Prediction of estrogen receptor β ligands potency and selectivity by docking and MM-GBSA scoring methods using three different scaffolds

J Enzyme Inhib Med Chem. 2012 Dec;27(6):832-44. doi: 10.3109/14756366.2011.618990. Epub 2011 Oct 14.

Abstract

This study aimed to identify the docking and molecular mechanics-generalized born surface area (MM-GBSA) re-scoring parameters which can correlate the binding affinity and selectivity of the ligands towards oestrogen receptor β (ERβ). Three different series of ERβ ligands were used as dataset and the compounds were docked against ERβ (protein data bank (PDB) ID: 1QKM) using Glide and ArgusLab. Glide docking showed superior results when compared with ArgusLab. Docked poses were then rescored using Prime-MM-GBSA to calculate free energy binding. Correlations were made between observed activities of ERβ ligands with computationally predicted values from docking, binding energy parameters. ERβ ligands experimental binding affinity/selectivity did not correlate well with Glide and ArgusLab score. Whereas calculated Glide energy (coulomb-van der Waal interaction energy) correlated significantly with binding affinity of ERβ ligands (r(2) = 0.66). MM-GBSA re-scoring showed correlation of r(2) = 0.74 with selectivity of ERβ ligands. These results will aid the discovery of novel ERβ ligands with isoform selectivity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Binding Sites
  • Estrogen Receptor beta / agonists*
  • Estrogen Receptor beta / chemistry*
  • Genistein / chemistry*
  • Humans
  • Kinetics
  • Ligands
  • Molecular Docking Simulation*
  • Molecular Dynamics Simulation
  • Oximes / chemistry*
  • Phenols / chemistry*
  • Protein Binding
  • Protein Isoforms / agonists
  • Protein Isoforms / chemistry
  • Research Design
  • Thermodynamics

Substances

  • Estrogen Receptor beta
  • Ligands
  • Oximes
  • Phenols
  • Protein Isoforms
  • Genistein