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F. DiMaio, A. Soni, G. Phillips & J. Shavlik (2009).
Spherical-Harmonic Decomposition for Molecular Recognition in Electron-Density Maps. International Journal of Data Mining and Bioinformatics, 3, pp. 205-227. doi: 10.1504/IJDMB.2009.024852 NIHMSID: NIHMS68171 PMCID: PMC2696052
(The paper is in pre-publication form. It is an extension to: DiMaio et al. (BIBM 2007))

This publication is available in PDF.


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.

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