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Modeling and fitting protein-protein complexes to predict change of binding energy
It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diag...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865953/ https://www.ncbi.nlm.nih.gov/pubmed/27173910 http://dx.doi.org/10.1038/srep25406 |
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author | Dourado, Daniel F.A.R. Flores, Samuel Coulbourn |
author_facet | Dourado, Daniel F.A.R. Flores, Samuel Coulbourn |
author_sort | Dourado, Daniel F.A.R. |
collection | PubMed |
description | It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable. |
format | Online Article Text |
id | pubmed-4865953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48659532016-05-23 Modeling and fitting protein-protein complexes to predict change of binding energy Dourado, Daniel F.A.R. Flores, Samuel Coulbourn Sci Rep Article It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (ΔΔG), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue ΔΔG prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict ΔΔG, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental ΔΔG measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable. Nature Publishing Group 2016-05-13 /pmc/articles/PMC4865953/ /pubmed/27173910 http://dx.doi.org/10.1038/srep25406 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Dourado, Daniel F.A.R. Flores, Samuel Coulbourn Modeling and fitting protein-protein complexes to predict change of binding energy |
title | Modeling and fitting protein-protein complexes to predict change of binding energy |
title_full | Modeling and fitting protein-protein complexes to predict change of binding energy |
title_fullStr | Modeling and fitting protein-protein complexes to predict change of binding energy |
title_full_unstemmed | Modeling and fitting protein-protein complexes to predict change of binding energy |
title_short | Modeling and fitting protein-protein complexes to predict change of binding energy |
title_sort | modeling and fitting protein-protein complexes to predict change of binding energy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865953/ https://www.ncbi.nlm.nih.gov/pubmed/27173910 http://dx.doi.org/10.1038/srep25406 |
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