QSAR assessment of aquatic toxicity potential of diverse agrochemicals.

Abstract

The fast-increasing number of commercially produced chemicals challenges the experimental ecotoxicity assessment methods, which are costly, time-consuming, and dependent on the sacrifice of animals. In this regard, Quantitative Structure-Property/Activity Relationships (QSPR/QSAR) have led the way in developing ecotoxicity assessment models. In this study, QSAR models have been developed using the pEC₅₀ values of 82 diverse agrochemicals or agro-molecules against a planktonic crustacean Daphnia magna with easily interpretable 2D descriptors. Moreover, a link among octanol-water partition coefficient (K_OW), bio-concentration factor (BCF), and critical body residue (CBR) has been addressed, and their imputation for the prediction of the toxicity endpoint (EC₅₀) has been done with an objective of the advanced exploration of several ecotoxicological parameters for toxic chemicals. The developed partial least squares (PLS) models were validated rigorously and proved to be robust, sound, and immensely well-predictive. The final Daphnia toxicity model derived from experimental derived properties along with computed descriptors emerged better in statistical quality and predictivity than those obtained solely from computed descriptors. Additionally, the pEC₅₀ and other important properties (log K_OW, log BCF, and log CBR) for a set of external agro-molecules, not employed in model development, were predicted to show the predictive ability of the models.