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Issue 10, 2013
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Modelling the possible bioactivity of ellagitannin-derived metabolites. In silico tools to evaluate their potential xenoestrogenic behavior

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Abstract

Estrogen Receptors (ERs) are ligand-dependent intracellular transcriptional factors involved in many diseases. ERs mediate many of the effects of estrogens, but also exogenous compounds are able to interfere with ER, disrupting endocrine signaling. Among these xenobiotics, compounds present in food and feed make ERs a relevant target in the context of dietary modulation of health. In this sense, urolithins, gut microbiota derived metabolites of plant polyphenolic ellagitannins, may represent good candidates to act as phytoestrogens that are able to modulate the activity of ERs. An in silico method to qualitatively evaluate the potential xenoestrogenic agonistic behavior of ellagitannin-derived metabolites is proposed. The “full-dry” in silico approach involved structure based virtual screening (SBVS), docking simulations and re-scoring procedures. Results provided valuable insights about the phase II conjugations (glucuronidation, sulfation, and methylation, occurring in vivo) affecting the estrogenicity of these compounds on α- and β-ER isoforms. Hydroxylation patterns also revealed a significant role in the agonistic behavior of urolithin derivatives. On the whole, ellagitannin-derived metabolites exerted different predicted xenoestrogenic activity depending on chemical structures, and the applied in silico approach may represent a successful and easy choice to analyze enormous datasets of food-related compounds in order to understand their potential biological features.

Graphical abstract: Modelling the possible bioactivity of ellagitannin-derived metabolites. In silico tools to evaluate their potential xenoestrogenic behavior

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Supplementary files

Article information


Submitted
01 Apr 2013
Accepted
23 Jul 2013
First published
24 Jul 2013

Food Funct., 2013,4, 1442-1451
Article type
Paper

Modelling the possible bioactivity of ellagitannin-derived metabolites. In silico tools to evaluate their potential xenoestrogenic behavior

L. Dellafiora, P. Mena, P. Cozzini, F. Brighenti and D. Del Rio, Food Funct., 2013, 4, 1442
DOI: 10.1039/C3FO60117J

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