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      Clustering procedures for the optimal selection of data sets from multiple crystals in macromolecular crystallography

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          Abstract

          A systematic approach to the scaling and merging of data from multiple crystals in macromolecular crystallography is introduced and explained.

          Abstract

          The availability of intense microbeam macromolecular crystallography beamlines at third-generation synchrotron sources has enabled data collection and structure solution from microcrystals of <10 µm in size. The increased likelihood of severe radiation damage where microcrystals or particularly sensitive crystals are used forces crystallographers to acquire large numbers of data sets from many crystals of the same protein structure. The associated analysis and merging of multi-crystal data is currently a manual and time-consuming step. Here, a computer program, BLEND, that has been written to assist with and automate many of the steps in this process is described. It is demonstrated how BLEND has successfully been used in the solution of a novel membrane protein.

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          Author and article information

          Journal
          Acta Crystallogr D Biol Crystallogr
          Acta Crystallogr. D Biol. Crystallogr
          Acta Cryst. D
          Acta Crystallographica Section D: Biological Crystallography
          International Union of Crystallography
          0907-4449
          1399-0047
          01 August 2013
          20 July 2013
          20 July 2013
          : 69
          : Pt 8 ( publisher-idID: d130800 )
          : 1617-1632
          Affiliations
          [a ]Membrane Protein Laboratory, Diamond Light Source , Harwell Science and Innovation Campus, Didcot, Oxfordshire OX11 0DE, England
          [b ]Division of Molecular Biosciences, Imperial College , London SW7 2AZ, England
          [c ]Diamond Light Source , Harwell Science and Innovation Campus, Didcot, Oxfordshire OX11 0DE, England
          [d ]Oxford e-Research Centre (OeRC) , Keble Road, Oxford OX1 3QG, England
          [e ]CCP4, Research Complex at Harwell (RCaH) , Harwell Science and Innovation Campus, Didcot, Oxfordshire OX11 0FA, England
          Author notes
          Article
          dz5278 ABCRE6 S0907444913012274
          10.1107/S0907444913012274
          3727331
          23897484
          © Foadi et al. 2013

          This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.

          Categories
          Research Papers

          Microscopy & Imaging

          multi-crystal data sets, merging, scaling, blend, multiple crystals, clustering

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