A comparative QSAR study on the estrogenic activities of persistent organic pollutants by PLS and SVM

Quantitative structure-activity relationships(QSARs)were determined using partial least square(PLS)and support vector machine(SVM).The predicted values by the final QSAR models were in good agreement with the corresponding experimental values.Chemical estrogenic activities are related to atomic properties(atomic Sanderson electronegativities,van der Waals volumes and polarizabilities).Comparison of the results obtained from two models,the SVM method exhibited better overall performances.Besides,three PLS models were constructed for some specific families based on their chemical structures.These predictive models should be useful to rapidly identify potential estrogenic endocrine disrupting chemicals.

Identification of resistant pharmaceuticals in ozonation using QSAR modeling and their fate in electro-peroxone process

The abatements of 89 pharmaceuticals in secondary effluent by ozonation and the electro-peroxone(E-peroxone)process were investigated.Based on the results,a quantitative structure-activity relationship(QSAR)model was developed to explore relationship between chemical structure of pharmaceuticals and their oxidation rates by ozone.The orthogonal projection to latent structure(OPLS)method was used to identify relevant chemical descriptors of the pharmaceuticals,from large number of descriptors,for model development.The resulting QSAR model,based on 44 molecular descriptors related to the ozone reactivity of the pharmaceuticals,showed high goodness of fit(R^(2)=0.963)and predictive power(Q^(2)=0.84).After validation,the model was used to predict second-order rate constants of 491 pharmaceuticals of special concern(k_(O_(3)))including the 89 studied experimentally.The predicted k_(O_(3))values and experimentally determined pseudo-first order rate constants of the pharmaceuticals’abatement during ozonation(k_(OZ))and the E-peroxone process(k_(EP))were then used to assess effects of switching from ozonation to the E-peroxone process on removal of these pharmaceuticals.The results indicate that the E-peroxone process could accelerate the abatement of pharmaceuticals with relatively low ozone reactivity(k_(O_(3))<∼10^(2)M^(−1)⋅s^(−1))than ozonation(3–10 min versus 5–20 min).The validated QSAR model predicted 66 pharmaceuticals to be highly O_(3)-resistant.The developed QSAR model may be used to estimate the ozone reactivity of pharmaceuticals of diverse chemistry and thus predict their fate in ozone-based processes.