Multi-position data collection and dynamic beam sizing: recent improvements to the automatic data-collection algorithms on MASSIF-1

被引:36
作者
Svensson, Olof [1 ]
Gilski, Maciej [2 ]
Nurizzo, Didier [1 ]
Bowler, Matthew W. [2 ]
机构
[1] European Synchrotron Radiat Facil, 71 Ave Martyrs,CS 40220, F-38043 Grenoble, France
[2] European Mol Biol Lab, Grenoble Outstn, 71 Ave Martyrs,CS 90181, F-38042 Grenoble, France
来源
ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY | 2018年 / 74卷
关键词
X-ray centring; synchrotron instrumentation; macromolecular crystallography; automation; helical data collection; multiple-crystal data collection; MASSIF-1; data-collection algorithms; robotics; PROTEIN CRYSTALS; SAMPLE-CHANGER; STRUCTURAL BIOLOGY; CRYSTALLOGRAPHY; SYSTEM; VARIABILITY; FAMILY;
D O I
10.1107/S2059798318003728
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Macromolecular crystallography is now a mature and widely used technique that is essential in the understanding of biology and medicine. Increases in computing power combined with robotics have not only enabled large numbers of samples to be screened and characterized but have also enabled better decisions to be taken on data collection itself. This led to the development of MASSIF-1 at the ESRF, the first beamline in the world to run fully automatically while making intelligent decisions taking user requirements into account. Since opening in late 2014, the beamline has processed over 42 000 samples. Improvements have been made to the speed of the sample-handling robotics and error management within the software routines. The workflows initially put into place, while highly innovative at the time, have been expanded to include increased complexity and additional intelligence using the information gathered during characterization; this includes adapting the beam diameter dynamically to match the diffraction volume within the crystal. Complex multi-position and multi-crystal data collections have now also been integrated into the selection of experiments available. This has led to increased data quality and throughput, allowing even the most challenging samples to be treated automatically.
引用
收藏
页码:433 / 440
页数:8
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