Evaluation of structural and thermodynamic insight of ERβ with DPN and derivatives through MMGBSA/MMPBSA methods

Estrogen receptors (ERs) are nuclear factors that exist as two subtypes: ER alpha and ER beta. Among the different selective ER beta agonist ligands, the widely used ER beta-selective agonist DPN (diarylpropionitrile) is highlighted. Recent experimental and thermodynamic information between R-DPN and S-DPN enantiomers with ER beta is important for evaluating further the ability of MD simulations combined with end-point methods to reproduce experimental binding affinity and generate structural insight not provided through crystallographic data. In this research, starting from crystallographic data and experimental binding affinities, we explored the structural and thermodynamic basis of the molecular recognition of ER beta with DPN and derivatives through triplicate MD simulations combined with end-point methods. Conformational analysis showed some regions with the highest mobility linked to ligand association that, at the time, impacted the total protein fluctuation. Binding free energy (Delta G) analysis revealed that the Molecular Mechanics Generalized-Born Surface Area (MMGBSA) approach was able to reproduce the experimental tendency with a strong correlation (R = 0.778), whereas per-residue decomposition analysis revealed that all the systems interacted strongly with eight residues (L298, E305, L339, M340, L343, F356, H475, and L476). The comparison between theoretical studies using the MMGBSA approach with experimental results provides new insights for drug designing of new DPN derivatives.

Automated summary

This study explores the structural and thermodynamic basis of molecular recognition between ERβ and DPN and its derivatives using molecular dynamics simulations and end-point methods. The results show that the MMGBSA approach is able to reproduce experimental trends and identify eight residues that strongly interact with the ligands.