The effect of nitroaromatics’ composition on their toxicity in vivo: Novel, efficient non-additive 1D QSAR analysis

• Published in: Chemosphere (Oxford) Vol. 72; no. 9; pp. 1373 - 1380
• Main Authors: Kuz’min, V.E., Muratov, E.N., Artemenko, A.G., Gorb, L., Qasim, M., Leszczynski, J.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.07.2008; Elsevier
• Subjects: Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Ecotoxicology, biological effects of pollution; Fundamental and applied biological sciences. Psychology; General aspects; Hydrocarbons, Aromatic - chemistry; Hydrocarbons, Aromatic - toxicity; Models, Molecular; Nitro Compounds - chemistry; Nitro Compounds - toxicity; Nitroaromatic compounds; QSAR; Quantitative Structure-Activity Relationship; SiRMS; Toxicity in vivo; SiRMS; Toxicity in vivo; QSAR; Nitroaromatic compounds; In vivo; Additive; Ecotoxicology; Structure activity relation; Toxicity; Toxicity in vivo,Nitroaromatic compounds; Property structure relationship
• ISSN: 0045-6535; 1879-1298
• DOI: 10.1016/j.chemosphere.2008.04.045

Novel 1D QSAR approach that allows analysis of non-additive effects of molecular fragments on toxicity has been proposed. Twenty-eight nitroaromatic compounds including some well-known explosives have been chosen for this study. The 50% lethal dose concentration for rats (LD 50) was used as the estimation of toxicity in vivo to develop 1D QSAR models on the framework of Simplex representation of molecular structure. The results of 1D QSAR analysis show that even the information about the composition of molecules provides the main trends of toxicity changes. The necessity of consideration of substituents’ mutual impacts for the development of adequate QSAR models of nitroaromatics’ toxicity was demonstrated. Statistic characteristics for all the developed partial least squares QSAR models, except the additive ones are quite satisfactory ( R 2 = 0.81–0.92; Q 2 = 0.64–0.83; R test 2 = 0.84 - 0.87 ). A successful performance of such models is due to their non-additivity i.e. possibility of taking into account the mutual influence of substituents in benzene ring which plays the governing role for toxicity change and could be mediated through the different C–H fragments of the ring. The correspondence between observed and predicted by these models toxicity values is good. This allowing combine advantages of such approaches and develop adequate consensus model that can be used as a toxicity virtual screening tool.