Abstract
Many amino compounds are highly toxic to living organisms and mammals. However, there is the increase of production and the consumption of these compounds annually as well as there is a need to design new amino compounds. A simple method is introduced to predict the toxicity of amino derivatives of organic compounds without using any computer codes, which can be done by prediction of the values of LD50 (lethal dose, 50 %) in rats via oral. It is based on the existence of some molecular moieties that may increase or decrease toxicity of amino derivatives. The predicted results of the new simple model for 58 aliphatic amines and anilines are more reliable than those values obtained by quantitative structure–toxicity relationship methods, where their computed data were available. The predicted results of the new method are also compared with experimental data for further 112 amino derivatives, which show good to excellent agreement.
Similar content being viewed by others
References
H. Greim, D. Bttry, H.-J. Klimisch, M. Oeben-Negele, K. Ziegler-Skylakakis, Toxicity of aliphatic amines: structure-activity relationship. Chemosphere 36, 271 (1998)
B. Rasulev, H. Kusic, D. Leszczynska, J. Leszczynski, N. Koprivanac, QSAR modeling of acute toxicity on mammals caused by aromatic compounds: the case study using oral LD50 for rats. J. Environ. Monit. 12, 1037 (2010)
R. A. Meyers, D. Kender Dittrick, The Wiley Encyclopedia of Environmental Pollution and Cleanup (Wiley, New York, 1999)
W.P. Cunningham, M.A. Cunningham, B. Saigo, Environmental Science, a Global Concern (McGraw-Hill Education, New York, 2005)
M. Sittig, Handbook of toxic and hazardous chemicals and carcinogens, 2nd edn. (Noyes Publications, Park Ridge, 1985)
B. Bukowska, S. Kowalska, The presence and toxicity of phenol derivatives—their effect on human erythrocytes. Curr. Top. Biophys. 27, 43 (2003)
U.S. Environmental Protection Agency. Toxicological review of phenol. EPA/635/R-02/006. In support of summary information on the integrated risk information system (IRIS), 2002
U.S. Environmental Protection Agency. Carcinogenic effects of benzene: an update. EPA/600/P-97/001F. 1998
K. Hayward, Drinking water contaminant hit-list for US EPA, Water 21, September–October, 4, 1998
E. Kriek, in Environmental Carcinogens, ed. by P. Emmelot, E. Kriek (Elsevier, Amsterdam, 1979), pp. 143–164
J. Lavoie, S. Srinivasan, R. Nagarajan, Using cheminformatics to find simulants for chemical warfare agents. J. Hazard. Mater. 194, 85 (2011)
E. Grabińska-Sota, Genotoxicity and biodegradation of quaternary ammonium salts in aquatic environments. J. Hazard. Mater. 195, 182 (2011)
H. Schmitt, R. Altenburger, B. Jastorff, G. Schuurmann, Quantitative structure-activity analysis of the algae toxicity of nitroaromatic compounds. Chem. Res. Toxicol. 13, 441 (2000)
M. Xu, A. Zhang, S. Han, L. Wang, Studies of 3D-quantitative structure-activity relationships on a set of nitroaromatic compounds: CoMFA, advanced CoMFA and CoMSIA. Chemosphere 48, 707 (2002)
O. Isayev, B. Rasulev, L. Gorb, J. Leszczynski, Structure-toxicity relationships of nitroaromatic compounds. Mol. Divers. 10, 233 (2006)
H. Jackel, W. Klein, Prediction of mammalian toxicity by quantitative structure-activity relationships: aliphatic amines and anilines. Quant. Struct. Act. Relat. 10, 198 (1991)
X. Lu, W. Yaping, H. Changyu, L. Hua, A QSAR of the toxicity of amino-benzenes and their structures. Sci. China 43, 129 (2000)
B. Rasulev, H. Kusic, D. Leszczynska, J. Leszczynski, N. Koprivanac, QSAR modeling of acute toxicity on mammals caused by aromatic compounds: the case study using oral LD50 for rats. J. Environ. Monit. 12, 1037 (2010)
M. Khayatzadeh Mahani, M. Chaloosi, M. Ghanadi Maragheh, A.R. Khanchi, D. Afzali, Prediction of Acute in vivo toxicity of some amine and amide drugs to rats by multiple linear regression, partial least squares and an artificial neural network. Anal. Sci. 23, 1091 (2007)
X. Lu, Y. Jiaan, Three-dimensional structural features and the toxicity of aminobenzenes and phenols. Sci. China 46, 431 (2003)
H. Greim, D. Bttry, H.J. Klimisch, M. Oeben-Negele, K.Z. Skylakakis, Toxicity of aliphatic amines: structure–activity relationship. Chemosphere 36, 271 (1998)
R. Gieleciak, J. Polanski, Modeling robust QSAR. 2. iterative variable elimination schemes for CoMSA: application for modeling benzoic acid pKa values. J. Chem. Inf. Model. 47, 547 (2007)
A.P. Freidig, S. Dekkers, M. Verwei, E. Zvinavashe, J.G. Bessems, J.J. van de Sandt, Development of a QSAR for worst case estimates of acute toxicity of chemically reactive compounds. Toxicol. Lett. 170, 214 (2007)
Y.Z. Sun, Z.J. Li, X.L. Yan, L. Wang, F.H. Meng, Study on the quantitative structure-toxicity relationships of benzoic acid derivatives in rats via oral LD50. Med. Chem. Res. 18, 712 (2009)
Z. Li, Y. Sun, X. Yan, F. Meng, Study on QSTR of benzoic acid compounds with MCI. Int. J. Mol. Sci. 11, 1228 (2010)
M.H. Keshavarz, 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, 2012. doi:10.1007/s00044-012-01347-7
M.H. Keshavarz, F. Gharagheizi, A. Shokrolahi, S. Zakinejad, Accurate prediction of the toxicity of benzoic acid compounds in mice via oral without using any computer codes. J. Hazard. Mater. 237–238, 79 (2012)
H.R. Pouretedal, M.H. Keshavarz, Prediction of toxicity of nitroaromatic compounds through their molecular structures. J. Iran. Chem. Soc. 8, 78 (2011)
V.E. Kuz’min, E.N. Muratov, A.G. Artemenko, L. Gorb, M. Qasim, J. Leszczynski, The effect of nitroaromatics’ composition on their toxicity in vivo: Novel, efficient non-additive 1D QSAR analysis. Chemosphere 72, 1373 (2008)
V.E. Kuz’min, E.N. Muratov, A.G. Artemenko, L. Gorb, M. Qasim, J. Leszczynski, The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study. Comput. Aided. Mol. Des. 22, 747 (2008)
W. J. Palm III, Matlab for Engineering Applications (WBC/McGraw-Hill, 1999), p. 339 and p. 227
National Library of Medicine. http://sis.nlm.nih.gov/chemical.html, references for individual molecules are given therein
Acknowledgments
We would like to thank the research committee of Malek-ashtar University of Technology (MUT) for supporting this work.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Pouretedal, H.R., Keshavarz, M.H. & Abbasi, A. A new approach for accurate prediction of toxicity of amino compounds. J IRAN CHEM SOC 12, 487–502 (2015). https://doi.org/10.1007/s13738-014-0506-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13738-014-0506-7