An assessment of mutagenicity of chemical substances by (quantitative) structure–activity relationship

Abstract

Currently, there are more than 100,000 industrial chemicals substances produced and present in our living environments. Some of them may have adverse effects on human health. Given the rapid expansion in the number of industrial chemicals, international organizations and regulatory authorities have expressed the need for effective screening tools to promptly and accurately identify chemical substances with potential adverse effects without conducting actual toxicological studies. (Quantitative) Structure-Activity Relationship ((Q)SAR) is a promising approach to predict the potential adverse effects of a chemical on the basis of its chemical structure. Significant effort has been devoted to the development of (Q) SAR models for predicting Ames mutagenicity, among other toxicological endpoints, owing to the significant amount of the necessary Ames test data that have already been accumulated. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) M7 guideline for the assessment and control of mutagenic impurities in pharmaceuticals was established in 2014. It is the first international guideline that addresses the use of (Q) SAR instead of actual toxicological studies for human health assessment. Therefore, (Q) SAR for Ames mutagenicity now require higher predictive power for identifying mutagenic chemicals. This review introduces the advantages and features of (Q)SAR. Several (Q) SAR tools for predicting Ames mutagenicity and approaches to improve (Q) SAR models are also reviewed. Finally, I mention the future of (Q) SAR and other advanced in silico technology in genetic toxicology.

Screening for Ames mutagenicity of food flavor chemicals by (quantitative) structure-activity relationship

“…These results implied that the application of (Q) SAR tools to assess the Ames mutagenicity of flavor chemicals was still premature. In recent years, however, the prediction power of Ames (Q) SAR tools has improved [ 8 ]. Honma et al conducted the Ames/(Q) SAR International Challenge Project with 12 (Q) SAR vendors to validate and improve the Ames mutagenicity prediction of their tools from 2014 to 2017 [ 20 ].…”

“…(Quantitative) Structure-Activity Relationship ((Q)SAR) is a promising approach to predict the potential adverse effects of chemicals based on their structure without performing toxicological studies [ 7 ]. Much effort has been invested in the development of (Q) SAR tools to predict Ames mutagenicity (among other toxicological endpoints) because of the large amounts of Ames test data that have already been accumulated [ 8 ]. The International Council for Harmonization of Pharmaceutical Regulations (ICH) M7 guideline, “Assessment and control of DNA reactive (mutagenic) impurities in pharmaceuticals to limit potential carcinogenic risk” approved (Q) SAR methodologies as an alternative to the Ames test to evaluate the mutagenicity of impurities [ 9 ].…”

Report of the Joint Meeting of the 6th Asian Congress on Environmental Mutagens and the 48th Annual Meeting of the Japanese Environmental Mutagen Society, Tokyo, November 18–20, 2019

“…In the field of genetic toxicology, an International Council for Harmonization of Pharmaceutical Regulations (ICH) guideline approved quantitative structure-activity relationship (QSAR) approaches to evaluate the mutagenicity of impurities as an alternative to the Ames test. This guideline has triggered growing interest in QSAR [ 1 ]. Dr. Romualdo Benigni from Italy thus delivered a keynote lecture on the subject, and a subsequent workshop was held.…”

Development of a new quantitative structure–activity relationship model for predicting Ames mutagenicity of food flavor chemicals using StarDrop™ auto-Modeller™

“…Additionally, the peculiar odor of some flavors sometimes makes it difficult to perform the test in the laboratory. Recently, quantitative structure–activity relationship (QSAR) approaches instead of the Ames test have been frequently used for assessing the mutagenicity of chemicals [ 3 ]. Ono et al assessed the viability of QSAR tools by using three QSAR tools to calculate the Ames mutagenicity of 367 flavor chemicals (for which Ames test results were available) [ 4 ].…”