Palczewska, A and Kovarich, S and Ciacci, A and Fioravanzo, E and Basan, A and Neagu, D
(2019)
Ranking strategies to support toxicity prediction: a case study on potential LXR binders.
Computational Toxicology, 10.
pp. 130-144.
ISSN 2468-1113
DOI: https://doi.org/10.1016/j.comtox.2019.01.004
Abstract
The current paradigm of toxicity testing is set within a framework of Mode-of-Action (MoA)/Adverse Outcome Pathway (AOP) investigations, where novel methodologies alternative to animal testing play a crucial role, and allow to consider causal links between molecular initiating events (MIEs), further key events and an adverse outcome. In silico (computational) models are developed to support toxicity assessment within the MoA/AOP framework. This paper focuses on the evaluation of potential binding to the Liver X Receptor (LXR), as this has been identified among the MIEs leading to liver steatosis within an AOP framework addressing repeated dose and target-organ toxicity.
More Information
Identification Number: | https://doi.org/10.1016/j.comtox.2019.01.004 |
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Status: | Published |
Refereed: | Yes |
Publisher: | Elsevier |
Depositing User (symplectic) | Deposited by Palczewska, Anna |
Date Deposited: | 20 Feb 2019 12:23 |
Last Modified: | 11 Jul 2024 21:00 |
Item Type: | Article |
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