Assessing the Chemical-induced Estrogenicity using in Silico and in Vitro Methods

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dc.contributor.authorGoya-Jorge, Elizabeth
dc.contributor.authorAmber, Mazia
dc.contributor.authorConnolly, Lisa
dc.contributor.authorBarigye, Stephen J.
dc.date.accessioned2023-02-09T17:52:27Z
dc.date.available2023-02-09T17:52:27Z
dc.date.issued2021
dc.description.abstractMultiple substances are considered endocrine disrupting chemicals (EDCs). However, there is a significant gap in the early prioritization of EDC’s effects. In this work, in silico and in vitro methods were used to model estrogenicity. Two Quantitative Structure-Activity Relationship (QSAR) models based on Logistic Regression and REPTree algorithms were built using a large and diverse database of estrogen receptor (ESR) agonism. A 10-fold external validation demonstrated their robustness and predictive capacity. Mechanistic interpretations of the molecular descriptors (C-026, nArOH,PW5, B06[Br-Br]) used for modelling suggested that the heteroatomic fragments, aromatic hydroxyls, and bromines, and the relative bond accessibility areas of molecules, are structural determinants in estrogenicity. As validation of the QSARs, ESR transactivity of thirteen persistent organic pollutants (POPs) and suspected EDCs was tested in vitro using the MMV-Luc cell line. A good correspondence between predictions and experimental bioassays demonstrated the value of the QSARs for prioritization of ESR agonist compounds.en_US
dc.identifier.citationGoya-Jorge, E., Amber, M., Gozalbes, R., Connolly, L., & Barigye, S. J. (2021). Assessing the chemical-induced estrogenicity using in silico and in vitro methods. Environmental Toxicology and Pharmacology, 87, 103688.https://doi.org/10.1016/j.etap.2021.103688en_US
dc.identifier.issn1382-6689
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/7717
dc.language.isoenen_US
dc.publisherEnvironmental Toxicology and Pharmacologyen_US
dc.subjectEstrogen receptoren_US
dc.subjectEndocrine disruptoren_US
dc.subjectPersistent organic pollutanten_US
dc.subjectPredictive toxicologyen_US
dc.titleAssessing the Chemical-induced Estrogenicity using in Silico and in Vitro Methodsen_US
dc.typeArticleen_US
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