Statistically significant quantitative structure-toxicity relationship (QSTR) models have been developed for assessing developmental toxicity potential (DTP) of chemicals.
Three submodels, one each for aliphatic, heteroaromatic and carboaromatic compounds, have been cross-validated to ascertain their robustness.
The specificities of the models range from 86% to 97%, and their sensitivities between 86% and 89%. For convenient computer-assisted application, the models are installed in a toxicity assessment software package, TOPKAT, which has been recently enhanced with algorithms to identify whether or not a query structure is inside the optimum prediction space (OPS) of a QSTR model.
Different functionalities of the TOPKAT program have been explained by assessing the DTP of a number of compounds not used in the model training sets.
The DTP of 18 existing drugs was assessed using these models ; the DT assay results were available for 5 of these.
Three of these 5 molecules were identified to be inside the OPS and their TOPKAT assessment matched their experimental assignment.
Mots-clés Pascal : Composé chimique, Polluant, Environnement, Toxicité, Reproduction pathologie, Tératogène, Evaluation, Prédiction, Relation structure activité, Modélisation, Méthode étude
Mots-clés Pascal anglais : Chemical compound, Pollutant, Environment, Toxicity, Reproduction diseases, Teratogen, Evaluation, Prediction, Structure activity relation, Modeling, Investigation method
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 95-0472973
Code Inist : 002A30E. Création : 01/03/1996.