title: Prediction of acute mammalian toxicity of organophosphorus pesticide compounds from molecular structure.
abstract: A quantitative structure-activity relationship (QSAR) investigation was done for the acute oral mammalian toxicity (LD50) of a set of 54 organophosphorus pesticide compounds. The compounds were represented with calculated molecular structure descriptors, which encoded their topological, electronic, and geometrical features. Feature selection was done with a genetic algorithm to find subsets of descriptors that would support a high quality computational neural network (CNN) model to link the structural descriptors to the -log(mmol/kg) values for the compounds. The best seven-descriptor non-linear CNN model found had an rms error of 0.22 log units for the training set compounds and 0.25 log units for the prediction set compounds.
authors.affiliation: Department of Chemistry, Penn State University, University Park 16802, USA.
authors.forename: D V
authors.initials: DV
authors.lastname: Eldred
authors.forename: P C
authors.initials: PC
authors.lastname: Jurs
mesh_terms: D000818:Animals; D005260:Female; D007306:Insecticides / Q000737:chemistry* / Q000633:toxicity*; D007928:Lethal Dose 50; D008297:Male; D008954:Models, Biological; D008956:Models, Chemical; D015394:Molecular Structure; D009010:Monte Carlo Method; D016571:Neural Networks, Computer; D009943:Organophosphorus Compounds; D051381:Rats; D015203:Reproducibility of Results; D013329:Structure-Activity Relationship
chemical_list: D007306:Insecticides; D009943:Organophosphorus Compounds