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Error from exceeding max reasonable bond distance
by Mullins, Elwood A. 13 Apr '22

13 Apr '22

I’m having an issue with a real-space refinement job crashing after giving the following error: "RuntimeError : Bond distance > max_reasonable_bond_distance: 62.8014 > 50". I found mention of this problem in a post from 2017. I tried the recommended solution (setting the max reasonable bond distance to 999), but that caused the job to hang. I also tried clicking “proceed with excessive length bonds”. That didn’t make a difference; I received the same error message. I ran validation on the model. There are no bond length outliers and only minor other issues. Any help would be greatly appreciated. Thanks, Elwood

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The lowest resolution score X-ray statics resolution bin is lower than overall datasets.
by Takebe Katsuki 11 Apr '22

11 Apr '22

Dear all, I am working on a 20 KD protein and We scaled the data sets 1.6Å. The lowest resolution score X-ray statics resolution bin is lower than overall datasets. Is this seriously problem? and How do I solve the problem? Could you give me some advice on this problem? DATA USED IN REFINEMENT. RESOLUTION RANGE HIGH (ANGSTROMS) : 1.600 RESOLUTION RANGE LOW (ANGSTROMS) : 44.488 　 [cid:[email protected]]

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2022 ACA session on AI predicted Models in Structural Biology/Crystallography
by Aaron Brewster 11 Apr '22

11 Apr '22

Hi all, we'd like to call your attention to the upcoming session at the 2022 ACA on the use of AI predicted Models in Structural Biology/Crystallography. We'd like to invite abstract submissions to this session from people, including early-career scientists, who have done difficult or interesting work using these AI predicted structural models, such as from AlphaFold2 and RoseTTAFold. We are very excited to hear what people are using these tools for and how the future might unfold in this new world of AI-aided structural analysis and design. Remember that the deadline to submit an abstract for talks is April 15, 2022@ 11:59 PM ET. The full abstract for the session is below. Thanks, -Aaron Brewster and John Moult Prediction of 3D protein structure by AlphaFold2 and RoseTTAFold has achieved revolutionary accuracy using new AI methods. These programs can accurately predict the 3D structure of many proteins from 1D amino acid sequences, opening up a vast array of exciting new experiments and challenges for researchers. In this session we will explore current applications of these structures in molecular replacement, cryo-EM fitting and refinement, structure-based drug design, and tomography. We will explore what kinds of new and difficult methods have been enabled and what remains difficult. Other topics may include how error estimates on AI protein models can be incorporated into these methods, progress in modeling of protein complexes, implications of AI structures on protein design, the generation and use of structure ensembles, and new data analysis best practices that need to be developed as the use of computer-generated structures becomes more common. Sponsored by the BioMAC and Best Practices for Data Analysis and Archiving SIGs

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The lowest resolution score X-ray statics resolution bin is lower than overall datasets.
by Takebe Katsuki 11 Apr '22

11 Apr '22

Dear all, I am working on a 20 KD protein and We scaled the data sets 1.6Å. The lowest resolution score X-ray statics resolution bin is lower than overall datasets. Is this seriously problem? and How do I solve the problem? Could you give me some advice on this problem? DATA USED IN REFINEMENT. RESOLUTION RANGE HIGH (ANGSTROMS) : 1.600 RESOLUTION RANGE LOW (ANGSTROMS) : 44.488 　 [cid:[email protected]]

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Fragment-based drug discovery session at ACA 2022
by Tanner, John J. 08 Apr '22

08 Apr '22

As many of you know, the 2022 ACA meeting will be held in Portland, OR on July 29 to August 2. I would like to draw your attention to the session on fragment-based drug discovery and invite you to submit an abstract for an oral presentation. We welcome contributions from students as well as PIs. The Abstract deadline is April 15. https://www.acameeting.com/ Session details: 3.2.2 Fragment Based Drug Discovery 8/1/2022 @ 2:00:00 PM - 5:00:00 PM Sponsoring SIG(s): Industrial Co-Sponsoring SIG(s): BioMac Session Chair(s): Matt Clifton, Jack Tanner Fragment Based Drug Discovery (FBDD) utilizes small molecule compounds to help identify starting points in the drug discovery process. This process allowed for the discovery of lead compounds for difficult protein targets with small/shallow pockets or protein-protein interactions. In contrast to other screening techniques such as High-Throughput Screening (HTS) or DNA-encoded Libraries (DEL), FBDD utilizes small libraries of molecules (< 2000) with molecular weights less than ~200 Da. FBDD has been key in the development of multiple approved drugs and dozens of other drugs in clinical trials. This session will focus on the biophysical and structural techniques used in FBDD to identify initial starting points, optimization by fragment growing/linking, and the route to lead optimization. -- John J. Tanner Professor of Biochemistry and Chemistry Associate Chair of Biochemistry Department of Biochemistry University of Missouri 117 Schweitzer Hall 503 S College Avenue Columbia, MO 65211 Phone: 573-884-1280 Email: tannerjj(a)missouri.edu<mailto:[email protected]> https://cafnrfaculty.missouri.edu/tannerlab/ Lab: Schlundt Annex rooms 3,6,9, 203B, 203C Office: Schlundt Annex 203A

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CCN submissions and current issue
by Nigel Moriarty 05 Apr '22

05 Apr '22

Folks The deadline for submissions to the Computational Crystallography Newsletter (CCN) is 1 JUN 2022. Please consider writing an article of general interest to the community. The Computational Crystallography Newsletter (CCN) is an electronic newsletter for structural biologists, and is published online every 6 months. Feature articles, meeting announcements and reports can be submitted to me at any time for consideration. Submission of text by email or word-processing files using the CCN templates is requested. Past newsletters and a Microsoft Word template is attached to this email. Current Issue: January 2022 Full issue <https://phenix-online.org/phenixwebsite_static/mainsite/files/newsletter/CC…> Articles: - Extreme backbone outlier patterns when AlphaFold gives up <https://phenix-online.org/phenixwebsite_static/mainsite/files/newsletter/CC…> - Difference Density Tracer: A Tool for Rapid Visualization of Difference Densities in Proteins to identify Dynamics <https://phenix-online.org/phenixwebsite_static/mainsite/files/newsletter/CC…> Fitting Tips: - Fitting tips #22 – Places where you should never fit a cis-nonPro peptide <https://phenix-online.org/phenixwebsite_static/mainsite/files/newsletter/CC…> Cheers Nigel --- Nigel W. Moriarty Building 33R0349, Molecular Biophysics and Integrated Bioimaging Lawrence Berkeley National Laboratory Berkeley, CA 94720-8235 Phone : 510-486-5709 Email : NWMoriarty(a)LBL.gov Fax : 510-486-5909 Web : CCI.LBL.gov ORCID : orcid.org/0000-0001-8857-9464

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Question about RMSD vs e/A^3
by Vatsal Purohit 30 Mar '22

30 Mar '22

Hi all, I had a question about comparing structures based on RMSD comparisons vs e-/A^3. While the former seems to be more frequently used in structural studies with a standard value of 1.0 rmsd for 2Fo-Fc and 3.0 rmsd for Fo-Fc, there are differences in RMSD based on resolution. Hence, I wanted to ask if e-/A^3 could be a more appropriate comparison for looking at differences in electron density in a ligand-binding site between 2 structures of the same enzyme? So, here you would try and set e-/A^3 of all the maps (2Fo-Fc and Fo-Fc) to the same value. The structures I’m referring to are between 2-2.5 angstroms in resolution. I have also worked with the map sigma level comparison tool on PHENIX and wanted to know if that might be an alternate way to compare maps in 2 structures accordingly. Regards, Vatsal Post-doctoral fellow, Davis Lab, Emory University vatsal.purohit(a)emory.edu <mailto:[email protected]> | 346-719-9409

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Phenix.refine question
by Mark Saper 23 Mar '22

23 Mar '22

Laurie, Really bizarre. The experts will have more info, I hope. When you model the Tyr in the posiive density, is the geometry satisfactory (including main-chain)? If so, then you might try turning off real space refinement and see what happens. Check the occupancies of the Tyr also. -Mark _____________________ Mark A. Saper, Ph.D. Associate Professor Emeritus of Biological Chemistry University of Michigan Medical School saper(a)umich.edu | +1 734 276 6505 Powered by Mailbutler <https://www.mailbutler.io/?utm_source=watermark&utm_medium=email&utm_campai…>, the email extension that does it all

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Phenix.refine question
by lbetts0508 18 Mar '22

18 Mar '22

I am refining a small protein crystal model with 1.3 A data, there is a Tyrosine that won't stay put where it looks to me it should go (see below in it's original position, in the negative density; I moved the ring into the positive Fo-Fc density). After I move it into the positive density, save the coordinates, and do another refinement with the new coordinates, I find it right back in the negative density, even if I only refine ADP or OCC. Is there some trivial reason this is happening, or can I tell it to not refine that residue? https://docs.google.com/document/d/1RkZSH312q2Pimxb9gKLjibm1XbpsVpyzmrX4wGx… THanks Laurie Betts

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Postdoctoral position in the MRC Laboratory of Molecular Biology
by Roger Williams - MRC LMB 16 Mar '22

16 Mar '22

Our group has an opening for a postdoctoral fellow to be funded on a Cancer Research UK programme aimed at understanding lysosomal control of cell proliferation and stress responses in cancer cells. The programme involves cryo-electron microscopy, X-ray crystallography, H/D exchange mass spectrometry, molecular dynamics as well as other biophysical and biochemical approaches. The post will focus on the reconstitution of large signalling assemblies that detect nutritional and stress signals on and off membranes. The candidate will join a vibrant team of researchers investigating structures, regulation, kinetics and dynamics of phosphoinositide 3-kinase family members reconstituted with their regulators on membrane surfaces. This programme concerns regulation of the lipid kinase VPS34 and protein kinase mTOR and ATM-containing complexes. The research combines biochemical, biophysical and cell biological methods with structural approaches. This is a unique opportunity to play a major role in exciting programme, introduce new ideas, and disseminate research results, while working in a collaborative and supportive environment. The position is available immediately, with an application closing date of 11 April 2022. For more details, please see https://www.nature.com/naturecareers/job/postdoctoral-scientist-pnac-dr-rog… <https://www.nature.com/naturecareers/job/postdoctoral-scientist-pnac-dr-rog…> Please contact Roger Williams at rlw(a)mrc-lmb.cam.ac.uk <mailto:[email protected]>, if you have any questions. Dr. Roger Williams, FMedSci, FRS rlw(a)mrc-lmb.cam.ac.uk MRC Laboratory of Molecular Biology Francis Crick Avenue Cambridge CB2 0QH UK Phone: +44 1223 267094

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