Quantitative structure-activity relationship (QSAR) analysis of four toxicological data sets is described. The toxicological data include three data sets retrieved from the literature (the toxic and metabolic effects of 23 aliphatic alcohols on the perfused rat liver; the toxicity of 21 pyridines to mice; the lethality of 55 halogenated hydrocarbons to the mould Aspergillus nidulans). In addition, the toxicity of 13 mono- and di-substituted nitrobenzenes in a 15 min assay using the alga Chlorella vulgaris was analysed. QSARs were developed successfully using descriptors to describe uptake in the organism (i.e. hydrophobicity as quantified by the logarithm of the octanol-water partition coefficient, log P) and reactivity at the site of action (i.e. electrophilicity as quantified by the energy of the lowest unoccupied molecular orbital, E(LUMO)). A further parameter describing molecular branching as also required to model the data for the aliphatic alcohols. The results demonstrate that mechanistically based QSARs can be developed for these diverse endpoints which are, in terms of statistical quality as good as, if not better, than QSARs based on less mechanistically interpretable descriptors.
A novel short term toxicity assay utilising the unicellular green alga Chlorella vulgaris is described. The test is based upon the premise that all living organisms contain nonspecific esterase enzymes, the activity of which can be assessed by the measurement of the disappearance of the ester, or appearance of the product. The novel assay described utilises fluorescein diacetate which is metabolised to fluorescein. The appearance of fluorescein, after 15 minutes exposure to the toxicant, was measured fluorimetrically. The concentration causing a 50% decrease in fluorescence, as compared to a control, was determined for 10 non-polar and 10 polar narcotics. Toxicity was related significantly to hydrophobicity for both mechanisms of action, with the QSAR for polar narcosis having a lower slope and higher intercept than that for non-polar narcosis. Significant inter-species relationships of the toxicity data with those for a 6 hour Chlorella vulgaris, and 40 hour Tetrahymena pyriformis, toxicity assay were also observed.
This study reports a database of toxicity values for 91 compounds assessed in a novel, rapid, and economical 15 min algal toxicity test. The toxicity data were measured using the unicellular green alga Chlorella vulgaris in an assay that determined the disappearance of fluorescein diacetate. The chemicals tested covered a wide range of physicochemical properties and mechanisms of action. Quantitative activity-activity relationships with the toxicity of the chemicals to other species (Tetrahymena pyriformis, Vibrio fischeri, and Pimephales promelas) showed strong relationships, although some differences resulting from different protocols were established. Quantitative structure-activity relationships (QSARs) were determined using linear [multiple linear regression (MLR)] and nonlinear [k-nearest neighbors (KNN)] methods. Three descriptors, accounting for hydrophobicity, electrophilicity, and a function of molecular size corrected for the presence of heteroatoms, were found to be important to model toxicity. The predictivity of MLR was compared to KNN using leave-one-out cross-validation and the simulation of an external test set. MLR demonstrated greater stability in validation. The results of this study showed that method selection in QSAR is task-dependent and it is inappropriate to resort to more complicated but less transparent methods, unless there are clear indications (e.g., inability of MLR to deal with the data set) for the need of such methods.
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