title: Fast Fourier feature recognition.
abstract: Various approaches have been demonstrated for the automatic interpretation of crystallographic data in terms of atomic models. The use of a masked Fourier-based search function has some benefits for this task. The application and optimization of this procedure is discussed in detail. The search function also acquires a statistical significance when used with an appropriate electron-density target and weighting, giving rise to improved results at low resolutions. Methods are discussed for building a library of protein fragments suitable for use with this procedure. These methods are demonstrated with the construction of a statistical target for the identification of short helical fragments in the electron density.
authors.affiliation: Department of Chemistry, University of York, Heslington, York YO10 5DD, England. cowtan@yorvic.york.ac.uk
authors.forename: K
authors.initials: K
authors.lastname: Cowtan
mesh_terms: D018360:Crystallography, X-Ray; D030562:Databases, Protein; D005583:Fourier Analysis; D008958:Models, Molecular; D015233:Models, Statistical; D010446:Peptide Fragments / Q000737:chemistry; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D010446:Peptide Fragments; D011506:Proteins