Study on QSAR of phenylsulfonyl carboxylate compounds by using artificial neural network

The systematic study of quantitative structure-activity relationship(QSAR) on 56 phenylsulfonyl carboxylate compounds between the structures and the acute toxicities to luminescent bacteria was performed by using the artificial neural network(ANN) based on the back propagation algorithm.For the ANN method,using the quantum chemical parameters about structure as the inputs and the acute toxicities as the outputs,the leave one out cross-validation regression coefficient was 0.986 3,the standard error was 0.075 3,the correlation coefficient of the test set was 0.988 0 and the absolute values of residual were less than 0.20.In order to make contrast,the QSAR model was set up by using multiple linear regressions(MLR) method.For the model built by MLR,the correlation coefficient was 0.947 2,the standard error was 0.141 3 and the absolute values of residual were less than 0.34.The results showed that the performance of ANN method is better than that of MLR method.