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IRaPPA: information retrieval based integration of biophysical models for protein assembly selection
MOTIVATION: In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783285/ https://www.ncbi.nlm.nih.gov/pubmed/28200016 http://dx.doi.org/10.1093/bioinformatics/btx068 |
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author | Moal, Iain H Barradas-Bautista, Didier Jiménez-García, Brian Torchala, Mieczyslaw van der Velde, Arjan Vreven, Thom Weng, Zhiping Bates, Paul A Fernández-Recio, Juan |
author_facet | Moal, Iain H Barradas-Bautista, Didier Jiménez-García, Brian Torchala, Mieczyslaw van der Velde, Arjan Vreven, Thom Weng, Zhiping Bates, Paul A Fernández-Recio, Juan |
author_sort | Moal, Iain H |
collection | PubMed |
description | MOTIVATION: In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction. RESULTS: Atomic modeling of protein–protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100. AVAILABILITY AND IMPLEMENTATION: IRaPPA has been implemented in the SwarmDock server (http://bmm.crick.ac.uk/∼SwarmDock/), pyDock server (http://life.bsc.es/pid/pydockrescoring/) and ZDOCK server (http://zdock.umassmed.edu/), with code available on request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-5783285 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57832852018-01-24 IRaPPA: information retrieval based integration of biophysical models for protein assembly selection Moal, Iain H Barradas-Bautista, Didier Jiménez-García, Brian Torchala, Mieczyslaw van der Velde, Arjan Vreven, Thom Weng, Zhiping Bates, Paul A Fernández-Recio, Juan Bioinformatics Original Papers MOTIVATION: In order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction. RESULTS: Atomic modeling of protein–protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100. AVAILABILITY AND IMPLEMENTATION: IRaPPA has been implemented in the SwarmDock server (http://bmm.crick.ac.uk/∼SwarmDock/), pyDock server (http://life.bsc.es/pid/pydockrescoring/) and ZDOCK server (http://zdock.umassmed.edu/), with code available on request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-06-15 2017-02-14 /pmc/articles/PMC5783285/ /pubmed/28200016 http://dx.doi.org/10.1093/bioinformatics/btx068 Text en © The Author 2017. 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 | Original Papers Moal, Iain H Barradas-Bautista, Didier Jiménez-García, Brian Torchala, Mieczyslaw van der Velde, Arjan Vreven, Thom Weng, Zhiping Bates, Paul A Fernández-Recio, Juan IRaPPA: information retrieval based integration of biophysical models for protein assembly selection |
title | IRaPPA: information retrieval based integration of biophysical models for protein assembly selection |
title_full | IRaPPA: information retrieval based integration of biophysical models for protein assembly selection |
title_fullStr | IRaPPA: information retrieval based integration of biophysical models for protein assembly selection |
title_full_unstemmed | IRaPPA: information retrieval based integration of biophysical models for protein assembly selection |
title_short | IRaPPA: information retrieval based integration of biophysical models for protein assembly selection |
title_sort | irappa: information retrieval based integration of biophysical models for protein assembly selection |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783285/ https://www.ncbi.nlm.nih.gov/pubmed/28200016 http://dx.doi.org/10.1093/bioinformatics/btx068 |
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