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

被引：200

作者：

Foadi, James ^{[1
,2
]}

Aller, Pierre ^{[3
]}

Alguel, Yilmaz ^{[2
]}

Cameron, Alex ^{[2
]}

Axford, Danny ^{[3
]}

Owen, Robin L. ^{[3
]}

Armour, Wes ^{[4
]}

Waterman, David G. ^{[5
]}

Iwata, So ^{[1
,2
]}

Evans, Gwyndaf ^{[3
]}

机构：

[1] Harwell Sci & Innovat Campus, Diamond Light Source, Membrane Prot Lab, Didcot OX11 0DE, Oxon, England

[2] Univ London Imperial Coll Sci Technol & Med, Div Mol Biosci, London SW7 2AZ, England

[3] Harwell Sci & Innovat Campus, Diamond Light Source, Didcot OX11 0DE, Oxon, England

[4] OeRC, Oxford OX1 3QG, England

[5] Harwell Sci & Innovat Campus, RCaH, CCP4, Didcot OX11 0FA, Oxon, England

来源：

ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY | 2013年 / 69卷

基金：

英国惠康基金;

关键词：

DIFFRACTION DATA; PROTEIN CRYSTALLIZATION; CELL; ALLOWS;

D O I：

10.1107/S0907444913012274

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

The availability of intense microbeam macromolecular crystallography beamlines at third-generation synchrotron sources has enabled data collection and structure solution from microcrystals of <10 mu m 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.

引用

页码：1617 / 1632

页数：16

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