Quantitative structure-toxicity relationship (QSTR) plays an important role in toxicity prediction. With the modified method, the quantum chemistry parameters of 57 benzoic acid compounds were calculated with modified molecular connectivity index (MCI) using Visual Basic Program Software, and the QSTR of benzoic acid compounds in mice via oral LD50 (acute toxicity) was studied. A model was built to more accurately predict the toxicity of benzoic acid compounds in mice via oral LD50: 39 benzoic acid compounds were used as a training dataset for building the regression model and 18 others as a forecasting dataset to test the prediction ability of the model using SAS 9.0 Program Software. The model is LogLD50 = 1.2399 × 0JA +2.6911 × 1JA – 0.4445 × JB (R2 = 0.9860), where 0JA is zero order connectivity index, 1JA is the first order connectivity index and JB = 0JA × 1JA is the cross factor. The model was shown to have a good forecasting ability.

Quantitative structure-toxicity relationship (QSTR) studies play an important role in toxicity forecasting, which is widely used in the study of modern compounds. Benzoic acid derivatives are an important type of organic chemicals. Most of them may cause serious public health and environmental problems. The effect of quantum-chemistry parameters on the toxicity of benzoic acid derivatives in rats via oral 50% lethal dose (LD 50 ) was studied by QSTR, and a model to predict the toxicity of benzoic acid derivatives was constructed. In order to obtain an accurate model, cross factors were considered and a model for predicting the toxicity of benzoic acid derivatives in rats via oral LD 50 was built using a linear regression method (correlation 0.990). The novel model is À log toxi ¼ 0:144 LogP À 0:0269SAG þ 0:0000127HoF À 0:000377PE, R 2 = 0.990, C(p) = 4.000, mean square error (MSE) = 0.785. The model demonstrated good forecasting ability.

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