The development of Adverse Outcome Pathways (AOPs) is becoming a key component of 21 st century toxicology. AOPs provide a conceptual framework that links the molecular initiating event to an adverse outcome through organised 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. Due to the heightened development of NR ligands there is increased need for the identification of related AOPs to facilitate their risk assessment. Many NR ligands have been linked specifically to steatosis. This paper reviews and summarises the role of NR and their importance with links between NR examined to identify plausible putative AOPs. The following NRs are shown to induce hepatic steatosis upon ligand binding: aryl hydrocarbon receptor, constitutive androstane receptor, oestrogen receptor, glucocorticoid receptor, farnesoid X receptor, liver X receptor, peroxisome proliferator-activated receptor, pregnane X receptor, and the retinoic acid receptor. A preliminary, putative AOP was formed for NR binding linked to hepatic steatosis as the adverse outcome.

This is a repository copy of Molecular fingerprint-derived similarity measures for toxicological read-across: Recommendations for optimal use.

In silico models are essential for the development of integrated alternative methods to identify organ level toxicity and lead towards 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 endpoints. Structural alerts are able both to predict toxicity directly and assist in the formation of categories to facilitate read-across.They are particularly important to decipher the myriad mechanisms of action that result in organ level toxicity. The aim of this study was to develop novel structural alerts for nuclear receptor (NR) ligands that are associated with inducing hepatic steatosis and to show the vast amount of current data that are available. Current knowledge on NR agonists was extended with data from the ChEMBL database (12,713 chemicals in total) of bioactive molecules and from studying NR ligand-binding interactions within the protein data base (PBD, 624 human NR structure files). A computational structural alerts based workflow was developed using KNIME from these data using molecular fragments and other relevant chemical features. In total 214 structural features were recorded computationally as SMARTS strings and, therefore, they can be used for grouping and screening during drug development and hazard assessment and provide knowledge to anchor adverse outcome pathways (AOPs) via there molecular initiating effects (MIE).4

In this study we demonstrate simple guidelines to generate a diverse range of fluorescent materials in both liquid and solid state by focusing on the most popular C-dots precursors, i.e. the binary systems of citric acid and urea. The pyrolytic treatment of those precursors combined with standard size separation techniques (dialysis and filtration), leads to four distinct families of photoluminescent materials in which the emissive signal predominantly arises from C-dots with embedded fluorophores, cyanuric acid-rich C-dots, a blend of molecular fluorophores and a mixture of C-dots with unbound molecular fluorophores, respectively. Within each one of those families the chemical composition and the optical properties of their members can be fine-tuned by adjusting the molar ratio of the reactants. Apart from generating a variety of aqueous dispersions, our approach leads to highly fluorescent powders derived from precursors comprising excessive amounts of urea that is consumed for the build-up of the carbogenic cores, the molecular fluorophores and the solid diluent matrix that suppresses self-quenching effects.

This study outlines the analysis of mitochondrial toxicity for a variety of pharmaceutical drugs extracted from Zhang et al. These chemicals were grouped into categories based upon structural similarity. Subsequently, mechanistic analysis was undertaken for each category to identify the Molecular Initiating Event driving mitochondrial toxicity. The mechanistic information elucidated during the analysis enabled mechanism-based structural alerts to be developed and combined together to form an in silico profiler. This profiler is envisaged to be used to develop chemical categories based upon similar mechanisms as part of the Adverse Outcome Pathway paradigm. Additionally, the profiler could be utilised in screening large dataset in order to identify chemicals with the potential to induce mitochondrial toxicity.

There are no in vivo repeated-dose data for the vast majority of β-olefinic alcohols.However, there are robust and consistent ex vivo data suggesting many of these chemicals are metabolically transformed, especially in the liver, to reactive electrophilic toxicants which react in a mechanistically similar manner to acrolein, the reactive metabolite of 2-propen-1-ol. Hence, an evaluation was conducted to determine suitability of 2-propen-1-ol as a read-across analogue for other β-olefinic alcohols. The pivotal issue to applying read-across to the proposed category is the confirmation of the biotransformation to metabolites having the same mechanism of electrophilic reactivity, via the same metabolic pathway, with a rate of transformation sufficient to induce the same in vivo outcome. The applicability domain for this case study was limited to small (C3 to C6) primary and secondary -olefinic alcohols. Mechanistically, these -unsaturated alcohols are considered to be readily metabolised by alcohol dehydrogenase to polarised α, -unsaturated aldehydes and ketones. These metabolites are able to react via the Michael addition reaction mechanism with thiol groups in proteins resulting in cellular apoptosis and/or necrosis. The addition of the non-animal in chemico reactivity data (50% depletion of free glutathione) reduced the uncertainty so the read-across prediction for the straight-chain olefinic -unsaturated alcohols is deemed equivalent to a standard test. Specifically, the rat oral 90-day repeated-dose No Observed Adverse Effect Level (NOAEL) for 2-propen-1-ol of 6 mg/kg body weight bw/d in males based on increase in relative weight of liver and 25 mg/kg bw/d in females based on bile duct hyperplasia and periportal hepatocyte hypertrophy in the liver, is read across to fill data gaps for the straight-chained analogues.

Assessing compounds for their pharmacological and toxicological properties is of great importance for industry and regulatory agencies. In this study an approach using open source software and open access databases to build screening tools for receptor-mediated effects is presented. The retinoic acid receptor (RAR), as a pharmacologically and toxicologically relevant target, was chosen for study. RAR agonists are used in the treatment of a number of dermal conditions and specific types of cancer, such as acute promyelocytic leukemia. However, when administered chronically, there is strong evidence that RAR agonists cause hepatosteatosis and liver injury. After compiling information on ligand-proteininteractions, common substructures and physico-chemical properties of ligands were identified manually and coded into SMARTS strings. Based on these SMARTS strings and calculated physico-chemical features, a rule-based screening workflow was built within the KNIME platform. The workflow was evaluated on two datasets: one with RAR agonists exclusively and another large, chemically diverse dataset containing only a few RAR agonists. Possible modifications and applications of screening workflows, dependent on their purpose, are presented.

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