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Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products
Sunscreen products are predominantly regulated as over-the-counter (OTC) drugs by the US FDA. The “active” ingredients function as ultraviolet filters. Once a sunscreen product is generally recognized as safe and effective (GRASE) via an OTC drug review process, new formulations using these ingredie...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5086697/ https://www.ncbi.nlm.nih.gov/pubmed/27690075 http://dx.doi.org/10.3390/ijerph13100958 |
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author | Hong, Huixiao Rua, Diego Sakkiah, Sugunadevi Selvaraj, Chandrabose Ge, Weigong Tong, Weida |
author_facet | Hong, Huixiao Rua, Diego Sakkiah, Sugunadevi Selvaraj, Chandrabose Ge, Weigong Tong, Weida |
author_sort | Hong, Huixiao |
collection | PubMed |
description | Sunscreen products are predominantly regulated as over-the-counter (OTC) drugs by the US FDA. The “active” ingredients function as ultraviolet filters. Once a sunscreen product is generally recognized as safe and effective (GRASE) via an OTC drug review process, new formulations using these ingredients do not require FDA review and approval, however, the majority of ingredients have never been tested to uncover any potential endocrine activity and their ability to interact with the estrogen receptor (ER) is unknown, despite the fact that this is a very extensively studied target related to endocrine activity. Consequently, we have developed an in silico model to prioritize single ingredient estrogen receptor activity for use when actual animal data are inadequate, equivocal, or absent. It relies on consensus modeling to qualitatively and quantitatively predict ER binding activity. As proof of concept, the model was applied to ingredients commonly used in sunscreen products worldwide and a few reference chemicals. Of the 32 chemicals with unknown ER binding activity that were evaluated, seven were predicted to be active estrogenic compounds. Five of the seven were confirmed by the published data. Further experimental data is needed to confirm the other two predictions. |
format | Online Article Text |
id | pubmed-5086697 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-50866972016-11-02 Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products Hong, Huixiao Rua, Diego Sakkiah, Sugunadevi Selvaraj, Chandrabose Ge, Weigong Tong, Weida Int J Environ Res Public Health Article Sunscreen products are predominantly regulated as over-the-counter (OTC) drugs by the US FDA. The “active” ingredients function as ultraviolet filters. Once a sunscreen product is generally recognized as safe and effective (GRASE) via an OTC drug review process, new formulations using these ingredients do not require FDA review and approval, however, the majority of ingredients have never been tested to uncover any potential endocrine activity and their ability to interact with the estrogen receptor (ER) is unknown, despite the fact that this is a very extensively studied target related to endocrine activity. Consequently, we have developed an in silico model to prioritize single ingredient estrogen receptor activity for use when actual animal data are inadequate, equivocal, or absent. It relies on consensus modeling to qualitatively and quantitatively predict ER binding activity. As proof of concept, the model was applied to ingredients commonly used in sunscreen products worldwide and a few reference chemicals. Of the 32 chemicals with unknown ER binding activity that were evaluated, seven were predicted to be active estrogenic compounds. Five of the seven were confirmed by the published data. Further experimental data is needed to confirm the other two predictions. MDPI 2016-09-29 2016-10 /pmc/articles/PMC5086697/ /pubmed/27690075 http://dx.doi.org/10.3390/ijerph13100958 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hong, Huixiao Rua, Diego Sakkiah, Sugunadevi Selvaraj, Chandrabose Ge, Weigong Tong, Weida Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products |
title | Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products |
title_full | Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products |
title_fullStr | Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products |
title_full_unstemmed | Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products |
title_short | Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products |
title_sort | consensus modeling for prediction of estrogenic activity of ingredients commonly used in sunscreen products |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5086697/ https://www.ncbi.nlm.nih.gov/pubmed/27690075 http://dx.doi.org/10.3390/ijerph13100958 |
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