The PrecisionTox chemical library: creation of a chemical collection to discover evolutionary conserved biomolecular signatures of toxicity
The large number and diversity of chemicals currently in use present significant challenges in assessing their human and environmental health risks due to a paucity of toxicological data. To address this shortage, high-throughput screening technologies are used to rapidly evaluate the toxicity of these chemicals. Suitable chemical libraries are crucial to evaluate the performance of these technologies and generate the cognate toxicity data. Unlike traditional chemical libraries designed for specific disease targets or receptor interactions, the PrecisionTox collection prioritizes diversity in targets and mechanisms of toxicity to ensure broad applicability in toxicity predictions to test the concept of phylotoxicology. Phylotoxicology proposes that mechanisms of toxicity are evolutionarily conserved among distantly related species. Furthermore, the application of phylotoxicology can contribute to the reduction of mammalian species in toxicity testing. Here, an approach for generating a chemical library based on chemical properties-physicochemical, biomolecular, and toxicological-as well as practical considerations, including compound availability, cost, purity, and shipping regulations, is reported. From an initial pool of over 1,500 nominees, a set of 200 chemicals was selected based on multiple criteria, including organ toxicity, environmental exposure, structure, modes of action, and toxicological relevance. Additionally, information on baseline toxicity, Absorption, Distribution, Metabolism, and Excretion properties and utility for in vitro testing was collected. This work underscores the necessity of thoughtful chemical selection to refine toxicological models, improve hazard identification, and support regulatory efforts to protect human and environmental health.
Authors
- Luise Henneberger (ORCID: https://orcid.org/0000-0002-3181-0044)
- Beate Isabella Escher (ORCID: https://orcid.org/0000-0002-5304-706X)
- Stavroula I. Sampani (ORCID: https://orcid.org/0000-0003-3916-1605)
- Carsten Weiß (ORCID: https://orcid.org/0000-0002-5380-3208)
- Thomas Dickmeis (ORCID: https://orcid.org/0000-0002-9819-1962)
- Jonathan H. Freedman (ORCID: https://orcid.org/0000-0002-6118-0290)
- Stefan Scholz (ORCID: https://orcid.org/0000-0002-6990-4716)
- Julia Huchthausen (ORCID: https://orcid.org/0000-0003-4916-1174)
- John K. Colbourne (ORCID: https://orcid.org/0000-0002-6966-2972)
- Juan Carlos González‐Sánchez (ORCID: https://orcid.org/0000-0002-7493-3669)
- Rubén Martínez (ORCID: https://orcid.org/0000-0001-9965-7042)
- Maurice Whelan (ORCID: https://orcid.org/0000-0002-7186-1663)
Institutions
- University of North Carolina at Chapel Hill (US)
- Helmholtz Centre for Environmental Research (DE)
- FIZ Karlsruhe – Leibniz Institute for Information Infrastructure (DE)
- Heidelberg University (DE)
- European Commission (BE)
- Kerntechnische Entsorgung Karlsruhe (Germany) (DE)
- Leitat Technological Center (ES)
- Joint Research Centre (DE)
- University of Birmingham (GB)
- Heidelberg University (US)
Publication Details
- Journal
- Toxicological Sciences
- Published
- 2025-10-31
- DOI
- https://doi.org/10.1093/toxsci/kfaf126
- Citations
- 1
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 1.50
Funders
- U.S. Department of Health and Human Services
- European Commission
- National Institutes of Health