Estrogen Receptor Binding Affinity of Food Contact Material Components Estimated by QSAR

Abstract

SUMMARY Aim:The presented work characterized components of food contact materials (FCM) with potential to bind to estrogen receptor (ER) and cause adverse effects in the human organism.Methods: The QSAR Toolbox, software application designed to identify and fill toxicological data gaps for chemical hazard assessment, was used. Estrogen receptors are much less of a lock-and-key interaction than highly specific ones. The ER is nonspecific enough to permit binding with a diverse array of chemical structures. There are three primary ER binding subpockets, each with different requirements for hydrogen bonding.Results: More than 900 compounds approved as of FCM components were evaluated for their potential to bind on ER. All evaluated chemicals were subcategorized to five groups with respect to the binding potential to ER: very strong, strong, moderate, weak binder, and no binder to ER. In total 46 compounds were characterized as potential disturbers of estrogen receptor.Conclusion: Among the group of selected chemicals, compounds with high and even very high affinity to the ER binding subpockets were found. These compounds may act as gene activators and cause adverse effects in the organism, particularly during pregnancy and breast-feeding. It should be considered to carry out further in vitro or in vivo tests to confirm their potential to disturb the regulation of physiological processes in humans by abnormal ER signaling and subsequently remove these chemicals from the list of approved food contact materials.

Endocrine Disruption by Mixtures in Topical Consumer Products

“…As such, despite a constantly growing list of known endocrine active substances and potential endocrine disruptors, there are no immediately available tools to evaluate how a complex product can affect the endocrine system. In silico tools are being developed and validated to this purpose but there are still several concerns about their reliability and their ability to detect the more complex and nuanced interactions in mixtures of endocrine actives and disruptors [35,38,135,136].…”

“…The budding databases of known and potential EDCs promoted by several agencies will be an invaluable tool for the next required step, in which the focus will likely be shifting from identifying endocrine disrupting substances to testing the effect of mixtures and combined EDCs in products [61]. Similarly, several in silico tools and computer models are being devised in order to streamline the identification and prioritization of potential EDCs for further studies [35,62].…”

“…Similarly, some EDCs were linked to decreased fertility and diminished ovarian reserves in women [30][31][32][33][34]. Animal studies confirmed that EDC exposure can affect mammary gland and uterine development, both in terms of timing and in terms of morphological changes and in silico analyses contributed to predict the mechanics behind this [16,35,36]. It is still debated however whether animal models can be accurate predictors of the effect of the same substances in humans.…”

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

“…Those structures are useful to understand the structural changes due to agonist and antagonist binding in the ERα LBP. Various computational techniques such as molecular docking [18][19][20][21][22][23][24], MD simulations [25][26][27][28][29][30], predictive modeling [31][32][33][34][35][36][37][38][39][40][41], and in vitro studies were conducted to predict ER binders or non-binders [42,43] and agonists or antagonists [44,45].…”

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

“…Experimental log 10 K ow values were preferred over predicted values. The target substance list was compiled from previously reported lists of EDs22,23,24 …”