2010
DOI: 10.1080/1062936x.2010.528961
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Evaluation of the OECD QSAR Application Toolbox and Toxtree for estimating the mutagenicity of chemicals. Part 2. α-β unsaturated aliphatic aldehydes

Abstract: The OECD QSAR Application Toolbox versions 1.1.01 and 1.1.02 and Toxtree version 1.60, which were developed for facilitating the practical use of (Q)SAR approaches by regulators, include a mechanistic SAR model for predicting the mutagenicity of α-β unsaturated aliphatic aldehydes. The aim of this study was to estimate the interest and limitations of this model. First, the model was re-computed to check its transparency and to verify its statistical validity. Then, the model implemented in the two software too… Show more

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Cited by 14 publications
(7 citation statements)
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“…Since among the list of 197 pesticides and biocides listed in Table 1, only this chemical included the structural feature corresponding to SA #30, we tried to see whether this lack of detection was confirmed with other chemicals including the structural feature associated with SA #30. This is the case for the 21 chemicals listed in Table 2, two of them being classified as 92 J. Devillers et al It is worth noting that a problem of detection of SA was recently stressed in a study focusing on the prediction of the mutagenicity of the -unsaturated aliphatic aldehydes [26]. A logical hypothesis explaining this misdetection of SAs should be that the algorithm for detecting the structural features is not efficient enough, or includes bugs.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Since among the list of 197 pesticides and biocides listed in Table 1, only this chemical included the structural feature corresponding to SA #30, we tried to see whether this lack of detection was confirmed with other chemicals including the structural feature associated with SA #30. This is the case for the 21 chemicals listed in Table 2, two of them being classified as 92 J. Devillers et al It is worth noting that a problem of detection of SA was recently stressed in a study focusing on the prediction of the mutagenicity of the -unsaturated aliphatic aldehydes [26]. A logical hypothesis explaining this misdetection of SAs should be that the algorithm for detecting the structural features is not efficient enough, or includes bugs.…”
Section: Resultsmentioning
confidence: 99%
“…The same type of external validation was also performed on the other SAR model implemented in both software tools for predicting the mutagenicity of the -unsaturated aliphatic aldehydes [24,25]. The results were totally different because important statistical failures were detected in the model, which showed limited and unreliable prediction performances [26]. The OECD QSAR Application Toolbox and Toxtree also include a system of structural alerts (SAs) for predicting the carcinogenicity potential of chemicals [27,28]; its prediction results were compared with experimental data collected in databases and original publications for more 500 structurally diverse chemicals [29].…”
Section: Introductionmentioning
confidence: 99%
“…Craig et al 2014), sulphur-containing compounds(Richarz et al 2014), pesticide/biocide carcinogenicity(Devillers et al 2011), unsaturated aliphatic aldehydes(Devillers and Mombelli 2010b), aromatic amines (Devillers and Mombelli 2010a), and chemical carcinogens(Mombelli and Devillers 2010).…”
mentioning
confidence: 99%
“…A particular focus is put on models that could provide information indicating whether the substance could be classified as carcinogenic, mutagenic or toxic to reproduction (CMR) according to Dangerous Substances Directive [9] or CLP Regulation [10]. To our knowledge, previous studies on the utility of non-experimental approaches to predicting CMR properties focused on comparing the results of specific assays to those obtained using selected in silico models rather than the use of in silico results for CLP classification and the prioritisation of industrial compounds for further testing according to the REACH legislation [11][12][13][14][15][16][17][18][19][20][21].…”
mentioning
confidence: 99%