ComparativeChemical Space Analysis of Pesticidesand Substances with Genotoxicity Data

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Experimental genotoxicitydata are required for pesticidalandbiocidal active substances prior to regulatory approval, while fortheir metabolites and impurities, in silico predictions are oftenaccepted. Nonetheless, the extent to which these compounds are representedin publicly available genotoxicity databases remains unclear. Herein,we utilize chemical space methods to define the overlap between pesticidesubstances (active substances, metabolites, and impurities) and activitydata for six genotoxicity test types commonly employed in regulatorytoxicology: the Ames test, the in vitro mammalian cell gene mutationtest, the in vitro micronucleus test, the in vitro chromosomal aberrationtest, the in vivo micronucleus test, and the in vivo chromosomal aberrationtest. After merging and performing structure standardization on 18public pesticide/biocide databases, we identified 4826 unique substances.Within 19 public genotoxicity databases, 19,897 substances had atleast one data point in at least one genotoxicity test. The chemicalspace overlap between the pesticide substances and each genotoxicityset was evaluated by calculating physicochemical descriptors and molecularfingerprints, which were visualized by using dimensionality reductionmethods. The chemical space of pesticide substances is well representedby substances with Ames test data and, to varying degrees, by substanceswith data from the other genotoxicity tests, with particularly lowcoverage for in vivo chromosomal aberration. The major scaffolds identifiedin pesticide substances were present in all of the genotoxicity datasets. Compared to pesticide substances, the genotoxicity data setswere enriched in functional groups characteristic of genotoxic compounds,such as annulated rings, but depleted in pesticide-typical structuralmotifs like halogens. Chemical space methods can assist regulatorytoxicologists in understanding regions of pesticide substance chemicalspace that are well- or poorly characterized by genotoxicity data.This understanding is important for the accurate and targeted useof databases and data-based nontesting methods in line with regulatoryrequirements.