Monica Enache

Quantitative cationic‐activity relationships for predicting toxicity of metals

Developing and validating quantitative cationic-activity relationships or (Q)CARs to predict the toxicity metals is challenging because of issues associated with metal speciation, complexation and interactions within biological systems and the media used to study these interactions. However, a number of simplifying assumptions can be used to develop and validate (Q)CARs to predict the toxicity of metals: The ionic form is the most active form of a metal; the bioactivity of a dissolved metal is correlated with its free ion concentration or activity; most metals exist in biological systems as cations, and differences in metal toxicity result from differences in metal ion binding to biological molecules (ligand-binding). In summary, it appears that certain useful correlations can be made between several physical and chemical properties of ions (mostly cations) and toxicity of metals. This review provides a historical perspective of studies that have reported correlations between physical and chemical properties of cations and toxicity to mammalian and nonmammalian species using in vitro and in vivo assays. To prepare this review, approximately 100 contributions dating from 1839 to 2003 were evaluated and the relationships between about 20 physical and chemical properties of cations and their potential to produce toxic effects were examined.

Fundamental QSARs for metal ions

Introduction The Concept of Structure-Activity Relationships (SARs) Metals in the Molecular Environment Metals in and Effect on Whole Organisms Electronic Structure of Metals and Atomic Parameters About QSAR and the Descriptors of Chemical Structure General Properties of Metals Characterization of Metals According to Their Electronic Configuration Properties of Metals and Metal Ions Related to QSAR Studies Properties of Metals and Metal Ions as Tools in Quantitative Structure-Activity Relationship (QSAR) Studies Electrochemical Characteristics of Metals Metal Ions in a Coordination Environment Properties of Metal Ions Relevant to Ionic and Covalent Bonding Tendencies Bronsted Acidity of Metal Ions Solubility of Metal Compounds and Metal Ion Hydration Descriptors for Organometallic Complexes Definitions Methods and Computer Programs Examples of Descriptors Examples of Descriptors Calculation for Organometallic Complexes Appendix 4.1: List of PRECLAV Whole Molecule Descriptors QSARs for Predicting Cation Toxicity, Bioconcentration, Biosorption, and Binding Introduction Most Common Physicochemical Properties Used to Predict Cation Toxicity Less Common Physicochemical Properties Used to Predict Cation Toxicity Nonphysicochemical Properties Used to Predict Cation Toxicity Physicochemical Properties Used to Predict Cation Binding Physicochemical Properties Used to Predict Cation Bioconcentration Physicochemical Properties Used to Predict Cation Biosorption QSARs versus BLM Introduction BLM QSARs versus the BLM Regulatory Limits and Applications Regulatory Limits Regulatory Applications Future Considerations Constructing QSARs for Metal Ions Selection and Transformations of Explanatory Variables Selection and Adjustment of Independent Variables Quantitative Ion Characteristic-Activity Relationship (QICAR) Models Appendix 8.1: SAS Bacterial Bioluminescence EC50 QICAR Data Set Appendix 8.2: SAS Bacterial Bioluminescence Binary Metal Mixture Example

Correlation of physico‐chemical parameters with toxicity of metal ions to plants

The in vivo toxicities of 12 metal ions to cabbage plants have been correlated with ion-specific physico-chemical parameters. Several regression models were statistically significant but two different electronegativities in combination with Kaisers electrochemical potential appeared to be the best determinants of metal ion toxicity, giving a good correlation (r2adjusted = 0.81 for 11 metal ions excluding copper, and 0.66 for all 12 metal ions). © 2000 Society of Chemical Industry