ArticleActa crystallographica. Section D, Structural biology2016
Can I solve my structure by SAD phasing? Anomalous signal in SAD phasing.
Article in Acta crystallographica. Section D, Structural biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- The Untangle Challenge for accurate ensemble models.bioRxiv : the preprint server for biology · 2026Article
- Crystal structure of a tRNA acceptor-stem mimic at 1.94 Å resolution.Acta crystallographica. Section F, Structural biology communications · 2026Article
- Article
- Experimental phasing opportunities for macromolecular crystallography at very long wavelengths.Communications chemistry · 2023Article
- Obtaining anomalous and ensemble information from protein crystals from 220 K up to physiological temperatures.Acta crystallographica. Section D, Structural biology · 2023Article
- Native SAD phasing at room temperature.Acta crystallographica. Section D, Structural biology · 2022Article
- Likelihood-based estimation of substructure content from single-wavelength anomalous diffraction (SAD) intensity data.Acta crystallographica. Section D, Structural biology · 2021Article
- Phosphorus and sulfur SAD phasing of the nucleic acid-bound DNA-binding domain of interferon regulatory factor 4.Acta crystallographica. Section F, Structural biology communications · 2021Article
- Article
- Experimental phasing with vanadium and application to nucleotide-binding membrane proteins.IUCrJ · 2020Article
- Beyond integration: modeling every pixel to obtain better structure factors from stills.IUCrJ · 2020Article
- Native de novo structural determinations of non-canonical nucleic acid motifs by X-ray crystallography at long wavelengths.Nucleic acids research · 2020Article
- Towards the automation of in situ experimental phasing.Acta crystallographica. Section D, Structural biology · 2020Article
- Article
- SAD phasing of XFEL data depends critically on the error model.Acta crystallographica. Section D, Structural biology · 2019Article
- Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix.Acta crystallographica. Section D, Structural biology · 2019Article
- Making routine native SAD a reality: lessons from beamline X06DA at the Swiss Light Source.Acta crystallographica. Section D, Structural biology · 2019Article
- Choosing your (Friedel) mates wisely: grouping data sets to improve anomalous signal.Acta crystallographica. Section D, Structural biology · 2019Article
- Cadmium SAD phasing at CuKα wavelength.F1000Research · 2019Article
- Fast and accurate data collection for macromolecular crystallography using the JUNGFRAU detector.Nature methods · 2018Article
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7 authors.
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Abstract
A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. A simple theoretical framework for describing measurements of anomalous differences and the resulting useful anomalous correlation and anomalous signal in a SAD experiment is presented. Here, the useful anomalous correlation is defined as the correlation of anomalous differences with ideal anomalous differences from the anomalous substructure. The useful anomalous correlation reflects the accuracy of the data and the absence of minor sites. The useful anomalous correlation also reflects the information available for estimating crystallographic phases once the substructure has been determined. In contrast, the anomalous signal (the peak height in a model-phased anomalous difference Fourier at the coordinates of atoms in the anomalous substructure) reflects the information available about each site in the substructure and is related to the ability to find the substructure. A theoretical analysis shows that the expected value of the anomalous signal is the product of the useful anomalous correlation, the square root of the ratio of the number of unique reflections in the data set to the number of sites in the substructure, and a function that decreases with increasing values of the atomic displacement factor for the atoms in the substructure. This means that the ability to find the substructure in a SAD experiment is increased by high data quality and by a high ratio of reflections to sites in the substructure, and is decreased by high atomic displacement factors for the substructure.
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