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

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 s...

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Detalles Bibliográficos
Autores principales: Foadi, James, Aller, Pierre, Alguel, Yilmaz, Cameron, Alex, Axford, Danny, Owen, Robin L., Armour, Wes, Waterman, David G., Iwata, So, Evans, Gwyndaf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3727331/
https://www.ncbi.nlm.nih.gov/pubmed/23897484
http://dx.doi.org/10.1107/S0907444913012274
Descripción
Sumario: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.