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Finding optimal interaction interface alignments between biological complexes
Motivation: Biological molecules perform their functions through interactions with other molecules. Structure alignment of interaction interfaces between biological complexes is an indispensable step in detecting their structural similarities, which are keys to understanding their evolutionary histo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4765866/ https://www.ncbi.nlm.nih.gov/pubmed/26072475 http://dx.doi.org/10.1093/bioinformatics/btv242 |
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author | Cui, Xuefeng Naveed, Hammad Gao, Xin |
author_facet | Cui, Xuefeng Naveed, Hammad Gao, Xin |
author_sort | Cui, Xuefeng |
collection | PubMed |
description | Motivation: Biological molecules perform their functions through interactions with other molecules. Structure alignment of interaction interfaces between biological complexes is an indispensable step in detecting their structural similarities, which are keys to understanding their evolutionary histories and functions. Although various structure alignment methods have been developed to successfully access the similarities of protein structures or certain types of interaction interfaces, existing alignment tools cannot directly align arbitrary types of interfaces formed by protein, DNA or RNA molecules. Specifically, they require a ‘blackbox preprocessing’ to standardize interface types and chain identifiers. Yet their performance is limited and sometimes unsatisfactory. Results: Here we introduce a novel method, PROSTA-inter, that automatically determines and aligns interaction interfaces between two arbitrary types of complex structures. Our method uses sequentially remote fragments to search for the optimal superimposition. The optimal residue matching problem is then formulated as a maximum weighted bipartite matching problem to detect the optimal sequence order-independent alignment. Benchmark evaluation on all non-redundant protein–DNA complexes in PDB shows significant performance improvement of our method over TM-align and iAlign (with the ‘blackbox preprocessing’). Two case studies where our method discovers, for the first time, structural similarities between two pairs of functionally related protein–DNA complexes are presented. We further demonstrate the power of our method on detecting structural similarities between a protein–protein complex and a protein–RNA complex, which is biologically known as a protein–RNA mimicry case. Availability and implementation: The PROSTA-inter web-server is publicly available at http://www.cbrc.kaust.edu.sa/prosta/. Contact: xin.gao@kaust.edu.sa |
format | Online Article Text |
id | pubmed-4765866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47658662016-03-04 Finding optimal interaction interface alignments between biological complexes Cui, Xuefeng Naveed, Hammad Gao, Xin Bioinformatics Ismb/Eccb 2015 Proceedings Papers Committee July 10 to July 14, 2015, Dublin, Ireland Motivation: Biological molecules perform their functions through interactions with other molecules. Structure alignment of interaction interfaces between biological complexes is an indispensable step in detecting their structural similarities, which are keys to understanding their evolutionary histories and functions. Although various structure alignment methods have been developed to successfully access the similarities of protein structures or certain types of interaction interfaces, existing alignment tools cannot directly align arbitrary types of interfaces formed by protein, DNA or RNA molecules. Specifically, they require a ‘blackbox preprocessing’ to standardize interface types and chain identifiers. Yet their performance is limited and sometimes unsatisfactory. Results: Here we introduce a novel method, PROSTA-inter, that automatically determines and aligns interaction interfaces between two arbitrary types of complex structures. Our method uses sequentially remote fragments to search for the optimal superimposition. The optimal residue matching problem is then formulated as a maximum weighted bipartite matching problem to detect the optimal sequence order-independent alignment. Benchmark evaluation on all non-redundant protein–DNA complexes in PDB shows significant performance improvement of our method over TM-align and iAlign (with the ‘blackbox preprocessing’). Two case studies where our method discovers, for the first time, structural similarities between two pairs of functionally related protein–DNA complexes are presented. We further demonstrate the power of our method on detecting structural similarities between a protein–protein complex and a protein–RNA complex, which is biologically known as a protein–RNA mimicry case. Availability and implementation: The PROSTA-inter web-server is publicly available at http://www.cbrc.kaust.edu.sa/prosta/. Contact: xin.gao@kaust.edu.sa Oxford University Press 2015-06-15 2015-06-10 /pmc/articles/PMC4765866/ /pubmed/26072475 http://dx.doi.org/10.1093/bioinformatics/btv242 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Ismb/Eccb 2015 Proceedings Papers Committee July 10 to July 14, 2015, Dublin, Ireland Cui, Xuefeng Naveed, Hammad Gao, Xin Finding optimal interaction interface alignments between biological complexes |
title | Finding optimal interaction interface alignments between biological complexes |
title_full | Finding optimal interaction interface alignments between biological complexes |
title_fullStr | Finding optimal interaction interface alignments between biological complexes |
title_full_unstemmed | Finding optimal interaction interface alignments between biological complexes |
title_short | Finding optimal interaction interface alignments between biological complexes |
title_sort | finding optimal interaction interface alignments between biological complexes |
topic | Ismb/Eccb 2015 Proceedings Papers Committee July 10 to July 14, 2015, Dublin, Ireland |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4765866/ https://www.ncbi.nlm.nih.gov/pubmed/26072475 http://dx.doi.org/10.1093/bioinformatics/btv242 |
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