[Genetic algorithms in 3D-QSAR: The use of multiple ligand orientations for improved predictions of toxicity] / Genetische Algorithmen im 3D-QSAR: Verwendung multipler Wirkstofforientierungen zur verbesserten Voraussage der Toxizität.

In a recent article in this journal, we discussed the application of a 3D-QSAR technique to the prediction of the toxicity of dibenzodioxins, dibenzofurans, and biphenyls (Vedani et al., 1999a). The use of such methods is legitimate because there is strong evidence that the toxicity is mediated by the Aryl hydrocarbon (Ah) receptor, a regulatory element involved in the mammalian metabolism of xenobiotics. In an extention to a concept developed at our laboratory (Vedani et al., 1998), we now show that safer predictions are possible if instead of a single - and, therefore, necessarily biased - assumption about the mutual orientation of the toxins, an ensemble of possible orientations is used for model construction. The contribution of a single entity within this ensemble to the toxin-receptor interaction energy is determined by a Boltzmann criterion. While in the single-orientation model two of the 26 toxins of an external test set were predicted false positive or false negative, all test substances are correctly predicted in the multiple-orientation model - including up to four different orientations per molecule - within a factor 10 of the experimental binding affinity. These results demonstrate that 3D-QSAR techniques based on a genetic algorithm can be used to predict the toxicity of chemical and pharmacological substances "in computo" if a receptor-mediated mechanism can be assumed. Consequently, the method can be used in toxicological screening assays, thereby replacing stressful tests on animals.

[Genetic algorithms in 3D-QSAR: Predicting the toxicity of dibenzodioxins, dibenzofurans and biphenyls] / Genetische Algorithmen im 3D-QSAR: Voraussage der Toxizität von Dibenzodioxinen, Dibenzofuranen und Biphenylen.

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) and related compounds represent serious environmental health hazards, whose effects include dermal toxicity, immunotoxicity, tumor promotion, developmental and reproductive toxicity. There is strong evidence that the toxicity is mediated by the Aryl hydrocarbon (Ah) receptor, a regulatory element involved in the mammalian metabolism of xenobiotics. Using Quasi-atomistic receptor modeling, a 3D-QSAR technique, we have generated a receptor model for the Ah receptor. The model was trained using 76 dibenzodioxins, dibenzofurans, and biphenyls, and tested using 26 compounds different therefrom. 24 of these test compounds (92.3%) were predicted to within a factor of 10 of the experimental binding affinity. One compound was predicted false positive, another false negative (7.7% total). The sensitivity of the model with respect to the biological activity was demonstrated by means of a scramble test with negative outcome. Quasi-atomistic receptor modeling can be used for the testing of chemicals and pharmaca for a toxicological potential in an early development phase and thereby replace stressful tests on animals