ABSTRACT
Quantitative structure-activity relationship studies were performed to describe and predict the mutagenic activity of a set of 48 nitrated polycyclic aromatic hydrocarbons. From a larger pool of molecular descriptors (topological indices) we arrived at much a smaller set consisting of three correlating parameters. Such a variable selection is made using ncss software in that successive regressions were attempted using maximum-R(2) method. The results are critically discussed using a variety of statistical parameters. Our results have shown that connectivity and shape type indices together with the distance-based Wiener index (W) play a dominating role in modelling of mutagenicity (logTA100). The predictive ability of the models is discussed on the basis of cross-validated parameters.
