Literature DB >> 21120759

Evaluation of the OECD (Q)SAR Application Toolbox and Toxtree for predicting and profiling the carcinogenic potential of chemicals.

E Mombelli1, J Devillers.   

Abstract

The OECD (Q)SAR Application Toolbox and Toxtree are software tools used in regulatory toxicology to fill gaps in (eco)toxicity data. They include different SAR and QSAR models for estimating (eco)toxicological endpoints. Among them, the Benigni/Bossa rule-based system is proposed to characterize the carcinogenic potential of chemicals. Our study evaluates the predictive performance that can be expected from the OECD (Q)SAR Toolbox and Toxtree when analysing chemicals by means of the structural alerts coded within the Benigni/Bossa rule-based system for carcinogenicity and the associated QSAR model (QSAR8). These evaluations have been carried out thanks to a large collection of chemicals retrieved from original publications and public databases. Overall, our findings confirm the performance of the system of structural alerts while suggesting that the sensitivity of QSAR8, as implemented in the two tools, is lower than what was previously reported. They also indicate that attention has to be paid when interpreting the output of the two tools because of possible malfunctions involving the coding of two-dimensional structures. A set of possible modulating factors for the structural alert identifying polycyclic aromatic hydrocarbons is also proposed together with candidates for putative new structural alerts not included in the tested tools.

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Year:  2010        PMID: 21120759     DOI: 10.1080/1062936X.2010.528598

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  6 in total

1.  In Silico Prediction of Chemically Induced Mutagenicity: A Weight of Evidence Approach Integrating Information from QSAR Models and Read-Across Predictions.

Authors:  Enrico Mombelli; Giuseppa Raitano; Emilio Benfenati
Journal:  Methods Mol Biol       Date:  2022

2.  3D QSAR studies of hydroxylated polychlorinated biphenyls as potential xenoestrogens.

Authors:  Patricia Ruiz; Kundan Ingale; John S Wheeler; Moiz Mumtaz
Journal:  Chemosphere       Date:  2015-11-19       Impact factor: 7.086

Review 3.  Building a virtual ligand screening pipeline using free software: a survey.

Authors:  Enrico Glaab
Journal:  Brief Bioinform       Date:  2015-06-20       Impact factor: 11.622

Review 4.  Ethics of animal research in human disease remediation, its institutional teaching; and alternatives to animal experimentation.

Authors:  Rajkumar Cheluvappa; Paul Scowen; Rajaraman Eri
Journal:  Pharmacol Res Perspect       Date:  2017-08

Review 5.  In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts.

Authors:  Hongbin Yang; Lixia Sun; Weihua Li; Guixia Liu; Yun Tang
Journal:  Front Chem       Date:  2018-02-20       Impact factor: 5.221

6.  Curation of cancer hallmark-based genes and pathways for in silico characterization of chemical carcinogenesis.

Authors:  Peir-In Liang; Chia-Chi Wang; Hsien-Jen Cheng; Shan-Shan Wang; Ying-Chi Lin; Pinpin Lin; Chun-Wei Tung
Journal:  Database (Oxford)       Date:  2020-01-01       Impact factor: 3.451

  6 in total

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