Projections for fast protein structure retrieval

<p>Abstract</p> <p>Background</p> <p>In recent times, there has been an exponential rise in the number of protein structures in databases e.g. PDB. So, design of fast algorithms capable of querying such databases is becoming an increasingly important research issue. Thi...

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Main Authors: Bhattacharyya Chiranjib, Bhattacharya Sourangshu, Chandra Nagasuma R
Format: Article
Language:English
Published: BMC 2006-12-01
Series:BMC Bioinformatics
Online Access:http://dx.doi.org/10.1186/1471-2105-7-S5-S5
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spelling doaj-a151dccaf5c34e9c90a46d4a220da9272020-11-25T02:27:43ZengBMCBMC Bioinformatics1471-21052006-12-017Suppl 5S510.1186/1471-2105-7-S5-S5Projections for fast protein structure retrievalBhattacharyya ChiranjibBhattacharya SourangshuChandra Nagasuma R<p>Abstract</p> <p>Background</p> <p>In recent times, there has been an exponential rise in the number of protein structures in databases e.g. PDB. So, design of fast algorithms capable of querying such databases is becoming an increasingly important research issue. This paper reports an algorithm, motivated from spectral graph matching techniques, for retrieving protein structures similar to a query structure from a large protein structure database. Each protein structure is specified by the 3D coordinates of residues of the protein. The algorithm is based on a novel characterization of the residues, called projections, leading to a similarity measure between the residues of the two proteins. This measure is exploited to efficiently compute the optimal equivalences.</p> <p>Results</p> <p>Experimental results show that, the current algorithm outperforms the state of the art on benchmark datasets in terms of speed without losing accuracy. Search results on SCOP 95% nonredundant database, for fold similarity with 5 proteins from different SCOP classes show that the current method performs competitively with the standard algorithm CE. The algorithm is also capable of detecting non-topological similarities between two proteins which is not possible with most of the state of the art tools like Dali.</p> http://dx.doi.org/10.1186/1471-2105-7-S5-S5
collection DOAJ
language English
format Article
sources DOAJ
author Bhattacharyya Chiranjib
Bhattacharya Sourangshu
Chandra Nagasuma R
spellingShingle Bhattacharyya Chiranjib
Bhattacharya Sourangshu
Chandra Nagasuma R
Projections for fast protein structure retrieval
BMC Bioinformatics
author_facet Bhattacharyya Chiranjib
Bhattacharya Sourangshu
Chandra Nagasuma R
author_sort Bhattacharyya Chiranjib
title Projections for fast protein structure retrieval
title_short Projections for fast protein structure retrieval
title_full Projections for fast protein structure retrieval
title_fullStr Projections for fast protein structure retrieval
title_full_unstemmed Projections for fast protein structure retrieval
title_sort projections for fast protein structure retrieval
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2006-12-01
description <p>Abstract</p> <p>Background</p> <p>In recent times, there has been an exponential rise in the number of protein structures in databases e.g. PDB. So, design of fast algorithms capable of querying such databases is becoming an increasingly important research issue. This paper reports an algorithm, motivated from spectral graph matching techniques, for retrieving protein structures similar to a query structure from a large protein structure database. Each protein structure is specified by the 3D coordinates of residues of the protein. The algorithm is based on a novel characterization of the residues, called projections, leading to a similarity measure between the residues of the two proteins. This measure is exploited to efficiently compute the optimal equivalences.</p> <p>Results</p> <p>Experimental results show that, the current algorithm outperforms the state of the art on benchmark datasets in terms of speed without losing accuracy. Search results on SCOP 95% nonredundant database, for fold similarity with 5 proteins from different SCOP classes show that the current method performs competitively with the standard algorithm CE. The algorithm is also capable of detecting non-topological similarities between two proteins which is not possible with most of the state of the art tools like Dali.</p>
url http://dx.doi.org/10.1186/1471-2105-7-S5-S5
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AT bhattacharyasourangshu projectionsforfastproteinstructureretrieval
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