Quantum vs. topological descriptors in the development of molecular models of groundwater pollution by pesticides

Using monitoring observations from two, independent studies of US groundwater comprising a total of 61 pesticide compounds, this study has shown that those compounds found in groundwater can be distinguished from those that cannot be found in groundwater on the basis of semi-empirical, quantum chemical and empirical molecular descriptors. For the semi-empirical descriptors, logistic regression models have been developed and validated against the dataset based on the semi-empirical and quantum chemical descriptors. Logistic regression models, based on the Debye dipole moment (mu), the hydration energy (DeltaHhyd), and van der Waals volume (VvdW), resulted in a maximal explained variation in the data of 74%. When topological indices were also included the explained variance in data increased to 91%, with 86% of the variation being explained by the rule that a compound will be found in groundwater if: 0.28mu < 6chip(v) where 6chip(v) is the sixth-order molecular path connectivity and mu is the dipole moment of the compound. The significance of the dipole moment and hydration energy (or van der Waals volume) indicates that it is water solubility that controls mobility, with the inclusion of topological descriptors representing structural factors limiting the solubility. The dependence of leaching potential on the descriptors that control solubility indicates that predictions of environmental fate based on this approach may represent a strong alternative to the use of adsorption and degradation parameters.