Ray-tracing analytical absorption correction for X-ray crystallography based on tomographic reconstructions.

X-ray tomography absorption correction long-wavelength crystallography ray tracing

Journal

Journal of applied crystallography
ISSN: 0021-8898
Titre abrégé: J Appl Crystallogr
Pays: United States
ID NLM: 9876190

Informations de publication

Date de publication:
01 Jun 2024
Historique:
received: 24 11 2023
accepted: 07 03 2024
medline: 7 6 2024
pubmed: 7 6 2024
entrez: 7 6 2024
Statut: epublish

Résumé

Processing of single-crystal X-ray diffraction data from area detectors can be separated into two steps. First, raw intensities are obtained by integration of the diffraction images, and then data correction and reduction are performed to determine structure-factor amplitudes and their uncertainties. The second step considers the diffraction geometry, sample illumination, decay, absorption and other effects. While absorption is only a minor effect in standard macromolecular crystallography (MX), it can become the largest source of uncertainty for experiments performed at long wavelengths. Current software packages for MX typically employ empirical models to correct for the effects of absorption, with the corrections determined through the procedure of minimizing the differences in intensities between symmetry-equivalent reflections; these models are well suited to capturing smoothly varying experimental effects. However, for very long wavelengths, empirical methods become an unreliable approach to model strong absorption effects with high fidelity. This problem is particularly acute when data multiplicity is low. This paper presents an analytical absorption correction strategy (implemented in new software

Identifiants

pubmed: 38846772
doi: 10.1107/S1600576724002243
pii: S1600576724002243
pmc: PMC11151674
doi:

Types de publication

Journal Article

Langues

eng

Pagination

649-658

Informations de copyright

© Yishun Lu et al. 2024.

Auteurs

Yishun Lu (Y)

Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford OX1 3QG, United Kingdom.

Ramona Duman (R)

Diamond Light Source, Harwell Science & Innovation Campus, Didcot OX11 0DE, United Kingdom.

James Beilsten-Edmands (J)

Diamond Light Source, Harwell Science & Innovation Campus, Didcot OX11 0DE, United Kingdom.

Graeme Winter (G)

Diamond Light Source, Harwell Science & Innovation Campus, Didcot OX11 0DE, United Kingdom.

Mark Basham (M)

Rosalind Franklin Institute, Harwell Science & Innovation Campus, Didcot OX11 0QX, United Kingdom.

Gwyndaf Evans (G)

Diamond Light Source, Harwell Science & Innovation Campus, Didcot OX11 0DE, United Kingdom.
Rosalind Franklin Institute, Harwell Science & Innovation Campus, Didcot OX11 0QX, United Kingdom.

Jos J A G Kamps (JJAG)

Diamond Light Source, Harwell Science & Innovation Campus, Didcot OX11 0DE, United Kingdom.
Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.

Allen M Orville (AM)

Diamond Light Source, Harwell Science & Innovation Campus, Didcot OX11 0DE, United Kingdom.
Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.

Hok-Sau Kwong (HS)

Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.
Department of Life Sciences, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom.

Konstantinos Beis (K)

Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.
Department of Life Sciences, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom.

Wesley Armour (W)

Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford OX1 3QG, United Kingdom.

Armin Wagner (A)

Diamond Light Source, Harwell Science & Innovation Campus, Didcot OX11 0DE, United Kingdom.

Classifications MeSH