Structure-toxicity relationships study of a series of organophosphorus insecticides
Structure-toxicity relationships were studied for a set of 47 insecticides by means of multiple linear regression (MLR) and artificial neural network (ANN). A model with three descriptors, including shape surface [S(R-2)], hydrogen-bonding acceptors [HBA(R-2)] and molar refraction [MR(R-1)], showed good statistics both in the regression (r = 0.875, s = 0.417 and q(2) = 0.675) and artificial neural network model with a configuration of [3-5-1] (r = 0.966, s = 0.200 and q(2) = 0.647). The statistics for the prediction on toxicity [log LD50 (lethal dose 50, oral, rat)] in the test set of 20 organophosphorus insecticides derivatives is (r = 0.849, s = 0.435) and (r = 0.748, s = 0.576) for MLR and ANN respectively. The model descriptors indicate the importance of molar refraction and shape contributions toward toxicity of organophosphorus insecticides derivatives used in this study. This information is pertinent to the further design of new insecticides.
organophosphorus insecticides multiple linear regression artificial neural network descriptors acute ld50