Abstract
Marine ecosystems are affected by aromatic hydrocarbons. The predicting ability based on the quantitative structureactivity relationships (QSAR) model of unknown aromatic hydrocarbons toxicity is one of the tasks of security precaution. To establish the QSAR model between the physical and chemical properties of aromatic hydrocarbons and the inhibited activity of Chlorella vulgaris(C. Vulgaris), the optimized geometries, based on the 96 hr-EC50 of 25 aromatic hydrocarbons with C. Vulgaris were carried out at the B3LYP/6-311G** level by density functional theory (DFT) calculation. With matlab2 010(a) software, genetic algorithm principal components regression (GAPCR) methods was used to develop the QSAR model and compared to traditional PCR model. PC1+PC3+PC5+PC6+PC8 were finally selected by GAPCR method. The of training, prediction data set and LOO cross validation are 0.918, 0.956 and 0.933, respectively. Meanwhile, the results of PCR were 0.949, 0.755 and 0.825, respectively. The results of this work showed that the GAPCR method has great results and good generalization capability. Comparing two motheds results indicting that GAPCR gives superior results to traditional PCR procedure.
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