Literature DB >> 26308263

Estrogenic activity data extraction and in silico prediction show the endocrine disruption potential of bisphenol A replacement compounds.

Hui Wen Ng1, Mao Shu1, Heng Luo1, Hao Ye1, Weigong Ge1, Roger Perkins1, Weida Tong1, Huixiao Hong1.   

Abstract

Bisphenol A (BPA) replacement compounds are released to the environment and cause widespread human exposure. However, a lack of thorough safety evaluations on the BPA replacement compounds has raised public concerns. We assessed the endocrine disruption potential of BPA replacement compounds in the market to assist their safety evaluations. A literature search was conducted to ascertain the BPA replacement compounds in use. Available experimental estrogenic activity data of these compounds were extracted from the Estrogenic Activity Database (EADB) to assess their estrogenic potential. An in silico model was developed to predict the estrogenic activity of compounds lacking experimental data. Molecular dynamics (MD) simulations were performed to understand the mechanisms by which the estrogenic compounds bind to and activate the estrogen receptor (ER). Forty-five BPA replacement compounds were identified in the literature. Seven were more estrogenic and five less estrogenic than BPA, while six were nonestrogenic in EADB. A two-tier in silico model was developed based on molecular docking to predict the estrogenic activity of the 27 compounds lacking data. Eleven were predicted as ER binders and 16 as nonbinders. MD simulations revealed hydrophobic contacts and hydrogen bonds as the main interactions between ER and the estrogenic compounds.

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Year:  2015        PMID: 26308263     DOI: 10.1021/acs.chemrestox.5b00243

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  15 in total

1.  Machine Learning Models for Predicting Liver Toxicity.

Authors:  Jie Liu; Wenjing Guo; Sugunadevi Sakkiah; Zuowei Ji; Gokhan Yavas; Wen Zou; Minjun Chen; Weida Tong; Tucker A Patterson; Huixiao Hong
Journal:  Methods Mol Biol       Date:  2022

2.  sNebula, a network-based algorithm to predict binding between human leukocyte antigens and peptides.

Authors:  Heng Luo; Hao Ye; Hui Wen Ng; Sugunadevi Sakkiah; Donna L Mendrick; Huixiao Hong
Journal:  Sci Rep       Date:  2016-08-25       Impact factor: 4.379

3.  Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs.

Authors:  Huixiao Hong; Shraddha Thakkar; Minjun Chen; Weida Tong
Journal:  Sci Rep       Date:  2017-12-11       Impact factor: 4.379

Review 4.  Endocrine Disrupting Chemicals Mediated through Binding Androgen Receptor Are Associated with Diabetes Mellitus.

Authors:  Sugunadevi Sakkiah; Tony Wang; Wen Zou; Yuping Wang; Bohu Pan; Weida Tong; Huixiao Hong
Journal:  Int J Environ Res Public Health       Date:  2017-12-23       Impact factor: 3.390

5.  Competitive docking model for prediction of the human nicotinic acetylcholine receptor α7 binding of tobacco constituents.

Authors:  Hui Wen Ng; Carmine Leggett; Sugunadevi Sakkiah; Bohu Pan; Hao Ye; Leihong Wu; Chandrabose Selvaraj; Weida Tong; Huixiao Hong
Journal:  Oncotarget       Date:  2018-02-08

6.  A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.

Authors:  Huixiao Hong; Jie Shen; Hui Wen Ng; Sugunadevi Sakkiah; Hao Ye; Weigong Ge; Ping Gong; Wenming Xiao; Weida Tong
Journal:  Int J Environ Res Public Health       Date:  2016-03-25       Impact factor: 3.390

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

Authors:  Huixiao Hong; Benjamin G Harvey; Giuseppe R Palmese; Joseph F Stanzione; Hui Wen Ng; Sugunadevi Sakkiah; Weida Tong; Joshua M Sadler
Journal:  Int J Environ Res Public Health       Date:  2016-07-12       Impact factor: 3.390

8.  Structural Changes Due to Antagonist Binding in Ligand Binding Pocket of Androgen Receptor Elucidated Through Molecular Dynamics Simulations.

Authors:  Sugunadevi Sakkiah; Rebecca Kusko; Bohu Pan; Wenjing Guo; Weigong Ge; Weida Tong; Huixiao Hong
Journal:  Front Pharmacol       Date:  2018-05-15       Impact factor: 5.810

9.  Integrating Exposure Knowledge and Serum Suspect Screening as a New Approach to Biomonitoring: An Application in Firefighters and Office Workers.

Authors:  Rachel Grashow; Vincent Bessonneau; Roy R Gerona; Aolin Wang; Jessica Trowbridge; Thomas Lin; Heather Buren; Ruthann A Rudel; Rachel Morello-Frosch
Journal:  Environ Sci Technol       Date:  2020-03-15       Impact factor: 9.028

10.  Amperometric Cytosensor for Studying Mitochondrial Interferences Induced by Plasticizers Bisphenol B and Bisphenol A.

Authors:  Roberto Dragone; Gerardo Grasso; Chiara Frazzoli
Journal:  Molecules       Date:  2020-11-07       Impact factor: 4.411

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