Application of in silico and in vitro methods in the development of adverse outcome pathway constructs in wildlife

There is a long history of using both in silico and in vitro methods to predict adverse effects in humans and environmental species where toxicity data are lacking. Currently, there is a great deal of interest in applying these methods to the development of so-called ‘adverse outcome pathway’ (AOP) constructs. The AOP approach provides a framework for organizing information at the chemical and biological level, allowing evidence from both in silico and in vitro studies to be rationally combined to fill gaps in knowledge concerning toxicological events. Fundamental to this new paradigm is a greater understanding of the mechanisms of toxicity and, in particular, where these mechanisms may be conserved across taxa, such as between model animals and related wild species. This presents an opportunity to make predictions across diverse species, where empirical data are unlikely to become available as is the case for most species of wildlife

Development of an In Silico Profiler for Respiratory Sensitisation

In this article, we outline work that led the QSAR and Molecular Modelling Group at Liverpool John Moores University to be jointly awarded the 2013 Lush Science Prize. Our research focuses around the development of in silico profilers for category formation within the Adverse Outcome Pathway paradigm. The development of a well-defined chemical category allows toxicity to be predicted via read-across. This is the central approach used by the OECD QSAR Toolbox. The specific work for which we were awarded the Lush Prize was for the development of such an in silico profiler for respiratory sensitisation. The profiler was developed by an analysis of the mechanistic chemistry associated with covalent bond formation in the lung. The data analysed were collated from clinical reports of occupational asthma in humans. The impact of the development of in silico profilers on the Three Rs is also discussed

Comparative metabolism as a key driver of wildlife species sensitivity to human and veterinary pharmaceuticals

Human and veterinary drug development addresses absorption, distribution, metabolism, elimination and toxicology (ADMET) of the Active Pharmaceutical Ingredient (API) in the target species. Metabolism is an important factor in controlling circulating plasma and target tissue API concentrations and in generating metabolites which are more easily eliminated in bile, faeces and urine. The essential purpose of xenobiotic metabolism is to convert lipid-soluble, non-polar and non-excretable chemicals into water soluble, polar molecules that are readily excreted. Xenobiotic metabolism is classified into Phase I enzymatic reactions (which add or expose reactive functional groups on xenobiotic molecules), Phase II reactions (resulting in xenobiotic conjugation with large water-soluble, polar molecules) and Phase III cellular efflux transport processes. The human-fish plasma model provides a useful approach to understanding the pharmacokinetics of APIs (e.g. diclofenac, ibuprofen and propranolol) in freshwater fish, where gill and liver metabolism of APIs have been shown to be of importance. By contrast, wildlife species with low metabolic competency may exhibit zero-order metabolic (pharmacokinetic) profiles and thus high API toxicity, as in the case of diclofenac and the dramatic decline of vulture populations across the Indian subcontinent. A similar threat looms for African Cape Griffon vultures exposed to ketoprofen and meloxicam, recent studies indicating toxicity relates to zero-order metabolism (suggesting P450 Phase I enzyme system or Phase II glucuronidation deficiencies). While all aspects of ADMET are important in toxicity evaluations, these observations demonstrate the importance of methods for predicting API comparative metabolism as a central part of environmental risk assessment

Investigation of the Verhaar scheme for predicting acute aquatic toxicity: improving predictions obtained from Toxtree ver. 2.6

Assessment of the potential of compounds to cause harm to the aquatic environment is an integral part 8 of the REACH legislation. To reduce the number of vertebrate and invertebrate animals required for 9 this analysis alternative approaches have been promoted. Category formation and read-across have 10 been applied widely to predict toxicity. A key approach to grouping for environmental toxicity is the 11 Verhaar scheme which uses rules to classify compounds into one of four mechanistic categories. 12 These categories provide a mechanistic basis for grouping and any further predictive modelling. A 13 computational implementation of the Verhaar scheme is available in Toxtree v2.6. The work 14 presented herein demonstrates how modifications to the implementation of Verhaar between version 15 1.5 and 2.6 of Toxtree have improved performance by reducing the number of incorrectly classified 16 compounds. However, for the datasets used in this analysis, version 2.6 classifies more compounds as 17 outside of the domain of the model. Further amendments to the classification rules have been 18 implemented here using a post-processing filter encoded as a KNIME workflow. This results in fewer 19 compounds being classified as outside of the model domain, further improving the predictivity of the 20 scheme. The utility of the modification described herein is demonstrated through building quality, 21 mechanism-specific Quantitative Structure Activity Relationship (QSAR) models for the compounds 22 within specific mechanistic categories

Linking existing in vitro dermal absorption data to physicochemical properties: Contribution to the design of a weight-of-evidence approach for the safety evaluation of cosmetic ingredients with low dermal bioavailability.

To characterize the risk of cosmetic ingredients when threshold toxicity is assumed, often the "margin of safety" (MoS) is calculated. This uncertainty factor is based on the systemic no observable (adverse) effect level (NO(A)EL) which can be derived from in vivo repeated dose toxicity studies. As in vivo studies for the purpose of the cosmetic legislation are no longer allowed in Europe and a validated in vitro alternative is not yet available, it is no longer possible to derive a NO(A)EL value for a new cosmetic ingredient. Alternatively, cosmetic ingredients with a low dermal bioavailability might not need repeated dose data, as internal exposure will be minimal and systemic toxicity might not be an issue. This study shows the possibility of identifying compounds suspected to have a low dermal bioavailability based on their physicochemical properties (molecular weight, melting point, topological polar surface area and log P) and their in vitro dermal absorption data. Although performed on a limited number of compounds, the study suggests a strategic opportunity to support the safety assessor's reasoning to omit a MoS calculation and to focus more on local toxicity and mutagenicity/genotoxicity for ingredients for which limited systemic exposure is to be expected

Adverse Outcome Pathway (AOP) Informed Modeling of Aquatic Toxicology: QSARs, Read-Across, and Interspecies Verification of Modes of Action.

Alternative approaches have been promoted to reduce the number of vertebrate and invertebrate animals required for the assessment of the potential of compounds to cause harm to the aquatic environment. A key philosophy in the development of alternatives is a greater understanding of the relevant adverse outcome pathway (AOP). One alternative method is the fish embryo toxicity (FET) assay. Although the trends in potency have been shown to be equivalent in embryo and adult assays, a detailed mechanistic analysis of the toxicity data has yet to be performed; such analysis is vital for a full understanding of the AOP. The research presented herein used an updated implementation of the Verhaar scheme to categorize compounds into AOP-informed categories. These were then used in mechanistic (quantitative) structure-activity relationship ((Q)SAR) analysis to show that the descriptors governing the distinct mechanisms of acute fish toxicity are capable of modeling data from the FET assay. The results show that compounds do appear to exhibit the same mechanisms of toxicity across life stages. Thus, this mechanistic analysis supports the argument that the FET assay is a suitable alternative testing strategy for the specified mechanisms and that understanding the AOPs is useful for toxicity prediction across test systems

Development of a Fragment-Based in Silico Profiler for Michael Addition Thiol Reactivity

The Adverse Outcome Pathway (AOP) paradigm details the existing knowledge that links the initial interaction between a chemical and a biological system, termed the molecular initiating event (MIE), through a series of intermediate events, to an adverse effect. An important example of a well-defined MIE is the formation of a covalent bond between a biological nucleophile and an electrophilic compound. This particular MIE has been associated with various toxicological end points such as acute aquatic toxicity, skin sensitization, and respiratory sensitization. This study has investigated the calculated parameters that are required to predict the rate of chemical bond formation (reactivity) of a dataset of Michael acceptors. Reactivity of these compounds toward glutathione was predicted using a combination of a calculated activation energy value (Eact, calculated using density functional theory (DFT) calculation at the B3YLP/6-31G+(d) level of theory, and solvent-accessible surface area values (SAS) at the α carbon. To further develop the method, a fragment-based algorithm was developed enabling the reactivity to be predicted for Michael acceptors without the need to perform the time-consuming DFT calculations. Results showed the developed fragment method was successful in predicting the reactivity of the Michael acceptors excluding two sets of chemicals: volatile esters with an extended substituent at the β-carbon and chemicals containing a conjugated benzene ring as part of the polarizing group. Additionally the study also demonstrated the ease with which the approach can be extended to other chemical classes by the calculation of additional fragments and their associated Eact and SAS values. The resulting method is likely to be of use in regulatory toxicology tools where an understanding of covalent bond formation as a potential MIE is important within the AOP paradigm

Validation of a fragment-based profiler for thiol reactivity for the prediction of toxicity: skin sensitisation and tetrahymena pyriformis

This study outlines the use of a recently developed fragment-based thiol reactivity profiler for Michael acceptors to predict toxicity towards Tetrahymena pyriformis and skin sensitisation potency as determined in the Local Lymph Node Assay (LLNA). The results showed that the calculated reactivity parameter from the profiler, -log RC50(calc), was capable of predicting toxicity for both endpoints with excellent statistics. However, the study highlighted the importance of a well-defined applicability domain for each endpoint. In terms of Tetrahymena pyriformis this domain was defined in terms of how fast or slowly a given Michael acceptor reacts with thiol leading to two separate quantitative structure-activity models. The first, for fast reacting chemicals required only –Log RC50(calc) as a descriptor, whilst the second required the addition of a descriptor for hydrophobicity. Modelling of the LLNA required only a single descriptor, -log RC50(calc), enabling potency to be predicted. The applicability domain excluded chemicals capable of undergoing polymerisation and those that were predicted to be volatile. The modelling results for both endpoints, using the –log RC50(calc) value from the profiler, were in keeping with previously published studies that have utilised experimentally determined measurements of reactivity. This results demonstrate the output from the fragment-based thiol reactivity profiler can be used to develop quantitative structure-activity relationship models where reactivity towards thiol is a driver of toxicity