Researchers developed a new model for predicting whether chemicals are toxic to the liver. The tool also identified a cellular pathway that might be involved in the process.
Traditional models are time-consuming and expensive. To build their model, the team gathered data from reference drug lists on hundreds of chemicals known to cause liver toxicity and others with no known liver effects. They refined their tool by separating the chemicals into two groups: those that activate a specific cellular pathway in the liver that causes oxidative stress — a sign of injury — and those that do not. The team also incorporated information about chemical structural features that are involved in triggering oxidative stress.
The researchers validated the model by exposing human liver cells to 16 chemicals either implicated in oxidative stress or not, and then compared their experimental results with the model’s predictions for those compounds. Next, they entered five chemicals previously shown to cause liver toxicity and seven nontoxic chemicals into the model. Overall, the model successfully predicted the liver toxicity potential for most chemicals tested.
According to the team, this novel strategy can be used to develop additional models that consider other pathways involved in liver toxicity.
Citation: Jia X, Wen X, Russo DP, Aleksunes LM, Zhu H. 2022. Mechanism-driven modeling of chemical hepatotoxicity using structural alerts and an in vitro screening assay. J Hazard Mater 436:129193.
Read more at: https://factor.niehs.nih.gov/2023/1/science-highlights/papers-of-the-year