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

J Comput Aided Mol Des. 2018 Jan;32(1):59-73. doi: 10.1007/s10822-017-0074-x. Epub 2017 Oct 20.

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 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.

Keywords: D3R; Docking; MD simulation; Pose prediction; Protein–ligand binding; Reconnaissance metadynamics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Binding Sites
  • Databases, Protein
  • Drug Design*
  • Drug Discovery
  • Humans
  • Ligands
  • Molecular Docking Simulation*
  • Molecular Dynamics Simulation
  • Protein Binding
  • Protein Conformation
  • Receptors, Cytoplasmic and Nuclear / agonists
  • Receptors, Cytoplasmic and Nuclear / antagonists & inhibitors
  • Receptors, Cytoplasmic and Nuclear / chemistry
  • Receptors, Cytoplasmic and Nuclear / metabolism*

Substances

  • Ligands
  • Receptors, Cytoplasmic and Nuclear
  • farnesoid X-activated receptor