Improving experimental phases for strong reflections prior to density modification.
Terwilliger, Thomas C
Acta Crystallogr D Biol Crystallogr
International Union of Crystallography (IUCr)
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Uervirojnangkoorn, M., Hilgenfeld, R., Terwilliger, T. C., & Read, R. (2013). Improving experimental phases for strong reflections prior to density modification.. Acta Crystallogr D Biol Crystallogr, 69 (Pt 10), 2039-2049. https://doi.org/10.1107/S0907444913018167
Experimental phasing of diffraction data from macromolecular crystals involves deriving phase probability distributions. These distributions are often bimodal, making their weighted average, the centroid phase, improbable, so that electron-density maps computed using centroid phases are often non-interpretable. Density modification brings in information about the characteristics of electron density in protein crystals. In successful cases, this allows a choice between the modes in the phase probability distributions, and the maps can cross the borderline between non-interpretable and interpretable. Based on the suggestions by Vekhter [Vekhter (2005), Acta Cryst. D61, 899-902], the impact of identifying optimized phases for a small number of strong reflections prior to the density-modification process was investigated while using the centroid phase as a starting point for the remaining reflections. A genetic algorithm was developed that optimizes the quality of such phases using the skewness of the density map as a target function. Phases optimized in this way are then used in density modification. In most of the tests, the resulting maps were of higher quality than maps generated from the original centroid phases. In one of the test cases, the new method sufficiently improved a marginal set of experimental SAD phases to enable successful map interpretation. A computer program, SISA, has been developed to apply this method for phase improvement in macromolecular crystallography.
Humans, Macromolecular Substances, Viral Proteins, X-Ray Diffraction, Crystallography, X-Ray, Chromosome Mapping, Recombination, Genetic, Algorithms, Models, Molecular, Computer Simulation, Child
Wellcome Trust (100140/Z/12/Z)
Wellcome Trust (082961/Z/07/Z)
National Institute of General Medical Sciences (P01GM063210)
External DOI: https://doi.org/10.1107/S0907444913018167
This record's URL: https://www.repository.cam.ac.uk/handle/1810/302070
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/