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DoSA: Database of Structural Alignments
Protein structure alignment is a crucial step in protein structure–function analysis. Despite the advances in protein structure alignment algorithms, some of the local conformationally similar regions are mislabeled as structurally variable regions (SVRs). These regions are not well superimposed bec...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3708618/ https://www.ncbi.nlm.nih.gov/pubmed/23846594 http://dx.doi.org/10.1093/database/bat048 |
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author | Mahajan, Swapnil Agarwal, Garima Iftekhar, Mohammed Offmann, Bernard de Brevern, Alexandre G. Srinivasan, Narayanaswamy |
author_facet | Mahajan, Swapnil Agarwal, Garima Iftekhar, Mohammed Offmann, Bernard de Brevern, Alexandre G. Srinivasan, Narayanaswamy |
author_sort | Mahajan, Swapnil |
collection | PubMed |
description | Protein structure alignment is a crucial step in protein structure–function analysis. Despite the advances in protein structure alignment algorithms, some of the local conformationally similar regions are mislabeled as structurally variable regions (SVRs). These regions are not well superimposed because of differences in their spatial orientations. The Database of Structural Alignments (DoSA) addresses this gap in identification of local structural similarities obscured in global protein structural alignments by realigning SVRs using an algorithm based on protein blocks. A set of protein blocks is a structural alphabet that abstracts protein structures into 16 unique local structural motifs. DoSA provides unique information about 159 780 conformationally similar and 56 140 conformationally dissimilar SVRs in 74 705 pairwise structural alignments of homologous proteins. The information provided on conformationally similar and dissimilar SVRs can be helpful to model loop regions. It is also conceivable that conformationally similar SVRs with conserved residues could potentially contribute toward functional integrity of homologues, and hence identifying such SVRs could be helpful in understanding the structural basis of protein function. Database URL: http://bo-protscience.fr/dosa/ |
format | Online Article Text |
id | pubmed-3708618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-37086182013-07-11 DoSA: Database of Structural Alignments Mahajan, Swapnil Agarwal, Garima Iftekhar, Mohammed Offmann, Bernard de Brevern, Alexandre G. Srinivasan, Narayanaswamy Database (Oxford) Original Article Protein structure alignment is a crucial step in protein structure–function analysis. Despite the advances in protein structure alignment algorithms, some of the local conformationally similar regions are mislabeled as structurally variable regions (SVRs). These regions are not well superimposed because of differences in their spatial orientations. The Database of Structural Alignments (DoSA) addresses this gap in identification of local structural similarities obscured in global protein structural alignments by realigning SVRs using an algorithm based on protein blocks. A set of protein blocks is a structural alphabet that abstracts protein structures into 16 unique local structural motifs. DoSA provides unique information about 159 780 conformationally similar and 56 140 conformationally dissimilar SVRs in 74 705 pairwise structural alignments of homologous proteins. The information provided on conformationally similar and dissimilar SVRs can be helpful to model loop regions. It is also conceivable that conformationally similar SVRs with conserved residues could potentially contribute toward functional integrity of homologues, and hence identifying such SVRs could be helpful in understanding the structural basis of protein function. Database URL: http://bo-protscience.fr/dosa/ Oxford University Press 2013-07-11 /pmc/articles/PMC3708618/ /pubmed/23846594 http://dx.doi.org/10.1093/database/bat048 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Mahajan, Swapnil Agarwal, Garima Iftekhar, Mohammed Offmann, Bernard de Brevern, Alexandre G. Srinivasan, Narayanaswamy DoSA: Database of Structural Alignments |
title | DoSA: Database of Structural Alignments |
title_full | DoSA: Database of Structural Alignments |
title_fullStr | DoSA: Database of Structural Alignments |
title_full_unstemmed | DoSA: Database of Structural Alignments |
title_short | DoSA: Database of Structural Alignments |
title_sort | dosa: database of structural alignments |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3708618/ https://www.ncbi.nlm.nih.gov/pubmed/23846594 http://dx.doi.org/10.1093/database/bat048 |
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