Quantum-Mechanical Approach to Predicting the Carcinogenic Potency of N-Nitroso Impurities in Pharmaceuticals.

N-Nitroso contaminants in medicinal products are of concern due to their high carcinogenic potency; however, not all these compounds are created equal, and some are relatively benign chemicals. Understanding the structure-activity relationships (SARs) that drive hazards in one molecule versus another is key to both protecting human health and alleviating costly and sometimes inaccurate animal testing. Here, we report on an extension of the CADRE (computer-aided discovery and REdesign) platform, which is used broadly by the pharmaceutical and personal care industries to assess environmental and human health endpoints, to predict the carcinogenic potency of N-nitroso compounds. The model distinguishes compounds in three potency categories with 77% accuracy in external testing, which surpasses the reproducibility of rodent cancer bioassays and constraints imposed by limited (high-quality) data. The robustness of predictions for more complex pharmaceuticals is maximized by capturing key SARs using quantum mechanics, that is, by hinging the model on the underlying chemistry versus chemicals in the training set. To this end, the present approach can be leveraged in a quantitative hazard assessment and to offer qualitative guidance using electronic structure comparisons between well-studied analogues and unknown contaminants.

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.

Electronic Effects of Support Doping on Hydrotalcite-Supported Iridium N-Heterocyclic Carbene Complexes.

The electronic effects of supports on immobilized organometallic complexes impact their activity and lifetime, yet remain poorly understood. Here we describe a systematic study of the support effects experienced by an organometallic complex immobilized on doped hydrotalcite-like materials. To that end, we describe the synthesis and characterization of the first organometallic species immobilized on a palette of doped hydrotalcites via sulfonate linkers. The organometallic species consists of iridium N-heterocyclic carbene (NHC) carbonyl complex ([Na][Ir-(NHC-Ph-SO3)2(CO)2]), a highly active molecular catalyst for transfer hydrogenation of glycerol. The hydrotalcite supports are composed of Al, Mg, and a compatible transition-metal dopant (Fe, Cu, Ni, Zn). The materials were characterized extensively by STEM, XPS, TGA, PXRD, FT-IR, N2 desorption, ICP-AES, TPD, and microcalorimetry to probe the morphology and electronic properties of the support and elucidate structure-property relationships.

Going All In: A Strategic Investment in In Silico Toxicology.

As vast numbers of new chemicals are introduced to market annually, we are faced with the grand challenge of protecting humans and the environment while minimizing economically and ethically costly animal testing. In silico models promise to be the solution we seek, but we find ourselves at crossroads of future development efforts that would ensure standalone applicability and reliability of these tools. A conscientious effort that prioritizes experimental testing to support the needs of in silico models (versus regulatory needs) is called for to achieve this goal. Using economic analogy in the title of this work, we argue that a prudent investment is to go all-in to support in silico model development, rather than gamble our future by keeping the status quo of a "balanced portfolio" of testing approaches. We discuss two paths to future in silico toxicology-one based on big-data statistics ("broadsword"), and the other based on direct modeling of molecular interactions ("scalpel")-and offer rationale that the latter approach is more transparent, is better aligned with our quest for fundamental knowledge, and has a greater potential to succeed if we are willing to transform our toxicity-testing paradigm.

Correction: Transfer hydrogenation of carbon dioxide and bicarbonate from glycerol under aqueous conditions.

Correction for 'Transfer hydrogenation of carbon dioxide and bicarbonate from glycerol under aqueous conditions' by Jacob M. Heltzel et al., Chem. Commun., 2018, 54, 6184-6187.

Microwave-Assisted Decarbonylation of Biomass-Derived Aldehydes using Pd-Doped Hydrotalcites.

Catalytic decarbonylation is an underexplored strategy for deoxygenation of biomass-derived aldehydes owing to a lack of low-cost and robust heterogeneous catalysts that can operate in benign solvents. A family of Pd-functionalized hydrotalcites (Pd-HTs) were synthesized, characterized, and applied to the decarbonylation of furfural, 5-hydroxymethylfurfural (HMF), and aromatic and aliphatic aldehydes under microwave conditions. This catalytic system delivered enhanced decarbonylation yields and turnover frequencies, even at a low Pd loading (0.5 mol %). Furfural decarbonylation was optimized in a benign solvent (ethanol) compatible with biomass processing; HMF selectively afforded an excellent yield (93 %) of furfuryl alcohol without humin formation; however, a longer reaction favored the formation of furan through tandem alcohol dehydrogenation and decarbonylation. Yields of the substituted benzaldehydes (37-99 %) were proportional to the calculated Mulliken charge of the carbonyl carbon. Activity and selectivity reflected loading-dependent Pd speciation. Continuous-flow testing of the best Pd-HT catalyst delivered good stability over 16 h on stream, with near-quantitative conversion of HMF.

CRISPR-Generated Nrf2a Loss- and Gain-of-Function Mutants Facilitate Mechanistic Analysis of Chemical Oxidative Stress-Mediated Toxicity in Zebrafish.

The transcription factor Nrf2a induces a cellular antioxidant response and provides protection against chemical-induced oxidative stress, as well as playing a critical role in development and disease. Zebrafish are a powerful model to study the role of Nrf2a in these processes but have been limited by reliance on transient gene knockdown techniques or mutants with only partial functional alteration. We developed several lines of zebrafish carrying different null (loss of function, LOF) or hyperactive (gain of function, GOF) mutations to facilitate our understanding of the Nrf2a pathway in protecting against oxidative stress. The mutants confirmed Nrf2a dependence for induction of the antioxidant genes gclc, gstp, prdx1, and gpx1a and identified a role for Nrf2a in the baseline expression of these genes, as well as for sod1. Specifically, the 4-fold induction of gstp by tert-butyl hydroperoxide (tBHP) in wild type fish was abolished in LOF mutants. In addition, baseline gstp expression in GOF mutants increased by 12.6-fold and in LOF mutants was 0.8-fold relative to wild type. Nrf2a LOF mutants showed increased sensitivity to the acute toxicity of cumene hydroperoxide (CHP) and tBHP throughout the first 4 days of development. Conversely, GOF mutants were less sensitive to CHP toxicity during the first 4 days of development and were protected against the toxicity of both hydroperoxides after 4 dpf. Neither gain nor loss of Nrf2a modulated the toxicity of R-(-)-carvone (CAR), despite the ability of this compound to potently induce Nrf2a-dependent antioxidant genes. Similar to other species, GOF zebrafish mutants exhibited significant growth and survival defects. In summary, these new genetic tools can be used to facilitate the identification of downstream gene targets of Nrf2a, better define the role of Nrf2a in the toxicity of environmental chemicals, and further the study of diseases involving altered Nrf2a function.

Decarbonylative Olefination of Aldehydes to Alkenes.

New atom-economical alternatives to Wittig chemistry are needed to construct olefins from carbonyl compounds, but none have been developed to-date. Here we report an atom-economical olefination of carbonyls via aldol-decarbonylative coupling of aldehydes using robust and recyclable supported Pd catalysts, producing only CO and H2O as waste. The reaction affords homocoupling of aliphatic aldehydes, as well as heterocoupling of aliphatic and aromatic ones. Computations provide insight into the selectivity and thermodynamics of the reaction. The tandem aldol-decarbonylation reaction opens the door to exploration of new carbonyl reactivity to construct olefins.

Toward Less Hazardous Industrial Compounds: Coupling Quantum Mechanical Computations, Biomarker Responses, and Behavioral Profiles To Identify Bioactivity of SN2 Electrophiles in Alternative Vertebrate Models.

Sustainable molecular design of less hazardous chemicals promises to reduce risks to public health and the environment. Computational chemistry modeling coupled with alternative toxicology models (e.g., larval fish) present unique high-throughput opportunities to understand structural characteristics eliciting adverse outcomes. Numerous environmental contaminants with reactive properties can elicit oxidative stress, an important toxicological response associated with diverse adverse outcomes (i.e., cancer, diabetes, neurodegenerative disorders, etc.). We examined a common chemical mechanism (bimolecular nucleophilic substitution (SN2)) associated with oxidative stress using property-based computational modeling coupled with acute (mortality) and sublethal (glutathione, photomotor behavior) responses in the zebrafish (Danio rerio) and the fathead minnow (Pimephales promelas) models to identify whether relationships exist among biological responses and molecular attributes of industrial chemicals. Following standardized methods, embryonic zebrafish and larval fathead minnows were exposed separately to eight different SN2 compounds for 96 h. Acute and sublethal responses were compared to computationally derived in silico chemical descriptors. Specifically, frontier molecular orbital energies were significantly related to acute LC50 values and photomotor response (PMR) no observed effect concentrations (NOECs) in both fathead minnow and zebrafish. This reactivity index, LC50 values, and PMR NOECs were also significantly related to whole body glutathione (GSH) levels, suggesting that acute and chronic toxicity results from protein adduct formation for SN2 electrophiles. Shared refractory locomotor response patterns among study compounds and two alternative vertebrate models appear informative of electrophilic properties associated with oxidative stress for SN2 chemicals. Electrophilic parameters derived from frontier molecular orbitals were predictive of experimental in vivo acute and sublethal toxicity. These observations provide important implications for identifying and designing less hazardous industrial chemicals with reduced potential to elicit oxidative stress through bimolecular nucleophilic substitution.

Kinetics of Glutathione Depletion and Antioxidant Gene Expression as Indicators of Chemical Modes of Action Assessed in Vitro in Mouse Hepatocytes with Enhanced Glutathione Synthesis.

Here we report a vertically integrated in vitro - in silico study that aims to elucidate the molecular initiating events involved in the induction of oxidative stress (OS) by seven diverse chemicals (cumene hydroperoxide, t-butyl hydroperoxide, hydroquinone, t-butyl hydroquinone, bisphenol A, Dinoseb, and perfluorooctanoic acid). To that end, we probe the relationship between chemical properties, cell viability, glutathione (GSH) depletion, and antioxidant gene expression. Concentration-dependent effects on cell viability were assessed by MTT assay in two Hepa-1 derived mouse liver cell lines: a control plasmid vector transfected cell line (Hepa-V), and a cell line with increased glutamate-cysteine ligase (GCL) activity and GSH content (CR17). Changes to intracellular GSH content and mRNA expression levels for the Nrf2-driven antioxidant genes Gclc, Gclm, heme oxygenase-1 ( Hmox1), and NADPH quinone oxidoreductase-1 ( Nqo1) were monitored after sublethal exposure to the chemicals. In silico models of covalent and redox reactivity were used to rationalize differences in activity of quinones and peroxides. Our findings show CR17 cells were generally more resistant to chemical toxicity and showed markedly attenuated induction of OS biomarkers; however, differences in viability effects between the two cell lines were not the same for all chemicals. The results highlight the vital role of GSH in protecting against oxidative stress-inducing chemicals as well as the importance of probing molecular initiating events in order to identify chemicals with lower potential to cause oxidative stress.

Comparative behavioral toxicology with two common larval fish models: Exploring relationships among modes of action and locomotor responses.

Behavioral responses inform toxicology studies by rapidly and sensitively detecting molecular initiation events that propagate to physiological changes in individuals. These behavioral responses can be unique to chemical specific mechanisms and modes of action (MOA) and thus present diagnostic utility. In an initial effort to explore the use of larval fish behavioral response patterns in screening environmental contaminants for toxicity and to identify behavioral responses associated with common chemical specific MOAs, we employed the two most common fish models, the zebrafish and the fathead minnow, to define toxicant induced swimming activity alterations during interchanging photoperiods. Though the fathead minnow (Pimephales promelas) is a common model for aquatic toxicology research and regulatory toxicology practice, this model has received little attention in behavioral studies compared to the zebrafish, a common biomedical model. We specifically compared behavioral responses among 7 different chemicals (1-heptanol, phenol, R-(-)-carvone, citalopram, diazinon, pentylenetetrazole (PTZ), and xylazine) that were selected and classified based on anticipated MOA (nonpolar narcosis, polar narcosis, electrophile, specific mechanism) according to traditional approaches to examine whether these comparative responses differ among chemicals with various structure-based predicted toxicity. Following standardized experimental guidelines, zebrafish embryos and fathead minnow larvae were exposed for 96 h to each compound then were observed using digital behavioral analysis. Behavioral observations included photomotor responses, distance traveled, and stimulatory, refractory and cruising locomotor activity. Though fathead minnow larvae displayed greater behavioral sensitivity to 1-heptanol, phenol and citalopram, zebrafish were more sensitive to diazinon and R-(-)-carvone. Both fish models were equally sensitive to xylazine and PTZ. Further, the pharmaceuticals citalopram and xylazine significantly affected behavior at therapeutic hazard values, and each of the seven chemicals elicited unique behavioral response profiles. Larval fish behaviors appear useful as early tier diagnostics to identify mechanisms and pathways associated with diverse biological activities for chemicals lacking mechanistic data.

Transfer hydrogenation of carbon dioxide and bicarbonate from glycerol under aqueous conditions.

The transfer hydrogenation of CO2 from glycerol to afford formic and lactic acid is a highly attractive path to valorizing two waste streams and is a significantly more thermodynamically favorable process than direct CO2 hydrogenation. We report the first homogeneous catalyst for this transformation consisting of a water-soluble Ru N-heterocyclic carbene complex. The catalyst affords lactic and formic acid selectively in the presence of a base at temperatures between 150 and 225 °C. Carbonate salts can also be utilized in place of CO2, affording the same products at higher rates.

The Molecular Design Research Network.

Herein, we provide an overview of a research network that is aimed at fostering interdisciplinary collaboration between chemists and toxicologists with the goal of rationally designing safer commercial chemicals. The collaborative is the Molecular Design Research Network (MoDRN) that was created in 2013 with funding from the EPA-National Science Foundation Networks for Sustainable Molecular Design and Synthesis (NSMDS) program. MoDRN is led by 4 universities, Baylor University, University of Washington, The George Washington University, and Yale University. The overarching goal of the network is to enable and empower the design of safer chemicals based on the fourth Principle of Green Chemistry that states, "chemical products should be designed to preserve efficacy of function while minimizing toxicity."

Toward the Design of Less Hazardous Chemicals: Exploring Comparative Oxidative Stress in Two Common Animal Models.

Sustainable molecular design of less hazardous chemicals presents a potentially transformative approach to protect public health and the environment. Relationships between molecular descriptors and toxicity thresholds previously identified the octanol-water distribution coefficient, log D, and the HOMO-LUMO energy gap, ΔE, as two useful properties in the identification of reduced aquatic toxicity. To determine whether these two property-based guidelines are applicable to sublethal oxidative stress (OS) responses, two common aquatic in vivo models, the fathead minnow (Pimephales promelas) and zebrafish (Danio rerio), were employed to examine traditional biochemical biomarkers (lipid peroxidation, DNA damage, and total glutathione) and antioxidant gene activation following exposure to eight structurally diverse industrial chemicals (bisphenol A, cumene hydroperoxide, dinoseb, hydroquinone, indene, perfluorooctanoic acid, R-(-)-carvone, and tert-butyl hydroperoxide). Bisphenol A, cumene hydroperoxide, dinoseb, and hydroquinone were consistent inducers of OS. Glutathione was the most consistently affected biomarker, suggesting its utility as a sensitivity response to support the design of less hazardous chemicals. Antioxidant gene expression (changes in nrf2, gclc, gst, and sod) was most significantly (p < 0.05) altered by R-(-)-carvone, cumene hydroperoxide, and bisphenol A. Results from the present study indicate that metabolism of parent chemicals and the role of their metabolites in molecular initiating events should be considered during the design of less hazardous chemicals. Current empirical and computational findings identify the need for future derivation of sustainable molecular design guidelines for electrophilic reactive chemicals (e.g., SN2 nucleophilic substitution and Michael addition reactivity) to reduce OS related adverse outcomes in vivo.

CADRE-SS, an in Silico Tool for Predicting Skin Sensitization Potential Based on Modeling of Molecular Interactions.

Using computer models to accurately predict toxicity outcomes is considered to be a major challenge. However, state-of-the-art computational chemistry techniques can now be incorporated in predictive models, supported by advances in mechanistic toxicology and the exponential growth of computing resources witnessed over the past decade. The CADRE (Computer-Aided Discovery and REdesign) platform relies on quantum-mechanical modeling of molecular interactions that represent key biochemical triggers in toxicity pathways. Here, we present an external validation exercise for CADRE-SS, a variant developed to predict the skin sensitization potential of commercial chemicals. CADRE-SS is a hybrid model that evaluates skin permeability using Monte Carlo simulations, assigns reactive centers in a molecule and possible biotransformations via expert rules, and determines reactivity with skin proteins via quantum-mechanical modeling. The results were promising with an overall very good concordance of 93% between experimental and predicted values. Comparison to performance metrics yielded by other tools available for this endpoint suggests that CADRE-SS offers distinct advantages for first-round screenings of chemicals and could be used as an in silico alternative to animal tests where permissible by legislative programs.

Identifying and designing chemicals with minimal acute aquatic toxicity.

Industrial ecology has revolutionized our understanding of material stocks and flows in our economy and society. For this important discipline to have even deeper impact, we must understand the inherent nature of these materials in terms of human health and the environment. This paper focuses on methods to design synthetic chemicals to reduce their intrinsic ability to cause adverse consequence to the biosphere. Advances in the fields of computational chemistry and molecular toxicology in recent decades allow the development of predictive models that inform the design of molecules with reduced potential to be toxic to humans or the environment. The approach presented herein builds on the important work in quantitative structure-activity relationships by linking toxicological and chemical mechanistic insights to the identification of critical physical-chemical properties needed to be modified. This in silico approach yields design guidelines using boundary values for physiochemical properties. Acute aquatic toxicity serves as a model endpoint in this study. Defining value ranges for properties related to bioavailability and reactivity eliminates 99% of the chemicals in the highest concern for acute aquatic toxicity category. This approach and its future implementations are expected to yield very powerful tools for life cycle assessment practitioners and molecular designers that allow rapid assessment of multiple environmental and human health endpoints and inform modifications to minimize hazard.