Literature DB >> 32334037

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across: An EFSA funded project.

Romualdo Benigni1, Rositsa Serafimova2, Juan Manuel Parra Morte2, Chiara Laura Battistelli3, Cecilia Bossa3, Alessandro Giuliani3, Elena Fioravanzo4, Arianna Bassan4, Mojca Fuart Gatnik4, James Rathman5, Chihae Yang5, Aleksandra Mostrag-Szlichtyng5, Oliver Sacher5, Olga Tcheremenskaia3.   

Abstract

To facilitate the practical implementation of the guidance on the residue definition for dietary risk assessment, EFSA has organized an evaluation of applicability of existing in silico models for predicting the genotoxicity of pesticides and their metabolites, including literature survey, application of QSARs and development of Read Across methodologies. This paper summarizes the main results. For the Ames test, all (Q)SAR models generated statistically significant predictions, comparable with the experimental variability of the test. The reliability of the models for other assays/endpoints appears to be still far from optimality. Two new Read Across approaches were evaluated: Read Across was largely successful for predicting the Ames test results, but less for in vitro Chromosomal Aberrations. The worse results for non-Ames endpoints may be attributable to the several revisions of experimental protocols and evaluation criteria of results, that have made the databases qualitatively non-homogeneous and poorly suitable for modeling. Last, Parent/Metabolite structural differences (besides known Structural Alerts) that may, or may not cause changes in the Ames mutagenicity were identified and catalogued. The findings from this work are suitable for being integrated into Weight-of-Evidence and Tiered evaluation schemes. Areas needing further developments are pointed out.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  (Q)SAR; Dietary risk assessment; Genotoxicity; In silico; Metabolite; Pesticide active substance; Read across; Structural changes

Year:  2020        PMID: 32334037     DOI: 10.1016/j.yrtph.2020.104658

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


  6 in total

1.  Scientific Opinion of the Scientific Panel on Plant Protection Products and their Residues (PPR Panel) on testing and interpretation of comparative in vitro metabolism studies.

Authors:  Antonio F Hernandez-Jerez; Paulien Adriaanse; Annette Aldrich; Philippe Berny; Tamara Coja; Sabine Duquesne; Andreas Focks; Marina Marinovich; Maurice Millet; Olavi Pelkonen; Silvia Pieper; Aaldrik Tiktak; Christopher J Topping; Anneli Widenfalk; Martin Wilks; Gerrit Wolterink; Ursula Gundert-Remy; Jochem Louisse; Serge Rudaz; Emanuela Testai; Alfonso Lostia; Jean-Lou Dorne; Juan Manuel Parra Morte
Journal:  EFSA J       Date:  2021-12-23

2.  In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs.

Authors:  Raymond R Tice; Arianna Bassan; Alexander Amberg; Lennart T Anger; Marc A Beal; Phillip Bellion; Romualdo Benigni; Jeffrey Birmingham; Alessandro Brigo; Frank Bringezu; Lidia Ceriani; Ian Crooks; Kevin Cross; Rosalie Elespuru; David M Faulkner; Marie C Fortin; Paul Fowler; Markus Frericks; Helga H J Gerets; Gloria D Jahnke; David R Jones; Naomi L Kruhlak; Elena Lo Piparo; Juan Lopez-Belmonte; Amarjit Luniwal; Alice Luu; Federica Madia; Serena Manganelli; Balasubramanian Manickam; Jordi Mestres; Amy L Mihalchik-Burhans; Louise Neilson; Arun Pandiri; Manuela Pavan; Cynthia V Rider; John P Rooney; Alejandra Trejo-Martin; Karen H Watanabe-Sailor; Angela T White; David Woolley; Glenn J Myatt
Journal:  Comput Toxicol       Date:  2021-09-23

3.  Migration of styrene oligomers from food contact materials: in silico prediction of possible genotoxicity.

Authors:  Elisa Beneventi; Christophe Goldbeck; Sebastian Zellmer; Stefan Merkel; Andreas Luch; Thomas Tietz
Journal:  Arch Toxicol       Date:  2022-08-13       Impact factor: 6.168

4.  Use of transcriptomics in hazard identification and next generation risk assessment: A case study with clothianidin.

Authors:  Heike Sprenger; Katrin Kreuzer; Jimmy Alarcan; Kristin Herrmann; Julia Buchmüller; Philip Marx-Stoelting; Albert Braeuning
Journal:  Food Chem Toxicol       Date:  2022-06-08       Impact factor: 5.572

Review 5.  Use of new approach methodologies (NAMs) to meet regulatory requirements for the assessment of industrial chemicals and pesticides for effects on human health.

Authors:  Andreas O Stucki; Tara S Barton-Maclaren; Yadvinder Bhuller; Joseph E Henriquez; Tala R Henry; Carole Hirn; Jacqueline Miller-Holt; Edith G Nagy; Monique M Perron; Deborah E Ratzlaff; Todd J Stedeford; Amy J Clippinger
Journal:  Front Toxicol       Date:  2022-09-01

6.  ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities.

Authors:  Marina Garcia de Lomana; Andrea Morger; Ulf Norinder; Roland Buesen; Robert Landsiedel; Andrea Volkamer; Johannes Kirchmair; Miriam Mathea
Journal:  J Chem Inf Model       Date:  2021-06-21       Impact factor: 4.956

  6 in total

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