Quantitative structure-lambda(max) relationship study on flavones by heuristic method and radial basis function neural network.

QSPR models for the prediction of UV maximum absorption wavelength (lambda(max)) of 69 flavones were developed based on their structures alone. A six-descriptor linear correlation by heuristic method (HM) and a nonlinear model using radial basis function neural network (RBFNN) approach were reported. The statistical parameters provided by the HM model (R2=0.961, F=207.820, RMS=6.555 for the training set and R2=0.967, F=293.218, RMS=7.176 for the test set) and the RBFNN model (R2=0.971, F=1826.086, RMS=5.350 for the training set, and R2=0.978, F=452.512, RMS=5.722 for the test set) indicated satisfactory stability and predictive ability. The descriptors appearing in these models are discussed. This QSPR approach is suitable for the prediction of maximum absorption wavelength of flavones, and can contribute to a better understanding of structural factors of the organic compounds responsible for it.