Quantitative Structure-Electrochemistry Relationship Study for Prediction of Half-Wave Reduction Potentials of Some Chlorinated Organic Compounds by Genetic Algorithm-Multiple Linear Regression - Mohammadhossein, Majid; Nekoei, Mehdi (Asian Journal of Chemistry, 2012)
Quantitative structure-electrochemistry relationship model has been used to predict and explain half-wave reduction potentials (E1/2). This method allows for the prediction of E1/2s in a variety of organic compounds based on their structures alone. Genetic algorithm-multiple linear regression (GA-MLR) was performed to build the model. The proposed methodology was validated using leave-one-out and leave-group-out cross validation using division of the available data set into training and test sets. The results illustrated that the linear techniques such as multiple linear regression combined with a successful variable selection procedure like GA are capable to generate an efficient quantitative structure-electrochemistry relationship model for predicting the E1/2s of different compounds. A model with low prediction error and good correlation coefficient was obtained (R2calibration = 0.923, R2prediction = 0.940, Q2LOO = 0.810, Q2LGO = 0.803, R2adj = 0.889, RMSEP = 0.203). This model was used for the prediction of the E1/2 values of some organic compounds, which were not used in the modeling procedure.