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

Bhakat, Soumendranath LU ; Åberg, Emil and Söderhjelm, Pär LU (2017) In Journal of Computer-Aided Molecular Design p.1-15
Abstract

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... (More)

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.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
epub
subject
keywords
D3R, Docking, MD simulation, Pose prediction, Protein–ligand binding, Reconnaissance metadynamics
in
Journal of Computer-Aided Molecular Design
pages
15 pages
publisher
Kluwer
external identifiers
  • scopus:85031894688
ISSN
0920-654X
DOI
10.1007/s10822-017-0074-x
language
English
LU publication?
yes
id
8b5997f1-98b9-4160-bfb6-20af1dfe68d8
date added to LUP
2017-10-30 13:44:51
date last changed
2018-01-07 12:24:17
@article{8b5997f1-98b9-4160-bfb6-20af1dfe68d8,
  abstract     = {<p>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.</p>},
  author       = {Bhakat, Soumendranath and Åberg, Emil and Söderhjelm, Pär},
  issn         = {0920-654X},
  keyword      = {D3R,Docking,MD simulation,Pose prediction,Protein–ligand binding,Reconnaissance metadynamics},
  language     = {eng},
  month        = {10},
  pages        = {1--15},
  publisher    = {Kluwer},
  series       = {Journal of Computer-Aided Molecular Design},
  title        = {Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling},
  url          = {http://dx.doi.org/10.1007/s10822-017-0074-x},
  year         = {2017},
}