Integrated approach to assess the domain of applicability of some commercial (Q)SAR models.
An integrated framework of data analysis has been proposed to systematically address the determination of the domain of applicability (DA) of some commercial Quantitative Structure Activity Relationship ((Q)SAR) models based on the structure of test chemicals. This framework forms one of the important steps in dealing with the growing concerns on reliability of model-based predictions on toxicity of chemicals specifically in the regulatory context. The present study uses some of the well-known mutagenicity and carcinogenicity models that are available within the Casetox (MultiCASE Inc.) and TOPKAT (Accelrys Software Inc.) programs. The approach enumerated in this paper employs chemoinformatics tools that facilitate comparisons of key structural features as well as application of cluster analysis techniques. The approach has been illustrated using a set of eleven chemical structures selected from the Canadian Domestic Substances List (DSL) that are not present in the model training sets, and the efficacy of the approach has also been assessed using seven chemicals with known toxicities. The methodologies presented here could help address the issue of DA of complex (Q)SAR models and at the same time, serve as useful tools for regulators to make a preliminary assessment of (Q)SAR based systems thereby helping the process of hazard-based regulatory assessments of chemicals.
Kulkarni
S A
SA
Chemistry Research Division, Safe Environments Programme, Health Canada, Ottawa, Ontario, Canada.
Zhu
J
J
D000818:Animals; D002273:Carcinogens / Q000737:chemistry* / Q000633:toxicity*; D016000:Cluster Analysis; D005260:Female; D008297:Male; D051379:Mice; D008954:Models, Biological; D009153:Mutagens / Q000737:chemistry* / Q000633:toxicity*; D021281:Quantitative Structure-Activity Relationship; D051381:Rats
D002273:Carcinogens; D009153:Mutagens