Processing macromolecular diffuse scattering data.

Data processing Diffuse scattering Reciprocal space mapping Software Tutorial X-ray diffraction

Journal

Methods in enzymology
ISSN: 1557-7988
Titre abrégé: Methods Enzymol
Pays: United States
ID NLM: 0212271

Informations de publication

Date de publication:
2023
Historique:
medline: 27 9 2023
pubmed: 26 9 2023
entrez: 25 9 2023
Statut: ppublish

Résumé

Diffuse scattering is a powerful technique to study disorder and dynamics of macromolecules at atomic resolution. Although diffuse scattering is always present in diffraction images from macromolecular crystals, the signal is weak compared with Bragg peaks and background, making it a challenge to visualize and measure accurately. Recently, this challenge has been addressed using the reciprocal space mapping technique, which leverages ideal properties of modern X-ray detectors to reconstruct the complete three-dimensional volume of continuous diffraction from diffraction images of a crystal (or crystals) in many different orientations. This chapter will review recent progress in reciprocal space mapping with a particular focus on the strategy implemented in the mdx-lib and mdx2 software packages. The chapter concludes with an introductory data processing tutorial using Python packages DIALS, NeXpy, and mdx2.

Identifiants

pubmed: 37748832
pii: S0076-6879(23)00215-X
doi: 10.1016/bs.mie.2023.06.010
pii:
doi:

Substances chimiques

Macromolecular Substances 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

43-86

Subventions

Organisme : NIGMS NIH HHS
ID : P30 GM124166
Pays : United States

Commentaires et corrections

Type : UpdateOf

Informations de copyright

Copyright © 2023. Published by Elsevier Inc.

Auteurs

Steve P Meisburger (SP)

Cornell High Energy Synchrotron Source, Cornell University, Ithaca, NY, United States. Electronic address: spm82@cornell.edu.

Nozomi Ando (N)

Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, United States. Electronic address: nozomi.ando@cornell.edu.

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Classifications MeSH