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Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A

Bisphenol A (BPA) is a ubiquitous compound used in polymer manufacturing for a wide array of applications; however, increasing evidence has shown that BPA causes significant endocrine disruption and this has raised public concerns over safety and exposure limits. The use of renewable materials as po...

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Autores principales: Hong, Huixiao, Harvey, Benjamin G., Palmese, Giuseppe R., Stanzione, Joseph F., Ng, Hui Wen, Sakkiah, Sugunadevi, Tong, Weida, Sadler, Joshua M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4962246/
https://www.ncbi.nlm.nih.gov/pubmed/27420082
http://dx.doi.org/10.3390/ijerph13070705
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author Hong, Huixiao
Harvey, Benjamin G.
Palmese, Giuseppe R.
Stanzione, Joseph F.
Ng, Hui Wen
Sakkiah, Sugunadevi
Tong, Weida
Sadler, Joshua M.
author_facet Hong, Huixiao
Harvey, Benjamin G.
Palmese, Giuseppe R.
Stanzione, Joseph F.
Ng, Hui Wen
Sakkiah, Sugunadevi
Tong, Weida
Sadler, Joshua M.
author_sort Hong, Huixiao
collection PubMed
description Bisphenol A (BPA) is a ubiquitous compound used in polymer manufacturing for a wide array of applications; however, increasing evidence has shown that BPA causes significant endocrine disruption and this has raised public concerns over safety and exposure limits. The use of renewable materials as polymer feedstocks provides an opportunity to develop replacement compounds for BPA that are sustainable and exhibit unique properties due to their diverse structures. As new bio-based materials are developed and tested, it is important to consider the impacts of both monomers and polymers on human health. Molecular docking simulations using the Estrogenic Activity Database in conjunction with the decision forest were performed as part of a two-tier in silico model to predict the activity of 29 bio-based platform chemicals in the estrogen receptor-α (ERα). Fifteen of the candidates were predicted as ER binders and fifteen as non-binders. Gaining insight into the estrogenic activity of the bio-based BPA replacements aids in the sustainable development of new polymeric materials.
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spelling pubmed-49622462016-08-01 Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A Hong, Huixiao Harvey, Benjamin G. Palmese, Giuseppe R. Stanzione, Joseph F. Ng, Hui Wen Sakkiah, Sugunadevi Tong, Weida Sadler, Joshua M. Int J Environ Res Public Health Article Bisphenol A (BPA) is a ubiquitous compound used in polymer manufacturing for a wide array of applications; however, increasing evidence has shown that BPA causes significant endocrine disruption and this has raised public concerns over safety and exposure limits. The use of renewable materials as polymer feedstocks provides an opportunity to develop replacement compounds for BPA that are sustainable and exhibit unique properties due to their diverse structures. As new bio-based materials are developed and tested, it is important to consider the impacts of both monomers and polymers on human health. Molecular docking simulations using the Estrogenic Activity Database in conjunction with the decision forest were performed as part of a two-tier in silico model to predict the activity of 29 bio-based platform chemicals in the estrogen receptor-α (ERα). Fifteen of the candidates were predicted as ER binders and fifteen as non-binders. Gaining insight into the estrogenic activity of the bio-based BPA replacements aids in the sustainable development of new polymeric materials. MDPI 2016-07-12 2016-07 /pmc/articles/PMC4962246/ /pubmed/27420082 http://dx.doi.org/10.3390/ijerph13070705 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
Harvey, Benjamin G.
Palmese, Giuseppe R.
Stanzione, Joseph F.
Ng, Hui Wen
Sakkiah, Sugunadevi
Tong, Weida
Sadler, Joshua M.
Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A
title Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A
title_full Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A
title_fullStr Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A
title_full_unstemmed Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A
title_short Experimental Data Extraction and in Silico Prediction of the Estrogenic Activity of Renewable Replacements for Bisphenol A
title_sort experimental data extraction and in silico prediction of the estrogenic activity of renewable replacements for bisphenol a
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4962246/
https://www.ncbi.nlm.nih.gov/pubmed/27420082
http://dx.doi.org/10.3390/ijerph13070705
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