PREDICTION OF RATE CONSTANTS FOR NITRATE RADICAL REACTIONS USING A SVM MODEL BASED ON DENSITY FUNCTIONAL THEORY

In the present paper, support vector machines (SVMs) are used to develop a quantitative structure-activity relationships (QSAR) model for the reaction rate constants (-logk NO3 ) of 115 heterogeneous organic compounds, through reaction with nitrate radicals (NO 3• ) in the troposphere.Two quantum chemical descriptors used as the inputs for the SVM model were calculated with density functional theory (DFT), at the B3LYP level of theory with 6-31G(d) basis set.The best predictions were obtained with the Gaussian radical basis kernel (C = 4, ε =0.15 and γ =3).The average root-mean square (RMS) error for the prediction of k NO3 is 0.502 log units, indicating good robustness and predictive ability.The SVM model, reported here, shows better statistical characteristics compared to existing QSAR models.