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

• Published in: Journal of enzyme inhibition and medicinal chemistry Vol. 27; no. 6; pp. 832 - 844
• Main Authors: Balaji, B., Ramanathan, M.
• Format: Journal Article
• Language: English
• Published: England Informa Healthcare 01.12.2012; Taylor & Francis
• Subjects: anticancer; Binding Sites; docking; Estrogen Receptor beta - agonists; Estrogen Receptor beta - chemistry; free energy binding; Genistein - chemistry; Humans; Kinetics; Ligands; MM-GBSA; Molecular Docking Simulation; Molecular Dynamics Simulation; oestrogen receptor β; Oximes - chemistry; Phenols - chemistry; Protein Binding; Protein Isoforms - agonists; Protein Isoforms - chemistry; Research Design; Thermodynamics
• ISSN: 1475-6366; 1475-6374
• DOI: 10.3109/14756366.2011.618990

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 (r2 = 0.66). MM-GBSA re-scoring showed correlation of r2 = 0.74 with selectivity of ERβ ligands. These results will aid the discovery of novel ERβ ligands with isoform selectivity.