Title: Spherical-harmonic decomposition for molecular recognition in electron-density maps

Authors: Frank P. DiMaio, Ameet B. Soni, George N. Phillips, Jude W. Shavlik

Addresses: Departments of Computer Sciences and Biostatistics and Medical Informatics, University of Wisconsin, 1210 W. Dayton St., Madison, WI, USA. ' Departments of Computer Sciences and Biostatistics and Medical Informatics, University of Wisconsin, 1210 W. Dayton St., Madison, WI, USA. ' Departments of Biochemistry and Computer Sciences, University of Wisconsin, 433 Babcock Dr., Madison, WI, USA. ' Departments of Computer Sciences and Biostatistics and Medical Informatics, University of Wisconsin, 1210 W. Dayton St., Madison, Madison, WI, USA

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.

Keywords: spherical harmonics; protein structure determination; electron density maps; map interpretation; protein modelling; bioinformatics; data mining; molecular recognition.

DOI: 10.1504/IJDMB.2009.024852

International Journal of Data Mining and Bioinformatics, 2009 Vol.3 No.2, pp.205 - 227

Published online: 01 May 2009 *

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