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Progress and challenges in predicting protein interfaces

The majority of biological processes are mediated via protein–protein interactions. Determination of residues participating in such interactions improves our understanding of molecular mechanisms and facilitates the development of therapeutics. Experimental approaches to identifying interacting resi...

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Detalles Bibliográficos
Autores principales: Esmaielbeiki, Reyhaneh, Krawczyk, Konrad, Knapp, Bernhard, Nebel, Jean-Christophe, Deane, Charlotte M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719070/
https://www.ncbi.nlm.nih.gov/pubmed/25971595
http://dx.doi.org/10.1093/bib/bbv027
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author Esmaielbeiki, Reyhaneh
Krawczyk, Konrad
Knapp, Bernhard
Nebel, Jean-Christophe
Deane, Charlotte M.
author_facet Esmaielbeiki, Reyhaneh
Krawczyk, Konrad
Knapp, Bernhard
Nebel, Jean-Christophe
Deane, Charlotte M.
author_sort Esmaielbeiki, Reyhaneh
collection PubMed
description The majority of biological processes are mediated via protein–protein interactions. Determination of residues participating in such interactions improves our understanding of molecular mechanisms and facilitates the development of therapeutics. Experimental approaches to identifying interacting residues, such as mutagenesis, are costly and time-consuming and thus, computational methods for this purpose could streamline conventional pipelines. Here we review the field of computational protein interface prediction. We make a distinction between methods which address proteins in general and those targeted at antibodies, owing to the radically different binding mechanism of antibodies. We organize the multitude of currently available methods hierarchically based on required input and prediction principles to provide an overview of the field.
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spelling pubmed-47190702016-01-21 Progress and challenges in predicting protein interfaces Esmaielbeiki, Reyhaneh Krawczyk, Konrad Knapp, Bernhard Nebel, Jean-Christophe Deane, Charlotte M. Brief Bioinform Papers The majority of biological processes are mediated via protein–protein interactions. Determination of residues participating in such interactions improves our understanding of molecular mechanisms and facilitates the development of therapeutics. Experimental approaches to identifying interacting residues, such as mutagenesis, are costly and time-consuming and thus, computational methods for this purpose could streamline conventional pipelines. Here we review the field of computational protein interface prediction. We make a distinction between methods which address proteins in general and those targeted at antibodies, owing to the radically different binding mechanism of antibodies. We organize the multitude of currently available methods hierarchically based on required input and prediction principles to provide an overview of the field. Oxford University Press 2016-01 2015-05-13 /pmc/articles/PMC4719070/ /pubmed/25971595 http://dx.doi.org/10.1093/bib/bbv027 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Papers
Esmaielbeiki, Reyhaneh
Krawczyk, Konrad
Knapp, Bernhard
Nebel, Jean-Christophe
Deane, Charlotte M.
Progress and challenges in predicting protein interfaces
title Progress and challenges in predicting protein interfaces
title_full Progress and challenges in predicting protein interfaces
title_fullStr Progress and challenges in predicting protein interfaces
title_full_unstemmed Progress and challenges in predicting protein interfaces
title_short Progress and challenges in predicting protein interfaces
title_sort progress and challenges in predicting protein interfaces
topic Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4719070/
https://www.ncbi.nlm.nih.gov/pubmed/25971595
http://dx.doi.org/10.1093/bib/bbv027
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