ArticleActa crystallographica. Section D, Structural biology2020
Shift-field refinement of macromolecular atomic models.
Article in Acta crystallographica. Section D, Structural biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- MUT-7 exoribonuclease activity and localization are mediated by an ancient domain.Nucleic acids research · 2024Article
- AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination.Nature methods · 2024Article
- An intact S-layer is advantageous to Clostridioides difficile within the host.PLoS pathogens · 2023Article
- The CCP4 suite: integrative software for macromolecular crystallography.Acta crystallographica. Section D, Structural biology · 2023Article
- Improved AlphaFold modeling with implicit experimental information.Nature methods · 2022Article
- ModelCraft: an advanced automated model-building pipeline using Buccaneer.Acta crystallographica. Section D, Structural biology · 2022Article
- Ten things I `hate' about refinement.Acta crystallographica. Section D, Structural biology · 2021Article
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Authors and funding
3 authors.
Funding
Abstract
The aim of crystallographic structure solution is typically to determine an atomic model which accurately accounts for an observed diffraction pattern. A key step in this process is the refinement of the parameters of an initial model, which is most often determined by molecular replacement using another structure which is broadly similar to the structure of interest. In macromolecular crystallography, the resolution of the data is typically insufficient to determine the positional and uncertainty parameters for each individual atom, and so stereochemical information is used to supplement the observational data. Here, a new approach to refinement is evaluated in which a `shift field' is determined which describes changes to model parameters affecting whole regions of the model rather than individual atoms only, with the size of the affected region being a key parameter of the calculation which can be changed in accordance with the resolution of the data. It is demonstrated that this approach can improve the radius of convergence of the refinement calculation while also dramatically reducing the calculation time.
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