Combining Molecular Docking and Pharmacophore Models Predicts Ligand Binding of Endocrine-Disrupting Chemicals to Nuclear Receptors

Nuclear receptors form a family of proteins capable of accommodating a wide variety of small molecules in their ligand binding domain, ranging from therapeutic compounds to endocrine-disrupting chemicals. The rapid identification of these compounds, especially within the latter category, is of paramount importance. Using data extracted from the CompTox Dashboard, an Environmental Protection Agency initiative, we assessed the effectiveness of a combination of molecular docking and pharmacophore models in identifying ligands binding to six nuclear receptors: androgen receptor, estrogen receptor alpha, estrogen receptor beta, glucocorticoid receptor, peroxisome proliferator-activated receptor gamma, and thyroid hormone receptor alpha. For each nuclear receptor, we selected a specifically designed and optimized in silico protocol that, in conjunction with experimental assays, can prioritize compounds for further evaluation to detect any potential toxicological concerns.

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Publication Details

Journal
Chemical Research in Toxicology
Published
2025-04-03
DOI
https://doi.org/10.1021/acs.chemrestox.4c00455
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50

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article

Combining Molecular Docking and Pharmacophore Models Predicts Ligand Binding of Endocrine-Disrupting Chemicals to Nuclear Receptors

Asma Sellami, Nathalie Lagarde, Matthieu Montès
1 citations
Chemical Research in Toxicology
Computational Drug Discovery Methods
1.50
article

Combining Molecular Docking and Pharmacophore Models Predicts Ligand Binding of Endocrine-Disrupting Chemicals to Nuclear Receptors

Asma Sellami, Nathalie Lagarde, Matthieu Montès
article en
1 citations

Abstract

Nuclear receptors form a family of proteins capable of accommodating a wide variety of small molecules in their ligand binding domain, ranging from therapeutic compounds to endocrine-disrupting chemicals. The rapid identification of these compounds, especially within the latter category, is of paramount importance. Using data extracted from the CompTox Dashboard, an Environmental Protection Agency initiative, we assessed the effectiveness of a combination of molecular docking and pharmacophore models in identifying ligands binding to six nuclear receptors: androgen receptor, estrogen receptor alpha, estrogen receptor beta, glucocorticoid receptor, peroxisome proliferator-activated receptor gamma, and thyroid hormone receptor alpha. For each nuclear receptor, we selected a specifically designed and optimized in silico protocol that, in conjunction with experimental assays, can prioritize compounds for further evaluation to detect any potential toxicological concerns.

Chemical Research in ToxicologyVol. 38(4)
Conservatoire National des Arts et Métiers (FR), Institut Universitaire de France (FR)
Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation
Openalex Percentile: Top 18%
Computational Drug Discovery Methods
1.50
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