title: Spherical-harmonic decomposition for molecular recognition in electron-density maps.
abstract: Several methods for automatically constructing a protein model from an electron-density map require searching for many small protein-fragment templates in the density. We propose to use the spherical-harmonic decomposition of the template and the maps density to speed this matching. Unlike other template-matching approaches, this allows us to eliminate large portions of the map unlikely to match any templates. We train several first-pass filters for this elimination task. We show our new template-matching method improves accuracy and reduces running time, compared to previous approaches. Finally, we extend our method to produce a structural-homology detection algorithm using electron density.
authors.affiliation: Department of Computer Sciences, University of Wisconsin, 1210 W. Dayton St., Madison, WI, USA. dimaio@u.washington.edu
authors.forename: Frank P
authors.initials: FP
authors.lastname: DiMaio
authors.forename: Ameet B
authors.initials: AB
authors.lastname: Soni
authors.forename: George N
authors.initials: GN
authors.lastname: Phillips
authors.forename: Jude W
authors.initials: JW
authors.lastname: Shavlik
mesh_terms: D000465:Algorithms; D018360:Crystallography, X-Ray / Q000379:methods*; D030562:Databases, Protein; D008958:Models, Molecular; D011336:Probability; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D011506:Proteins