Modeling diffuse scattering with simple, physically interpretable models

Peck, Ariana; Lane, Thomas J.; Poitevin, Frédéric

doi:10.1016/bs.mie.2023.06.022

Cited by 2 publications

(1 citation statement)

References 43 publications

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“…Building on the diffuse scattering methods used in materials science [exemplified by programs such as XCAVATE (Estermann & Steurer, 1998;Scheidegger et al, 2000), Mantid (Arnold et al, 2014) and Meerkat (Simonov et al, 2020)], software tools including Lunus (Wall, 2009), EVAL (Schreurs et al, 2010), Diffuse (Peck et al, 2018) and mdx-lib (Meisburger et al, 2020) have been developed to address unique challenges in macromolecular diffuse scattering. These programs produce patterns that can be compared quantitatively with various models (Wych & Wall, 2023;Case, 2023;Peck et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Scaling and merging macromolecular diffuse scattering with mdx2

Meisburger,

Ando

2024

Acta Cryst Sect D Struct Biol

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Diffuse scattering is a promising method to gain additional insight into protein dynamics from macromolecular crystallography experiments. Bragg intensities yield the average electron density, while the diffuse scattering can be processed to obtain a three-dimensional reciprocal-space map that is further analyzed to determine correlated motion. To make diffuse scattering techniques more accessible, software for data processing called mdx2 has been created that is both convenient to use and simple to extend and modify. mdx2 is written in Python, and it interfaces with DIALS to implement self-contained data-reduction workflows. Data are stored in NeXus format for software interchange and convenient visualization. mdx2 can be run on the command line or imported as a package, for instance to encapsulate a complete workflow in a Jupyter notebook for reproducible computing and education. Here, mdx2 version 1.0 is described, a new release incorporating state-of-the-art techniques for data reduction. The implementation of a complete multi-crystal scaling and merging workflow is described, and the methods are tested using a high-redundancy data set from cubic insulin. It is shown that redundancy can be leveraged during scaling to correct systematic errors and obtain accurate and reproducible measurements of weak diffuse signals.

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Section: Introductionmentioning

confidence: 99%

Scaling and merging macromolecular diffuse scattering with mdx2

Meisburger,

Ando

2024

Acta Cryst Sect D Struct Biol

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Scaling and merging macromolecular diffuse scattering withmdx2

Meisburgera,

Andob

2024

Preprint

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Diffuse scattering is a promising method to gain additional insight into protein dynamics from macromolecular crystallography (MX) experiments. Bragg intensities yield the average electron density, while the diffuse scattering can be processed to obtain a three-dimensional reciprocal space map, that is further analyzed to determine correlated motion. To make diffuse scattering techniques more accessible, we have created software for data processing called mdx2 that is both convenient to use and simple to extend and modify. Mdx2 is written in Python, and it interfaces with DIALS to implement self-contained data reduction workflows. Data are stored in NeXus format for software interchange and convenient visualization. Mdx2 can be run on the command line or imported as a package, for instance to encapsulate a complete workflow in a Jupyter notebook for reproducible computing and education. Here, we describe mdx2 version 1.0, a new release incorporating state-of-the-art techniques for data reduction. We describe the implementation of a complete multi-crystal scaling and merging workflow, and test the methods using a high-redundancy dataset from cubic insulin. We show that redundancy can be leveraged during scaling to correct systematic errors, and obtain accurate and reproducible measurements of weak diffuse signals.

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Modeling diffuse scattering with simple, physically interpretable models

Cited by 2 publications

References 43 publications

Scaling and merging macromolecular diffuse scattering with mdx2

Scaling and merging macromolecular diffuse scattering with mdx2

Scaling and merging macromolecular diffuse scattering withmdx2

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