Read-across for the prediction of genotoxicity of dimethenamid-P groundwater metabolites: A case study using synthetic chemistry and computational toxicology.

This work presents a read-across case study to predict the genotoxicity of two previously untested groundwater metabolites of dimethenamid-P (α-chloroacetamide herbicide). Due to synthesis challenges, direct testing of the metabolites was not feasible. Structural space alerts and matched molecular pairs analysis were employed to identify analogues and assess structural features. These analyses indicated that these features were not associated with genotoxicity. However, neither method provided evidence regarding the genotoxic potential of the lactone/hemiacetal moiety unique to the metabolites. To address this data gap, a surrogate compound containing the relevant moiety was synthesised and tested negative for genotoxicity. Computational profiling and metabolic simulation further demonstrated structural and metabolic similarity between the surrogate and the target metabolites. This work shows that structural data gaps can be resolved through the synthesis of a surrogate compound combined with experimental toxicological data. The integrated weight of evidence from synthetic and computational chemistry supports the conclusion that the two dimethenamid-P groundwater metabolites are unlikely to be genotoxic. Overall, this study demonstrates that the use of synthetic chemistry and computational toxicology can provide a robust strategy to address structural moiety data gaps in the genotoxicity evaluation of plant protection products, their active ingredients, and their metabolites.