Cargando…
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...
Autores principales: | , , |
---|---|
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 |
_version_ | 1783292491689099264 |
---|---|
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. |
format | Online Article Text |
id | pubmed-5767213 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT bhakatsoumendranath predictionofbindingposestofxrusingmultitargeteddockingcombinedwithmoleculardynamicsandenhancedsampling AT abergemil predictionofbindingposestofxrusingmultitargeteddockingcombinedwithmoleculardynamicsandenhancedsampling AT soderhjelmpar predictionofbindingposestofxrusingmultitargeteddockingcombinedwithmoleculardynamicsandenhancedsampling |