Computational screening for potentially bioactive molecules using advanced molecular modeling approaches including molecular docking and molecular dynamic simulation is mainstream in certain fields like drug discovery. Significant advances in computationally predicting protein structures from sequence information have also expanded the availability of structures for nonmodel species. Therefore, the objective of the present study was to develop an analysis pipeline to harness the power of these bioinformatics approaches for cross-species extrapolation for evaluating chemical safety. The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool compares protein-sequence similarity across species for conservation of known chemical targets, providing an initial line of evidence for extrapolation of toxicity knowledge. However, with the development of structural models from tools like the Iterative Threading ASSEmbly Refinement (ITASSER), analyses of protein structural conservation can be included to add further lines of evidence and generate protein models across species. Models generated through such a pipeline could then be used for advanced molecular modeling approaches in the context of species extrapolation. Two case examples illustrating this pipeline from SeqAPASS sequences to I-TASSERgenerated protein structures were created for human liver fatty acid-binding protein (LFABP) and androgen receptor (AR). Ninety-nine LFABP and 268 AR protein models representing diverse species were generated and analyzed for conservation using template modeling (TM)-align. The results from the structural comparisons were in line with the sequence-based SeqAPASS workflow, adding further evidence of LFABL and AR conservation across vertebrate species. The present study lays the foundation for expanding the capabilities of the web-based SeqAPASS tool to include structural comparisons for species extrapolation, facilitating more rapid and efficient toxicological assessments among species with limited or no existing toxicity data.

Anthropogenic activities introduce complex mixtures into aquatic environments, necessitating mixture toxicity evaluation during risk assessment. There are many alternative approaches that can be used to complement traditional techniques for mixture assessment. Our study aimed to demonstrate how these approaches could be employed for mixture evaluation in a target watershed. Evaluations were carried out over 2 years (2017–2018) across 8–11 study sites in the Milwaukee Estuary (WI, USA). Whole mixtures were evaluated on a site‐specific basis by deploying caged fathead minnows (Pimephales promelas) alongside composite samplers for 96 h and characterizing chemical composition, in vitro bioactivity of collected water samples, and in vivo effects in whole organisms. Chemicals were grouped based on structure/mode of action, bioactivity, and pharmacological activity. Priority chemicals and mixtures were identified based on their relative contributions to estimated mixture pressure (based on cumulative toxic units) and via predictive assessments (random forest regression). Whole mixture assessments identified target sites for further evaluation including two sites targeted for industrial/urban chemical mixture effects assessment; three target sites for pharmaceutical mixture effects assessment; three target sites for further mixture characterization; and three low‐priority sites. Analyses identified 14 mixtures and 16 chemicals that significantly contributed to cumulative effects, representing high or medium priority targets for further ecotoxicological evaluation, monitoring, or regulatory assessment. Overall, our study represents an important complement to single‐chemical prioritizations, providing a comprehensive evaluation of the cumulative effects of mixtures detected in a target watershed. Furthermore, it demonstrates how different tools and techniques can be used to identify diverse facets of mixture risk and highlights strategies that can be considered in future complex mixture assessments. Environ Toxicol Chem 2023;42:1229–1256. © 2023 SETAC

Evaluating interspecies toxicity variation is a long-standing challenge for chemical hazard assessment. This study developed a quantitative interspecies thermal shift assay (QITSA) for in situ, quantitative, and modest-throughput investigation of chemical–protein interactions in cell and tissue samples across species. By using liver fatty acid binding protein (L-FABP) as a case study, the QITSA method was benchmarked with six per- and polyfluoroalkyl substances, and thermal shifts (ΔT m) were inversely related to their dissociation constants (R 2 = 0.98). The QITSA can also distinguish binding modes of chemicals exemplified by palmitic acid. The QITSA was applied to determine the interactions between perfluorooctanesulfonate (PFOS) and L-FABP in liver cells or tissues from humans, mice, rats, and zebrafish. The largest thermal stability enhancement by PFOS was observed for human L-FABP followed by the mouse, rat, and zebrafish. While endogenous ligands were revealed to partially contribute to the large interspecies variation, recombinant proteins were employed to confirm the high binding affinity of PFOS to human L-FABP, compared to the rat and mouse. This study implemented an experimental strategy to characterize chemical–protein interactions across species, and future application of QITSA to other chemical contaminants is of great interest.

For the majority of developed adverse outcome pathways (AOPs), the taxonomic domain of applicability (tDOA) is typically narrowly defined with a single or a handful of species. Defining the tDOA of an AOP is critical for use in regulatory decision‐making, particularly when considering protection of untested species. Structural and functional conservation are two elements that can be considered when defining the tDOA. Publicly accessible bioinformatics approaches, such as the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool, take advantage of existing and growing databases of protein sequence and structural information to provide lines of evidence toward structural conservation of key events (KEs) and KE relationships (KERs) of an AOP. It is anticipated that SeqAPASS results could readily be combined with data derived from empirical toxicity studies to provide evidence of both structural and functional conservation, to define the tDOA for KEs, KERs, and AOPs. Such data could be incorporated in the AOP‐Wiki as lines of evidence toward biological plausibility for the tDOA. We present a case study describing the process of using bioinformatics to define the tDOA of an AOP using an AOP linking the activation of the nicotinic acetylcholine receptor to colony death/failure in Apis mellifera. Although the AOP was developed to gain a particular biological understanding relative to A. mellifera health, applicability to other Apis bees, as well as non‐Apis bees, has yet to be defined. The present study demonstrates how bioinformatics can be utilized to rapidly take advantage of existing protein sequence and structural knowledge to enhance and inform the tDOA of KEs, KERs, and AOPs, focusing on providing evidence of structural conservation across species. Environ Toxicol Chem 2023;42:71–87. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

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