Literature DB >> 19770017

A framework for using structural, reactivity, metabolic and physicochemical similarity to evaluate the suitability of analogs for SAR-based toxicological assessments.

Shengde Wu1, Karen Blackburn, Jack Amburgey, Joanna Jaworska, Thomas Federle.   

Abstract

A systematic expert-driven process is presented for evaluating analogs for read across in SAR (structure activity relationship) toxicological assessments. The approach involves categorizing potential analogs based upon their degree of structural, reactivity, metabolic and physicochemical similarity to the chemical with missing toxicological data (target chemical). It extends beyond structural similarity, and includes differentiation based upon chemical reactivity and addresses the potential that an analog and target could show toxicologically significant metabolic convergence or divergence. In addition, it identifies differences in physicochemical properties, which could affect bioavailability and consequently biological responses observed in vitro or in vivo. The approach provides a stepwise decision tree for categorizing the suitability of analogs, which qualitatively characterizes the strength of the evidence supporting the hypothesis of similarity and level of uncertainty associated with their use for read across. The result is a comprehensive framework to apply chemical, biochemical and toxicological principles in a systematic manner to identify and evaluate factors that can introduce uncertainty into SAR assessments, while maximizing the appropriate use of all available data. 2009. Published by Elsevier Inc.

Mesh:

Year:  2009        PMID: 19770017     DOI: 10.1016/j.yrtph.2009.09.006

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  22 in total

1.  Predicting the future: opportunities and challenges for the chemical industry to apply 21st-century toxicity testing.

Authors:  Raja S Settivari; Nicholas Ball; Lynea Murphy; Reza Rasoulpour; Darrell R Boverhof; Edward W Carney
Journal:  J Am Assoc Lab Anim Sci       Date:  2015-03       Impact factor: 1.232

2.  A case study on the application of an expert-driven read-across approach in support of quantitative risk assessment of p,p'-dichlorodiphenyldichloroethane.

Authors:  Lucina E Lizarraga; Jeffry L Dean; J Phillip Kaiser; Scott C Wesselkamper; Jason C Lambert; Q Jay Zhao
Journal:  Regul Toxicol Pharmacol       Date:  2019-02-19       Impact factor: 3.271

3.  Navigating through the minefield of read-across tools: A review of in silico tools for grouping.

Authors:  Patlewicz Grace; Helman George; Pradeep Prachi; Shah Imran
Journal:  Comput Toxicol       Date:  2017-08

4.  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

5.  The Next Generation Blueprint of Computational Toxicology at the U.S. Environmental Protection Agency.

Authors:  Russell S Thomas; Tina Bahadori; Timothy J Buckley; John Cowden; Chad Deisenroth; Kathie L Dionisio; Jeffrey B Frithsen; Christopher M Grulke; Maureen R Gwinn; Joshua A Harrill; Mark Higuchi; Keith A Houck; Michael F Hughes; E Sidney Hunter; Kristin K Isaacs; Richard S Judson; Thomas B Knudsen; Jason C Lambert; Monica Linnenbrink; Todd M Martin; Seth R Newton; Stephanie Padilla; Grace Patlewicz; Katie Paul-Friedman; Katherine A Phillips; Ann M Richard; Reeder Sams; Timothy J Shafer; R Woodrow Setzer; Imran Shah; Jane E Simmons; Steven O Simmons; Amar Singh; Jon R Sobus; Mark Strynar; Adam Swank; Rogelio Tornero-Valez; Elin M Ulrich; Daniel L Villeneuve; John F Wambaugh; Barbara A Wetmore; Antony J Williams
Journal:  Toxicol Sci       Date:  2019-06-01       Impact factor: 4.849

6.  Extending the Generalised Read-Across approach (GenRA): A systematic analysis of the impact of physicochemical property information on read-across performance.

Authors:  George Helman; Imran Shah; Grace Patlewicz
Journal:  Comput Toxicol       Date:  2018

7.  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

8.  In silico toxicology protocols.

Authors:  Glenn J Myatt; Ernst Ahlberg; Yumi Akahori; David Allen; Alexander Amberg; Lennart T Anger; Aynur Aptula; Scott Auerbach; Lisa Beilke; Phillip Bellion; Romualdo Benigni; Joel Bercu; Ewan D Booth; Dave Bower; Alessandro Brigo; Natalie Burden; Zoryana Cammerer; Mark T D Cronin; Kevin P Cross; Laura Custer; Magdalena Dettwiler; Krista Dobo; Kevin A Ford; Marie C Fortin; Samantha E Gad-McDonald; Nichola Gellatly; Véronique Gervais; Kyle P Glover; Susanne Glowienke; Jacky Van Gompel; Steve Gutsell; Barry Hardy; James S Harvey; Jedd Hillegass; Masamitsu Honma; Jui-Hua Hsieh; Chia-Wen Hsu; Kathy Hughes; Candice Johnson; Robert Jolly; David Jones; Ray Kemper; Michelle O Kenyon; Marlene T Kim; Naomi L Kruhlak; Sunil A Kulkarni; Klaus Kümmerer; Penny Leavitt; Bernhard Majer; Scott Masten; Scott Miller; Janet Moser; Moiz Mumtaz; Wolfgang Muster; Louise Neilson; Tudor I Oprea; Grace Patlewicz; Alexandre Paulino; Elena Lo Piparo; Mark Powley; Donald P Quigley; M Vijayaraj Reddy; Andrea-Nicole Richarz; Patricia Ruiz; Benoit Schilter; Rositsa Serafimova; Wendy Simpson; Lidiya Stavitskaya; Reinhard Stidl; Diana Suarez-Rodriguez; David T Szabo; Andrew Teasdale; Alejandra Trejo-Martin; Jean-Pierre Valentin; Anna Vuorinen; Brian A Wall; Pete Watts; Angela T White; Joerg Wichard; Kristine L Witt; Adam Woolley; David Woolley; Craig Zwickl; Catrin Hasselgren
Journal:  Regul Toxicol Pharmacol       Date:  2018-04-17       Impact factor: 3.271

9.  Comparing the performance and coverage of selected in silico (liver) metabolism tools relative to reported studies in the literature to inform analogue selection in read-across: A case study.

Authors:  Matthew Boyce; Brian Meyer; Chris Grulke; Lucina Lizarraga; Grace Patlewicz
Journal:  Comput Toxicol       Date:  2022-02-01

10.  Integrative chemical-biological read-across approach for chemical hazard classification.

Authors:  Yen Low; Alexander Sedykh; Denis Fourches; Alexander Golbraikh; Maurice Whelan; Ivan Rusyn; Alexander Tropsha
Journal:  Chem Res Toxicol       Date:  2013-08-05       Impact factor: 3.739

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