External validation of acute-to-chronic models for estimation of reproductive toxicity to Daphnia magna.

We evaluated the predictivity and applicability of previously proposed models for the reproductive toxicity of chemicals to Daphnia magna [SAR QSAR Environ. Res. 27:10, 833-850] by using external data from the United States Environmental Protection Agency database ECOTOX. These models were based on quantitative structure-activity-activity relationships (QSAARs) and a quantitative activity-activity relationship (QAAR): the models can be categorized as acute-to-chronic models with (QSAAR) and without (QAAR) structural and physicochemical (e.g. distribution coefficients, log D) descriptors. We found that the QSAAR models were suitable for chemicals with an '-NH2 attached to aromatic carbon' sub-structure, whereas the QAAR model was better for multicomponent compounds, coordination complexes, tin compounds and straight-chain primary amines. For chemicals with a known specific mode of action (e.g. pesticides and antibacterial agents and their derivatives), toxicity estimation within the acute-to-chronic framework requires special attention. We evaluated the applicability of the models on the basis of the descriptors in the models. We recommend that chemicals be pre-screened before their toxicities are estimated with these models: pre-screening enabled the estimation of the toxicities of some chemicals within the applicability domains of the models.

Acute to chronic estimation of Daphnia magna toxicity within the QSAAR framework.

We constructed models for acute to chronic estimation of the Daphnia magna reproductive toxicities of chemical substances from their Daphnia magna acute immobilization toxicities. The models combined the acute toxicities with structural and physicochemical descriptors. We used multiregression analysis and selected the descriptors for the models by means of a genetic algorithm. Of the best 100 models (as indicated by the lack of fit score), 90% included the following descriptors: acute toxicity (i.e. an activity parameter), distribution coefficient (log D) and structural indicator variables that indicate the presence of -NH2 attached to aromatic carbon and the presence of a chlorine atom. We compared the predictive abilities of five of these quantitative structure-activity-activity relationship (QSAAR) acute to chronic estimation models with the predictive ability of a simple linear regression model. The comparison revealed that inclusion of structural and physicochemical descriptors such as those in QSAAR models can improve models for extrapolation from acute to chronic toxicity. Our results also provide a QSAAR framework that is expected to be useful for the further development of chronic toxicity estimation models.

Predicting algal growth inhibition toxicity: three-step strategy using structural and physicochemical properties.

We propose a three-step strategy that uses structural and physicochemical properties of chemicals to predict their 72 h algal growth inhibition toxicities against Pseudokirchneriella subcapitata. In Step 1, using a log D-based criterion and structural alerts, we produced an interspecies QSAR between algal and acute daphnid toxicities for initial screening of chemicals. In Step 2, we categorized chemicals according to the Verhaar scheme for aquatic toxicity, and we developed QSARs for toxicities of Class 1 (non-polar narcotic) and Class 2 (polar narcotic) chemicals by means of simple regression with a hydrophobicity descriptor and multiple regression with a hydrophobicity descriptor and a quantum chemical descriptor. Using the algal toxicities of the Class 1 chemicals, we proposed a baseline QSAR for calculating their excess toxicities. In Step 3, we used structural profiles to predict toxicity either quantitatively or qualitatively and to assign chemicals to the following categories: Pesticide, Reactive, Toxic, Toxic low and Uncategorized. Although this three-step strategy cannot be used to estimate the algal toxicities of all chemicals, it is useful for chemicals within its domain. The strategy is also applicable as a component of Integrated Approaches to Testing and Assessment.

Determination of cytochrome P450 1A activities in mammalian liver microsomes by high-performance liquid chromatography with fluorescence detection.

A sensitive method for the determination of cytochrome P450 (P450 or CYP) 1A activities such as ethoxyresorufin O-deethylase (EROD) and methoxyresorufin O-demethylase (MROD) in liver microsomes from human, monkey, rat and mouse by high-performance liquid chromatography with fluorescence detection is reported. The newly developed method was found to be more sensitive than previous methods using a spectrofluorimeter and fluorescence plate reader. The detection limit for resorufin (signal-to-noise ratio of 3) was 0.80 pmol/assay. Intra-day and inter-day precisions (expressed as relative standard deviation) were less than 6% for both enzyme activities. With this improved sensitivity, the kinetics of EROD and MROD activities in mammalian liver microsomes could be determined more precisely. EROD activities in human and monkey liver microsomes, and MROD activities in liver microsomes from all animal species exhibited a monophasic kinetic pattern, whereas the pattern of EROD activities in rat and mouse liver microsomes was biphasic. In addition, the method could determine the non-inducible and 3-methylcholanthrene-inducible activities of EROD and MROD in rat and mouse liver microsomes under the same assay conditions. Therefore, this method is applicable to in vivo and in vitro studies on the interaction of xenobiotic chemicals with cytochrome CYP1A isoforms in mammals.