Elucidation of Agonist and Antagonist Dynamic Binding Patterns in ER-α by Integration of Molecular Docking, Molecular Dynamics Simulations and Quantum Mechanical Calculations

Abstract

Estrogen receptor alpha (ERα) is a ligand-dependent transcriptional factor in the nuclear receptor superfamily. Many structures of ERα bound with agonists and antagonists have been determined. However, the dynamic binding patterns of agonists and antagonists in the binding site of ERα remains unclear. Therefore, we performed molecular docking, molecular dynamics (MD) simulations, and quantum mechanical calculations to elucidate agonist and antagonist dynamic binding patterns in ERα. 17β-estradiol (E2) and 4-hydroxytamoxifen (OHT) were docked in the ligand binding pockets of the agonist and antagonist bound ERα. The best complex conformations from molecular docking were subjected to 100 nanosecond MD simulations. Hierarchical clustering was conducted to group the structures in the trajectory from MD simulations. The representative structure from each cluster was selected to calculate the binding interaction energy value for elucidation of the dynamic binding patterns of agonists and antagonists in the binding site of ERα. The binding interaction energy analysis revealed that OHT binds ERα more tightly in the antagonist conformer, while E2 prefers the agonist conformer. The results may help identify ERα antagonists as drug candidates and facilitate risk assessment of chemicals through ER-mediated responses.

In Vivo Optogenetic Manipulation of Transgene Expression in Retinal Neurovasculature

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Ethyl gallate concurrent administration protects against acetaminophen‐induced acute liver injury in mice: An in vivo and in silico approach

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Editorial: Molecular level atomistic and structural insights on biological macromolecules, inhibition, and dynamics studies

“…In general, the authors of these articles have used Artificial Intelligence and molecular modeling approaches to bring insightful information on atomistic mechanisms and explore functions of the biological macromolecule using atom-level calculations ( Huggins et al 2012 ; Selvaraj et al 2022 ). Some studies have performed extensive molecular dynamics simulations like microsecond level molecular dynamics simulations and accurate Quantum Mechanical Calculations for understanding the atomic role in molecular mechanisms ( Sakkiah et al 2021 ). The conclusions of the major articles are based on theoretical approaches from the software and publicly available information, with very little confirmation in laboratory conditions.…”