# Approximate calculation of the binding energy between 17$\beta$-estradiol and human estrogen receptor alpha

## TL;DR

This study uses multilayer fragment molecular orbital calculations to estimate the binding energy between 17β-estradiol and the human estrogen receptor alpha, aiding in assessing endocrine-disrupting chemicals.

## Contribution

It introduces a novel computational approach combining molecular dynamics and MFMO to evaluate ligand-receptor binding energies for EDC risk assessment.

## Key findings

- Binding energy of -67.2 kcal/mol was calculated.
- Dispersion and electrostatic interactions identified as key.
- Model can help identify potential endocrine disruptors.

## Abstract

Estrogen receptors (ERs) are a group of proteins activated by 17$\beta$-estradiol. The endocrine-disrupting chemicals (EDCs) mimic estrogen action by bind directly to the ligand binding domain of ER. From this perspective, ER represent a good model for identifying and assessing the health risk of potential EDCs. This ability is best reflected by the ligand-ER binding energy. Multilayer fragment molecular orbital (MFMO) calculations were performed which allowed us to obtain the binding energy using a calculation scheme that considers the molecular interactions that occur on the following model systems: the bound and free receptor, 17$\beta$-estradiol and a water cluster. The bound and free receptor and 17$\beta$-estradiol were surrounded by a water shell containing the same number of molecules as the water cluster. The structures required for MFMO calculations were obtained from molecular dynamics simulations and cluster analysis. Attractive dispersion interactions were observed between 17$\beta$-estradiol and the binding site hydrophobic residues. In addition, strong electrostatic interactions were found between 17$\beta$-estradiol and the following charged/polarized residues: Glu 353, His 524 and Arg 394. The FMO2-RHF/STO-3G:MP2/6-31G(d) weighted binding energy was of -67.2 kcal/mol. We hope that the model developed in this study can be useful for identifying and assessing the health risk of potential EDCs.