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R. Keegan 1, J. Bibby 3, C. Ballard 1, E. Krissinel 1, D. Waterman 1, A. Lebedev 1, M. Winn 2, D. Rigden 3 1 Research Complex at Harwell, STFC Rutherford.

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Presentation on theme: "R. Keegan 1, J. Bibby 3, C. Ballard 1, E. Krissinel 1, D. Waterman 1, A. Lebedev 1, M. Winn 2, D. Rigden 3 1 Research Complex at Harwell, STFC Rutherford."— Presentation transcript:

1 R. Keegan 1, J. Bibby 3, C. Ballard 1, E. Krissinel 1, D. Waterman 1, A. Lebedev 1, M. Winn 2, D. Rigden 3 1 Research Complex at Harwell, STFC Rutherford Appleton Laboratory, UK 2 STFC Daresbury Laboratory, UK, 3 School of Biological Sciences, University of Liverpool, UK About CCP4 Produce a comprehensive software suite for macromolecular crystallography Develop cutting edge approaches to structure solution Community-based resource – reach out to academic, non-profit and for-profit organisations Provide education and training in structural biology Encourage the wide dissemination of new ideas, techniques and practice. CCP4 is the Collaborative Computational Project No. 4 Set up in the late 1970’s in the UK to bring together developers of PX software Goal was to assemble a comprehensive collection of software, based around standard file formats A little history CCP4 Mission Statement Funded by BBSRC and MRC in the UK, and coordinated by STFC Core group based at the Research Complex at Harwell Supports software developers in the UK and further afield Annual Study Weekend in January - next on “Data Collection and Processing at Synchrotrons” at Warwick University, UK Teaching workshops worldwide CCP4 Today Visit us at Exhibition Booth #47 The CCP4 Software Suite 6.2.x Future Developments MAP SHARPENING at 4Å (2R6C) OriginalSharpened Qt-based version of CCP4mg: Quaternary structure prediction with PISA: COOT 0.6.2: Phase improvement with DM/PIRATE/PARROT Data processing with iMOSFLM: Molecular Replacement MrBUMP SEQ SHLVKCAEKEKTFCVN GGECFMVKDLSNPSR YLCKCQPGFTGARCT ENVPMKVQ data target sequence automation pipelines (using Molrep/Phaser) homologous structures positioned in cell Determine Laue group and spacegroup with POINTLESS: Automated data processing from images to |F| for multi-wedge, multi-pass, multiwavelength data Experimental Phasing Automated model building with BUCCANEER Phasing via Molecular Replacement and/or SAD CRANK DIMPLE: Difference map pipeline for high speed automated processing of structures with potentially bound ligands "Cut-glass" transparent surface effect Data Processing, Experimental Phasing and Molecular Replacement jLIGAND: Graphical interface for linking ligands and creating link descriptions Creation of library descriptions for single ligands Refinement, Model Building and Molecular Graphics REFMAC 5.6 Refine against SIRAS data Jelly body refinement Occupancy group refinement Restrain to reference structures Regularised map sharpening Automatic and local NCS restraints Linked with SBase - idealised coordinates for all monomer types in PDB. Interfaces ProDRG (soon in CCP4) for generation of restraints ViewHKL: New graphical viewer for reflection data. Supports most of widely used file formats: MTZ, SHELX, XDS, Saint and Scalepack Make PDF and postscript outputs NEW PROGRAMS: Aimless – replacement for Scala and Pointless with increased functionality Sculptor & Ensembler – tools for preparing search models for Molecular Replacement Prosmart- structural comparison of protein chains Zanuda – checking refinement results, e.g. Checking for false origins in the presence of pseudo translation Related Developments Data Structure Solution by Molecular Replacement using ab initio protein models Our method employs ab initio polyalanine models (or ‘decoys’), produced in large numbers then clustered based on the presence of similar core structures. The largest of these clusters is likely to be closest to the native structure [2]. Such ab initio modelling may result in an accurate prediction of the structural core of the target, but with inaccurate loops and termini. This pipeline will be made freely available, and may ultimately require only the input of the protein sequence along with the experimental data. Unlike other computationally intensive methods [3], this method is suitable for modest hardware, allowing for broader adoption.


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