Ant colony optimization as a descriptor selection in QSPR modeling for prediction of λmax of azo dyes

A quantitative structure–property relationship (QSPR) study was suggested for the prediction of λmax of azo dyes. After optimization of 3D geometry of structures, different descriptors were calculated by the HyperChem and Dragon softwares. A major problem of QSPR is the high dimensionality of the descriptor space; therefore, descriptor selection is the most important step for these studies. In this paper, an ant colony optimization (ACO) algorithm was proposed to select the best descriptors.