Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations

Int J Mol Sci. 2019 Nov 20;20(23):5834. doi: 10.3390/ijms20235834.


Pharmacophore models are widely used for the identification of promising primary hits in compound large libraries. Recent studies have demonstrated that pharmacophores retrieved from protein-ligand molecular dynamic trajectories outperform pharmacophores retrieved from a single crystal complex structure. However, the number of retrieved pharmacophores can be enormous, thus, making it computationally inefficient to use all of them for virtual screening. In this study, we proposed selection of distinct representative pharmacophores by the removal of pharmacophores with identical three-dimensional (3D) pharmacophore hashes. We also proposed a new conformer coverage approach in order to rank compounds using all representative pharmacophores. Our results for four cyclin-dependent kinase 2 (CDK2) complexes with different ligands demonstrated that the proposed selection and ranking approaches outperformed the previously described common hits approach. We also demonstrated that ranking, based on averaged predicted scores obtained from different complexes, can outperform ranking based on scores from an individual complex. All developments were implemented in open-source software pharmd.

Keywords: molecular dynamics; pharmacophore; virtual screening.

MeSH terms

  • Binding Sites
  • Computer Simulation
  • Cyclin-Dependent Kinase 2 / chemistry*
  • Cyclin-Dependent Kinase 2 / metabolism
  • Drug Discovery / methods*
  • Humans
  • Ligands
  • Molecular Docking Simulation / methods
  • Molecular Dynamics Simulation*
  • Protein Binding
  • Protein Kinase Inhibitors / chemistry
  • Protein Kinase Inhibitors / pharmacology
  • Small Molecule Libraries / chemistry*
  • Small Molecule Libraries / pharmacology


  • Ligands
  • Protein Kinase Inhibitors
  • Small Molecule Libraries
  • Cyclin-Dependent Kinase 2