title: Fingerprint-based structure retrieval using electron density.
abstract: We present a computational approach that can quickly search a large protein structural database to identify structures that fit a given electron density, such as determined by cryo-electron microscopy. We use geometric invariants (fingerprints) constructed using 3D Zernike moments to describe the electron density, and reduce the problem of fitting of the structure to the electron density to simple fingerprint comparison. Using this approach, we are able to screen the entire Protein Data Bank and identify structures that fit two experimental electron densities determined by cryo-electron microscopy.
authors.affiliation: Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7260, USA.
authors.forename: Shuangye
authors.initials: S
authors.lastname: Yin
authors.forename: Nikolay V
authors.initials: NV
authors.lastname: Dokholyan
mesh_terms: D018360:Crystallography, X-Ray; D030562:Databases, Protein; D016247:Information Storage and Retrieval; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins