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Protein-protein binding site identification by enumerating the configurations
BACKGROUND: The ability to predict protein-protein binding sites has a wide range of applications, including signal transduction studies, de novo drug design, structure identification and comparison of functional sites. The interface in a complex involves two structurally matched protein subunits, a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3478195/ https://www.ncbi.nlm.nih.gov/pubmed/22768846 http://dx.doi.org/10.1186/1471-2105-13-158 |
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author | Guo, Fei Li, Shuai Cheng Wang, Lusheng Zhu, Daming |
author_facet | Guo, Fei Li, Shuai Cheng Wang, Lusheng Zhu, Daming |
author_sort | Guo, Fei |
collection | PubMed |
description | BACKGROUND: The ability to predict protein-protein binding sites has a wide range of applications, including signal transduction studies, de novo drug design, structure identification and comparison of functional sites. The interface in a complex involves two structurally matched protein subunits, and the binding sites can be predicted by identifying structural matches at protein surfaces. RESULTS: We propose a method which enumerates “all” the configurations (or poses) between two proteins (3D coordinates of the two subunits in a complex) and evaluates each configuration by the interaction between its components using the Atomic Contact Energy function. The enumeration is achieved efficiently by exploring a set of rigid transformations. Our approach incorporates a surface identification technique and a method for avoiding clashes of two subunits when computing rigid transformations. When the optimal transformations according to the Atomic Contact Energy function are identified, the corresponding binding sites are given as predictions. Our results show that this approach consistently performs better than other methods in binding site identification. CONCLUSIONS: Our method achieved a success rate higher than other methods, with the prediction quality improved in terms of both accuracy and coverage. Moreover, our method is being able to predict the configurations of two binding proteins, where most of other methods predict only the binding sites. The software package is available at http://sites.google.com/site/guofeics/dobi for non-commercial use. |
format | Online Article Text |
id | pubmed-3478195 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34781952012-10-23 Protein-protein binding site identification by enumerating the configurations Guo, Fei Li, Shuai Cheng Wang, Lusheng Zhu, Daming BMC Bioinformatics Research Article BACKGROUND: The ability to predict protein-protein binding sites has a wide range of applications, including signal transduction studies, de novo drug design, structure identification and comparison of functional sites. The interface in a complex involves two structurally matched protein subunits, and the binding sites can be predicted by identifying structural matches at protein surfaces. RESULTS: We propose a method which enumerates “all” the configurations (or poses) between two proteins (3D coordinates of the two subunits in a complex) and evaluates each configuration by the interaction between its components using the Atomic Contact Energy function. The enumeration is achieved efficiently by exploring a set of rigid transformations. Our approach incorporates a surface identification technique and a method for avoiding clashes of two subunits when computing rigid transformations. When the optimal transformations according to the Atomic Contact Energy function are identified, the corresponding binding sites are given as predictions. Our results show that this approach consistently performs better than other methods in binding site identification. CONCLUSIONS: Our method achieved a success rate higher than other methods, with the prediction quality improved in terms of both accuracy and coverage. Moreover, our method is being able to predict the configurations of two binding proteins, where most of other methods predict only the binding sites. The software package is available at http://sites.google.com/site/guofeics/dobi for non-commercial use. BioMed Central 2012-07-06 /pmc/articles/PMC3478195/ /pubmed/22768846 http://dx.doi.org/10.1186/1471-2105-13-158 Text en Copyright ©2012 Guo et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Guo, Fei Li, Shuai Cheng Wang, Lusheng Zhu, Daming Protein-protein binding site identification by enumerating the configurations |
title | Protein-protein binding site identification by enumerating the configurations |
title_full | Protein-protein binding site identification by enumerating the configurations |
title_fullStr | Protein-protein binding site identification by enumerating the configurations |
title_full_unstemmed | Protein-protein binding site identification by enumerating the configurations |
title_short | Protein-protein binding site identification by enumerating the configurations |
title_sort | protein-protein binding site identification by enumerating the configurations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3478195/ https://www.ncbi.nlm.nih.gov/pubmed/22768846 http://dx.doi.org/10.1186/1471-2105-13-158 |
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