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Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular...

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Detalles Bibliográficos
Autores principales: Bhakat, Soumendranath, Åberg, Emil, Söderhjelm, Pär
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5767213/
https://www.ncbi.nlm.nih.gov/pubmed/29052792
http://dx.doi.org/10.1007/s10822-017-0074-x
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author Bhakat, Soumendranath
Åberg, Emil
Söderhjelm, Pär
author_facet Bhakat, Soumendranath
Åberg, Emil
Söderhjelm, Pär
author_sort Bhakat, Soumendranath
collection PubMed
description Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-017-0074-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-57672132018-01-25 Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling Bhakat, Soumendranath Åberg, Emil Söderhjelm, Pär J Comput Aided Mol Des Article Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-017-0074-x) contains supplementary material, which is available to authorized users. Springer International Publishing 2017-10-20 2018 /pmc/articles/PMC5767213/ /pubmed/29052792 http://dx.doi.org/10.1007/s10822-017-0074-x Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Bhakat, Soumendranath
Åberg, Emil
Söderhjelm, Pär
Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
title Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
title_full Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
title_fullStr Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
title_full_unstemmed Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
title_short Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
title_sort prediction of binding poses to fxr using multi-targeted docking combined with molecular dynamics and enhanced sampling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5767213/
https://www.ncbi.nlm.nih.gov/pubmed/29052792
http://dx.doi.org/10.1007/s10822-017-0074-x
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