Advances in quantitative ion character-activity relationships (QICARs): Using metal-ligand binding characteristics to predict metal toxicity

Environmental toxicologists readily adopted QSARs from pharmacology to predict organic contaminant toxicity. In contrast, models relating metal ion characteristics to their bioactivity remain poorly explored and underutilized. Quantitative Ion Character-Activity Relationships (QICARs) have recently been developed to predict metal toxicity. The QICAR approach, based on metal-ligand binding tendencies, has been applied successfully to a wide range of effects, species, and media on a single metal basis. In previous single metal studies, a softness parameter and the \log K-OH\ were among the ion qualities with the highest predictive value for toxicity. Here, QICAR modeling is extended to predict toxicity using data from the US EPA ECOTOX database and for To receive all correspondence binary metal mixtures. Using the US EPA ECOTOX database, predictive single metal models were produced for four fish species (bluegill, carp, fathead minnow, and mummichog). Using the Microtox((R)) bioassay, the interactions of binary mixtures of metals (Co, Cu, Mn, Ni, and Zn) were quantified using a linear model with an interaction term. A predictive relationship was developed for metal interaction between metal pairs and the difference in softness. This study supports the hypothesis that general prediction of metal toxicity and interactions from ion characteristics is feasible. It is important that additional work with metals of different valences and sizes be done to further enhance the general accuracy of metal interaction predictions.