Citation:

Schumann, P., C. Rivetti, J. Houghton, B. Campos, G. Hodges, AND C. LaLone. Combination of computational new approach methodologies for enhancing evidence of biological pathway conservation across species. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, Netherlands, 912:168573, (2024). https://doi.org/10.1016/j.scitotenv.2023.168573

Impact/Purpose:

There are thousands of new chemicals marketed each year. Many of these chemicals will eventually end up in the environment in some form. This a problem because the rate at which these chemicals can be adequately tested for environmental safety is outpaced by the rate at which they are being produced. Currently, testing a chemical for environmental safety is dependent on the use of animals, which is time-consuming and ethically challenging. Therefore, there is a need to develop ways of assessing chemical safety that are non-animal based. As technology and computational power continues to advance, it is more possible to use computational methods to help assess the environmental safety of a chemical. This work demonstrates one aspect of improving computational methods by making use of biological pathway information. A biological pathway describes a series of actions that molecules (for example, proteins) take to lead to certain changes in an organism, such as photosynthesis, which allows for energy production in plants. Biological pathways can also be used to help describe adverse changes in an organism, which is the case when there is an exposure to a toxic chemical. This work shows that the different proteins of a biological pathway can be used to help make predictions of what organisms are the most likely to be impacted by exposure to a particular chemical. This is done by combining two different computational tools, Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) and Genes to Pathways – Species Conservation Analysis (G2P-SCAN). By improving predictions of what organisms are the most likely impacted by a chemical, the ways in which those chemicals are used can also be improved to ultimately help protect the health of the environment.

Description:

The ability to predict which chemicals are of concern for environmental safety is dependent, in part, on the ability to extrapolate chemical effects across many species. This work investigated the complementary use of two computational new approach methodologies to support cross-species predictions of chemical susceptibility: the US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool and Unilever's recently developed Genes to Pathways – Species Conservation Analysis (G2P-SCAN) tool. These stand-alone tools rely on existing biological knowledge to help understand chemical susceptibility and biological pathway conservation across species. The utility and challenges of these combined computational approaches were demonstrated using case examples focused on chemical interactions with peroxisome proliferator activated receptor alpha (PPARα), estrogen receptor 1 (ESR1), and gamma-aminobutyric acid type A receptor subunit alpha (GABRA1). Overall, the biological pathway information enhanced the weight of evidence to support cross-species susceptibility predictions. Through comparisons of relevant molecular and functional data gleaned from adverse outcome pathways (AOPs) to mapped biological pathways, it was possible to gain a toxicological context for various chemical-protein interactions. The information gained through this computational approach could ultimately inform chemical safety assessments by enhancing cross-species predictions of chemical susceptibility. It could also help fulfill a core objective of the AOP framework by potentially expanding the biologically plausible taxonomic domain of applicability of relevant AOPs.

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