Median lethal concentration values of rodents are commonly used to express the relative risk related to the acute toxicity of new and available chemicals. These toxicity tests are costly and time demanding. Consequently, computational approaches can be used as alternative frameworks. The search for interspecies correlations also represents important substitute methods to the classical mammalian laboratory tests. In this paper we considered rat and mouse acute toxicity data (LD50 values) of organophosphorous compounds (OPs) with diverse structures. Interspecies QSTTR (quantitative structure-toxicity–toxicity relationships) models were developed to predict the oral acute toxicity to a particular species using the available experimental data towards a different species. The multiple linear regression approach was applied to extrapolate the known toxicity of chemicals of interests to species missing toxicity data. OPs structures were optimized by means of molecular mechanics calculations using the MMFF94s force field. Structural parameters were calculated based on the optimized structures. The acute toxicity data of OPs on one species was related to the acute toxicity on another species using the multiple linear regression (MLR) approach. Additional descriptors improved the fitting quality of the MLR models. Model validation was performed using several statistical parameters to test the model predictive power. The results suggest the suitability of the developed QSTTR models to reliably predict the acute toxicity of organophosphorous chemicals.
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Interspecies Quantitative Structure-Toxicity-Toxicity Relationships for Predicting the Acute Toxicity of Organophosphorous Compounds
Published:
13 November 2021
by MDPI
in The 25th International Electronic Conference on Synthetic Organic Chemistry
session Computational Chemistry
Abstract:
Keywords: Organophosphourus compunds; acute toxicity; Omega; quantitative structure-toxicity-toxicity relationships