A simple approach for assessment of toxicity of nitroaromatic compounds without using complex descriptors and computer codes

References

• J.P. Agrawal, High Energy Materials: Propellants, Explosives and Pyrotechnics, Wiley-VCH, Cornwall, UK, 2010.
   Google Scholar
• M.H. Keshavarz and T.M. Klapötke, Energetic Compounds: Methods for Prediction of their Performance, Walter de Gruyter GmbH & Co KG, Berlin/Boston, 2017.
   Google Scholar
• M.H. Keshavarz and T.M. Klapötke, The Properties of Energetic Materials: Sensitivity, Physical and Thermodynamic Properties, Walter de Gruyter GmbH & Co KG, Berlin/Boston, 2017.
   Google Scholar
• M.H. Keshavarz, T.M. Klapötke, and M. Sućeska, Energetic materials designing bench (EMDB), Version 1.0, Propel. Explos. Pyrotech. 42 (2017), pp. 854–856.
   Google Scholar
• T.M. Klapötke, Chemistry of High-Energy Materials, 4th ed., Walter de Gruyter GmbH & Co KG, Germany, 2017.
   Google Scholar
• T.M. Klapötke, Energetic Materials Encyclopedia, Walter de Gruyter GmbH & Co KG, Berlin/Boston, 2018.
   Google Scholar
• S. Zeman and M. Jungová, Sensitivity and performance of energetic materials, Propel. Explos. Pyrotech. 41 (2016), pp. 426–451.
   Web of Science ®Google Scholar
• M.H. Keshavarz, Combustible Organic Materials: Determination and Prediction of Combustion Properties, Walter de Gruyter GmbH & Co KG, Berlin/Boston, 2018.
   Google Scholar
• D.E. Rickert, Toxicity of Nitroaromatic Compounds, Hemisphere Publishing Corporation, Washington, 1985.
   Google Scholar
• N. Čėnas, A. Nemeikaitė-Čėnienė, E. Sergedienė, H. Nivinskas, Ž. Anusevičius, and J. Šarlauskas, Quantitative structure–activity relationships in enzymatic single-electron reduction of nitroaromatic explosives: Implications for their cytotoxicity, BBA-General Subjects. 1528 (2001), pp. 31–38.
   Google Scholar
• H. Schmitt, R. Altenburger, B. Jastorff, and G. Schüürmann, Quantitative structure−activity analysis of the algae toxicity of nitroaromatic compounds, Chem. Res. Toxicol. 13 (2000), pp. 441–450.
   PubMed Web of Science ®Google Scholar
• S.S. Talmage, D.M. Opresko, C.J. Maxwell, C.J.E. Welsh, F.M. Cretella, P.H. Reno, and F.B. Daniel, Nitroaromatic munition compounds: Environmental effects and screening values, Rev. Environ. Contam. Toxicol. 161(1999), pp. 1–156.
   Google Scholar
• X. Wang, Z. Lin, D. Yin, S. Liu, and L. Wang, 2D/3D-QSAR comparative study on mutagenicity of nitroaromatics, Sci. China, Ser. B, Chem. 48 (2005), pp. 246–252.
   Google Scholar
• O. Mekenyan, D.W. Roberts, and W. Karcher, Molecular orbital parameters as predictors of skin sensitization potential of halo-and pseudohalobenzenes acting as SNAr electrophiles, Chem. Res. Toxicol. 10 (1997), pp. 994–1000.
   PubMed Web of Science ®Google Scholar
• B. Bukowska and S. Kowalska, The presence and toxicity of phenol derivatives-their effect on human erythrocytes, Curr. Top. Biophys. 27 (2003), pp. 43–51.
   Google Scholar
• W.P. Cunningham, B.W. Saigo, and M.A. Cunningham, Environmental Science: A Global Concern Vol. 412, McGraw-Hill, Boston, MA, 2001.
   Google Scholar
• G. Hakimelahi and G. Khodarahmi, The identification of toxicophores for the prediction of mutagenicity, hepatotoxicity and cardiotoxicity, J. Iran. Chem. Soc. 2 (2005), pp. 244–267.
   Web of Science ®Google Scholar
• M.H. Keshavarz and H.R. Pouretedal, Simple and reliable prediction of toxicological activities of benzoic acid derivatives without using any experimental data or computer codes, Med. Chem. Res. 22 (2013), pp. 1238–1257.
   Google Scholar
• M.H. Keshavarz, F. Gharagheizi, A. Shokrolahi, A. Shokrolahi, and S. Zakinejad, Accurate prediction of the toxicity of benzoic acid compounds in mice via oral without using any computer codes, J. Hazard. Mater. 237 (2012), pp. 79–101.
   PubMed Web of Science ®Google Scholar
• H.R. Pouretedal, M.H. Keshavarz, and A. Abbasi, A new approach for accurate prediction of toxicity of amino compounds, J. Iran. Chem. Soc. 12 (2015), pp. 487–502.
   Web of Science ®Google Scholar
• R. Veerasamy, H. Rajak, A. Jain, S. Sivadasan1, C.P. Varghese1, and R.K. Agrawal, Validation of QSAR models-strategies and importance, Int. J. Drug Des. Disc. 3 (2011), pp. 511–519.
   Google Scholar
• A. Gooch, N. Sizochenko, B. Rasulev, L. Gorb, and J. Leszczynski, In vivo toxicity of nitroaromatics: A comprehensive quantitative structure–activity relationship study, Environ. Toxicol. Chem. 36 (2017), pp. 2227–2233.
   PubMed Web of Science ®Google Scholar
• O. Isayev, B. Rasulev, L. Gorb, and J. Leszczynski, Structure-toxicity relationships of nitroaromatic compounds, Molec. Divers. 10 (2006), pp. 233–245.
   PubMed Web of Science ®Google Scholar
• C. Selassie and R.P. Verma, History of quantitative structure–activity relationships, Burger’s Medicinal Chemistry and Drug Discovery, Sixth Edition, Volume 1: Drug Discovery, Edited by Donald J. Abraham,  John Wiley & Sons, Inc., New York, 2003, pp. 1–96.
   Google Scholar
• V.E. Kuz’min, E.N. Muratov, A.G. Artemenko, M. Qasim, and J. Leszczynski, The effect of nitroaromatics’ composition on their toxicity in vivo: Novel, efficient non-additive 1D QSAR analysis, Chemosphere 72 (2008), pp. 1373–1380.
   Google Scholar
• M. Cronin, B. Gregory, and T. Schultz, Quantitative structure−activity analyses of nitrobenzene toxicity to Tetrahymena pyriformis, Chem. Res. Toxicol. 11 (1998), pp. 902–908.
   PubMed Web of Science ®Google Scholar
• V.E. Kuz’min, E.N. Muratov, A.G. Artemenko, L. Gorb, M. Qasim, and J. Leszczynski, The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study, J. Comput.-aided Molec. Des. 22 (2008), pp. 747.
   PubMed Web of Science ®Google Scholar
• X.F. Yan, H.M. Xiao, X.D. Gong, and X.H. Ju, Quantitative structure–activity relationships of nitroaromatics toxicity to the algae (Scenedesmus obliguus), Chemosphere 59 (2005), pp. 467–471.
   Google Scholar
• L. Su, X. Zhang, X. Yuan, Y. Zhao, D. Zhang, and W. Qin, Evaluation of joint toxicity of nitroaromatic compounds and copper to Photobacterium phosphoreum and QSAR analysis, J. Hazard. Mater. 241 (2012), pp. 450–455.
   PubMed Web of Science ®Google Scholar
• H.R. Pouretedal and M.H. Keshavarz, Prediction of toxicity of nitroaromatic compounds through their molecular structures, J. Iran. Chem. Soc. 8 (2011), pp. 78–89.
   Web of Science ®Google Scholar
• A.G. Artemenko, E.N. Muratov, V.E. Kuz’min, N.N. Muratov, E.V. Varlamova, A.V. Kuz‘mina, L.G. Gorb, A. Golius, F.C. Hill, J. Leszczynski, and A. Tropsha, QSAR analysis of the toxicity of nitroaromatics in Tetrahymena pyriformis: Structural factors and possible modes of action, SAR QSAR Environ. Res. 22 (2011), pp. 575–601.
   Google Scholar
• X.F. Yan, H.M. Xiao, X.D. Gong, and X.H. Ju, A comparison of semiempirical and first principle methods for establishing toxicological QSARs of nitroaromatics, J. Molec. Struc. THEOCHEM. 764 (2006), pp. 141–148.
   Web of Science ®Google Scholar
• K. Roy and P.L.A. Popelier, Exploring predictive QSAR models using quantum topological molecular similarity (QTMS) descriptors for toxicity of nitroaromatics to Saccharomyces cerevisiae, QSAR Comb. Sci. 27 (2008), pp. 1006–1012.
   Web of Science ®Google Scholar
• V. Agrawal and P. Khadikar, QSAR prediction of toxicity of nitrobenzenes, Bioorg. Med. Chem. 9 (2001), pp. 3035–3040.
   Web of Science ®Google Scholar
• A. Niazi, S. Jameh-Bozorghi, and D. Nori-Shargh, Prediction of toxicity of nitrobenzenes using ab initio and least squares support vector machines, J. Hazard. Mater. 151 (2008), pp. 603–609.
   PubMed Web of Science ®Google Scholar
• TOXNET-ChemIDplus USNLoM, 2018; software available at: https://chem.nlm.nih.gov/chemidplus/chemidlite.jsp.
   Google Scholar
• Kode SRI. Dragon (Software for Molecular Descriptor Calculation) version 7.0, 2017; software available at: http://chm.kode-solutions.net.
   Google Scholar
• A.A. Toropov, B.F. Rasulev, and J. Leszczynski, QSAR modeling of acute toxicity for nitrobenzene derivatives towards rats: Comparative analysis by MLRA and optimal descriptors, QSAR Comb. Sci. 26 (2007), pp. 686–693.
   Web of Science ®Google Scholar
• W.J. Palm, Introduction to MATLAB 7 for Engineers. McGraw-Hill, New York, 2005.
   Google Scholar
• C. Nantasenamat, C. Isarankura-Na-Ayudhya, and V. Prachayasittikul, Advances in computational methods to predict the biological activity of compounds, Expert. Opin. Drug Disc. 5 (2010), pp. 633–654.
   PubMed Web of Science ®Google Scholar
• K. Ulm, Screening results on the toxicity of numerous fluoro organic compounds, J. Fluorine Chem. 21 (1982), p. 69.
   Web of Science ®Google Scholar
• A.R. Leach and V.J. Gillet, An Introduction to Chemoinformatics, Springer, The Netherlands, 2007.
   Google Scholar
• P. Gramatica and A. Sangion, A historical excursus on the statistical validation parameters for QSAR models: A clarification concerning metrics and terminology, J. Chem. Info. Model. 56 (2016), pp. 1127–1131.
   PubMed Web of Science ®Google Scholar
• P. Gramatica, Principles of QSAR models validation: Internal and external, QSAR Comb. Sci. 26 (2007), pp. 694–701.
   Web of Science ®Google Scholar