Abstract:The molecular structures of eleven kinds of p-hydroxybenzoate esters were optimized by using density functional theory (DFT) B3LYP method of quantum chemistry, and the quantitative structure-activity relationship (QSAR) of these compounds was studied. Stepwise multiple linear regression was used to select the descriptors and to generate the best prediction model that relates the structural features to inhibitory activity. The results suggested that ELUMO and had positive correlation on the activities of p-hydroxybenzoate esters, with correlation coefficient of 0.9910. The results showed that the lowest unoccupied molecular orbit ELUMO and the increase of dipole moment were the main independent factors contributing to the antifungal activity of the compounds. The antifungal activity increased with the increase of ELUMO and . The obtained QSAR model could provide theory reference to design p-hydroxybenzoate esters with stronger antibacterial activity.
