Due to the lack of experimental data, there has been increasing use of theoretical structural descriptors in the hazard assessment of chemicals. We have used a hierarchical approach to develop class-specific quantitative structure - activity relationship (QSAR) models for the prediction of mutagenicity of a set of 95 aromatic and heteroaromatic amines. The hierarchical approach begins with the simplest molecular descriptors, the topostructural, which encode limited chemical information. The complexity is then increased, adding topochemical, geometric, and finally quantum chemical parameters. We have also added log P to the set of independent variables. The results indicate that the topological parameters, i.e., the topostructural and topochemical indices, explain the majority of the variance, and that the inclusion of log P, geometric, and quantum chemical parameters does not result in significantly improved predictive models.
|Original language||English (US)|
|Number of pages||8|
|Journal||Journal of chemical information and computer sciences|
|State||Published - Jan 1 2001|