• Nilesh Tawari Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Matunga (E), Mumbai 400019, India.
  • Arundhati Lele Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Matunga (E), Mumbai 400019, India.
  • Mihir Khambete Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Matunga (E), Mumbai 400019, India.
  • Mariam Degani Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Matunga (E), Mumbai 400019, India.


Nitroaromatic, Mutagenicity, Molecular electrostatic profile (MESP), lowest unoccupied molecular orbital (LUMO), Quantitative Structure Toxicity Relationship (QSTR)


Objective: Nitroaromatic compounds are important industrial chemicals widely used in the synthesis of many diverse products including drugs, dyes, polymers, pesticides and explosives. However, the mutagenicity associated with nitroaromatic compounds is a toxicological feature which poses great concern. On the other hand, there are successful examples of non-mutagenic nitroaromatic molecules; indicating that safer nitroaromatic compounds can be developed. In this light the aim of the present work was to predict the mutagenicity of nitroaromatic compounds using an atom based QSTR model.

Methods: An atom based QSTR model was developed using PHASE. In addition, molecules were studied by complete geometry optimization using DFT at B3LYP/3-21G* level of theory.

Results: An atom based QSTR model was generated for prediction of mutagenicity of the compounds.

Conclusion: The visualization of different properties highlighted key inferences. These include the likelihood of mutagenicity for the molecules with more fused planar hydrophobic rings having hydrogen bond acceptor and electron donating substitutions. Also, all highly mutagenic compounds have two or more negative potential regions. Specific electronic properties such as HOMO and LUMO indicate that most of the mutagenic molecules are very reactive in nature. The results of this study would be useful as a predictive tool to screen out mutagenic nitroarenes and design safer non-mutagenic nitro compounds.


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How to Cite

Tawari, N., A. Lele, M. Khambete, and M. Degani. “MUTAGENICITY PREDICTION FOR NITROAROMATIC COMPOUNDS USING QSTR MODELING”. International Journal of Pharmacy and Pharmaceutical Sciences, vol. 6, no. 7, July 2014, pp. 149-57,



Original Article(s)