ArticleEnvironmental health perspectives2016
Evaluation of OASIS QSAR Models Using ToxCast™ in Vitro Estrogen and Androgen Receptor Binding Data and Application in an Integrated Endocrine Screening Approach.
Article in Environmental health perspectives, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 30 citations in OpenAlex.
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- Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens.International journal of molecular sciences · 2020Review
- Integrative Strategy of Testing Systems for Identification of Endocrine Disruptors Inducing Metabolic Disorders-An Introduction to the OBERON Project.International journal of molecular sciences · 2020Review
- KnowTox: pipeline and case study for confident prediction of potential toxic effects of compounds in early phases of development.Journal of cheminformatics · 2020Article
- Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction.Molecular pharmaceutics · 2018Article
- A hierarchical testing strategy for micropollutants in drinking water regarding their potential endocrine-disrupting effects-towards health-related indicator values.Environmental science and pollution research international · 2018Article
- Development of an in Vitro-Based Risk Assessment Framework for Predicting Ambient Particulate Matter-Bound Polycyclic Aromatic Hydrocarbon-Activated Toxicity Pathways.Environmental science & technology · 2017Article
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6 authors at 1 institution in 1 country.
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Abstract
backgroundIntegrative testing strategies (ITSs) for potential endocrine activity can use tiered in silico and in vitro models. Each component of an ITS should be thoroughly assessed.
objectivesWe used the data from three in vitro ToxCast™ binding assays to assess OASIS, a quantitative structure-activity relationship (QSAR) platform covering both estrogen receptor (ER) and androgen receptor (AR) binding. For stronger binders (described here as AC50 < 1 μM), we also examined the relationship of QSAR predictions of ER or AR binding to the results from 18 ER and 10 AR transactivation assays, 72 ER-binding reference compounds, and the in vivo uterotrophic assay.
methodsNovaScreen binding assay data for ER (human, bovine, and mouse) and AR (human, chimpanzee, and rat) were used to assess the sensitivity, specificity, concordance, and applicability domain of two OASIS QSAR models. The binding strength relative to the QSAR-predicted binding strength was examined for the ER data. The relationship of QSAR predictions of binding to transactivation- and pathway-based assays, as well as to in vivo uterotrophic responses, was examined.
resultsThe QSAR models had both high sensitivity (> 75%) and specificity (> 86%) for ER as well as both high sensitivity (92-100%) and specificity (70-81%) for AR. For compounds within the domains of the ER and AR QSAR models that bound with AC50 < 1 μM, the QSAR models accurately predicted the binding for the parent compounds. The parent compounds were active in all transactivation assays where metabolism was incorporated and, except for those compounds known to require metabolism to manifest activity, all assay platforms where metabolism was not incorporated. Compounds in-domain and predicted to bind by the ER QSAR model that were positive in ToxCast™ ER binding at AC50 < 1 μM were active in the uterotrophic assay.
conclusionsWe used the extensive ToxCast™ HTS binding data set to show that OASIS ER and AR QSAR models had high sensitivity and specificity when compounds were in-domain of the models. Based on this research, we recommend a tiered screening approach wherein a) QSAR is used to identify compounds in-domain of the ER or AR binding models and predicted to bind; b) those compounds are screened in vitro to assess binding potency; and c) the stronger binders (AC50 < 1 μM) are screened in vivo. This scheme prioritizes compounds for integrative testing and risk assessment. Importantly, compounds that are not in-domain, that are predicted either not to bind or to bind weakly, that are not active in in vitro, that require metabolism to manifest activity, or for which in vivo AR testing is in order, need to be assessed differently. CITATION: Bhhatarai B, Wilson DM, Price PS, Marty S, Parks AK, Carney E. 2016. Evaluation of OASIS QSAR models using ToxCast™ in vitro estrogen and androgen receptor binding data and application in an integrated endocrine screening approach. Environ Health Perspect 124:1453-1461; http://dx.doi.org/10.1289/EHP184.
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