Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
(2018) In Journal of Computer-Aided Molecular Design 32(1). p.59-73- 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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- author
- Bhakat, Soumendranath LU ; Åberg, Emil and Söderhjelm, Pär LU
- organization
- publishing date
- 2018-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- D3R, Docking, MD simulation, Pose prediction, Protein–ligand binding, Reconnaissance metadynamics
- in
- Journal of Computer-Aided Molecular Design
- volume
- 32
- issue
- 1
- pages
- 59 - 73
- publisher
- Springer
- external identifiers
-
- scopus:85031894688
- pmid:29052792
- 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
- 2024-09-02 10:10:14
@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}}, keywords = {{D3R; Docking; MD simulation; Pose prediction; Protein–ligand binding; Reconnaissance metadynamics}}, language = {{eng}}, number = {{1}}, pages = {{59--73}}, publisher = {{Springer}}, 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}}, doi = {{10.1007/s10822-017-0074-x}}, volume = {{32}}, year = {{2018}}, }