1. Evaluation of structural and thermodynamic insight of ERβ with DPN and derivatives through MMGBSA/MMPBSA methods.
- Author
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Bello, Martiniano
- Subjects
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MOLECULAR recognition , *CONFORMATIONAL analysis , *ESTROGEN receptors , *DRUG design , *SURFACE area - Abstract
[Display omitted] • Binding free energy studies showed that MMGBSA approach reproduced better the experimental binding free energy tendency. • Per-residue decomposition analysis allowed identification of the key residues contributing the most to the binding. • Differences in affinity between ERβ and ligands result from the number and energy of the total per-residue contribution. Estrogen receptors (ERs) are nuclear factors that exist as two subtypes: ERα and ERβ. Among the different selective ERβ agonist ligands, the widely used ERβ-selective agonist DPN (diarylpropionitrile) is highlighted. Recent experimental and thermodynamic information between R-DPN and S-DPN enantiomers with ERβ 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 ERβ 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 (ΔG) 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. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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