- phenixbb - phenix-online.org

Extending a structure
by E Artikis 10 Sep '21

10 Sep '21

I have a pdb with a fibril composed of three identical chains. I'd like to expand the fibril from three to 15 chains. Is there a way to do this? It's essentially a copy/paste action, but I can't figure it out. Thanks!

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Phenix opens COOT but does not load map or model
by Boniecki, Michal 08 Sep '21

08 Sep '21

Hello, I used to be able (with previous phenix versions) load models into COOT after refinement. Now when I click open in COOT, only COOT window is open but neither maps or model are loaded.Also there is no "connected to phenix' displayed in COOT sidebar I have no problems with loading and displaying both in phenix or pymol (open with phenix or open with pymol buttons). Any suggestions how to solve it would be appreciated. COOT 0.9.5, phenix 1.19.2-4158 Michal

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Job posting: Scientist (crystallography) at Frederick National Laboratory for Cancer Research
by Dhirendra K Simanshu 08 Sep '21

08 Sep '21

Hello everyone, The Frederick National Laboratory for Cancer Research is looking for a Scientist with experience in protein chemistry and structural biology (crystallography). The candidate will join the structural biology group within the NCI RAS Initiative program and work on the protein-protein and protein-small molecule complexes. For detailed information and to apply for this position, please use this link: https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leido… Best regards Dhirendra Simanshu -- Dhirendra Simanshu Principal Scientist, Team Lead - RAS Structural Biology NCI RAS Initiative Frederick National Laboratory for Cancer Research 8560 Progress Drive, C1012, Frederick, MD 21701 Dhirendra.Simanshu(a)fnlcr.nih.gov <Dhirendra.Simanshu(a)nih.gov>

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IUCr’s Committee on Data recent meeting minutes now online
by John R Helliwell 06 Sep '21

06 Sep '21

Dear Colleagues, I imagine that you will be interested in the IUCr’s Committee on Data recent meeting minutes which are now online here:- https://forums.iucr.org/viewtopic.php?f=39&t=441 Best wishes, John Emeritus Professor John R Helliwell DSc Chairman IUCr Committee on Data

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copy R-free array from reference mtz using command line?
by Aaron Thompson 30 Aug '21

30 Aug '21

PhenixBB, I know this can be done via GUI, but is it possible to copy the R-free array from a reference mtz to a new mtz using the command line? I don’t see this as an option in phenix.reflection_file_converter. Thank you, Aaron

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NORA workshop on AlphaFold2 and RoseTTAFold, 31 August and 1 September
by Randy John Read 27 Aug '21

27 Aug '21

Hi, I’ve just learned that this online workshop is generally open, not just to members of the Norwegian Artificial Intelligence Consortium (NORA), and it’s free! Information, including the current programme and a link to registration, can be found here: https://www.nora.ai/events/AlphaFoldv2.0-and-RoseTTAFold-workshop%20.html I’ll be talking a bit about experiences with models from AlphaFold2 and RoseTTAFold, but the real draw should be talks by people who really understand these two deep learning algorithms: Minkyung Baek (first author on the RoseTTAFold paper, from David Baker’s group) and a representative of the DeepMind team that developed the two versions of AlphaFold. Sameer Velankar will also be there to talk about the exciting new AlphaFold database at the EBI. Best wishes, Randy Read ----- Randy J. Read Department of Haematology, University of Cambridge Cambridge Institute for Medical Research Tel: +44 1223 336500 The Keith Peters Building Fax: +44 1223 336827 Hills Road E-mail: rjr27(a)cam.ac.uk Cambridge CB2 0XY, U.K. www-structmed.cimr.cam.ac.uk

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Re: [phenixbb] NORA workshop on AlphaFold2 and RoseTTAFold, 31 August and 1 September
by Randy John Read 27 Aug '21

27 Aug '21

9 am CEST (Norway). Pretty early for our North American colleagues, especially those on the west coast! > On 27 Aug 2021, at 05:18, Robert Rose <rbrose2(a)ncsu.edu> wrote: > > Does the workshop start on August 31 at 9 am GMT? > > On Thu, Aug 26, 2021 at 2:27 PM Randy John Read <rjr27(a)cam.ac.uk> wrote: > Hi, > > I’ve just learned that this online workshop is generally open, not just to members of the Norwegian Artificial Intelligence Consortium (NORA), and it’s free! Information, including the current programme and a link to registration, can be found here: > > https://www.nora.ai/events/AlphaFoldv2.0-and-RoseTTAFold-workshop%20.html > > I’ll be talking a bit about experiences with models from AlphaFold2 and RoseTTAFold, but the real draw should be talks by people who really understand these two deep learning algorithms: Minkyung Baek (first author on the RoseTTAFold paper, from David Baker’s group) and a representative of the DeepMind team that developed the two versions of AlphaFold. Sameer Velankar will also be there to talk about the exciting new AlphaFold database at the EBI. > > Best wishes, > > Randy Read > > ----- > Randy J. Read > Department of Haematology, University of Cambridge > Cambridge Institute for Medical Research Tel: +44 1223 336500 > The Keith Peters Building Fax: +44 1223 336827 > Hills Road E-mail: rjr27(a)cam.ac.uk > Cambridge CB2 0XY, U.K. www-structmed.cimr.cam.ac.uk > > > _______________________________________________ > phenixbb mailing list > phenixbb(a)phenix-online.org > http://phenix-online.org/mailman/listinfo/phenixbb > Unsubscribe: phenixbb-leave(a)phenix-online.org ----- Randy J. Read Department of Haematology, University of Cambridge Cambridge Institute for Medical Research Tel: +44 1223 336500 The Keith Peters Building Fax: +44 1223 336827 Hills Road E-mail: rjr27(a)cam.ac.uk Cambridge CB2 0XY, U.K. www-structmed.cimr.cam.ac.uk

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Peptide bond to symmetry related molecule
by Damian Ekiert 23 Aug '21

23 Aug '21

Hi All, We are refining several structures in which the N-terminal residue of chain A appears to form a peptide bond to the C-terminal residue of its symmetry mate, chain A. In reality, the target protein consists of 4 identical helical repeats that pack end to end. Slippage and averaging over the 4 possible registers leads to the appearance of an infinitely long polymer in the crystal, with no breaks between protomers. Is it possible to enforce a peptide bond to symmetry mates in Phenix, and what is the easiest way to do this? I have found a several cases in the archives on how to deal with symmetry clashes, but struggling to figure out how to deal with a peptide bond. Thanks for your help! Best, Damian - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Damian Ekiert Assistant Professor Skirball Institute | NYU School of Medicine Depts. Cell Biology and Microbiology damian.ekiert(a)ekiertlab.org www.bhabhaekiertlab.org

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Postdoctoral position in Computational Biochemistry
by Yasser Almeida 23 Aug '21

23 Aug '21

Dear all, The group of Computational Biochemistry of Prof. Elsa Sánchez-García at the University of Duisburg-Essen is announcing a Postdoc position focused on the computational design of chemical tools and inhibitors for the study of proteins and protein-protein interactions involved in cell state transition. The deadline for applications has been changed to September 30th. More information can be found at https://www.uni-due.de/computational-biochemistry. Best regards, Yasser -- Dr. Yasser Almeida-Hernandez Postdoctoral Researcher Computational Biochemistry group T01 R03 D45 Faculty of Biology University of Duisburg-Essen Universitätsstr. 2, 45117 Essen Email: yasser.almeida-hernandez(a)uni-due.de <%20yasser.almeida-hernandez(a)uni-due.de> Phone: +49 201 183 2457

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Project Scientist and Postdoctoral research positions in XFEL, ML, and material science computational methods
by Aaron Brewster 18 Aug '21

18 Aug '21

Hello, I'm excited to announce that two positions are immediately open in my group in the fields of material science, serial X-ray crystallography, and machine learning. Links to postings: Computational Project Scientist - https://lbl.taleo.net/careersection/2/jobdetail.ftl?job=93507 Computational Postdoctoral Scholar - https://lbl.taleo.net/careersection/2/jobdetail.ftl?job=93506 In these exciting roles, you will work in the Molecular Biophysics and Integrated Bioimaging Division on a project that will research adding advanced spatial and symmetry aware neural network training methods to small-molecule chemical crystallography and material science data processing. This will use AI methods developed as part of a close collaboration between teams at Lawrence Berkeley National Labs (LBNL), University of Connecticut, and MIT. The larger group is researching crystal engineering of hybrid coordination polymers towards achieving rational control over the optoelectronic properties of low-dimensional nanostructures. These positions are focused on the chemical crystallography aspect of the program, but the successful candidates will be expected to participate in all aspects of the program, including data collection at X-ray free electron lasers worldwide, data analysis on supercomputing facilities, structure solution, research on AI driven structure prediction, paper writing, and software management. Both roles are 3 year appointments. This work will be part of the Department of Energy Integrated Computational and Data Infrastructure for Science <https://insidehpc.com/2021/08/doe-funds-15m-for-integrated-computational-an…> Research program. Specific details follow. Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA) <https://diversity.lbl.gov/ideaberkeleylab/> and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab’s mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. *Computational Project Scientist* *What You Will Do:* - Design and train neural networks that allow determination of the unit cell and crystal orientations of small molecule crystals from sparse, randomly oriented diffraction patterns. This will involve curating training sets from simulated datasets and from existing and new experimental data that will be collected. - Research methods to scale training and use of these neural networks on multiple nodes in high performance computing environments. - Lead data collection and processing at X-ray free electron sources. - Maintain a detailed record of work performed. - Document and manage code developed using standard source control methods. - Publish in peer-reviewed journals. - Present research at seminars and conferences. - Assist Principal Investigator in developing grant proposals. - Document and maintain existing and new data processing software, including the cctbx build system. *What is Required:* - 2-5 years of relevant experience beyond the highest degree in Physics, Statistics, Crystallography, Artificial Intelligence, or a related field. - A strong background in Python, C++, or an equivalent platform for scientific computing. - A track record of critical thinking, problem solving, and mathematical intuition, demonstrated through publications and presentations. *Desired Qualifications:* - Familiarity with general Python scientific data packages such as NumPy, SciPy, and pandas. - Versed in modern coding practices for scientific computing, including algorithm design and evaluation, source code management under a revision control system like git, and incorporation of readable documentation and comments. - Expertise in computational approaches in at least one of the areas related to the research is required, including but not limited to small-molecular crystallography, structure solution and refinement, unit cell determination, neural network design, training, and evaluation, high speed computing, image analysis, large dataset analysis, graph theory, error propagation and statistics, signal processing, and GPU acceleration. - Familiarity with small-molecule material design and synthesis. - Strong analytical and organizational skills. - Excellent interpersonal, oral, and written communication skills. - Ability to work independently as well as part of a diverse team. *Computational **Postdoctoral Scholar* *What You Will Do:* - Design and train neural networks to model diffraction from small molecule crystals. This will involve curating training sets from simulated datasets and from existing and new experimental data that will be collected. - Assist in data collection and processing at X-ray free electron sources. - Maintain a detailed record of work performed. - Document and manage code developed using standard source control methods. - Publish in peer-reviewed journals. - Present research at seminars and conferences. * What is Required:* - PhD degree in Physics, Statistics, Crystallography, Artificial Intelligence, or a related field. - Experience in computational approaches in at least one of the areas related to the research, including but not limited to small-molecular crystallography, structure solution and refinement, unit cell determination, neural network design, training, and evaluation, high speed computing, image analysis, large dataset analysis, graph theory, error propagation and statistics, signal processing, and GPU acceleration. - Strong analytical and organizational skills. - Excellent interpersonal, oral, and written communication skills. - Ability to work independently as well as part of a diverse team. * Desired Qualifications:* - Familiarity with Python, C++, and general scientific data packages such as NumPy, SciPy, and pandas. - Familiarity with small-molecule material design and synthesis. Please do not hesitate to reach out to me for more information. Thank you, Aaron S. Brewster, PhD Computational Research Scientist, Molecular Biophysics and Integrated Bioimaging Division Lawrence Berkeley National Laboratory 1 Cyclotron Rd., Bldg. 33R0345 Berkeley, CA 94720

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