In Silico Identification of Chemicals Capable of Binding to the Ecdysone Receptor.

The process of molting, known alternatively as ecdysis, is a feature integral in the life cycles of species across the arthropod phylum. Regulation occurs as a function of the interaction of ecdysteroid hormones with the arthropod nuclear ecdysone receptor-a process preceding the triggering of a series of downstream events constituting an endocrine signaling pathway highly conserved throughout environmentally prevalent insect, crustacean, and myriapod organisms. Inappropriate ecdysone receptor binding and activation forms the essential molecular initiating event within possible adverse outcome pathways relating abnormal molting to mortality in arthropods.

A Mechanistic Framework for Integrating Chemical Structure and High-Throughput Screening Results to Improve Toxicity Predictions.

Adverse Outcome Pathways (AOPs) establish a connection between a molecular initiating event (MIE) and an adverse outcome. Detailed understanding of the MIE provides the ideal data for determining chemical properties required to elicit the MIE. This study utilized high-throughput screening data from the ToxCast program, coupled with chemical structural information, to generate chemical clusters using three similarity methods pertaining to nine MIEs within an AOP network for hepatic steatosis.

A critical review of adverse effects to the kidney: mechanisms, data sources, and in silico tools to assist prediction.

The kidney is a major target for toxicity elicited by pharmaceuticals and environmental pollutants. Standard testing which often does not investigate underlying mechanisms has proven not to be an adequate hazard assessment approach. As such, there is an opportunity for the application of computational approaches that utilize multiscale data based on the Adverse Outcome Pathway (AOP) paradigm, coupled with an understanding of the chemistry underpinning the molecular initiating event (MIE) to provide a deep understanding of how structural fragments of molecules relate to specific mechanisms of nephrotoxicity.

Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects.

methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself.

Using Molecular Initiating Events to Develop a Structural Alert Based Screening Workflow for Nuclear Receptor Ligands Associated with Hepatic Steatosis.

In silico models are essential for the development of integrated alternative methods to identify organ level toxicity and lead toward the replacement of animal testing. These models include (quantitative) structure-activity relationships ((Q)SARs) and, importantly, the identification of structural alerts associated with defined toxicological end points. Structural alerts are able both to predict toxicity directly and assist in the formation of categories to facilitate read-across.

The identification of nuclear receptors associated with hepatic steatosis to develop and extend adverse outcome pathways.

The development of adverse outcome pathways (AOPs) is becoming a key component of twenty-first century toxicology. AOPs provide a conceptual framework that links the molecular initiating event to an adverse outcome through organized toxicological knowledge, bridging the gap from chemistry to toxicological effect. As nuclear receptors (NRs) play essential roles for many physiological processes within the body, they are used regularly as drug targets for therapies to treat many diseases including diabetes, cancer and neurodegenerative diseases.

Development of an in Silico Profiler for Mitochondrial Toxicity.

This study outlines the analysis of mitochondrial toxicity for a variety of pharmaceutical drugs extracted from Zhang et al. ((2009) Toxicol. In Vitro, 23, 134-140).