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Predictive toxicology is increasingly reliant on innovative computational methods to address pressing questions in chemicals assessment. Of importance is the evaluation of contaminant impact differences across species to inform ecosystem protection and identify appropriate model species for human toxicity studies. Here we evaluated 2 complementary tools to predict cross-species differences in binding affinity between per- and polyfluoroalkyl substances (PFAS) and the liver fatty acid-binding protein (LFABP): the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool and molecular dynamics (MD). SeqAPASS determined that the structure of human LFABP, a key determinant of PFAS bioaccumulation, was conserved in the majority of vertebrate species, indicating these species would have similar PFAS bioaccumulation potentials. Level 3 SeqAPASS evaluation identified several potentially destabilizing amino acid differences across species, which were generally supported by DUET stability change predictions. Nine single-residue mutations and 7 whole species sequences were selected for MD evaluation. One mutation (F50V for PFNA) showed a statistically significant difference with stronger affinity than wild-type human LFABP. Predicted binding affinities for 9 different PFAS across 7 species showed human, rat, chicken, and rainbow trout had similar binding affinities to one another for each PFAS, whereas Japanese medaka and fathead minnow had significantly weaker LFABP-binding affinity for some PFAS. Based on these analyses, the combined use of SeqAPASS and MD provides rapid screening for potential species differences with deeper structural insight. This approach can be easily extended to other important biological receptors and potential ligands., (Published by Oxford University Press on behalf of the Society of Toxicology 2021.)

There is significant concern regarding potential impairment of fish reproduction associated with endocrine disrupting chemicals. Aromatase (CYP19) is a steroidogenic enzyme involved in the conversion of androgens to estrogens. Inhibition of aromatase by chemicals can result in reduced concentrations of estrogens leading to adverse reproductive effects. These effects have been extensively investigated in a small number of laboratory model fishes, such as fathead minnow (Pimephales promelas), Japanese medaka (Oryzias latipes), and zebrafish (Danio rerio). But, differences in sensitivity among species are largely unknown. Therefore, this study took a first step toward understanding potential differences in sensitivity to aromatase inhibitors among fishes. Specifically, a standard in vitro aromatase inhibition assay using subcellular fractions of whole tissue homogenates was used to evaluate the potential sensitivity of 18 phylogenetically diverse species of freshwater fish to the nonsteroidal aromatase inhibitor fadrozole. Sensitivity to fadrozole ranged by more than 52-fold among these species. Five species were further investigated for sensitivity to up to 4 additional nonsteroidal aromatase inhibitors, letrozole, imazalil, prochloraz, and propiconazole. Potencies of each of these chemicals relative to fadrozole ranged by up to 2 orders of magnitude among the 5 species. Fathead minnow, Japanese medaka, and zebrafish were among the least sensitive to all the investigated chemicals; therefore, ecological risks of aromatase inhibitors derived from these species might not be adequately protective of more sensitive native fishes. This information could guide more objective ecological risk assessments of native fishes to chemicals that inhibit aromatase., (Published by Oxford University Press on behalf of the Society of Toxicology 2019.)

Chemical hazard assessment requires extrapolation of information from model organisms to all species of concern. The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed as a rapid, cost-effective method to aid cross-species extrapolation of susceptibility to chemicals acting on specific protein targets through evaluation of protein structural similarities and differences. The greatest resolution for extrapolation of chemical susceptibility across species involves comparisons of individual amino acid residues at key positions involved in protein-chemical interactions. However, a lack of understanding of whether specific amino acid substitutions among species at key positions in proteins affect interaction with chemicals made manual interpretation of alignments time consuming and potentially inconsistent. Therefore, this study used in silico site-directed mutagenesis coupled with docking simulations of computational models for acetylcholinesterase (AChE) and ecdysone receptor (EcR) to investigate how specific amino acid substitutions impact protein-chemical interaction. This study found that computationally derived substitutions in identities of key amino acids caused no change in protein-chemical interaction if residues share the same side chain functional properties and have comparable molecular dimensions, while differences in these characteristics can change protein-chemical interaction. These findings were considered in the development of capabilities for automatically generated species-specific predictions of chemical susceptibility in SeqAPASS. These predictions for AChE and EcR were shown to agree with SeqAPASS predictions comparing the primary sequence and functional domain sequence of proteins for more than 90% of the investigated species, but also identified dramatic species-specific differences in chemical susceptibility that align with results from standard toxicity tests. These results provide a compelling line of evidence for use of SeqAPASS in deriving screening level, species-specific, susceptibility predictions across broad taxonomic groups for application to human and ecological hazard assessment.