Protein structure alignment using geometrical features

Authors:
S. Alireza Aghili;Divyakant Agrawal;Amr El Abbadi
Affiliations:
University of California Santa Barbara, Santa Barbara, CA;University of California Santa Barbara, Santa Barbara, CA;University of California Santa Barbara, Santa Barbara, CA
Venue:
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Year:
2004

Citing 2
Cited 1

Towards Index-based Similarity Search for Protein Structure Databases

CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
CTSS: A Robust and Efficient Method for Protein Structure Alignment Based on Local Geometrical and Biological Features

CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics

PADS: protein structure alignment using directional shape signatures

DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications

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Abstract

A novel approach for similarity search on protein structure databases is proposed which incorporates the three dimensional coordinates of the main atoms of each amino acid and extracts a geometrical signature along with the direction of the given amino acid. As a result, each protein is presented by a series of feature vectors representing local geometry, shape, direction, and secondary structure assignment of its amino acid constituents. Furthermore, a residue-to-residue distance matrix is calculated and is incorporated into a local alignment dynamic programming algorithm to find the similar portions of two given proteins and finally a sequence alignment step is used as the last filtration step. The optimal superimposition of the detected similar regions is used to assess the quality of the results. The proposed algorithm is fast and accurate and hence could be used for the analysis of large protein structure similarity.