Cargando…
Contacts-based prediction of binding affinity in protein–protein complexes
Almost all critical functions in cells rely on specific protein–protein interactions. Understanding these is therefore crucial in the investigation of biological systems. Despite all past efforts, we still lack a thorough understanding of the energetics of association of proteins. Here, we introduce...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523921/ https://www.ncbi.nlm.nih.gov/pubmed/26193119 http://dx.doi.org/10.7554/eLife.07454 |
_version_ | 1782384135828930560 |
---|---|
author | Vangone, Anna Bonvin, Alexandre MJJ |
author_facet | Vangone, Anna Bonvin, Alexandre MJJ |
author_sort | Vangone, Anna |
collection | PubMed |
description | Almost all critical functions in cells rely on specific protein–protein interactions. Understanding these is therefore crucial in the investigation of biological systems. Despite all past efforts, we still lack a thorough understanding of the energetics of association of proteins. Here, we introduce a new and simple approach to predict binding affinity based on functional and structural features of the biological system, namely the network of interfacial contacts. We assess its performance against a protein–protein binding affinity benchmark and show that both experimental methods used for affinity measurements and conformational changes have a strong impact on prediction accuracy. Using a subset of complexes with reliable experimental binding affinities and combining our contacts and contact-types-based model with recent observations on the role of the non-interacting surface in protein–protein interactions, we reach a high prediction accuracy for such a diverse dataset outperforming all other tested methods. DOI: http://dx.doi.org/10.7554/eLife.07454.001 |
format | Online Article Text |
id | pubmed-4523921 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-45239212015-08-05 Contacts-based prediction of binding affinity in protein–protein complexes Vangone, Anna Bonvin, Alexandre MJJ eLife Biophysics and Structural Biology Almost all critical functions in cells rely on specific protein–protein interactions. Understanding these is therefore crucial in the investigation of biological systems. Despite all past efforts, we still lack a thorough understanding of the energetics of association of proteins. Here, we introduce a new and simple approach to predict binding affinity based on functional and structural features of the biological system, namely the network of interfacial contacts. We assess its performance against a protein–protein binding affinity benchmark and show that both experimental methods used for affinity measurements and conformational changes have a strong impact on prediction accuracy. Using a subset of complexes with reliable experimental binding affinities and combining our contacts and contact-types-based model with recent observations on the role of the non-interacting surface in protein–protein interactions, we reach a high prediction accuracy for such a diverse dataset outperforming all other tested methods. DOI: http://dx.doi.org/10.7554/eLife.07454.001 eLife Sciences Publications, Ltd 2015-07-20 /pmc/articles/PMC4523921/ /pubmed/26193119 http://dx.doi.org/10.7554/eLife.07454 Text en © 2015, Vangone and Bonvin http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Biophysics and Structural Biology Vangone, Anna Bonvin, Alexandre MJJ Contacts-based prediction of binding affinity in protein–protein complexes |
title | Contacts-based prediction of binding affinity in protein–protein complexes |
title_full | Contacts-based prediction of binding affinity in protein–protein complexes |
title_fullStr | Contacts-based prediction of binding affinity in protein–protein complexes |
title_full_unstemmed | Contacts-based prediction of binding affinity in protein–protein complexes |
title_short | Contacts-based prediction of binding affinity in protein–protein complexes |
title_sort | contacts-based prediction of binding affinity in protein–protein complexes |
topic | Biophysics and Structural Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523921/ https://www.ncbi.nlm.nih.gov/pubmed/26193119 http://dx.doi.org/10.7554/eLife.07454 |
work_keys_str_mv | AT vangoneanna contactsbasedpredictionofbindingaffinityinproteinproteincomplexes AT bonvinalexandremjj contactsbasedpredictionofbindingaffinityinproteinproteincomplexes |