Predicting Ecotoxicology of Organophosphorous Insecticides: Successful Parameter Selection with the Genetic Function Algorithm

QSARs have been developed for 20 organophosphates, using good experimental data in the form of LC50 toxicity values towards guppy from previously published work. A large number of steric, physical and electronic descriptors have been calculated. After the removal of descriptors that were highly cross-correlated or correlated poorly with activity, the genetic algorithm was employed to select the optimum descriptors for use in multivariate regression. Best equation r2 and r2cv values were 0.943 and 0.905 respectively. Molecular field Analysis was also used in conjunction with the Genetic Function Approximation (GFA) algorithm to obtain predictive equations, r2 and r2cv values were 0.939 and 0.896 respectively. However, when the data were randomised, results proved to be as good, (and in one case better) than using the correct experimental values. For equations subsequently derived using the Genetic Partial Least Squares (G/PLS) technique (best r2 and r2cv values being 0.943, 0.905 respectively), randomisation gave worse answers than using the correct experimental values. This work demonstrates the danger of using the powerful GFA technique to select from a large number of parameters, but establishes that the G/PLS method is sufficiently robust to provide reliable results.