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Docking approaches for modeling multi-molecular assemblies

Computational docking approaches aim to overcome the limited availability of experimental structural data on protein–protein interactions, which are key in biology. The field is rapidly moving from the traditional docking methodologies for modeling of binary complexes to more integrative approaches...

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Detalles Bibliográficos
Autores principales: Rosell, Mireia, Fernández-Recio, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7324114/
https://www.ncbi.nlm.nih.gov/pubmed/32615514
http://dx.doi.org/10.1016/j.sbi.2020.05.016
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author Rosell, Mireia
Fernández-Recio, Juan
author_facet Rosell, Mireia
Fernández-Recio, Juan
author_sort Rosell, Mireia
collection PubMed
description Computational docking approaches aim to overcome the limited availability of experimental structural data on protein–protein interactions, which are key in biology. The field is rapidly moving from the traditional docking methodologies for modeling of binary complexes to more integrative approaches using template-based, data-driven modeling of multi-molecular assemblies. We will review here the predictive capabilities of current docking methods in blind conditions, based on the results from the most recent community-wide blind experiments. Integration of template-based and ab initio docking approaches is emerging as the optimal strategy for modeling protein complexes and multimolecular assemblies. We will also review the new methodological advances on ab initio docking and integrative modeling.
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spelling pubmed-73241142020-06-30 Docking approaches for modeling multi-molecular assemblies Rosell, Mireia Fernández-Recio, Juan Curr Opin Struct Biol Article Computational docking approaches aim to overcome the limited availability of experimental structural data on protein–protein interactions, which are key in biology. The field is rapidly moving from the traditional docking methodologies for modeling of binary complexes to more integrative approaches using template-based, data-driven modeling of multi-molecular assemblies. We will review here the predictive capabilities of current docking methods in blind conditions, based on the results from the most recent community-wide blind experiments. Integration of template-based and ab initio docking approaches is emerging as the optimal strategy for modeling protein complexes and multimolecular assemblies. We will also review the new methodological advances on ab initio docking and integrative modeling. Elsevier Ltd. 2020-10 2020-06-29 /pmc/articles/PMC7324114/ /pubmed/32615514 http://dx.doi.org/10.1016/j.sbi.2020.05.016 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Rosell, Mireia
Fernández-Recio, Juan
Docking approaches for modeling multi-molecular assemblies
title Docking approaches for modeling multi-molecular assemblies
title_full Docking approaches for modeling multi-molecular assemblies
title_fullStr Docking approaches for modeling multi-molecular assemblies
title_full_unstemmed Docking approaches for modeling multi-molecular assemblies
title_short Docking approaches for modeling multi-molecular assemblies
title_sort docking approaches for modeling multi-molecular assemblies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7324114/
https://www.ncbi.nlm.nih.gov/pubmed/32615514
http://dx.doi.org/10.1016/j.sbi.2020.05.016
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