Advances in X-ray free electron laser (XFEL) diffraction data processing applied to the crystal structure of the synaptotagmin-1 / SNARE complex
Abstract
X-ray free electron lasers (XFELs) reduce the effects of radiation damage on macromolecular diffraction data and thereby extend the limiting resolution. Previously, we adapted classical post-refinement techniques to XFEL diffraction data to produce accurate diffraction data sets from a limited number of diffraction images (Uervirojnangkoorn et al., 2015), and went on to use these techniques to obtain a complete data set from crystals of the synaptotagmin-1 / SNARE complex and to determine the structure at 3.5 Å resolution (Zhou et al., 2015). Here, we describe new advances in our methods and present a reprocessed XFEL data set of the synaptotagmin-1 / SNARE complex. The reprocessing produced small improvements in electron density maps and the refined atomic model. The maps also contained more information than those of a lower resolution (4.1 Å) synchrotron data set. Processing a set of simulated XFEL diffraction images revealed that our methods yield accurate data and atomic models.
Data availability
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Structure of the Ca2+-bound synaptotagmin-1 SNARE complex (long unit cell form) - from XFEL diffractionPublicly available at the RCSB Protein Data Bank (accession no: 5KJ7).
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Structure of the Ca2+-bound synaptotagmin-1 SNARE complex (long unit cell form) - from synchrotron diffractionPublicly available at the RCSB Protein Data Bank (accession no: 5KJ8).
Article and author information
Author details
Funding
Howard Hughes Medical Institute (Collaborative Innovation Award)
- William I Weis
- Axel T Brunger
National Institutes of Health (R01GM102520)
- Nicholas K Sauter
National Institutes of Health (R01GM117126)
- Nicholas K Sauter
National Institute of General Medical Sciences (P41 GM103403)
- Axel T Brunger
National Institutes of Health (S10 RR029205)
- Axel T Brunger
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2016, Lyubimov et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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