Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project

ABSTRACT

Quantitative structure−activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR models for regulatory use should demonstrate high sensitivity, low false-negative rate and wide coverage of chemical space. To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences, Japan (DGM/NIHS), conducted the Second Ames/QSAR International Challenge Project (2020–2022) as a successor to the First Project (2014–2017), with 21 teams from 11 countries participating. The DGM/NIHS provided a curated training dataset of approximately 12,000 chemicals and a trial dataset of approximately 1,600 chemicals, and each participating team predicted the Ames mutagenicity of each trial chemical using various Ames/QSAR models. The DGM/NIHS then provided the Ames test results for trial chemicals to assist in model improvement. Although overall model performance on the Second Project was not superior to that on the First, models from the eight teams participating in both projects achieved higher sensitivity than models from teams participating in only the Second Project. Thus, these evaluations have facilitated the development of QSAR models.

KEYWORDS:

• Ames mutagenicity prediction
• ANEI-HOU new chemical
• sensitivity
• Ames/QSAR International Challenge Projects
• imbalanced toxicity data
• model performance

Acknowledgments

The authors report there are no competing interests to declare. The authors express their gratitude to the Chemical Hazards Control Division, Industrial Safety and Health Department, MHLW, for allowing us to use ANEI-HOU Ames data in these projects. The authors express their acknowledgement to Dr. Toshio Kasamatsu for Ames data curation. This article reflects the views of the authors and does not necessarily reflect those of the U.S. Food and Drug Administration.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed at: https://doi.org/10.1080/1062936X.2023.2284902.

Additional information

Funding

This work was supported by the Ministry of Health, Labour and Welfare (MHLW) of Japan grant numbers H27-Chemistry-Designation-005, H28-Food-General-001 and H30-Chemistry-Destination-005, [21KD2005 and 21KA1001].