Literature DB >> 23897986

EADB: an estrogenic activity database for assessing potential endocrine activity.

Jie Shen1, Lei Xu, Hong Fang, Ann M Richard, Jeffrey D Bray, Richard S Judson, Guangxu Zhou, Thomas J Colatsky, Jason L Aungst, Christina Teng, Steve C Harris, Weigong Ge, Susie Y Dai, Zhenqiang Su, Abigail C Jacobs, Wafa Harrouk, Roger Perkins, Weida Tong, Huixiao Hong.   

Abstract

Endocrine-active chemicals can potentially have adverse effects on both humans and wildlife. They can interfere with the body's endocrine system through direct or indirect interactions with many protein targets. Estrogen receptors (ERs) are one of the major targets, and many endocrine disruptors are estrogenic and affect the normal estrogen signaling pathways. However, ERs can also serve as therapeutic targets for various medical conditions, such as menopausal symptoms, osteoporosis, and ER-positive breast cancer. Because of the decades-long interest in the safety and therapeutic utility of estrogenic chemicals, a large number of chemicals have been assayed for estrogenic activity, but these data exist in various sources and different formats that restrict the ability of regulatory and industry scientists to utilize them fully for assessing risk-benefit. To address this issue, we have developed an Estrogenic Activity Database (EADB; http://www.fda.gov/ScienceResearch/BioinformaticsTools/EstrogenicActivityDatabaseEADB/default.htm) and made it freely available to the public. EADB contains 18,114 estrogenic activity data points collected for 8212 chemicals tested in 1284 binding, reporter gene, cell proliferation, and in vivo assays in 11 different species. The chemicals cover a broad chemical structure space and the data span a wide range of activities. A set of tools allow users to access EADB and evaluate potential endocrine activity of chemicals. As a case study, a classification model was developed using EADB for predicting ER binding of chemicals.

Entities:  

Keywords:  database.; endocrine disruptor; estrogen receptor; estrogenic activity

Mesh:

Substances:

Year:  2013        PMID: 23897986     DOI: 10.1093/toxsci/kft164

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  25 in total

1.  A systematic evaluation of analogs and automated read-across prediction of estrogenicity: A case study using hindered phenols.

Authors:  Prachi Pradeep; Kamel Mansouri; Grace Patlewicz; Richard Judson
Journal:  Comput Toxicol       Date:  2017-11-01

2.  A Demonstration of the Uncertainty in Predicting the Estrogenic Activity of Individual Chemicals and Mixtures From an In Vitro Estrogen Receptor Transcriptional Activation Assay (T47D-KBluc) to the In Vivo Uterotrophic Assay Using Oral Exposure.

Authors:  Justin M Conley; Bethany R Hannas; Johnathan R Furr; Vickie S Wilson; L Earl Gray
Journal:  Toxicol Sci       Date:  2016-07-29       Impact factor: 4.849

3.  AroER tri-screen™ is a novel functional assay to estimate both estrogenic and estrogen precursor activity of chemicals or biological specimens.

Authors:  Noriko Kanaya; Duc M Nguyen; Hannah Lu; Yuan-Zhong Wang; Li-Yu Hsin; Myrto Petreas; David Nelson; Weihong Guo; Peggy Reynolds; Tim Synold; Shiuan Chen
Journal:  Breast Cancer Res Treat       Date:  2015-05-12       Impact factor: 4.872

4.  Editor's Highlight: Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space.

Authors:  Richard Judson; Keith Houck; Matt Martin; Ann M Richard; Thomas B Knudsen; Imran Shah; Stephen Little; John Wambaugh; R Woodrow Setzer; Parth Kothiya; Jimmy Phuong; Dayne Filer; Doris Smith; David Reif; Daniel Rotroff; Nicole Kleinstreuer; Nisha Sipes; Menghang Xia; Ruili Huang; Kevin Crofton; Russell S Thomas
Journal:  Toxicol Sci       Date:  2016-05-20       Impact factor: 4.849

5.  Competitive molecular docking approach for predicting estrogen receptor subtype α agonists and antagonists.

Authors:  Hui Wen Ng; Wenqian Zhang; Mao Shu; Heng Luo; Weigong Ge; Roger Perkins; Weida Tong; Huixiao Hong
Journal:  BMC Bioinformatics       Date:  2014-10-21       Impact factor: 3.169

Review 6.  Nanomaterial Databases: Data Sources for Promoting Design and Risk Assessment of Nanomaterials.

Authors:  Zuowei Ji; Wenjing Guo; Sugunadevi Sakkiah; Jie Liu; Tucker A Patterson; Huixiao Hong
Journal:  Nanomaterials (Basel)       Date:  2021-06-18       Impact factor: 5.076

Review 7.  Versatility or promiscuity: the estrogen receptors, control of ligand selectivity and an update on subtype selective ligands.

Authors:  Hui Wen Ng; Roger Perkins; Weida Tong; Huixiao Hong
Journal:  Int J Environ Res Public Health       Date:  2014-08-26       Impact factor: 3.390

8.  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

9.  Pathway Analysis Revealed Potential Diverse Health Impacts of Flavonoids that Bind Estrogen Receptors.

Authors:  Hao Ye; Hui Wen Ng; Sugunadevi Sakkiah; Weigong Ge; Roger Perkins; Weida Tong; Huixiao Hong
Journal:  Int J Environ Res Public Health       Date:  2016-03-26       Impact factor: 3.390

10.  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

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