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.
Nicole M. Scarborough, G. M. Dilshan P. Godaliyadda, Dong Hye Ye, David J. Kissick, Shijie Zhang, Justin A. Newman, Michael J. Sheedlo, Azhad Chowdhury, Robert F. Fischetti, Chittaranjan Das, Gregery T. Buzzard, Charles A. Bouman, Garth J. Simpson, "Synchrotron X-Ray Diffraction Dynamic Sampling for Protein Crystal Centering" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Computational Imaging XV, 2017, pp 6 - 9, https://doi.org/10.2352/ISSN.2470-1173.2017.17.COIMG-415