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Determination of crystallographic intensities from sparse data
X-ray serial microcrystallography involves the collection and merging of frames of diffraction data from randomly oriented protein microcrystals. The number of diffracted X-rays in each frame is limited by radiation damage, and this number decreases with crystal size. The data in the frame are said...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4285878/ https://www.ncbi.nlm.nih.gov/pubmed/25610625 http://dx.doi.org/10.1107/S2052252514022313 |
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author | Ayyer, Kartik Philipp, Hugh T. Tate, Mark W. Wierman, Jennifer L. Elser, Veit Gruner, Sol M. |
author_facet | Ayyer, Kartik Philipp, Hugh T. Tate, Mark W. Wierman, Jennifer L. Elser, Veit Gruner, Sol M. |
author_sort | Ayyer, Kartik |
collection | PubMed |
description | X-ray serial microcrystallography involves the collection and merging of frames of diffraction data from randomly oriented protein microcrystals. The number of diffracted X-rays in each frame is limited by radiation damage, and this number decreases with crystal size. The data in the frame are said to be sparse if too few X-rays are collected to determine the orientation of the microcrystal. It is commonly assumed that sparse crystal diffraction frames cannot be merged, thereby setting a lower limit to the size of microcrystals that may be merged with a given source fluence. The EMC algorithm [Loh & Elser (2009 ▶), Phys. Rev. E, 80, 026705] has previously been applied to reconstruct structures from sparse noncrystalline data of objects with unknown orientations [Philipp et al. (2012 ▶), Opt. Express, 20, 13129–13137; Ayyer et al. (2014 ▶), Opt. Express, 22, 2403–2413]. Here, it is shown that sparse data which cannot be oriented on a per-frame basis can be used effectively as crystallographic data. As a proof-of-principle, reconstruction of the three-dimensional diffraction intensity using sparse data frames from a 1.35 kDa molecule crystal is demonstrated. The results suggest that serial microcrystallography is, in principle, not limited by the fluence of the X-ray source, and collection of complete data sets should be feasible at, for instance, storage-ring X-ray sources. |
format | Online Article Text |
id | pubmed-4285878 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-42858782015-01-21 Determination of crystallographic intensities from sparse data Ayyer, Kartik Philipp, Hugh T. Tate, Mark W. Wierman, Jennifer L. Elser, Veit Gruner, Sol M. IUCrJ Research Papers X-ray serial microcrystallography involves the collection and merging of frames of diffraction data from randomly oriented protein microcrystals. The number of diffracted X-rays in each frame is limited by radiation damage, and this number decreases with crystal size. The data in the frame are said to be sparse if too few X-rays are collected to determine the orientation of the microcrystal. It is commonly assumed that sparse crystal diffraction frames cannot be merged, thereby setting a lower limit to the size of microcrystals that may be merged with a given source fluence. The EMC algorithm [Loh & Elser (2009 ▶), Phys. Rev. E, 80, 026705] has previously been applied to reconstruct structures from sparse noncrystalline data of objects with unknown orientations [Philipp et al. (2012 ▶), Opt. Express, 20, 13129–13137; Ayyer et al. (2014 ▶), Opt. Express, 22, 2403–2413]. Here, it is shown that sparse data which cannot be oriented on a per-frame basis can be used effectively as crystallographic data. As a proof-of-principle, reconstruction of the three-dimensional diffraction intensity using sparse data frames from a 1.35 kDa molecule crystal is demonstrated. The results suggest that serial microcrystallography is, in principle, not limited by the fluence of the X-ray source, and collection of complete data sets should be feasible at, for instance, storage-ring X-ray sources. International Union of Crystallography 2015-01-01 /pmc/articles/PMC4285878/ /pubmed/25610625 http://dx.doi.org/10.1107/S2052252514022313 Text en © Kartik Ayyer et al. 2015 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. |
spellingShingle | Research Papers Ayyer, Kartik Philipp, Hugh T. Tate, Mark W. Wierman, Jennifer L. Elser, Veit Gruner, Sol M. Determination of crystallographic intensities from sparse data |
title | Determination of crystallographic intensities from sparse data |
title_full | Determination of crystallographic intensities from sparse data |
title_fullStr | Determination of crystallographic intensities from sparse data |
title_full_unstemmed | Determination of crystallographic intensities from sparse data |
title_short | Determination of crystallographic intensities from sparse data |
title_sort | determination of crystallographic intensities from sparse data |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4285878/ https://www.ncbi.nlm.nih.gov/pubmed/25610625 http://dx.doi.org/10.1107/S2052252514022313 |
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