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Modeling of quantitative structure - activity relationships between physicochemical descriptors of organic chemicals and their acute intravenous toxicity in mice have been presented. This approach includes three steps: structure-similarity chemicals selection for every chemical-of-interest (clusterization); construction of quantitative structure - toxicity models for every cluster (without including of chemical-of-interest); application of obtained QSAR equations for chemical-of-interest toxicity estimation. This approach has been applied for acute intravenous toxicity calculations of 10241 organic chemicals. For 7759 chemicals which has enough quantity of structural neighbours with the Tanimoto index (Tc) on the level 0.30 and over, a standard deviation of calculation vs. experimental log(1/LD50) values is equal to 0.51 at the estimation of experimental determination on the level 0.50. The results of calculations isn't so good for remain chemicals (~24%). It is connect with absence of sufficient number of structure similarity neighbours. It's assumed this QSAR approach can be useful for activity and toxicity prediction of chemicals large sets.

Acute intravenous toxicity to mice calculations on the basis local regression models in superoverlapping clusters (LRMSC)