The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants

Abstract

In advanced water treatment processes, the degradation efficiency of contaminants depends on the reactivity of the hydroxyl radical toward a target micropollutant. The present study predicts the hydroxyl radical rate constant in water (k _OH) for 118 emerging micropollutants, by means of quantitative structure-property relationships (QSPR). The conformation-independent QSPR approach is employed, together with a large number of 15,251 molecular descriptors derived with the PaDEL, Epi Suite, and Mold2 freewares. The best multivariable linear regression (MLR) models are found with the replacement method variable subset selection technique. The proposed five-descriptor model has the following statistics for the training set: \( {R}_{\mathrm{train}}^2=0.88 \) , RMS _train = 0.21, while for the test set is \( {R}_{\mathrm{test}}^2=0.87 \) , RMS _test = 0.11. This QSPR serves as a rational guide for predicting oxidation processes of micropollutants.