Applications of the BLEND Software to Crystallographic Data from Membrane Proteins

X-ray diffraction from crystals of membrane proteins very often yields incomplete datasets due to, among other things, severe radiation damage. Multiple crystals are thus required to form complete datasets, provided the crystals themselves are isomorphous. Selection and combination of data from mult...

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Autores principales: Aller, Pierre, Geng, Tian, Evans, Gwyndaf, Foadi, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6126465/
https://www.ncbi.nlm.nih.gov/pubmed/27553239
http://dx.doi.org/10.1007/978-3-319-35072-1_9
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author Aller, Pierre
Geng, Tian
Evans, Gwyndaf
Foadi, James
author_facet Aller, Pierre
Geng, Tian
Evans, Gwyndaf
Foadi, James
author_sort Aller, Pierre
collection PubMed
description X-ray diffraction from crystals of membrane proteins very often yields incomplete datasets due to, among other things, severe radiation damage. Multiple crystals are thus required to form complete datasets, provided the crystals themselves are isomorphous. Selection and combination of data from multiple crystals is a difficult and tedious task that can be facilitated by purpose-built software. BLEND, in the CCP4 suite of programs for macromolecular crystallography (MX), has been created exactly for this reason. In this chapter the program is described and its workings illustrated by means of data from two membrane proteins.
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spelling pubmed-61264652018-09-11 Applications of the BLEND Software to Crystallographic Data from Membrane Proteins Aller, Pierre Geng, Tian Evans, Gwyndaf Foadi, James Adv Exp Med Biol Article X-ray diffraction from crystals of membrane proteins very often yields incomplete datasets due to, among other things, severe radiation damage. Multiple crystals are thus required to form complete datasets, provided the crystals themselves are isomorphous. Selection and combination of data from multiple crystals is a difficult and tedious task that can be facilitated by purpose-built software. BLEND, in the CCP4 suite of programs for macromolecular crystallography (MX), has been created exactly for this reason. In this chapter the program is described and its workings illustrated by means of data from two membrane proteins. Springer International Publishing 2016-04-28 /pmc/articles/PMC6126465/ /pubmed/27553239 http://dx.doi.org/10.1007/978-3-319-35072-1_9 Text en © The Author(s) 2016 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
spellingShingle Article
Aller, Pierre
Geng, Tian
Evans, Gwyndaf
Foadi, James
Applications of the BLEND Software to Crystallographic Data from Membrane Proteins
title Applications of the BLEND Software to Crystallographic Data from Membrane Proteins
title_full Applications of the BLEND Software to Crystallographic Data from Membrane Proteins
title_fullStr Applications of the BLEND Software to Crystallographic Data from Membrane Proteins
title_full_unstemmed Applications of the BLEND Software to Crystallographic Data from Membrane Proteins
title_short Applications of the BLEND Software to Crystallographic Data from Membrane Proteins
title_sort applications of the blend software to crystallographic data from membrane proteins
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6126465/
https://www.ncbi.nlm.nih.gov/pubmed/27553239
http://dx.doi.org/10.1007/978-3-319-35072-1_9
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