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Protein interface classification by evolutionary analysis

BACKGROUND: Distinguishing biologically relevant interfaces from lattice contacts in protein crystals is a fundamental problem in structural biology. Despite efforts towards the computational prediction of interface character, many issues are still unresolved. RESULTS: We present here a protein-prot...

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Detalles Bibliográficos
Autores principales: Duarte, Jose M, Srebniak, Adam, Schärer, Martin A, Capitani, Guido
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3556496/
https://www.ncbi.nlm.nih.gov/pubmed/23259833
http://dx.doi.org/10.1186/1471-2105-13-334
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author Duarte, Jose M
Srebniak, Adam
Schärer, Martin A
Capitani, Guido
author_facet Duarte, Jose M
Srebniak, Adam
Schärer, Martin A
Capitani, Guido
author_sort Duarte, Jose M
collection PubMed
description BACKGROUND: Distinguishing biologically relevant interfaces from lattice contacts in protein crystals is a fundamental problem in structural biology. Despite efforts towards the computational prediction of interface character, many issues are still unresolved. RESULTS: We present here a protein-protein interface classifier that relies on evolutionary data to detect the biological character of interfaces. The classifier uses a simple geometric measure, number of core residues, and two evolutionary indicators based on the sequence entropy of homolog sequences. Both aim at detecting differential selection pressure between interface core and rim or rest of surface. The core residues, defined as fully buried residues (>95% burial), appear to be fundamental determinants of biological interfaces: their number is in itself a powerful discriminator of interface character and together with the evolutionary measures it is able to clearly distinguish evolved biological contacts from crystal ones. We demonstrate that this definition of core residues leads to distinctively better results than earlier definitions from the literature. The stringent selection and quality filtering of structural and sequence data was key to the success of the method. Most importantly we demonstrate that a more conservative selection of homolog sequences - with relatively high sequence identities to the query - is able to produce a clearer signal than previous attempts. CONCLUSIONS: An evolutionary approach like the one presented here is key to the advancement of the field, which so far was missing an effective method exploiting the evolutionary character of protein interfaces. Its coverage and performance will only improve over time thanks to the incessant growth of sequence databases. Currently our method reaches an accuracy of 89% in classifying interfaces of the Ponstingl 2003 datasets and it lends itself to a variety of useful applications in structural biology and bioinformatics. We made the corresponding software implementation available to the community as an easy-to-use graphical web interface at http://www.eppic-web.org.
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spelling pubmed-35564962013-01-29 Protein interface classification by evolutionary analysis Duarte, Jose M Srebniak, Adam Schärer, Martin A Capitani, Guido BMC Bioinformatics Research Article BACKGROUND: Distinguishing biologically relevant interfaces from lattice contacts in protein crystals is a fundamental problem in structural biology. Despite efforts towards the computational prediction of interface character, many issues are still unresolved. RESULTS: We present here a protein-protein interface classifier that relies on evolutionary data to detect the biological character of interfaces. The classifier uses a simple geometric measure, number of core residues, and two evolutionary indicators based on the sequence entropy of homolog sequences. Both aim at detecting differential selection pressure between interface core and rim or rest of surface. The core residues, defined as fully buried residues (>95% burial), appear to be fundamental determinants of biological interfaces: their number is in itself a powerful discriminator of interface character and together with the evolutionary measures it is able to clearly distinguish evolved biological contacts from crystal ones. We demonstrate that this definition of core residues leads to distinctively better results than earlier definitions from the literature. The stringent selection and quality filtering of structural and sequence data was key to the success of the method. Most importantly we demonstrate that a more conservative selection of homolog sequences - with relatively high sequence identities to the query - is able to produce a clearer signal than previous attempts. CONCLUSIONS: An evolutionary approach like the one presented here is key to the advancement of the field, which so far was missing an effective method exploiting the evolutionary character of protein interfaces. Its coverage and performance will only improve over time thanks to the incessant growth of sequence databases. Currently our method reaches an accuracy of 89% in classifying interfaces of the Ponstingl 2003 datasets and it lends itself to a variety of useful applications in structural biology and bioinformatics. We made the corresponding software implementation available to the community as an easy-to-use graphical web interface at http://www.eppic-web.org. BioMed Central 2012-12-22 /pmc/articles/PMC3556496/ /pubmed/23259833 http://dx.doi.org/10.1186/1471-2105-13-334 Text en Copyright ©2012 Duarte 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
Duarte, Jose M
Srebniak, Adam
Schärer, Martin A
Capitani, Guido
Protein interface classification by evolutionary analysis
title Protein interface classification by evolutionary analysis
title_full Protein interface classification by evolutionary analysis
title_fullStr Protein interface classification by evolutionary analysis
title_full_unstemmed Protein interface classification by evolutionary analysis
title_short Protein interface classification by evolutionary analysis
title_sort protein interface classification by evolutionary analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3556496/
https://www.ncbi.nlm.nih.gov/pubmed/23259833
http://dx.doi.org/10.1186/1471-2105-13-334
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