Literature DB >> 21034757

Assessing the toxic effects of ethylene glycol ethers using Quantitative Structure Toxicity Relationship models.

Patricia Ruiz1, Moiz Mumtaz, Vijay Gombar.   

Abstract

Experimental determination of toxicity profiles consumes a great deal of time, money, and other resources. Consequently, businesses, societies, and regulators strive for reliable alternatives such as Quantitative Structure Toxicity Relationship (QSTR) models to fill gaps in toxicity profiles of compounds of concern to human health. The use of glycol ethers and their health effects have recently attracted the attention of international organizations such as the World Health Organization (WHO). The board members of Concise International Chemical Assessment Documents (CICAD) recently identified inadequate testing as well as gaps in toxicity profiles of ethylene glycol mono-n-alkyl ethers (EGEs). The CICAD board requested the ATSDR Computational Toxicology and Methods Development Laboratory to conduct QSTR assessments of certain specific toxicity endpoints for these chemicals. In order to evaluate the potential health effects of EGEs, CICAD proposed a critical QSTR analysis of the mutagenicity, carcinogenicity, and developmental effects of EGEs and other selected chemicals. We report here results of the application of QSTRs to assess rodent carcinogenicity, mutagenicity, and developmental toxicity of four EGEs: 2-methoxyethanol, 2-ethoxyethanol, 2-propoxyethanol, and 2-butoxyethanol and their metabolites. Neither mutagenicity nor carcinogenicity is indicated for the parent compounds, but these compounds are predicted to be developmental toxicants. The predicted toxicity effects were subjected to reverse QSTR (rQSTR) analysis to identify structural attributes that may be the main drivers of the developmental toxicity potential of these compounds.
Copyright © 2010. Published by Elsevier Inc.

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Year:  2010        PMID: 21034757     DOI: 10.1016/j.taap.2010.10.024

Source DB:  PubMed          Journal:  Toxicol Appl Pharmacol        ISSN: 0041-008X            Impact factor:   4.219


  7 in total

1.  Integration of in silico methods and computational systems biology to explore endocrine-disrupting chemical binding with nuclear hormone receptors.

Authors:  P Ruiz; A Sack; M Wampole; S Bobst; M Vracko
Journal:  Chemosphere       Date:  2017-03-09       Impact factor: 7.086

Review 2.  Joint toxicity of alkoxyethanol mixtures: contribution of in silico applications.

Authors:  H R Pohl; P Ruiz; F Scinicariello; M M Mumtaz
Journal:  Regul Toxicol Pharmacol       Date:  2012-06-28       Impact factor: 3.271

3.  Exploring current read-across applications and needs among selected U.S. Federal Agencies.

Authors:  Grace Patlewicz; Lucina E Lizarraga; Diego Rua; David G Allen; Amber B Daniel; Suzanne C Fitzpatrick; Natàlia Garcia-Reyero; John Gordon; Pertti Hakkinen; Angela S Howard; Agnes Karmaus; Joanna Matheson; Moiz Mumtaz; Andrea-Nicole Richarz; Patricia Ruiz; Louis Scarano; Takashi Yamada; Nicole Kleinstreuer
Journal:  Regul Toxicol Pharmacol       Date:  2019-05-10       Impact factor: 3.271

4.  Translational research to develop a human PBPK models tool kit-volatile organic compounds (VOCs).

Authors:  M Moiz Mumtaz; Meredith Ray; Susan R Crowell; Deborah Keys; Jeffrey Fisher; Patricia Ruiz
Journal:  J Toxicol Environ Health A       Date:  2012

5.  Application of physiologically based pharmacokinetic models in chemical risk assessment.

Authors:  Moiz Mumtaz; Jeffrey Fisher; Benjamin Blount; Patricia Ruiz
Journal:  J Toxicol       Date:  2012-03-19

6.  Characterization of Phase I Hepatic Metabolites of Anti-Premature Ejaculation Drug Dapoxetine by UHPLC-ESI-Q-TOF.

Authors:  Robert Skibiński; Jakub Trawiński; Maciej Gawlik
Journal:  Molecules       Date:  2021-06-22       Impact factor: 4.411

7.  Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products.

Authors:  Patricia Ruiz; Gino Begluitti; Terry Tincher; John Wheeler; Moiz Mumtaz
Journal:  Molecules       Date:  2012-07-27       Impact factor: 4.411

  7 in total

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