Comparative QSTR studies for predicting mutagenicity of nitro compounds

Mutagenicity and carcinogenicity are toxicological endpoints which pose a great concern being the major determinants of cancers and tumours. Nitroarenes possess genotoxic properties as they can form various electrophilic intermediates and adducts with biological systems. Different QSTR techniques were employed to develop models for the prediction of mutagenicity of nitroarenes using a diverse set of 197 nitro aromatic and hetero aromatic molecules. The 2D and 3D QSTR methods used for model development gave statistically significant results. The alignment for 3D methods was obtained by maximum common substructures (MCS) approach, by taking the most mutagenic molecule of the dataset as the template. All the QSTR models were developed with the same set of training and test set molecules. The 3D contours and 2D contribution maps along with molecular fingerprints provide useful information about the mutagenic potentials of the molecules. The GFA based model shows thermodynamic and topological descriptors play an important role in characterizing mutagenicity of nitroarenes. Atomic-level thermodynamic descriptor namely AlogP throws light on hydrophobic features and helps to understand the bilinear model. Topological aspects of these classes of compounds were depicted by the fragment fingerprints and Balaban indices obtained from HQSAR and GFA models, respectively. The predictive abilities of 2D and 3D QSTR models may be useful as a vibrant predictive tool to screen out mutagenic nitroarenes and design safer non-mutagenic nitro compounds.