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NOXclass: prediction of protein-protein interaction types

BACKGROUND: Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. Th...

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Detalles Bibliográficos
Autores principales: Zhu, Hongbo, Domingues, Francisco S, Sommer, lngolf, Lengauer, Thomas
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1386716/
https://www.ncbi.nlm.nih.gov/pubmed/16423290
http://dx.doi.org/10.1186/1471-2105-7-27
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author Zhu, Hongbo
Domingues, Francisco S
Sommer, lngolf
Lengauer, Thomas
author_facet Zhu, Hongbo
Domingues, Francisco S
Sommer, lngolf
Lengauer, Thomas
author_sort Zhu, Hongbo
collection PubMed
description BACKGROUND: Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available. RESULTS: Six interface properties have been investigated on a dataset of 243 protein interactions. The six properties have been combined using a support vector machine algorithm, resulting in NOXclass, a classifier for distinguishing obligate, non-obligate and crystal packing interactions. We achieve an accuracy of 91.8% for the classification of these three types of interactions using a leave-one-out cross-validation procedure. CONCLUSION: NOXclass allows the interpretation and analysis of protein quaternary structures. In particular, it generates testable hypotheses regarding the nature of protein-protein interactions, when experimental results are not available. We expect this server will benefit the users of protein structural models, as well as protein crystallographers and NMR spectroscopists. A web server based on the method and the datasets used in this study are available at .
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spelling pubmed-13867162006-04-14 NOXclass: prediction of protein-protein interaction types Zhu, Hongbo Domingues, Francisco S Sommer, lngolf Lengauer, Thomas BMC Bioinformatics Software BACKGROUND: Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available. RESULTS: Six interface properties have been investigated on a dataset of 243 protein interactions. The six properties have been combined using a support vector machine algorithm, resulting in NOXclass, a classifier for distinguishing obligate, non-obligate and crystal packing interactions. We achieve an accuracy of 91.8% for the classification of these three types of interactions using a leave-one-out cross-validation procedure. CONCLUSION: NOXclass allows the interpretation and analysis of protein quaternary structures. In particular, it generates testable hypotheses regarding the nature of protein-protein interactions, when experimental results are not available. We expect this server will benefit the users of protein structural models, as well as protein crystallographers and NMR spectroscopists. A web server based on the method and the datasets used in this study are available at . BioMed Central 2006-01-19 /pmc/articles/PMC1386716/ /pubmed/16423290 http://dx.doi.org/10.1186/1471-2105-7-27 Text en Copyright © 2006 Zhu et al; licensee BioMed Central Ltd.
spellingShingle Software
Zhu, Hongbo
Domingues, Francisco S
Sommer, lngolf
Lengauer, Thomas
NOXclass: prediction of protein-protein interaction types
title NOXclass: prediction of protein-protein interaction types
title_full NOXclass: prediction of protein-protein interaction types
title_fullStr NOXclass: prediction of protein-protein interaction types
title_full_unstemmed NOXclass: prediction of protein-protein interaction types
title_short NOXclass: prediction of protein-protein interaction types
title_sort noxclass: prediction of protein-protein interaction types
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1386716/
https://www.ncbi.nlm.nih.gov/pubmed/16423290
http://dx.doi.org/10.1186/1471-2105-7-27
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