically to undertake research to investigate the structures and regulation of the mTORC1 complex assembled with its regulators on lysosomal membranes. The objective is to determine the structures of mTORC1 in complexes with its regulators and to understand how these complexes assemble on lysosomal membranes. Methods involved in the study include large scale mammalian cell culture, cryo-electron microscopy; X-ray crystallography; hydrogen-deuterium exchange mass spectrometry; biophysical measurements of assembly on membranes by confocal microscopy, flow cytometry and single-molecule fluorescence; and enzyme assays. The candidate should have a Ph.D. degree or due to complete doctoral studies within 6 months of applying. It is essential that the candidate has an enthusiasm for structural biology. Experience with electron microscopy, X-ray crystallography, mass spectrometry or large scale eukaryotic expression systems would be desirable, but a motivated candidate could learn any or all of these. The MRC Laboratory of Molecular Biology is one of the birthplaces of modern molecular biology and has amazing support for all aspects of structural biology. For full details, see the MRC link https://mrc.tal.net/vx/mobile-0/appcentre-ext/brand-3/candidate/so/pm/4/pl/… <https://mrc.tal.net/vx/mobile-0/appcentre-ext/brand-3/candidate/so/pm/4/pl/…> or contact Roger Williams: email rlw(a)mrc-lmb.cam.ac.uk <mailto:[email protected]> or phone: +44 1223 267094 Dr. Roger Williams, FMedSci rlw(a)mrc-lmb.cam.ac.uk <mailto:[email protected]> MRC Laboratory of Molecular Biology Francis Crick Avenue Cambridge Biomedical Campus Cambridge CB2 0QH UK Phone: +44 1223 267094

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Job opportunity at the NKI
by Anastassis Perrakis 27 Jan '16

27 Jan '16

We are looking for an enthusiastic co-worker who recently got a PhD in Structural Biology and has strong working experience in X-ray crystallography and a clear interest in cell biology mechanisms, aspiring to connect molecular chemistry and structure to the inner workings of a cell, using a wide portfolio of approaches. You will study with us the mechanisms that ensure correct chromosome segregation during cell division in a project with a two-fold scope. First, in collaboration with the group of Geert Kops (Hubrecht Institute) we want to determine new structures and understand the function of proteins that control spindle checkpoint signaling. Second, in collaboration with the EMBL Grenoble Unit and the Diamond Light Source in the iNEXT (www.inext-eu.org <http://www.inext-eu.org/>) project, we want to establish, benchmark and extend fragment-based screening, using as our major targets mitotic proteins we work on. The two projects are scientifically coherent and significant preliminary work is in place. You will be responsible for designing and executing all experiments as part of a small but lively team. The project will be supported by the NKI Protein Facility and state of the art instrumentation for expressing, purifying and crystallising proteins (including robotics), as well as a wealth of biophysical equipment, including surface plasmon resonance, microscale thermophoresis, isothermal titration calorimetry, fluorescence measurement, and light scattering. The NKI also offers a Robotics and Screening Centre, a Genomics core, Proteomics, Peptide synthesis, and Microscopy facilities. The group is hosted in the Department of Biochemistry, a diverse and lively environment with enthusiastic colleagues. The NKI is an integrated hospital and research centre for cancer, and is located within minutes from the centre of Amsterdam and it’s cultural amenities. The temporary employment will be for an initial period of 2 years. The gross salary per month will be ~3,300 Euro, according to the FWG-function group 55.6, or higher depending on previous experience. Foreigners are entitles to a 30% tax break, subject to a decision of the tax authorities. For further information please contact Anastassis Perrakis, a.perrakis(a)nki.nl <mailto:[email protected]>, or send directly your CV including the names of three referees, no later than 19 February. Anastassis (Tassos) Perrakis, Principal Investigator / Staff Member Department of Biochemistry (B8) Netherlands Cancer Institute, Dept. B8, 1066 CX Amsterdam, The Netherlands Tel: +31 20 512 1951 Fax: +31 20 512 1954 Mobile / SMS: +31 6 28 597791

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Re: [phenixbb] [ccp4bb] Modify methionine to acetylated methionine in coot
by Anshul Bhardwaj 26 Jan '16

26 Jan '16

Thanks Paul for the quick response. Simple enough and works beautifully for modifying N-terminus methionine to AME in coot. Anshul Bhardwaj ________________________________________ From: Paul Emsley <pemsley(a)mrc-lmb.cam.ac.uk> Sent: Monday, January 25, 2016 7:39 PM To: Anshul Bhardwaj; COOT(a)jiscmail.ac.uk Subject: Re: [ccp4bb] Modify methionine to acetylated methionine in coot On 25/01/2016 23:33, Anshul Bhardwaj wrote: > Hello, Hello. > How to replace 'M' with 'AME' in coot itself? an option like mutate residue, etc. > I couldn't figure out right away so I worked my way around by simply copying AME from one of the pdb from RCSB database and replaced methionine in my model. Linked AME to residue# 2 in coot and refinement was straightforward after generating restraints for the modified model. So it worked for now but still curious as there has to be a way to replace 'M' with 'AME' in coot, isn't it (?). > Generally, for this sort of thing one would use: Extensions -> Modelling -> Replace Residue -> AME But this might not work in the case because the modification is on the main-chain not the side-chain. But it might do if the AME is at the N-terminus. This thread might shed some light on things: https://www.mail-archive.com/[email protected]/msg02536.html Paul. The information contained in this transmission contains privileged and confidential information. It is intended only for the use of the person named above. If you are not the intended recipient, you are hereby notified that any review, dissemination, distribution or duplication of this communication is strictly prohibited. If you are not the intended recipient, please contact the sender by reply email and destroy all copies of the original message. CAUTION: Intended recipients should NOT use email communication for emergent or urgent health care matters.

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Modify methionine to acetylated methionine in coot
by Anshul Bhardwaj 26 Jan '16

26 Jan '16

Hello, How to replace 'M' with 'AME' in coot itself? an option like mutate residue, etc. I couldn't figure out right away so I worked my way around by simply copying AME from one of the pdb from RCSB database and replaced methionine in my model. Linked AME to residue# 2 in coot and refinement was straightforward after generating restraints for the modified model. So it worked for now but still curious as there has to be a way to replace 'M' with 'AME' in coot, isn't it (?). Thanks, Anshul Bhardwaj P.S. Hope it's okay to cross-post on both ccp4bb and phenixbb to get an answer quickly. The information contained in this transmission contains privileged and confidential information. It is intended only for the use of the person named above. If you are not the intended recipient, you are hereby notified that any review, dissemination, distribution or duplication of this communication is strictly prohibited. If you are not the intended recipient, please contact the sender by reply email and destroy all copies of the original message. CAUTION: Intended recipients should NOT use email communication for emergent or urgent health care matters.

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Coot 3D for Geforce GTX 970 Graphics card on Windows 7 and Fedora
by Xiao Lei 26 Jan '16

26 Jan '16

Hi Phenixbb members, My lab has a desktop PC which has Windows 7 with Geforce GTX 970 Graphics card, is this card ok for the Coot 3D function with 3D monitor and Nvidia 3D kit? Do I need to do some settings before I can use the Coot 3D function? I'm also thinking installing Fedora 23 on the PC and use coot 3D, is there any settings in the Fedora environment before using coot 3D? Thanks ahead.

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Changing NCS groups
by Marie Elizabeth Fraser 26 Jan '16

26 Jan '16

Hello, I would like to edit the NCS information for a model with two chains. I've tried running find_ncs and editing the phil file, but I get an error when I try to use my edited file in the next cycle of refinement. I've tried using the utility to detect NCS groups, then edited in the little windows - also no success. How are other people defining NCS when they aren't content with the equivalences the program finds? Thank you for your insight, Marie

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Xtriage systematic results is not consistent with HKL2000
by Alex Lee 24 Jan '16

24 Jan '16

Dear All, I scaled a dataset of SG P2221 in HKL2000 and got systematic absence results as below, it seems clearly HKL2000 showed the data had systematic absence violations, but when I used the .sca file from HKL2000 as input in Xtriage, the result did not show any systematic violations. Which result should I rely on? HKL200 Results: Summary of reflections intensities and R-factors by shells R linear = SUM ( ABS(I - <I>)) / SUM (I) R square = SUM ( (I - <I>) ** 2) / SUM (I ** 2) Chi**2 = SUM ( (I - <I>) ** 2) / (Error ** 2 * N / (N-1) ) ) In all sums single measurements are excluded Shell Lower Upper Average Average Norm. Linear Square limit Angstrom I error stat. Chi**2 R-fac R-fac Rmeas Rpim CC1/2 CC* 50.00 5.60 2819.0 103.7 44.8 0.607 0.033 0.040 0.037 0.017 0.998 0.999 5.60 4.45 1801.5 63.8 28.1 0.914 0.043 0.050 0.048 0.022 0.997 0.999 4.45 3.88 1435.3 52.6 25.5 0.980 0.048 0.051 0.054 0.024 0.997 0.999 3.88 3.53 738.7 31.8 20.5 1.117 0.068 0.067 0.075 0.032 0.996 0.999 3.53 3.28 489.7 26.5 20.1 1.134 0.092 0.080 0.102 0.043 0.996 0.999 3.28 3.08 236.3 19.8 17.4 0.975 0.147 0.108 0.162 0.069 0.993 0.998 3.08 2.93 93.4 16.4 16.0 0.850 0.296 0.277 0.327 0.138 0.947 0.986 2.93 2.80 62.9 16.3 16.0 0.737 0.422 0.384 0.467 0.197 0.921 0.979 2.80 2.69 42.6 16.7 16.5 0.677 0.622 0.515 0.688 0.291 0.879 0.967 2.69 2.60 29.3 20.0 19.9 0.680 0.924 0.842 0.000 0.440 0.659 0.891 All reflections 798.1 37.4 22.6 0.873 0.064 0.050 0.068 0.031 Intensities of systematic absences h k l Intensity Sigma I/Sigma 0 0 3 -0.4 1.3 -0.3 0 0 5 10.4 3.0 3.5 0 0 7 11.4 3.9 2.9 0 0 9 8.7 4.3 2.0 0 0 11 18.6 6.4 2.9 0 0 13 182.9 17.1 10.7 0 0 15 3.0 7.8 0.4 0 0 17 11.9 9.2 1.3 0 0 19 30.0 14.3 2.1 0 0 21 7.4 11.1 0.7 0 0 23 54.2 15.6 3.5 0 0 25 43.1 16.1 2.7 0 0 27 12.5 18.9 0.7 0 0 29 -16.6 20.9 -0.8 0 0 31 31.0 25.4 1.2 0 0 33 3.4 29.2 0.1 0 0 35 -24.2 32.0 -0.8 0 0 37 50.9 42.5 1.2 0 0 39 -53.3 66.4 -0.8 0 0 41 65.8 50.6 1.3 0 0 43 -24.3 46.8 -0.5 0 0 45 -6.1 48.3 -0.1 0 0 47 -14.8 45.8 -0.3 0 0 49 1.1 53.5 0.0 0 0 51 -7.9 64.2 -0.1 Phenix Xtriage Results: ----------Space group identification---------- Analyses of the absences table indicates a number of likely space group candidates, which are listed below. For each space group, the number of systematic absence violations are listed under the '+++' column. The number of non-absence violations (weak reflections) are listed under '---'. The last column is a likelihood based score for the particular space group. Note that enantiomorphic spacegroups will have equal scores. Also, if absences were removed while processing the data, they will be regarded as missing information, rather then as enforcing that absence in the space group choices. ------------------------------------------------------------------------------------- | space group | # absent | <Z>_absent | <Z/sigZ>_absent | +++ | --- | score | ------------------------------------------------------------------------------------- | P 2 2 2 | 0 | 0.00 | 0.00 | 0 | 4 | 0.000e+00 | | P 2 2 21 | 0 | 0.00 | 0.00 | 0 | 4 | 0.000e+00 | | P 2 21 2 | 5 | 3.07 | 16.77 | 5 | 4 | 1.038e+01 | | P 2 21 21 | 5 | 3.07 | 16.77 | 5 | 4 | 1.038e+01 | | P 21 2 2 | 5 | 1.89 | 15.21 | 5 | 4 | 1.250e+01 | | P 21 2 21 | 5 | 1.89 | 15.21 | 5 | 4 | 1.250e+01 | | P 21 21 2 | 10 | 2.48 | 15.99 | 10 | 4 | 2.288e+01 | | P 21 21 21 | 10 | 2.48 | 15.99 | 10 | 4 | 2.288e+01 | ------------------------------------------------------------------------------------- ----------List of individual systematic absences---------- Note: this analysis uses the original input data rather than the filtered data used for twinning detection; therefore, the results shown here may include more reflections than shown above. P 2 2 2: no systematic absences possible P 2 2 21 (input space group): no absences found P 21 2 2 ( 5, 0, 0): i/sigi = 21.0 ( 7, 0, 0): i/sigi = 4.8 ( 9, 0, 0): i/sigi = 14.3 ( 11, 0, 0): i/sigi = 15.2 ( 13, 0, 0): i/sigi = 18.3 ( 15, 0, 0): i/sigi = 12.7 ( 17, 0, 0): i/sigi = 4.1 P 2 21 2 ( 0, 3, 0): i/sigi = 21.3 ( 0, 5, 0): i/sigi = 21.4 ( 0, 7, 0): i/sigi = 20.7 ( 0, 9, 0): i/sigi = 21.4 ( 0, 11, 0): i/sigi = 20.7 ( 0, 13, 0): i/sigi = 14.5 ( 0, 17, 0): i/sigi = 10.4 ( 0, 21, 0): i/sigi = 14.4 ( 0, 23, 0): i/sigi = 0.8 ( 0, 25, 0): i/sigi = 2.3 ( 0, 27, 0): i/sigi = 2.0 P 21 21 2 ( 0, 3, 0): i/sigi = 21.3 ( 0, 5, 0): i/sigi = 21.4 ( 0, 7, 0): i/sigi = 20.7 ( 0, 9, 0): i/sigi = 21.4 ( 0, 11, 0): i/sigi = 20.7 ( 0, 13, 0): i/sigi = 14.5 ( 0, 17, 0): i/sigi = 10.4 ( 0, 21, 0): i/sigi = 14.4 ( 0, 23, 0): i/sigi = 0.8 ( 0, 25, 0): i/sigi = 2.3 ( 0, 27, 0): i/sigi = 2.0 ( 5, 0, 0): i/sigi = 21.0 ( 7, 0, 0): i/sigi = 4.8 ( 9, 0, 0): i/sigi = 14.3 ( 11, 0, 0): i/sigi = 15.2 ( 13, 0, 0): i/sigi = 18.3 ( 15, 0, 0): i/sigi = 12.7 ( 17, 0, 0): i/sigi = 4.1 P 2 21 21 ( 0, 3, 0): i/sigi = 21.3 ( 0, 5, 0): i/sigi = 21.4 ( 0, 7, 0): i/sigi = 20.7 ( 0, 9, 0): i/sigi = 21.4 ( 0, 11, 0): i/sigi = 20.7 ( 0, 13, 0): i/sigi = 14.5 ( 0, 17, 0): i/sigi = 10.4 ( 0, 21, 0): i/sigi = 14.4 ( 0, 23, 0): i/sigi = 0.8 ( 0, 25, 0): i/sigi = 2.3 ( 0, 27, 0): i/sigi = 2.0 P 21 2 21 ( 5, 0, 0): i/sigi = 21.0 ( 7, 0, 0): i/sigi = 4.8 ( 9, 0, 0): i/sigi = 14.3 ( 11, 0, 0): i/sigi = 15.2 ( 13, 0, 0): i/sigi = 18.3 ( 15, 0, 0): i/sigi = 12.7 ( 17, 0, 0): i/sigi = 4.1 P 21 21 21 ( 0, 3, 0): i/sigi = 21.3 ( 0, 5, 0): i/sigi = 21.4 ( 0, 7, 0): i/sigi = 20.7 ( 0, 9, 0): i/sigi = 21.4 ( 0, 11, 0): i/sigi = 20.7 ( 0, 13, 0): i/sigi = 14.5 ( 0, 17, 0): i/sigi = 10.4 ( 0, 21, 0): i/sigi = 14.4 ( 0, 23, 0): i/sigi = 0.8 ( 0, 25, 0): i/sigi = 2.3 ( 0, 27, 0): i/sigi = 2.0 ( 5, 0, 0): i/sigi = 21.0 ( 7, 0, 0): i/sigi = 4.8 ( 9, 0, 0): i/sigi = 14.3 ( 11, 0, 0): i/sigi = 15.2 ( 13, 0, 0): i/sigi = 18.3 ( 15, 0, 0): i/sigi = 12.7 ( 17, 0, 0): i/sigi = 4.1 Thanks ahead

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Change of PHIL definitions in phenix.find_alt_orig_sym_mate
by R.D. Oeffner 23 Jan '16

23 Jan '16

I have changed the PHIL definitions in this program from AltOrigSymMates.moving_pdb to AltOrigSymMates.moving.pdb and from AltOrigSymMates.fixed_pdb to AltOrigSymMates.fixed.pdb. I'm not sure if it is being used elsewhere but let me know if you encounter an error due to this. Regards, Rob

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anomalous completeness from Phenix Xtriage result
by Alex Lee 23 Jan '16

23 Jan '16

Dear All, After check my data with Phenix Xtriage, I got a warning of "the anomalous completeness is 42.34%". I do not know if I need to pay attention to this? I did not do experimental phasing and I did not add heavy metal to my crystal nor there is selenium on my protein. I even don't know why I still get the anomalous signal. But from the detailed summary below I guess in my case it's not a problem? ----------Summary---------- File name: P2_rejoutput.sca Data labels: I(+),SIGI(+),I(-),SIGI(-) Space group: P 1 2 1 Unit cell: 72.255, 46.617, 134.086, 90, 90.052, 90 Data type: xray.intensity Resolution: 49.1682 - 2.5855 Anomalous: True Number of reflections (non-anomalous): 27184 Completeness (non-anomalous): 95.42% Number of reflections (all): 38285 Completeness (all): 69.98% Anomalous completeness: 42.34% Completeness (non-anomalous) is the completeness of the data after merging Friedel pairs. Completeness (all) is the completeness of the data before merging Friedel pairs. Completeness (anomalous) is the completeness of the anomalous data. The anomalous completeness is calcluated by dividing the number of measured acentric, Bijvoet mates by the total possible number of acentric indices. Completeness (non-anomalous) should be used to determine if there is sufficient data for non-anomalous purposes (refinement, model-building). A value greater than 90% is generally desired, while a value less than 75% is considered poor. Values in between will provide less than optimal results. Completeness (anomalous) should be used to determine if there is sufficient data for anomalous purposes (phasing, finding anomalous atoms, refinement of anomalous occupancies or scattering factors). A value greater than 80% is generally desired, while a value less than 50% is considered poor. Values in between will provide less than optimal results. Thanks.

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