Two-dimensional structure from random multiparticle X-ray scattering images using cross-correlations
B. Pedrini (),
A. Menzel,
M. Guizar-Sicairos,
V. A. Guzenko,
S. Gorelick,
C. David,
B. D. Patterson and
R. Abela
Additional contact information
B. Pedrini: Paul Scherrer Institute
A. Menzel: Paul Scherrer Institute
M. Guizar-Sicairos: Paul Scherrer Institute
V. A. Guzenko: Paul Scherrer Institute
S. Gorelick: Paul Scherrer Institute
C. David: Paul Scherrer Institute
B. D. Patterson: Paul Scherrer Institute
R. Abela: Paul Scherrer Institute
Nature Communications, 2013, vol. 4, issue 1, 1-9
Abstract:
Abstract Knowledge of the structure of biological macromolecules, especially in their native environment, is crucial because of the close structure–function relationship. X-ray small-angle scattering is used to determine the shape of particles in solution, but the achievable resolution is limited owing to averaging over particle orientations. In 1977, Kam proposed to obtain additional structural information from the cross-correlation of the scattering intensities. Here we develop the method in two dimensions, and give a procedure by which the single-particle diffraction pattern is extracted in a model-independent way from the correlations. We demonstrate its application to a large set of synchrotron X-ray scattering images on ensembles of identical, randomly oriented particles of 350 or 200 nm in size. The obtained 15 nm resolution in the reconstructed shape is independent of the number of scatterers. The results are discussed in view of proposed ‘snapshot’ scattering by molecules in the liquid phase at X-ray free-electron lasers.
Date: 2013
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.nature.com/articles/ncomms2622 Abstract (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms2622
Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/
DOI: 10.1038/ncomms2622
Access Statistics for this article
Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie
More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().