SAR genotoxicity and tumorigenicity predictions for 2-MI and 4-MI using multiple SAR software

Abstract

Context: Caramel coloring chemicals, 2-methylimidazole (2-MI) and 4-methylimidazole (4-MI) have been used extensively in coloring soft drinks. The health effects of these chemicals have been concerned in the recent years.

Objective: In the present investigation, 2- and 4-MI were subjected to three commonly used structure–activity relationship (SAR) software to understand the utility of such software as a method of alternatives to animal testing in predicting potential genotoxicity and tumorigenicity.

Materials and methods: Three SAR software: Osiris, ToxTree and DEREK, were used. Published procedures and/or manuals of respective software were utilized to generate data outputs and the data were evaluated in comparison with available toxicological data on 2- and 4-MI.

Results: The results show that these software predicted genotoxic activity in comparison with published genotoxicity for 2- and 4-MI. However, only one of three software used (Osiris) predicted imidazole ring in 4-MI to be tumorigenic; other software predicted them to be negative.

Discussion: Based on the weight of evidence of SAR results observed in this study and the genotoxicity and tumorigenicity reported using actual in vitro and in vivo animal testing in literature, it was concluded that the models used are useful for routine screening of chemicals; however, for better prediction, additional models may be employed. Software’s ability to predict health effects depends on the type of structural alerts used as knowledgebase in developing such software.

Conclusion: Three computational software used in this study predicted genotoxic activity of 2- and 4-MI, but did not predict tumorigenicity conclusively when compared to literature reported animal data. Additional mechanistic non-clinical studies may be conducted to better understand reported tumorigenicity.

• 2-methylimidazole
• 4-methylimidazole
• DEREK
• genotoxicity
• in silico computational models
• Osiris
• ToxTree
• tumorigenicity

Acknowledgements

Kavya Krishna appreciates the opportunity to present these data in the form of a poster at the 2011 Society of Toxicology annual meeting in Washington DC.