A supervised learning approach for dynamic sampling (SLADS) was developed to reduce X-ray exposure prior to data collection in protein structure determination. Implementation of this algorithm allowed reduction of the X-ray dose to the central core of the crystal by up to 20-fold compared to current raster scanning approaches. This dose reduction corresponds directly to a reduction on X-ray damage to the protein crystals prior to data collection for structure determination. Implementation at a beamline at Argonne National Laboratory suggests promise for the use of the SLADS approach to aid in the analysis of X-ray labile crystals. The potential benefits match a growing need for improvements in automated approaches for microcrystal positioning.
|Original language||English (US)|
|Number of pages||4|
|Journal||IS and T International Symposium on Electronic Imaging Science and Technology|
|State||Published - 2017|
|Event||Computational Imaging XV 2017 - Burlingame, United States|
Duration: Jan 29 2017 → Feb 2 2017
Bibliographical noteFunding Information:
NMS, SZ, JAN, MJS, AC, CD, and GJS gratefully acknowledge support from the NIH Grant Numbers R01GM-103401 and R01GM-103910 from the NIGMS.
© 2017, Society for Imaging Science and Technology.