Computational assessment of environmental hazards of nitroaromatic compounds: influence of the type and position of aromatic ring substituents on toxicity
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This study summarizes the results of our recent QSAR and QSPR investigations on prediction of numerous aspects of environmental behavior of nitro compounds. In this study, we applied the QSAR/QSPR models previously developed by our group for virtual screening of energetic compounds, their precursors and other compounds containing nitro groups. To make predictions on the environmental impact of nitro compounds, we analyzed the trends in the change of the experimentally obtained and QSAR/QSPR-predicted values of aqueous solubility, lipophilicity, Ames mutagenicity, bioavailability, blood–brain barrier penetration, aquatic toxicity on T. pyriformis and acute oral toxicity on rats as a function of chemical structure of nitro compounds. All the models were developed using simplex descriptors in combination with random forest (RF) modeling techniques. We interpreted the possible environmental impact (different toxicological properties) in terms of dividing considered nitro compounds based on hydrophobic and hydrophilic characteristics and in terms of the influence of their molecular fragments that promote and interfere with toxicity. In particular, we found that, in general, the presence of amide or tertiary amine groups leads to an increase in toxicity. Also, it was predicted that compounds containing a NO2 group in the para-position of a benzene ring are more toxic than meta-isomers, which, in turn, are more toxic than ortho-isomers. In general, we concluded that hydrophobic nitroaromatic compounds, especially the ones with electron-accepting substituents, halogens and amino groups, are the most environmentally hazardous.
KeywordsNitroaromatic xenobiotics Acute toxicity SiRMS Virtual screening
We thank ERDC for financial support (grant number W912HZ-13-P-0037). The computation time was provided by the Extreme Science and Engineering Discovery Environment (XSEDE) by National Science Foundation Grant Number OCI-1053575 and XSEDE award allocation Number DMR110088 and by the Mississippi Center for Supercomputer Research. EM is grateful for financial support from the US National Institutes of Health (GM 096967 and GM66940). The use of trade, product or firm names in this report is for descriptive purposes only and does not imply endorsement by the US Government. Results in this study were funded and obtained from research conducted under the Environmental Quality Technology Program of the United States Army Corps of Engineers by the US Army ERDC. Permission was granted by the Chief of Engineers to publish this information. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents.
- 2.Donlon BA, Razo-Flores E, Field JA, Lettinga G (1995) Toxicity of N-substituted aromatics to acetoclastic methanogenic activity in granular sludge. Appl Environ Microbiol 61:3889–3893Google Scholar
- 3.Nemeikaitė-Čėnienė A, Miliukienė V, Šarlauskas V, Maldutis E, Čėnas N (2006) Chemical aspects of cytotoxicity of nitroaromatic explosives: a review. Chemija 17:34–41Google Scholar
- 5.Donlon BA, Razo-Flores E, Field JA, Lettinga G (1995) Toxicity of N-substituted aromatics to acetoclastic methanogenic activity in granular sludge. Appl Environ Microbiol 61:3889–3893Google Scholar
- 9.Ayyapan G (2013) Chemo Informatics QSAR analysis of nitroaromatic compounds toxicity. Int J Innov Res Sci En Technol 2(2):372–375Google Scholar
- 11.Elidrissi B, Ousaa A, Ghamalia M, Chtitaa S, Ajanaa MA, Bouachrineb M, Lakhlifia T (2014) Toxicity in vivo of nitro-aromatic compounds: DFT and QSAR results. J Comput Aided Mol Des 4(3):28–37Google Scholar
- 13.Muratov EN, Artemenko AG, Kuz’min AG, Lozitsky VE, Fedchuk VP, Lozytska AS, Boschenko RN, Gridina YA (2005) Investigation of anti-influenza activity using hierarchic QSAR technology on the base of simplex representation of molecular structure. Antiv Res 65:A62–A63Google Scholar
- 22.Golovenko NYA, Kuz’min VE, Artemenko AG et al (2011) Prediction of bioavailability of drugs by the method of classification models. J Klin Inform Telemed 7:88–92Google Scholar
- 23.Kosinskaya AP, Ognichenko LN, Polishchuk PG, Kuz’min VE (2014) Structural and functional interpretation of 2D QSAR models of structure-blood-brain barrier permeability relationship of organic compounds. In: Abstracts of the 20th international conference on EuroQSAR (understanding chemical–biological interactions). St-Petersburg, Russia, 31 Aug–Sep 4, 2014, p 147Google Scholar
- 24.Tinkov OV, Polishchuk PG, Artemenko AG, Kuz’min VE (2012) The investigation of acute toxicity and physical-chemical properties of organic compounds. J Sib Fed Univ 5:95–104Google Scholar
- 26.Heytler PG (1979) Uncouplers of oxidative phosphorylation. Methods Enzymol 55:442–462Google Scholar
- 27.Nelson DL, Cox MM (2000) Lehniger principles of biochemistry. Worth Publishers, New YorkGoogle Scholar