Chemistry-Based Risk Assessment for Skin Sensitization: Quantitative Mechanistic Modeling for the SNAr Domain

Computer-Aided Discovery and Redesign for Respiratory Sensitization: A Tiered Mechanistic Model to Deliver Robust Performance Across a Diverse Chemical Space

Asthma is among the most common occupational diseases with considerable public health and economic costs. Chemicals that induce hypersensitivity in the airways can cause respiratory distress and comorbidities with respiratory infections such as COVID. Robust predictive models for this end point are still elusive due to the lack of an experimental benchmark and the over-reliance of existing in silico tools on structural alerts and structural (vs chemical) similarities. The Computer-Aided Discovery and REdesign (CADRE) platform is a proven strategy for providing robust computational predictions for hazard end points using a tiered hybrid system of expert rules, molecular simulations, and quantum mechanics calculations. The recently developed CADRE model for respiratory sensitization is based on a highly curated data set of structurally diverse chemicals with high-fidelity biological data. The model evaluates absorption kinetics in lung mucosa using Monte Carlo simulations, assigns reactive centers in a molecule and possible biotransformations via expert rules, and determines subsequent reactivity with cell proteins via quantum-mechanics calculations using a multi-tiered regression. The model affords an accuracy above 0.90, with a series of external validations based on literature data in the range of 0.88-0.95. The model is applicable to all low-molecular-weight organics and can inform not only chemical substitution but also chemical redesign to advance development of safer alternatives.

Semi-correlations as a tool to model for skin sensitization

Semi-correlation specifically assesses the correlation between a binary variable and a continuous variable. Semi-correlations were applied to develop binary models for various endpoints. We applied the semi-correlation to develop models of two kinds of skin sensitization one related to animals (local lymph node assay LLNA) and one to human beings (direct peptide reactivity assay DPRA and/or human cell line activation test h-CLAT). The models refer to binary classification for a two-level strategy: the first level (analysis of all compounds) is used in the format "sensitizer or non-sensitizer", and the second level (only sensitizers) is a further classification in the format "strong or weak sensitizer". The ranges of statistical characteristics of the models depend on the endpoint, LLNA or DPRA/h-CLAT: for the first level, sensitivity: 0.69-0.88, specificity: 0.75-0.89, accuracy: 0.77-0.87, Matthew's correlation coefficient (MCC): 0.54-0.57 and for the second level, sensitivity: 0.70-1.0, specificity: 0.78-0.83, accuracy: 0.77-0.87, MCC: 0.54-0.76. Thus, the described approach can be applied to building up models of the skin sensitization potency.

Do Similar Structures Have Similar No Observed Adverse Effect Level (NOAEL) Values? Exploring Chemoinformatics Approaches for Estimating NOAEL Bounds and Uncertainties

Determination of the no observed adverse effect level (NOAEL) of a substance is an important step in safety and regulatory assessments. Application of conventional in silico strategies, for example, quantitative structure-activity relationship (QSAR) models, to predict NOAEL values is inherently problematic. Whereas QSAR models for well-defined toxicity endpoints such as Ames mutagenicity or skin sensitization can be developed from mechanistic knowledge of molecular initiating events and adverse outcome pathways, QSAR is not appropriate for predicting a NOAEL value, a concentration at which "no effect" is observed. This paper presents a chemoinformatics approach and explores how it can be further refined through the incorporation of toxicity endpoint-specific information to estimate confidence bounds for the NOAEL of a target substance, given experimentally determined NOAEL values for one or more suitable analogues. With a sufficiently large NOAEL database, we analyze how a difference in NOAEL values for pairs of structures depends on their pairwise similarity, where similarity takes both structural features and physicochemical properties into account. The width of the estimate NOAEL confidence interval is proportional to the uncertainty. Using the new threshold of toxicological concern (TTC) database enriched with antimicrobials, examples are presented to illustrate how uncertainty decreases with increasing analogue quality and also how NOAEL bounds estimation can be significantly improved by filtering the full database to include only substances that are in structure categories relevant to the target and analogue.

How Do Aromatic Nitro Compounds React with Nucleophiles? Theoretical Description Using Aromaticity, Nucleophilicity and Electrophilicity Indices

In this study, we present a complete description of the addition of a model nucleophile to the nitroaromatic ring in positions occupied either by hydrogen (the first step of the S_NAr-H reaction) or a leaving group (S_NAr-X reaction) using theoretical parameters including aromaticity (HOMA), electrophilicity and nucleophilicity indices. It was shown both experimentally and by our calculations, including kinetic isotope effect modeling, that the addition of a nucleophile to the electron-deficient aromatic ring is the rate limiting step of both S_NAr-X and S_NAr-H reactions when the fast transformation of σ^H-adduct into the products is possible due to the specific reaction conditions, so this is the most important step of the entire reaction. The results described in this paper are helpful for better understanding of the subtle factors controlling the reaction direction and rate.

Skin sensitization in silico protocol

The assessment of skin sensitization has evolved over the past few years to include in vitro assessments of key events along the adverse outcome pathway and opportunistically capitalize on the strengths of in silico methods to support a weight of evidence assessment without conducting a test in animals. While in silico methods vary greatly in their purpose and format; there is a need to standardize the underlying principles on which such models are developed and to make transparent the implications for the uncertainty in the overall assessment. In this contribution, the relationship between skin sensitization relevant effects, mechanisms, and endpoints are built into a hazard assessment framework. Based on the relevance of the mechanisms and effects as well as the strengths and limitations of the experimental systems used to identify them, rules and principles are defined for deriving skin sensitization in silico assessments. Further, the assignments of reliability and confidence scores that reflect the overall strength of the assessment are discussed. This skin sensitization protocol supports the implementation and acceptance of in silico approaches for the prediction of skin sensitization.

Using 2D Structural Alerts to Define Chemical Categories for Molecular Initiating Events

Molecular initiating events (MIEs) are important concepts for in silico predictions. They can be used to link chemical characteristics to biological activity through an adverse outcome pathway (AOP). In this work, we capture chemical characteristics in 2D structural alerts, which are then used as models to predict MIEs. An automated procedure has been used to identify these alerts, and the chemical categories they define have been used to provide quantitative predictions for the activity of molecules that contain them. This has been done across a diverse group of 39 important pharmacological human targets using open source data. The alerts for each target combine into a model for that target, and these models are joined into a tool for MIE prediction with high average model performance (sensitivity = 82%, specificity = 93%, overall quality = 93%, Matthews correlation coefficient = 0.57). The result is substantially improved from our previous study (Allen, T. E. H., Goodman, J. M., Gutsell, S., and Russell, P. J. 2016. A history of the molecular initiating event. Chem. Res. Toxicol. 29, 2060-2070) for which the mean sensitivity for each target was only 58%. This tool provides the first step in an AOP-based risk assessment, linking chemical structure to toxicity endpoint.

Predicting skin sensitization potential of organic compounds based on toxicity enhancement to Tetrahymena pyriformis, fathead minnow, and Daphnia magna

Skin sensitization is an important occupational health problem and immunotoxicity endpoint. Considering animal welfare and time and cost savings, many alternative approaches, such as those conducted in vitro, in silico, and in chemo, have been proposed and applied to predict skin sensitization of compounds. Toxicologically, sensitizers can elicit excess toxicity at greater levels than non-sensitizers due to their capacity to react with proteins/peptides. Based on this understanding, calculated toxicity enhancements (T_e) of 65 organic compounds from three in vitro bioassays, i.e. 48-hr ciliate (Tetrahymena pyriformis) growth inhibition, and both 96-hr fathead minnow and 48-hr Daphnia magna acute lethal toxicities, were employed to qualitatively and quantitatively predict skin sensitization potencies of the test agents. The sensitivity, specificity, and accuracy reaching 80% strongly suggested toxicity enhancement was an excellent parameter for predicting skin sensitization. Linear regressions of skin sensitization against toxicity enhancement were fitted for each bioassay, and they were improved after the sensitizers were categorized into different reaction mechanistic domains, which, in decreasing order of contribution from T_e to sensitization, were S_NAr > S_N1 > MA. These results indicated that toxicity bioassays are useful tools and that T_e could be a useful parameter that might be applied to predict skin sensitization.

A History of the Molecular Initiating Event

The adverse outcome pathway (AOP) framework provides an alternative to traditional in vivo experiments for the risk assessment of chemicals. AOPs consist of a number of key events (KEs) linked by key event relationships across a range of biological organization backed by scientific evidence. The first KE in the pathway is the molecular initiating event (MIE)-the initial chemical trigger that starts an AOP. Over the past 3 years the AOP conceptual framework has gained a large amount of momentum in toxicology as an alternative to animal methods, and so the MIE has come into the spotlight. What is an MIE? How can MIEs be measured or predicted? What research is currently contributing to our understanding of MIEs? In this Perspective we outline answers to these key questions.

Skin Sensitisation, Adverse Outcome Pathways and Alternatives

For toxicologists who are in any way associated with skin sensitisation, the last two decades have seen a series of fundamental changes. We have migrated from old-style guinea-pig assays, via the refined and reduced Local Lymph Node Assay (LLNA), to witness the imminent dominance of in vitro and in silico methods. Yet, over the same period, the use of the output data for human safety assurance has evolved from ‘black box’ risk assessment, via the quantitative risk assessment enabled by the LLNA measurement of potency, to a new period of relative uncertainty. This short review will endeavour to address these topics, all the while keeping a focus on three essential principles: a) that skin sensitisation potential is intrinsic in the molecular structure of the chemical; b) that test methods should have a mechanistic foundation; and finally c) that the only reason for undertaking any skin sensitisation work has to be the protection of human health.

Adverse Outcome Pathways for Regulatory Applications: Examination of Four Case Studies With Different Degrees of Completeness and Scientific Confidence

Adverse outcome pathways (AOPs) offer a pathway-based toxicological framework to support hazard assessment and regulatory decision-making. However, little has been discussed about the scientific confidence needed, or how complete a pathway should be, before use in a specific regulatory application. Here we review four case studies to explore the degree of scientific confidence and extent of completeness (in terms of causal events) that is required for an AOP to be useful for a specific purpose in a regulatory application: (i) Membrane disruption (Narcosis) leading to respiratory failure (low confidence), (ii) Hepatocellular proliferation leading to cancer (partial pathway, moderate confidence), (iii) Covalent binding to proteins leading to skin sensitization (high confidence), and (iv) Aromatase inhibition leading to reproductive dysfunction in fish (high confidence). Partially complete AOPs with unknown molecular initiating events, such as 'Hepatocellular proliferation leading to cancer', were found to be valuable. We demonstrate that scientific confidence in these pathways can be increased though the use of unconventional information (eg, computational identification of potential initiators). AOPs at all levels of confidence can contribute to specific uses. A significant statistical or quantitative relationship between events and/or the adverse outcome relationships is a common characteristic of AOPs, both incomplete and complete, that have specific regulatory uses. For AOPs to be useful in a regulatory context they must be at least as useful as the tools that regulators currently possess, or the techniques currently employed by regulators.

How Does Nucleophilic Aromatic Substitution Really Proceed in Nitroarenes? Computational Prediction and Experimental Verification

The aim of this paper is to present a correct and complete mechanistic picture of nucleophilic substitution in nitroarenes based on the results obtained by theoretical calculations and experimental observations coming from numerous publications, reviews, and monographs. This work gives the theoretical background to the very well documented experimentally yet still ignored observations that the addition of nucleophiles to halo nitroarenes resulting in the formation of σ(H) adducts, which under proper reaction conditions can be transformed into the product of the SNArH reaction, is faster than the competing process of addition to the carbon atom bearing a nucleofugal group (usually a halogen atom) resulting in the "classic" SNAr reaction. Only when the σ(H) adduct cannot be transformed into the SNArH reaction product, SNAr reaction is observed.

Special endpoint and product specific considerations in pharmaceutical acceptable daily exposure derivation

Recently, a guideline has been published by the European Medicines Agency (EMA) on setting safe limits, permitted daily exposures (PDE) [also called acceptable daily exposures (ADE)], for medicines manufactured in multi-product facilities. The ADE provides a safe exposure limit for inadvertent exposure of a drug due to cross-contamination in manufacturing. The ADE determination encompasses a standard risk assessment, requiring an understanding of the toxicological and pharmacological effects, the mechanism of action, drug compound class, and the dose-response as well as the pharmacokinetic properties of the compound. While the ADE concept has broad application in pharmaceutical safety there are also nuances and specific challenges associated with some toxicological endpoints or drug product categories. In this manuscript we discuss considerations for setting ADEs when the following specific adverse health endpoints may constitute the critical effect: genotoxicity, developmental and reproductive toxicity (DART), and immune system modulation (immunostimulation or immunosuppression), and for specific drug classes, including antibody drug conjugates (ADCs), emerging medicinal therapeutic compounds, and compounds with limited datasets. These are challenging toxicological scenarios that require a careful evaluation of all of the available information in order to establish a health-based safe level.

Influence of Solvation and Dynamics on the Mechanism and Kinetics of Nucleophilic Aromatic Substitution Reactions in Liquid Ammonia

The role of the solvent and the influence of dynamics on the kinetics and mechanism of the SNAr reaction of several halonitrobenzenes in liquid ammonia, using both static calculations and dynamic ab initio molecular dynamics simulations, are investigated. A combination of metadynamics and committor analysis methods reveals how this reaction can change from a concerted, one-step mechanism in gas phase to a stepwise pathway, involving a metastable Meisenheimer complex, in liquid ammonia. This clearly establishes, among others, the important role of the solvent and highlights the fact that accurately treating solvation is of crucial importance to correctly unravel the reaction mechanism. It is indeed shown that H-bond formation of the reacting NH3 with the solvent drastically reduces the barrier of NH3 addition. The halide elimination step, however, is greatly facilitated by proton transfer from the reacting NH3 to the solvent. Furthermore, the free energy surface strongly depends on the halide substituent and the number of electron-withdrawing nitro substituents.

Reactivity measurement in estimation of benzoquinone and benzoquinone derivatives' allergenicity

Benzoquinone (BQ) and benzoquinone derivatives (BQD) are used in the production of dyes and cosmetics. While BQ, an extreme skin sensitizer, is an electrophile known to covalently modify proteins via Michael Addition (MA) reaction whilst halogen substituted BQD undergo nucleophilic vinylic substitution (SNV) mechanism onto amine and thiol moieties on proteins, the allergenic effects of adding substituents on BQ have not been reported. The effects of inserting substituents on the BQ ring has not been studied in animal assays. However, mandated reduction/elimination of animals used in cosmetics testing in Europe has led to an increased need for alternatives for the prediction of skin sensitization potential. Electron withdrawing and electron donating substituents on BQ were assessed for effects on BQ reactivity toward nitrobenzene thiol (NBT). The NBT binding studies demonstrated that addition of EWG to BQ as exemplified by the chlorine substituted BQDs increased reactivity while addition of EDG as in the methyl substituted BQDs reduced reactivity. BQ and BQD skin allerginicity was evaluated in the murine local lymph node assay (LLNA). BQD with electron withdrawing groups had the highest chemical potency followed by unsubstituted BQ and the least potent were the BQD with electron donating groups. The BQD results demonstrate the impact of inductive effects on both BQ reactivity and allergenicity, and suggest the potential utility of chemical reactivity data for electrophilic allergen identification and potency ranking.

The Myeloid U937 Skin Sensitization Test (U-SENS) addresses the activation of dendritic cell event in the adverse outcome pathway for skin sensitization

The U-SENS™ assay, formerly known as MUSST (Myeloid U937 Skin Sensitization Test), is an in vitro method to assess skin sensitization. Dendritic cell activation following exposure to sensitizers was modelled in the U937 human myeloid cell line by measuring the induction of the expression of CD86 by flow cytometry. The predictive performance of U-SENS™ was assessed via a comprehensive comparison analysis with the available human and LLNA data of 175 substances. U-SENS™ showed 79% specificity, 90% sensitivity and 88% accuracy. A four laboratory ring study demonstrated the transferability, reliability and reproducibility of U-SENS™, with a reproducibility of 95% within laboratories and 79% between-laboratories, showing that the U-SENS™ assay is a promising tool in a skin sensitization risk assessment testing strategy.

A novel class of mitochondria-targeted soft electrophiles modifies mitochondrial proteins and inhibits mitochondrial metabolism in breast cancer cells through redox mechanisms

Despite advances in screening and treatment over the past several years, breast cancer remains a leading cause of cancer-related death among women in the United States. A major goal in breast cancer treatment is to develop safe and clinically useful therapeutic agents that will prevent the recurrence of breast cancers after front-line therapeutics have failed. Ideally, these agents would have relatively low toxicity against normal cells, and will specifically inhibit the growth and proliferation of cancer cells. Our group and others have previously demonstrated that breast cancer cells exhibit increased mitochondrial oxygen consumption compared with non-tumorigenic breast epithelial cells. This suggests that it may be possible to deliver redox active compounds to the mitochondria to selectively inhibit cancer cell metabolism. To demonstrate proof-of-principle, a series of mitochondria-targeted soft electrophiles (MTSEs) has been designed which selectively accumulate within the mitochondria of highly energetic breast cancer cells and modify mitochondrial proteins. A prototype MTSE, IBTP, significantly inhibits mitochondrial oxidative phosphorylation, resulting in decreased breast cancer cell proliferation, cell attachment, and migration in vitro. These results suggest MTSEs may represent a novel class of anti-cancer agents that prevent cancer cell growth by modification of specific mitochondrial proteins.

Modeling skin sensitization potential of mechanistically hard-to-be-classified aniline and phenol compounds with quantum mechanistic properties

Background

Advanced structure-activity relationship (SAR) modeling can be used as an alternative tool for identification of skin sensitizers and in improvement of the medical diagnosis and more effective practical measures to reduce the causative chemical exposures. It can also circumvent ethical concern of using animals in toxicological tests, and reduce time and cost. Compounds with aniline or phenol moieties represent two large classes of frequently skin sensitizing chemicals but exhibiting very variable, and difficult to predict, potency. The mechanisms of action are not well-understood.

Methods

A group of mechanistically hard-to-be-classified aniline and phenol chemicals were collected. An in silico model was established by statistical analysis of quantum descriptors for the determination of the relationship between their chemical structures and skin sensitization potential. The sensitization mechanisms were investigated based on the features of the established model. Then the model was utilized to analyze a subset of FDA approved drugs containing aniline and/or phenol groups for prediction of their skin sensitization potential.

Results and discussion

A linear discriminant model using the energy of the highest occupied molecular orbital (ϵ_HOMO) as the descriptor yielded high prediction accuracy. The contribution of ϵ_HOMO as a major determinant may suggest that autoxidation or free radical binding could be involved. The model was further applied to predict allergic potential of a subset of FDA approved drugs containing aniline and/or phenol moiety. The predictions imply that similar mechanisms (autoxidation or free radical binding) may also play a role in the skin sensitization caused by these drugs.

Conclusions

An accurate and simple quantum mechanistic model has been developed to predict the skin sensitization potential of mechanistically hard-to-be-classified aniline and phenol chemicals. The model could be useful for the skin sensitization potential predictions of a subset of FDA approved drugs.

Electronic supplementary material

The online version of this article (doi:10.1186/2050-6511-15-76) contains supplementary material, which is available to authorized users.

Towards AOP application--implementation of an integrated approach to testing and assessment (IATA) into a pipeline tool for skin sensitization

Since the OECD published the Adverse Outcome Pathway (AOP) for skin sensitization, many efforts have focused on how to integrate and interpret nonstandard information generated for key events in a manner that can be practically useful for decision making. These types of frameworks are known as Integrated Approaches to Testing and Assessment (IATA). Here we have outlined an IATA for skin sensitization which focuses on existing information including non testing approaches such as QSAR and read-across. The IATA was implemented into a pipeline tool using OASIS technology to provide a means of systematically collating and compiling relevant information which could be used in an assessment of skin sensitization potential. A test set of 100 substances with available skin sensitization information was profiled using the pipeline IATA. In silico and in chemico profiling information alone was able to correctly predict skin sensitization potential, with a preliminary accuracy of 73.85%. Information from other relevant endpoints (e.g., Ames mutagenicity) was found to improve the accuracy (to 87.6%) when coupled with a reaction chemistry mechanistic understanding. This pipeline platform could be useful in the assessment of skin sensitization potential and marks a step change in how non testing approaches can be practically applied.

The definition of the applicability domain relevant to skin sensitization for the aromatic nucleophilic substitution mechanism

This study outlines how a glutathione reactivity assay (so-called in chemico data) can be used to define the applicability domain for the nucleophilic aromatic substitution (S(N)Ar) reaction for benzenes. This reaction is one of the six mechanistic domains that have been shown to be important in toxicological endpoints in which the ability to bind covalently to a protein is a key molecular initiating event. This study has analysed the experimental data, allowing a clear and interpretable structure-activity relationship to be developed for the S(N)Ar domain. The applicability domain has resulted in a series of structural alerts. The definition of the applicability domain for the S(N)Ar reaction and the resulting structural alerts are likely to be beneficial in the development of computational tools for category formation and read-across. The study concludes with how this information can be used in the development of adverse outcome pathways.

Guiding principles for the implementation of non-animal safety assessment approaches for cosmetics: skin sensitisation

Characterisation of skin sensitisation potential is a key endpoint for the safety assessment of cosmetic ingredients especially when significant dermal exposure to an ingredient is expected. At present the mouse local lymph node assay (LLNA) remains the 'gold standard' test method for this purpose however non-animal test methods are under development that aim to replace the need for new animal test data. COLIPA (the European Cosmetics Association) funds an extensive programme of skin sensitisation research, method development and method evaluation and helped coordinate the early evaluation of the three test methods currently undergoing pre-validation. In May 2010, a COLIPA scientific meeting was held to analyse to what extent skin sensitisation safety assessments for cosmetic ingredients can be made in the absence of animal data. In order to propose guiding principles for the application and further development of non-animal safety assessment strategies it was evaluated how and when non-animal test methods, predictions based on physico-chemical properties (including in silico tools), threshold concepts and weight-of-evidence based hazard characterisation could be used to enable safety decisions. Generation and assessment of potency information from alternative tools which at present is predominantly derived from the LLNA is considered the future key research area.