Prediction of the maximum absorption wavelength of azobenzene dyes by QSPR tools

The maximum absorption wavelength (λ(max)) of a large data set of 191 azobenzene dyes was predicted by quantitative structure-property relationship (QSPR) tools. The λ(max) was correlated with the 4 molecular descriptors calculated from the structure of the dyes alone. The multiple linear regression method (MLR) and the non-linear radial basis function neural network (RBFNN) method were applied to develop the models. The statistical parameters provided by the MLR model were R(2)=0.893, R(adj)(2)=0.893, q(LOO)(2)=0.884, F=1214.871, RMS=11.6430 for the training set; and R(2)=0.849, R(adj)(2)=0.845, q(ext)(2)=0.846, F=207.812, RMS=14.0919 for the external test set. The RBFNN model gave even improved statistical results: R(2)=0.920, R(adj)(2)=0.919, q(LOO)(2)=0.898, F=1664.074, RMS=9.9215 for the training set, and R(2)=0.895, R(adj)(2)=0.892, q(ext)(2)=0.895, F=314.256, RMS=11.6427 for the external test set. This theoretical method provides a simple, precise and an alternative method to obtain λ(max) of azobenzene dyes.