Predicting Carcinogenicity of Anilines by Quantitative Structure-Toxicity Relationship

Zhi Xiang Zhou; Yang Hua Liu; Xiao Long Zhang

doi:10.4028/www.scientific.net/AMM.665.559

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 665Predicting Carcinogenicity of Anilines by...

Predicting Carcinogenicity of Anilines by Quantitative Structure-Toxicity Relationship

Abstract:

Carcinogenicity is an important toxicological endpoint which poses a great concern being the major determinants of cancers and tumours. Anilines possess such toxic properties as they can form various electrophilic intermediates and adducts with biological systems. In the present work, the molecular descriptors of anilines have been calculated with semi-empirical AM1 and E-dragon methods, and a quantitative structure–toxicity relationships (QSTR) model for carcinogenic potency (pTD₅₀) model of anilines was developed with multiple linear regression (MLR) analysis. The validation results through the test set indicate that the proposed model is robust and satisfactory. The QSTR study suggests that the molecular structure and the electronegativity of chemicals are closely related to the Carcinogenicity.

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Periodical:

Applied Mechanics and Materials (Volume 665)

Pages:

559-562

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.665.559

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Online since:

October 2014

Authors:

Zhi Xiang Zhou*, Yang Hua Liu, Xiao Long Zhang

Keywords:

Anilines, Carcinogenic Potency (pTD₅₀), Carcinogenicity, MLR, Quantitative Structure Toxicity Relationship (QSTR)

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References

[1] Z. Rappoport, Patai series, The Chemistry of Anilines, Wiley, 2007, p.1180.

Google Scholar

[2] Pramosd C. Nair, M. Elizabeth Sobhia, Comparative QSTR studies for predicting mutagenicity of Anilines, Journal of Molecular Graphics and Modeling. 26 (2008) 916-934.

DOI: 10.1016/j.jmgm.2007.06.006

Google Scholar

[3] Sun, Y.Z., Yan, X.L., Li, Z.J., et al., Application of Chemical Models in Toxicological Study, Chinese J. Environ. Health. 24 (2007) 734–736.

Google Scholar

[4] YAN xiu-Fen, XIAO He-Ming, QSAR Study of Anilines' Toxicity to Tetrahymena Pyriformis Using Semi-empirical Quantum Chemical Methods, Chinese J. Struct. Chem. 1 (2007) 7-14.

Google Scholar

[5] M. K. Leong, S. W. Lin, H. B. Chen, et al., Predicting mutagenicity of aromatic amines by various machine learning approaches, Toxicological Sciences. 116 (2010) 498-513.

DOI: 10.1093/toxsci/kfq159

Google Scholar