| Literature DB >> 29527589 |
Nicole M Scarborough1, G M Dilshan P Godaliyadda2, Dong Hye Ye2, David J Kissick3, Shijie Zhang1, Justin A Newman1, Michael J Sheedlo1, Azhad Chowdhury1, Robert F Fischetti3, Chittaranjan Das1, Gregery T Buzzard4, Charles A Bouman2, Garth J Simpson1.
Abstract
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.Entities:
Year: 2017 PMID: 29527589 PMCID: PMC5842693 DOI: 10.2352/ISSN.2470-1173.2017.17.COIMG-415
Source DB: PubMed Journal: IS&T Int Symp Electron Imaging