Prediction of toxicity of organophosphorus insecticides against the midge, Chironomus riparius, via a QSAR neural network model integrating environmental variables

A quantitative structure-activity relationship (QSAR) investigation was done for estimating the toxicity of organophosphorus compounds measured against midge Larvae (Chironomus riparius) under varying temperature (11, 18, and 25 degrees C) and pH (6, 7, and 8) conditions and with or without sediment. Chemicals were described by means of an autocorrelation vector encoding lipophilicity. A three-Layer feedforward neural network trained by the back-propagation algorithm was used as the statistical engine for deriving a powerful QSAR model accounting for environmental constraints.