Mechanisms of Chemical Carcinogenicity and Mutagenicity: A Review with Implications for Predictive Toxicology

Prioritizing of potential environmental exposure carcinogens beyond IARC group 1-2B based on weight of evidence (WoE) approach

Environmental exposures are the main cause of cancer, and their carcinogenicity has not been fully evaluated, identifying potential carcinogens that have not been evaluated is critical for safety. This study is the first to propose a weight of evidence (WoE) approach based on computational methods to prioritize potential carcinogens. Computational methods such as read across, structural alert, (Quantitative) structure-activity relationship and chemical-disease association were evaluated and integrated. Four different WoE approach was evaluated, compared to the best single method, the WoE-1 approach gained 0.21 and 0.39 improvement in the area under the receiver operating characteristic curve (AUC) and Matthew's correlation coefficient (MCC) value, respectively. The evaluation of 681 environmental exposures beyond IARC list 1-2B prioritized 52 chemicals of high carcinogenic concern, of which 21 compounds were known carcinogens or suspected carcinogens, and eight compounds were identified as potential carcinogens for the first time. This study illustrated that the WoE approach can effectively complement different computational methods, and can be used to prioritize chemicals of carcinogenic concern.

Safety evaluation of 8 drug degradants present in over-the-counter cough and cold medications

Although the United States Food & Drug Administration (FDA) has provided guidance on the control of drug degradants for prescription drugs, there is less guidance on how to set degradant specifications for FDA OTC monograph drugs. Given that extensive impurity testing was not part of the safety paradigm in original OTC monographs, a weight of evidence (WOE) approach to qualify OTC degradants is proposed. This approach relies on in silico tools and read-across approaches alongside standard toxicity testing to determine safety. Using several drugs marketed under 21 CFR 341 as case studies, this research demonstrates the utility of a WOE approach across data-rich and data-poor degradants. Based on degradant levels ranging from 1 to 4% of the maximum daily doses of each case study drug and 10th percentile body weight data for each patient group, children were recognized as having the highest potential exposure relative to adults per body mass. Depending on data availability and relationship to the parent API, margins of safety (MOS) or exposure margins were calculated for each degradant. The findings supported safe use, and indicated that this contemporary WOE approach could be utilized to assess OTC degradants. This approach is valuable to establish specifications for degradants in OTCs.

Prediction of molecular-specific mutagenic alerts and related mechanisms of chemicals by a convolutional neural network (CNN) model based on SMILES split

Structural alerts (SAs) are essential to identify chemicals for toxicity evaluation and health risk assessment. We constructed a novel SMILES split-based deep learning model (SSDL) that was trained and verified with 5850 chemicals from the ISSSTY database and 384 external test chemicals from published papers. The training accuracy was above 0.90 and the evaluation metrics (precision, recall and F1-score) all reached 0.78 or above on both internal and external test chemicals. In this model, the molecular-specific fragment importance of chemicals was first quantified independently. Then, the SA identification method based on the importance of these fragments was statistically analyzed and verified with the ISSSTY test and external test chemicals containing one of 28 typical SAs, and most of the performances were better than that of expert rules. Furthermore, a mutagenicity mechanism prediction method was developed using 237 chemicals with four known mutagenic mechanisms based on molecular similarity calibrated by the SSDL method and fragment importance, which significantly improved accuracy in three mechanisms and had comparable accuracy in the other one compared to traditional methods. Overall, the SSDL model quantifying fragment toxicity within molecules would be a novel potentially powerful tool in the determination and visualization of molecular-specific SAs and the prediction of mutagenicity mechanisms for environmental or industrial compounds and drugs.

Deciphering exogenous chemical carcinogenicity through interpretable deep learning: A novel approach for evaluating atmospheric pollutant hazards

Cancer remains a significant global health concern, with millions of deaths attributed to it annually. Environmental pollutants play a pivotal role in cancer etiology and contribute to the growing prevalence of this disease. The carcinogenic assessment of these pollutants is crucial for chemical health evaluation and environmental risk assessments. Traditional experimental methods are expensive and time-consuming, prompting the development of alternative approaches such as in silico methods. In this regard, deep learning (DL) has shown potential but lacks optimal performance and interpretability. This study introduces an interpretable DL model called CarcGC for chemical carcinogenicity prediction, utilizing a graph convolutional neural network (GCN) that employs molecular structural graphs as inputs. Compared to existing models, CarcGC demonstrated enhanced performance, with the area under the receiver operating characteristic curve (AUCROC) reaching 0.808 on the test set. Due to air pollution is closely related to the incidence of lung cancers, we applied the CarcGC to predict the potential carcinogenicity of chemicals listed in the United States Environmental Protection Agency's Hazardous Air Pollutants (HAPs) inventory, offering a foundation for environmental carcinogenicity screening. This study highlights the potential of artificially intelligent methods in carcinogenicity prediction and underscores the value of CarcGC interpretability in revealing the structural basis and molecular mechanisms underlying chemical carcinogenicity.

The comprehensive prediction of carcinogenic potency and tumorigenic dose (TD50) for two problematic N-nitrosamines in food: NMAMPA and NMAMBA using toxicology in silico methods

The identification and toxicological assessment of potential carcinogens is of paramount importance for public health and safety. This study aimed to predict the carcinogenic potency and tumorigenic dose (TD50) for two problematic N-nitrosamines (N-NAs) commonly found in food: N-2-methylpropyl-N-1-methylacetonylnitrosamine (NMAMPA, CAS: 93755-83-0) and N-3-Methylbutyl-N-1-methylacetonylnitrosamine (NMAMBA, CAS: 71016-15-4). To achieve this goal, in silico toxicology methods were employed due to their practical applications and potential in risk assessment. The justification for conducting these studies was incoherent results published by the European Food Safety Authority (EFSA). For this purpose, we applied various in silico tools, including qualitative methods (ToxTree, ProTox II and CarcinoPred-EL) and quantitative methods (QSAR Toolbox and LAZAR) were applied to predict the carcinogenic potency. These tools leverage computational approaches to analyze chemical structures for finding toxicophores and generating predictions, making them efficient alternatives to traditional in vivo experiments. The results obtained indicated that N-NAs are carcinogenic compounds, and quantitative data was obtained in the form of estimated doses of TD50 for the compounds tested.

Toxicological Profiling of Potential Shikimate Kinase Inhibitors Against Mycobacterium tuberculosis

Over the last decade, Mycobacterium tuberculosis has mutated into a putative 'superbug', as treatments against it have failed due to increasing antimicrobial resistance. As a result, the rising incidence of multidrug-resistant tuberculosis (MDR-TB) is posing a significant public health threat, thus, the need to develop effective drugs for MDR-TB has become an urgent priority. To identify new drug candidates for the treatment of MDR-TB, the present study was based on mycobacterial shikimate kinase (MtSK) as the pharmacological target. One hundred potential MtSK inhibitors were identified from literature and database searches to identify compounds that were designed to specifically function as MtSK antagonists. The ADME properties of these compounds were evaluated by using the SwissADME web tool. ProTox-II software was also used to investigate any potential endocrine disrupting effects, mediated through their interaction with oestrogenic and/or androgenic receptors. This study also aimed to predict LD50 values of potential drug candidates that would be active against the standard H37Rv strain of M. tuberculosis, by using the ProTox-II in silico tool. The molecules for which no structural hazard alerts were identified with these software tools were further subjected to molecular docking analyses and molecular dynamic simulations to estimate their ability to interact with the MtSK enzyme. Preliminary results from SwissADME indicated that 30 molecules were drug-like, due to their physicochemical and pharmacokinetic properties. However, subsequent analysis with ToxTree and ProTox-II indicated that only three of these 30 drug-like molecules were suitable for taking forward into further in vitro experiments. This study, which is based on the use of commonly used open-source in silico tools, identified new MtSK ligands for potential use in the development of new drugs for the therapeutic management of tuberculosis. An initial prediction of their safety profile was also generated.

An Integrated Workflow Assisted by In Silico Predictions To Expand the List of Priority Polycyclic Aromatic Compounds

The limited information in existing mass spectral libraries hinders an accurate understanding of the composition, behavior, and toxicity of organic pollutants. In this study, a total of 350 polycyclic aromatic compounds (PACs) in 9 categories were successfully identified in fine particulate matter by gas chromatography high resolution mass spectrometry. Using mass spectra and retention indexes predicted by in silico tools as complementary information, the scope of chemical identification was efficiently expanded by 27%. In addition, quantitative structure-activity relationship models provided toxicity data for over 70% of PACs, facilitating a comprehensive health risk assessment. On the basis of extensive identification, the cumulative noncarcinogenic risk of PACs warranted attention. Meanwhile, the carcinogenic risk of 53 individual analogues was noteworthy. These findings suggest that there is a pressing need for an updated list of priority PACs for routine monitoring and toxicological research since legacy polycyclic aromatic hydrocarbons (PAHs) contributed modestly to the overall abundance (18%) and carcinogenic risk (8%). A toxicological priority index approach was applied for relative chemical ranking considering the environmental occurrence, fate, toxicity, and analytical availability. A list of 39 priority analogues was compiled, which predominantly consisted of high-molecular-weight PAHs and alkyl derivatives. These priority PACs further enhanced source interpretation, and the highest carcinogenic risk was attributed to coal combustion.

Insight into personal exposure characteristics and health effects of PM2.5 and PM0.25-bound PAHs and their derivatives with different heating ways in the Fenwei Plain, China

Personal exposure (PE) to polycyclic aromatic hydrocarbons (PAHs) and their derivatives in particulate matter with two aerodynamic sizes of 2.5 and 0.25 μm (PM2.5 and PM0.25) from rural housewives was studied in the Fenwei Plain, China. A total of 15 households were divided into five different groups based on the type of solid fuel and heating device used, including biomass briquette-furnace (BBF), biomass-elevated Kang (BEK), outdoor lump coal-boiler (OLC), indoor briquette coal-stove (IBC), and electricity (ELE). The PE concentrations of the PAHs and biomarkers in urine collected from the participants were determined. The results showed that the PE concentrations of total quantified PAHs in the biomass group (i.e., BBF and BEK) were 2.2 and 2.0 times higher than those in the coal groups (i.e., OLC and IBC) in PM2.5 and PM0.25, respectively. The housewives who used biomass as fuel suffered from higher potential health impacts than the coal fuel users. The incremental lifetime cancer risk for the PAHs in PM2.5 in the BBF and BEK groups exceeded the international safety threshold. Furthermore, the PE concentrations of oxygenated PAH (o-PAHs) in PM2.5 and PM0.25 in the biomass groups and the nitrated PAHs (n-PAHs) in PM0.25 in the coal groups showed strong correlations with the biomarkers. The results of this study proved the associations between exposure to the different classes of PAHs and health hazards. The findings could also serve as a guideline in establishing efficient measures for using solid fuels for cooking and household warming in northern China.

A Systematic Review of Polycyclic Aromatic Hydrocarbon Derivatives: Occurrences, Levels, Biotransformation, Exposure Biomarkers, and Toxicity

Polycyclic aromatic hydrocarbon (PAH) derivatives constitute a significant class of emerging contaminants that have been ubiquitously detected in diverse environmental matrixes, with some even exhibiting higher toxicities than their corresponding parent PAHs. To date, compared with parent PAHs, fewer systematic summaries and reanalyses are available for PAH derivatives with great environmental concerns. This review summarizes the current knowledge on the chemical species, levels, biotransformation patterns, chemical analytical methods, internal exposure routes with representative biomarkers, and toxicity of PAH derivatives, primarily focusing on nitrated PAHs (NPAHs), oxygenated PAHs (OPAHs), halogenated PAHs (XPAHs), and alkylated PAHs (APAHs). A collection of 188 compounds from four categories, 44 NPAHs, 36 OPAHs, 56 APAHs, and 52 XPAHs, has been compiled from 114 studies that documented the environmental presence of PAH derivatives. These compounds exhibited weighted average air concentrations that varied from a lower limit of 0.019 pg/m3 to a higher threshold of 4060 pg/m3. Different analytical methods utilizing comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry (GC × GC-TOF-MS), gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS), comprehensive two-dimensional gas chromatography coupled to quadrupole mass spectrometry (GC × GC-QQQ-MS), and Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS), that adopted untargeted strategies for the identification of PAH derivatives are also reviewed here. Additionally, an in-depth analysis of biotransformation patterns for each category is provided, including the likelihood of specific biotransformation reaction types. For the toxicity, we primarily summarized key metabolic activation pathways, which could result in the formation of reactive metabolites capable of covalently bonding with DNA and tissue proteins, and potential health outcomes such as carcinogenicity and genotoxicity, oxidative stress, inflammation and immunotoxicity, and developmental toxicity that might be mediated by the aryl hydrocarbon receptor (AhR). Finally, we pinpoint research challenges and emphasize the need for further studies on identifying PAH derivatives, tracking external exposure levels, evaluating internal exposure levels and associated toxicity, clarifying exposure routes, and considering mixture exposure effects. This review aims to provide a broad understanding of PAH derivatives' identification, environmental occurrence, human exposure, biotransformation, and toxicity, offering a valuable reference for guiding future research in this underexplored area.

DCAMCP: A deep learning model based on capsule network and attention mechanism for molecular carcinogenicity prediction

The carcinogenicity of drugs can have a serious impact on human health, so carcinogenicity testing of new compounds is very necessary before being put on the market. Currently, many methods have been used to predict the carcinogenicity of compounds. However, most methods have limited predictive power and there is still much room for improvement. In this study, we construct a deep learning model based on capsule network and attention mechanism named DCAMCP to discriminate between carcinogenic and non-carcinogenic compounds. We train the DCAMCP on a dataset containing 1564 different compounds through their molecular fingerprints and molecular graph features. The trained model is validated by fivefold cross-validation and external validation. DCAMCP achieves an average accuracy (ACC) of 0.718 ± 0.009, sensitivity (SE) of 0.721 ± 0.006, specificity (SP) of 0.715 ± 0.014 and area under the receiver-operating characteristic curve (AUC) of 0.793 ± 0.012. Meanwhile, comparable results can be achieved on an external validation dataset containing 100 compounds, with an ACC of 0.750, SE of 0.778, SP of 0.727 and AUC of 0.811, which demonstrate the reliability of DCAMCP. The results indicate that our model has made progress in cancer risk assessment and could be used as an efficient tool in drug design.

DeepAmes: A deep learning-powered Ames test predictive model with potential for regulatory application

The Ames assay is required by the regulatory agencies worldwide to assess the mutagenic potential risk of consumer products. As well as this in vitro assay, in silico approaches have been widely used to predict Ames test results as outlined in the International Council for Harmonization (ICH) guidelines. Building on this in silico approach, here we describe DeepAmes, a high performance and robust model developed with a novel deep learning (DL) approach for potential utility in regulatory science. DeepAmes was developed with a large and consistent Ames dataset (>10,000 compounds) and was compared with other five standard Machine Learning (ML) methods. Using a test set of 1,543 compounds, DeepAmes was the best performer in predicting the outcome of Ames assay. In addition, DeepAmes yielded the best and most stable performance up to when compounds were >30% outside of the applicability domain (AD). Regarding the potential for regulatory application, a revised version of DeepAmes with a much-improved sensitivity of 0.87 from 0.47. In conclusion, DeepAmes provides a DL-powered Ames test predictive model for predicting the results of Ames tests; with its defined AD and clear context of use, DeepAmes has potential for utility in regulatory application.

A review of the biological effects of Myrtus communis

The World Health Organization stated that 1.6 million deaths worldwide were caused by contact with chemicals and toxins in 2019. In the same year, the Centers for Disease Control and Prevention stated that natural toxins caused 3960 deaths. Myrtus communis, also known as common Myrtle, is a flowering plant native to the Mediterranean region. Myrtle has been traditionally used to treat diarrhea, inflammation, bleeding, headache, pulmonary and skin diseases. This review was performed to assess Myrtle's protective and therapeutic efficacy against various chemical, natural, and radiational noxious. Multiple databases such as PubMed, Web of Sciences, and Scopus were investigated without publication time limitation. Recent studies have demonstrated its potential as a protective agent against both natural and chemical toxins. One of Myrtle's most significant protective properties is its high antioxidant content. Studies have shown that the antioxidant properties of Myrtle can protect against harmful substances such as heavy metals, pesticides, and other environmental toxins. Additionally, Myrtle has anti-inflammatory properties that can help reduce the damage caused by long-term exposure to toxins. The anti-inflammatory and antimicrobial properties of Myrtle have also proven effective in alleviating gastrointestinal conditions such as gastric ulcers.

Approaches for the setting of occupational exposure limits (OELs) for carcinogens

This article addresses issues of importance for occupational exposure limits (OELs) and chemical carcinogens with a focus on non-threshold carcinogens. It comprises scientific as well as regulatory issues. It is an overview, not a comprehensive review. A central topic is mechanistic research and insights, and its implications for cancer risk assessment. Alongside scientific advancements, the approaches of hazard identification and qualitative and quantitative risk assessment have developed over the years. The key steps in a quantitative risk assessment are outlined, with special attention given to the dose-response assessment and the derivation of an OEL using risk calculations or default assessment factors. The work procedures of several bodies performing cancer hazard identifications and quantitative risk assessments, as well as regulatory procedures to derive OELs for non-threshold carcinogens, are presented. Non-threshold carcinogens for which the European Union (EU) introduced binding OELs in 2017-2019 serve as illustrations together with some currently used strategies in the EU and elsewhere. Available knowledge supports the derivation of health-based OELs (Hb-OELs) for non-threshold carcinogens, and the use of a risk-based approach with low-dose linear extrapolation (linear non-threshold, LNT) as the default for non-threshold carcinogens. However, there is a need to develop methods that allow recent years' advances in cancer research to be used for improving risk estimates. It is recommended that defined risk levels (terminology and numerical values) are harmonised, and that both collective and individual risks are considered and clearly communicated. Socioeconomic aspects should be dealt with transparently and separated from the scientific health risk assessment.

MicotoXilico: An Interactive Database to Predict Mutagenicity, Genotoxicity, and Carcinogenicity of Mycotoxins

Mycotoxins are secondary metabolites produced by certain filamentous fungi. They are common contaminants found in a wide variety of food matrices, thus representing a threat to public health, as they can be carcinogenic, mutagenic, or teratogenic, among other toxic effects. Several hundreds of mycotoxins have been reported, but only a few of them are regulated, due to the lack of data regarding their toxicity and mechanisms of action. Thus, a more comprehensive evaluation of the toxicity of mycotoxins found in foodstuffs is required. In silico toxicology approaches, such as Quantitative Structure-Activity Relationship (QSAR) models, can be used to rapidly assess chemical hazards by predicting different toxicological endpoints. In this work, for the first time, a comprehensive database containing 4360 mycotoxins classified in 170 categories was constructed. Then, specific robust QSAR models for the prediction of mutagenicity, genotoxicity, and carcinogenicity were generated, showing good accuracy, precision, sensitivity, and specificity. It must be highlighted that the developed QSAR models are compliant with the OECD regulatory criteria, and they can be used for regulatory purposes. Finally, all data were integrated into a web server that allows the exploration of the mycotoxin database and toxicity prediction. In conclusion, the developed tool is a valuable resource for scientists, industry, and regulatory agencies to screen the mutagenicity, genotoxicity, and carcinogenicity of non-regulated mycotoxins.

Determination of Potential Genotoxic Impurities (Orthophenylene Diamine Dihydrochloride), 4'-Bromomethyl-2-Cyanobiphenyl, 4'(Dibromomethyl)[1,1'-Biphenyl]-2-Carbonitrile in Telmisartan by ESI-MS/MS

A sensitive, simple, rapid and robust LC-MS/MS method was developed for the determination of potential genotoxic impurities OPDA HCl (orthophenylene diamine dihydrochloride), bromo OTBN (4'-bromomethyl-2-cyanobiphenyl), dibromo (4'(dibromomethyl)[1,1'-biphenyl]-2-carbonitrile) in Telmisartan by using ESI-MS/MS Technic; the study was performed with gradient elution (time/% mobile phase B: 0/10, 3/10, 30/80, 35/80, 36/10, 40/10). The mobile phase consisted of a mixture of formic acid, methanol and acetonitrile. The buffer was degassed before running at a flow rate of 1.0 mL/min. The column temperature was at 40°C. The 20 μL volume of sample was injected per run and peaks were detected using DAD detector. The LC-ESI/MS/MS studies were carried out on Ultivo Triple Quadrupole LC/MS/MS (Agilent, USA) G6470A mass spectrometer, ion source voltage 3500 V, de clustering potential 40 V, entrance potential 10 V, with the nebulizer gas as nitrogen at 45 psi. The LC part consisted of Agilent 1260 series HPLC system with binary gradient pump with a degasser and an auto sampler. Inert sustain AQ-C18, 250 × 4.6 mm, 5-μm particle size was used for chromatographic separation. Developed method is validated as per ICH guidelines and found to be linear, accurate, specific, selective, precise and robust. Test solution was found to be stable up to 48 h. This method can be successfully applied for the determination of genotoxic impurities in Telmisarta for routine analysis and stability assessment.

Exhaustive in silico design and screening of novel antipsychotic compounds with improved pharmacodynamics and blood-brain barrier permeation properties

Antipsychotic drugs or neuroleptics are widely used in the treatment of psychosis as a manifestation of schizophrenia and bipolar disorder. However, their effectiveness largely depends on the blood-brain barrier (BBB) permeation (pharmacokinetics) and drug-receptor pharmacodynamics. Therefore, in this study, we developed and implemented the in silico pipeline to design novel compounds (n = 260) as leads using the standard drug scaffolds with improved PK/PD properties from the standard scaffolds. As a result, the best candidates (n = 3) were evaluated in molecular docking to interact with serotonin and dopamine receptors. Finally, haloperidol (HAL) derivative (1-(4-fluorophenyl)-4-(4-hydroxy-4-{4-[(2-phenyl-1,3-thiazol-4-yl)methyl]phenyl}piperidin-1-yl)butan-1-one) was identified as a "magic shotgun" lead compound with better affinity to the 5-HT2A, 5-HT1D, D2, D3, and 5-HT1B receptors than the control molecule. Additionally, this hit substance was predicted to possess similar BBB permeation properties and much lower toxicological profiles in comparison to HAL. Overall, the proposed rational drug design platform for novel antipsychotic drugs based on the BBB permeation and receptor binding might be an invaluable asset for a medicinal chemist or translational pharmacologist.Communicated by Ramaswamy H. Sarma.

Mutagenic potential and structural alerts of phytotoxins

Toxic plant-produced chemicals, so-called phytotoxins, constitute a category of natural compounds belonging to a diversity of chemical classes. Some of them (e.g., alkaloids, terpenes, saponins) are associated with high toxic potency, while for many of others no toxicological data is available. In this study, the mutagenic potential of 1586 phytotoxins, as obtained from a publicly available database, was investigated applying different in silico approaches. (Q)SAR models (including statistical-based and rule-based systems) were used for the prediction of bacterial in vitro mutagenicity (Ames test) and the results from multiple tools were combined to assign consensus predicted values (i.e., positive, negative, inconclusive). The overall consensus outcome was then employed to investigate relationships between structural features of classes of phytotoxins and potential mutagenicity, allowing the identification of structural alerts raising a specific concern. The results highlighted that about 10% of the screened compounds were predicted to have mutagenic potential and the critical classes of concern, such as alkaloids, were further investigated in terms of subclasses (e.g., indole alkaloids, isoquinoline alkaloids), getting a deeper insight into the mutagenic potential of possible naturally occurring chemicals in plant materials and their structural alerts.

Automated detection of toxicophores and prediction of mutagenicity using PMCSFG algorithm

Maximum common substructures (MCS) have received a lot of attention in the chemoinformatics community. They are typically used as a similarity measure between molecules, showing high predictive performance when used in classification tasks, while being easily explainable substructures. In the present work, we applied the Pairwise Maximum Common Subgraph Feature Generation (PMCSFG) algorithm to automatically detect toxicophores (structural alerts) and to compute fingerprints based on MCS. We present a comparison between our MCS-based fingerprints and 12 well-known chemical fingerprints when used as features in machine learning models. We provide an experimental evaluation and discuss the usefulness of the different methods on mutagenicity data. The features generated by the MCS method have a state-of-the-art performance when predicting mutagenicity, while they are more interpretable than the traditional chemical fingerprints.

From Structural Alerts to Signature Fragment Alerts: A Case Study on Pyrrolizidine Alkaloids

Even though modeling is considered a valid alternative to mutagenicity testing for substances with known structures, it can be applied for mixtures only if all of the single chemical structures are identified. Within the present work, we investigate a new avenue to exploit computational toxicology for mixtures, such as plant-based food ingredients. Indeed, considering that in the absence of toxicological information, an important early consideration is whether any substance may be genotoxic through the mutagenic mechanism of action, we tried to establish a correspondence between genotoxic structural alerts (SAs) and so-called signature fragment alerts (SFAs). Once this correspondence is established, chromatograms could be screened for chemical features associated with genotoxic alerts. Pyrrolizidine alkaloids (PAs), a large group of natural toxins (several of them known as genotoxic) were used as a case study because their early identification would bring significant benefits. The method was built using 56 PA pure standards, resulting in the characterization of signature fragment alerts. Finally, the approach was verified in real plant-based samples such as herbal tea and alfalfa, where the screening of signature fragment alerts allowed highlighting quickly the presence of genotoxic PAs in plant-based mixtures. Therefore, the SFA analysis can be used for risk prioritization of newly identified PAs and for their identification in mixtures, contributing to the unnecessary use of animal experimentation for genotoxicity testing.

Assessing chemical hazard and unraveling binding affinity of priority pollutants to lignin modifying enzymes for environmental remediation

Lignin-modifying enzymes (LMEs) are impactful biocatalysts in environmental remediation applications. However, LMEs-assisted experimental degradation neglects the molecular basis of pollutant degradation. Furthermore, throughout the remediation process, the inherent hazards of environmental pollutants remain untapped for in-depth toxicological endpoints. In this investigation, a predictive toxicological framework and a computational framework adopting LMEs were employed to assess the hazards of Priority Pollutants (PP) and its possible LMEs-assisted catalytic screening. The potential hazardous outcomes of PP were assessed using Quantitative structure-activity relationship (QSARs)-based techniques including Toxtree, ECOSAR, and T.E.S.T. tools. Toxicological findings revealed positive outcomes in a multitude of endpoints for all PP. The PP compound 2,3,7,8-TCDD (dioxin) was found to exhibit the lowest concentration of aquatic toxicity implementing aquatic model systems; LC₅₀ as 0.01, 0.01, 0.04 (mg L^-1) for Fish (96 H), Daphnid (48 H), Green algae (96 H) respectively. T.E.S.T. results revealed that chloroform, and 2-chlorophenol both seem to be developmental toxicants. Subsequently, LMEs-assisted docking procedure was employed in predictive mitigation of PP. The docking approach as predicted degradation revealed the far lowest docking energy score for Versatile peroxidase (VP)- 2,3,7,8-TCDD docked complex with a binding energy of -9.2 (kcal mol^-1), involved PHE-46, PRO-139, PRO-141, ILE-148, LEU-165, HIS-169, LEU-228, MET-262, and MET-265 as key interacting amino acid residues. Second most ranked but lesser than VP, Lignin peroxidase (LiP)- 2,3,7,8-TCDD docked complex exhibited a rather lower binding affinity score (-8.8 kcal mol^-1). Predictive degradation screening employing comparative docking revealed varying binding affinities, portraying that each LMEs member has independent feasibility to bind PP as substrate. Predictive findings endorsed the hazardous nature of associated PP in a multitude of endpoints, which could be attenuated by undertaking LMEs as a predictive approach to protect the environment and implement it in regulatory considerations.

Oxygenated and Nitrated Polycyclic Aromatic Hydrocarbons: Sources, Quantification, Incidence, Toxicity, and Fate in Soil—A Review Study

The genotoxicity, mutagenesis, and carcinogenic effects of polycyclic aromatic hydrocarbon (PAH) derivatives may exceed the parent PAHs. However, their influence on the soil environment has not been explored to a large extent. Oxygenated polycyclic aromatic hydrocarbons (OPAHs) and nitrated polycyclic aromatic hydrocarbons (NPAHs) are typical polar substituted compounds. We offer a review of the literature on the sources, quantification, incidence, toxicity, and transport of these compounds in soil. Although their environmental concentrations are lower than those of their parent compounds, they exert higher toxicity. Both types of substances are basically related to carcinogenesis. OPAHs are not enzymatically activated and can generate reactive oxygen species in biological cells, while NPAHs have been shown to be mutagenic, genotoxic, and cytotoxic. These compounds are largely derived from the transformation of PAHs, but they behave differently in soil because of their higher molecular weight and dissimilar adsorption mechanisms. Therefore, specialized knowledge of model derivatives is required. We also made recommendations for future directions based on existing research. It is expected that the review will trigger scientific discussions and provide a research basis for further study on PAH derivatives in the soil environment.

Review of ecologically relevant in vitro bioassays to supplement current in vivo tests for whole effluent toxicity testing - Part 2: Non-apical endpoints

Whole effluent toxicity (WET) testing uses whole animal exposures to assess the toxicity of complex mixtures, like wastewater. These assessments typically include four apical endpoints: mortality, growth, development, and reproduction. In the last decade, there has been a shift to alternative methods that align with the 3Rs to replace, reduce, and refine the use of animals in research. In vitro bioassays can provide a cost-effective, high-throughput, ethical alternative to in vivo assays. In addition, they can potentially include additional, more sensitive, environmentally relevant endpoints than traditional toxicity tests. However, the ecological relevance of these endpoints must be established before they are adopted into regulatory frameworks. This is Part 2 of a two-part review that aims to identify in vitro bioassays that are linked to ecologically relevant endpoints that could be included in WET testing. Part 2 of this review focuses on non-apical endpoints that should be incorporated into WET testing. In addition to the four apical endpoints addressed in Part 1, this review identified seven additional toxic outcomes: endocrine disruption, xenobiotic metabolism, carcinogenicity, oxidative stress, inflammation, immunotoxicity and neurotoxicity. For each, the response at the molecular or cellular level measured in vitro was linked to the response at the organism level through a toxicity pathway. Literature from 2015 to 2020 was used to identify suitable bioassays that could be incorporated into WET testing.

In silico Prediction and Pharmacokinetic Studies on Glucosinolates as a Potential Drug and Key Inhibitor Molecule for Lanosterol-14α- demethylase: A Fungal Membrane Biosynthesis Enzyme

BACKGROUND

Glucosinolates (β-thioglucoside-N-hydroxysulfates) are a water-soluble organic anion with sulfur- and nitrogen-containing glycosides which are found in abundance in Cruciferous plants. Ergosterol (ERG13) lanosterol-14α-demethylase protein has been targeted for inhibition studies as a key regulator enzyme of fungal membrane biosynthesis.

OBJECTIVES

To understand the molecular mechanism of inhibition of Ergosterol (ERG13) lanosterol- 14α-demethylase by various phytochemicals from brassicales, i.e., glucosinolates and their potential role as putative drug molecules.

METHODS

In this study, in silico analyses were performed to predict the molecular basis of various glucosinolates as a potential inhibitor of lanosterol-14α-demethylase protein, which is a key regulator of fungal membrane biosynthesis and its pharmacodynamics and toxicity profile. 3d structures of various glucosinolates were retrieved from PubChem, and the target protein, lanosterol-14α-demethylase (Pdb ID- 4lxj), was retrieved from the RCSB protein data bank. Molecular docking and interactions were carried out using the PyRx software using the AutoDOCK toolbar with default parameters. Dru- LiTo, ORISIS web servers were used to predict various drug likeliness predictions and Lipinski's Rule of 5, whereas admetSAR was used for prediction of toxicity, and PASS Program was used to study the antifungal and antimicrobial properties of these compounds.

RESULTS

This study shows that among the different compounds screened, gluconasturtiin, Glucotropaeolin, and Indolylmethyl-Glucosinolate showed the highest binding energies of -8.7 kcal/mol, -8.5 kcal/mol, and -8.3 kcal/mol with the lanosterol-14α-demethylase, respectively. Further all the compounds follow the Lipinski's rule as well as they are found to be non-carcinogenic and non-cytotoxic in nature. These compounds also show antifungal properties.

CONCLUSION

This study thus reveals that various glucosinolates interact with the ERG13 enzyme at various amino acid positions, which behaves as a catalytic site, thus indicates the probable mechanism of inactivation, and subsequently, these can be used as potential drug molecules. In vitro studies can be taken to further examine the utility of these compounds as antifungal agents.

Identification of CB1 Ligands among Drugs, Phytochemicals and Natural-Like Compounds: Virtual Screening and In Vitro Verification

Cannabinoid receptor type 1 (CB1) is an important modulator of many key physiological functions and thus a compelling molecular target. However, safe CB1 targeting is a non-trivial task. In recent years, there has been a surge of data indicating that drugs successfully used in the clinic for years (e.g. paracetamol) show CB1 activity. Moreover, there is a lot of promise in finding CB1 ligands in plants other than Cannabis sativa. In this study, we searched for possible CB1 activity among already existing drugs, their metabolites, phytochemicals, and natural-like molecules. We conducted two iterations of virtual screening, verifying the results with in vitro binding and functional assays. The in silico procedure consisted of a wide range of structure- and ligand-based methods, including docking, molecular dynamics, and quantitative structure-activity relationship (QSAR). As a result, we identified travoprost and ginkgetin as CB1 ligands, which provides a starting point for future research on the impact of their metabolites or preparations on the endocannabinoid system. Moreover, we found five natural-like compounds with submicromolar or low micromolar affinity to CB1, including one mixed partial agonist/antagonist viable for hit-to-lead phase. Finally, the computational procedure established in this work will be of use for future screening campaigns for novel CB1 ligands.

Genotoxicity evaluation of a valsartan-related complex N-nitroso-impurity

Recently, the formation of genotoxic and carcinogenic N-nitrosamines impurities during drug manufacturing of tetrazole-containing angiotensin-II blockers has been described. However, drug-related (complex) nitrosamines may also be generated under certain conditions, i.e., through nitrosation of vulnerable amines in drug substances in the presence of nitrite. An investigation of valsartan drug substance showed that a complex API-related N-nitrosamine chemically designated as (S)-2-(((2'-(1H-tetrazol-5-yl)-[1,1'-biphenyl]-4-yl)methyl)(nitroso)amino)-3-methylbutanoic acid (named 181-14) may be generated. 181-14 was shown to be devoid of a mutagenic potential in the Non-GLP Ames test. According to ICH M7 (R1) (2018), impurities that are not mutagenic in the Ames test would be considered Class 5 impurities and limited according to ICH Q3A (R2) and B (R2) (2006) guidelines. However, certain regulatory authorities raised the concern that the Ames test may not be sufficiently sensitive to detect a mutagenic potential of nitrosamines and requested a confirmatory in vivo study using a transgenic animal genotoxicity model. Our data show that 181-14 was not mutagenic in the transgenic gene mutation assay in Muta^TMMice. The data support the conclusion that the Ames test is an adequate and sensitive test system to assess a mutagenic potential of nitrosamines.

Evaluation of fluorene-caused ecotoxicological responses and the mechanism underlying its toxicity in Eisenia fetida: Multi-level analysis of biological organization

Fluorene is an important toxic chemical that exists ubiquitously in the environment, and it has also been suggested to exert potential deleterious effects on soil invertebrates. However, knowledge about the toxic effects of fluorene and its underlying mechanisms of the effects on key soil organism earthworms remains limited. From this view point, this study was undertaken to explore the potential effects of fluorene and its underlying mechanisms in Eisenia fetida at the level of experimental animals, tissue, cell, and molecule. It was concluded that fluorene exerted lethal activity to adult E. fetida on day 14 with the LC₅₀ determined to be 88.61 mg/kg. Fluorene-induced ROS caused oxidative stress in E. fetida, resulting in DNA damage, protein carbonylation, and lipid peroxidation. Moreover, changed antioxidative enzymatic activities, non-enzymatic antioxidative activities, and total antioxidative capacity in E. fetida by fluorene stress are associated with antioxidative and protective effects. High-dose fluorene (> 2.5 mg/kg) exposure significantly caused histopathological lesions including the microstructure of body wall, intestine, and seminal vesicle of earthworms. Also, the reproductive system of E. fetida was clearly disrupted by fluorene stress, leading to poor reproduction ability (decreased cocoon and juvenile production) in earthworms. It is found that E. fetida growth was significantly inhibited when treated with high-dose fluorene, thereby causing normal growth disorders. Additionally, fluorene stress triggered the abnormal mRNA expression related to oxidative stress (e.g., metallothionein and heat shock protein 70), growth (translationally controlled tumour protein), reproduction (annetocin precursor) in E. fetida. Together, both high-dose and long-term exposure elicited more severe poisoning effects on earthworms using the Integrated Biological Response (IBR) index, and E. fetida coelomocyte DNA was the most negatively affected by fluorene stress. This study comprehensively evaluated fluorene-induced toxicity in E. fetida, and its underlying molecular mechanisms mediating the toxic responses have been elucidated. These findings provide valuable data for assessing potential ecological risks posed by fluorene-contaminated soil.

Nonclinical safety evaluation of a novel ionizable lipid for mRNA delivery

mRNA vaccines hold tremendous potential in disease control and prevention for their flexibility with respect to production, application, and design. Recent breakthroughs in mRNA vaccination would have not been possible without major advances in lipid nanoparticles (LNPs) technologies. We developed an LNP containing a novel ionizable cationic lipid, Lipid-1, and three well known excipients. An in silico toxicity hazard assessment for genotoxicity, a genotoxicity assessment, and a dose range finding toxicity study were performed to characterize the safety profile of Lipid-1. The in silico toxicity hazard assessment, utilizing two prediction systems DEREK and Leadscope, did not find any structural alert for mutagenicity and clastogenicity, and prediction in the statistical models were all negative. In addition, applying a read-across approach a structurally very similar compound was tested negative in two in vitro assays confirming the low genotoxicity potential of Lipid-1. A dose range finding toxicity study in rabbits, receiving a single intramuscular injection of either different doses of an mRNA encoding Influenza Hemagglutinin H3 antigen encapsulated in the LNP containing Lipid-1 or the empty LNP, evaluated local tolerance and systemic toxicity during a 2-week observation period. Only rabbits exposed to the vaccine were able to develop a specific IgG response, indicating an appropriate vaccine take. The vaccine was well tolerated up to 250 μg mRNA/injection, which was defined as the No Observed Adverse Effect Level (NOAEL). These results support the use of the LNP containing Lipid-1 as an mRNA delivery system for different vaccine formulations and its deployment into clinical trials.

Kinetics and Reaction Mechanism of Biothiols Involved in SNAr Reactions: An Experimental Study

Few kinetic parameters, or reaction rates, are known up to date in detail about 1-chloro and 1-fluoro-2,4-dinitrobenzene (ClDNB and FDNB, respectively) with a series of biothiols in aqueous media. These biological nucleophiles with thiol groups have been widely used as a reference in nucleophile reactivity assays due to their prevalence and cellular abundance. The main aim of this study was to elucidate the reaction mechanism based on Brönsted-type plots and reactivity patterns of the electrophile/nucleophile pairs. A complete kinetic study was performed in terms of the comparison of Brönsted-type slope parameters (β_nuc) for the reactions and was used for assigning the mechanism and the rate-determining step associated with the reaction route. A mass spectrometry analysis demonstrated that the nucleophilic center of the biothiols is the -SH group and there is only one kinetic product. The kinetic study suggests that the reaction mechanism might be the borderline between concerted and stepwise pathways. An amine–enol equilibrium for the most reactive nucleophiles appears to be the main determining factor controlling the nucleophilic attack in the nucleophilic aromatic substitution reactions investigated, highlighting the anionic form for these nucleophiles. This amine–enol equilibrium involves a hydrogen bond which stabilizes the intermediate species in the reaction pathway. Thus, intramolecular bonds are formed and enhance the nucleophilic strength through the contribution of the solvent surrounding the electrophile/nucleophile pairs. Finally, we highlight the importance of the formation of electrophile/nucleophile adducts that could modify structures and/or functions of biological systems with potential toxic effects. Therefore, it is essential to know all these kinetic and reactivity patterns and their incidence on other studies.

Personal exposure to electrophilic compounds of fine particulate matter and the inflammatory response: The role of atmospheric transformation

Atmospheric oxidation can produce electrophilic compounds, altering the health effects induced by fine particulate matter (PM_2.5); however, little is known about these electrophilic compounds or their health effects. Using electron capture negative ionization, we systematically detected 301 electrophilic compounds from personal PM_2.5 samples in a panel study in urban Beijing. Most were oxygen-containing compounds with 3-17 double bond equivalents (DBE), suggesting the dominance of oxidized aromatic structures. Over 64% of the species, mostly outdoor-originated, were associated with inflammatory cytokines in both exhaled breath condensate and serum. Primary components of polycyclic aromatic hydrocarbons (PAHs) and high-DBE oxygenated PAHs, mainly from fossil fuel combustion, were positively associated with interleukin (IL)- 6, a cytokine related to oxidative homeostasis. Oxidized secondary species, particularly maleic and phthalic anhydrides, were negatively associated with IL-2/IL-8, which changed by - 3.8% to - 16.4% per one-fold increase in the abundance of the secondary source, indicating the immune disorders in response to the oxidized aerosols. Mediation analysis demonstrated the necessity of transformation products between atmospheric oxidation capacity and IL-2/IL-8 inhibition. This study provides new information on particulate electrophilic compounds and highlights the role of atmospheric chemistry in specific immune disorders.

Use of transcriptomics in hazard identification and next generation risk assessment: A case study with clothianidin

Toxicological risk assessment is essential in the evaluation and authorization of different classes of chemical substances. Genotoxicity and mutagenicity testing are of highest priority and rely on established in vitro systems with bacterial and mammalian cells, sometimes followed by in vivo testing using rodent animal models. Transcriptomic approaches have recently also shown their value to determine transcript signatures specific for genotoxicity. Here, we studied how transcriptomic data, in combination with in vitro tests with human cells, can be used for the identification of genotoxic properties of test compounds. To this end, we used liver samples from a 28-day oral toxicity study in rats with the pesticidal active substances imazalil, thiacloprid, and clothianidin, a neonicotinoid-type insecticide with, amongst others, known hepatotoxic properties. Transcriptomic results were bioinformatically evaluated and pointed towards a genotoxic potential of clothianidin. In vitro Comet and γH2AX assays in human HepaRG hepatoma cells, complemented by in silico analyses of mutagenicity, were conducted as follow-up experiments to check if the genotoxicity alert from the transcriptomic study is in line with results from a battery of guideline genotoxicity studies. Our results illustrate the combined use of toxicogenomics, classic toxicological data and new approach methods in risk assessment. By means of a weight-of-evidence decision, we conclude that clothianidin does most likely not pose genotoxic risks to humans.

•

Analysis of clothianidin genotoxicity in silico, in vitro and in vivo.

•

Application of a toxicogenomics approach to analyze genotoxicity.

•

Weight-of-evidence decision supports classification as “non-genotoxic”.

The effects of polycyclic aromatic compounds (PACs) on mammalian ovarian function

•

Toxicity of polycyclic aromatic compounds (PACs) is limited to a subset of PACs.

•

Exposure to these compounds impact major processes necessary for ovarian function.

•

PAC exposure causes follicle loss and aberrant steroid production and angiogenesis.

•

PAC exposure may increase the risk for impaired fertility and ovarian pathologies.

•

The study of PACs as ovarian toxicants should include additional compounds.

Polycyclic aromatic compounds (PACs) are a broad class of contaminants ubiquitously present in the environment due to natural and anthropogenic activities. With increasing industrialization and reliance on petroleum worldwide, PACs are increasingly being detected in different environmental compartments. Previous studies have shown that PACs possess endocrine disruptive properties as these compounds often interfere with hormone signaling and function. In females, the ovary is largely responsible for regulating reproductive and endocrine function and thus, serves as a primary target for PAC-mediated toxicity. Perturbations in the signaling pathways that mediate ovarian folliculogenesis, steroidogenesis and angiogenesis can lead to adverse reproductive outcomes including polycystic ovary syndrome, premature ovarian insufficiency, and infertility. To date, the impact of PACs on ovarian function has focused predominantly on polycyclic aromatic hydrocarbons like benzo(a)pyrene, 3-methylcholanthrene and 7,12-dimethylbenz[a]anthracene. However, investigation into the impact of substituted PACs including halogenated, heterocyclic, and alkylated PACs on mammalian reproduction has been largely overlooked despite the fact that these compounds are found in higher abundance in free-ranging wildlife. This review aims to discuss current literature on the effects of PACs on the ovary in mammals, with a particular focus on folliculogenesis, steroidogenesis and angiogenesis, which are key processes necessary for proper ovarian functions.

A local QSAR model based on the stability of nitrenium ions to support the ICH M7 expert review on the mutagenicity of primary aromatic amines

BACKGROUND

Aromatic amines, often used as intermediates for pharmaceutical synthesis, may be mutagenic and therefore pose a challenge as metabolites or impurities in drug development. However, predicting the mutagenicity of aromatic amines using commercially available, quantitative structure-activity relationship (QSAR) tools is difficult and often requires expert review. In this study, we developed a shareable QSAR tool based on nitrenium ion stability.

RESULTS

The evaluation using in-house aromatic amine intermediates revealed that our model has prediction accuracy of aromatic amine mutagenicity comparable to that of commercial QSAR tools. The effect of changing the number and position of substituents on the mutagenicity of aromatic amines was successfully explained by the change in the nitrenium ion stability. Furthermore, case studies showed that our QSAR tool can support the expert review with quantitative indicators.

CONCLUSIONS

This local QSAR tool will be useful as a quantitative support tool to explain the substituent effects on the mutagenicity of primary aromatic amines. By further refinement through method sharing and standardization, our tool can support the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) M7 expert review with quantitative indicators.

Determination of Methyl Methanesulfonate and Ethyl Methylsulfonate in New Drug for the Treatment of Fatty Liver Using Derivatization Followed by High-Performance Liquid Chromatography with Ultraviolet Detection

A new derivatization high-performance liquid chromatography method with ultraviolet detection was developed and validated for the quantitative analysis of methanesulfonate genotoxic impurities in an innovative drug for the treatment of non-alcoholic fatty liver disease. In this study, sodium dibenzyldithiocarbamate was used as a derivatization reagent for the first time to enhance the sensitivity of the analysis, and NaOH aqueous solution was chosen as a pH regulator to avoid the interference of the drug matrix. Several key experimental parameters of the derivatization reaction were investigated and optimized. In addition, specificity, linearity, precision, stability, and accuracy were validated. The determined results of the samples were consistent with those obtained from the derivatization gas chromatography–mass spectrometry analysis. Thus, the proposed method is a reliable and practical protocol for the determination of trace methanesulfonate genotoxic impurities in drugs containing mesylate groups.

Evaluation of toxicological aspects of three new benzoxazole compounds with sunscreen photophysical properties using in silico and in vitro methods

Sunscreening chemicals protect against damage caused by sunlight most absorbing UVA or UVB radiations. In this sense, 2-(2'-hydroxyphenyl)benzoxazole derivatives with amino substituents in the 4' and 5' positions have an outstandingly high Sun Protection Factor and adequate photostability, but their toxicity is not yet known. This study aimed to evaluate the toxicity of three synthetic 2-(2'-hydroxyphenyl)benzoxazole derivatives for their possible application as sunscreens. In silico tools were used in order to assess potential risks regarding mutagenic, carcinogenic, and skin sensitizing potential. Bioassays were performed in L929 cells to assess cytotoxicity in MTT assay and genotoxic activities in the Comet assay and micronucleus test. Also, the Salmonella/microsome assay was performed to evaluate gene mutations. The in silico predictions indicate a low risk of mutagenicity and carcinogenicity of the compounds while the skin sensitizing potential was low or inconclusive. The 2-(4'-amino-2'-hydroxyphenyl)benzoxazol compound was the most cytotoxic and genotoxic among the compounds evaluated in L929 cells, but none induced mutations in the Salmonella/microsome assay. The amino substituted at the 4' position of the phenyl ring appears to have greater toxicological risks than substituents at the 5' position of 2-(phenyl)benzoxazole. The findings warrant further studies of these compounds in cosmetic formulations.

Amino Reactivity of Glutardialdehyde and Monoaldehydes─Chemoassay Profile vs Skin Sensitization Potency

Chemoassay profiling of organic electrophiles through the direct peptide reactivity assay has become an OECD-accepted nonanimal component in the REACH evaluation of potential skin sensitizers. For aldehydes forming imines (Schiff bases), however, existing chemoassays yielded inconclusive results, indicating issues with their NH₂ sensitivity and the reversibility of the reaction. In the present study, a new kinetic chemoassay employing the N terminus of glycine-para-nitroanilide, Gly-pNA, as a model nucleophile for protein NH₂ groups is introduced and applied to nine aliphatic monoaldehydes and glutardialdehyde (1,5-pentanedial) that have log K_ow (octanol/water partition coefficient) values from 0.63 to 3.99. The Gly-pNA second-order rate constants k₁ range from 8.56 to 150 L·mol^-1·min^-1 for the monoaldehydes. Interestingly, glutardialdehyde with a k₁ of 17 731 L·mol^-1·min^-1 is 170-fold more reactive than its monoaldehyde counterpart pentanal. This can be rationalized by hydration or tautomerization of the dialdehyde to monoaldehydic forms, now facilitating Schiff base formation through an intramolecular H bond. Comparison with murine local lymph node assay data from the literature reveals that adduct stability in terms of reaction thermodynamics (K = k₁/k_-1^pseudo) rather than formation kinetics (k₁) governs the skin sensitization potency of Schiff-base-forming aldehydes. The discussion includes analytically determined adduct patterns, and the impact of α- and β-carbon substitution as well as hydrophobicity on aldehyde reactivity.

Promising effects of gingerol against toxins: A review article

Ginger is a medicinal and valuable culinary plant. Gingerols, as an active constituent in the fresh ginger rhizomes of Zingiber officinale, exhibit several promising pharmacological properties. This comprehensive literature review was performed to assess gingerol's protective and therapeutic efficacy against the various chemical, natural, and radiational stimuli. Another objective of this study was to investigate the mechanism of anti-inflammatory, antioxidant, and antiapoptotic properties of gingerol. It should be noted that the data were gathered from in vivo and in vitro experimental studies. Gingerols can exert their protective activity through different mechanisms and cell signaling pathways. For example, these are mitogen-activated protein kinase (MAPK), nuclear factor-kappa B (NF-kB), Wnt/β-catenin, nuclear factor erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE), transforming growth factor beta1/Smad3 (TGF-β1/Smad3), and extracellular signal-related kinase/cAMP-response element-binding protein (ERK/CREB). We hope that more researchers can benefit from this review to conduct preclinical and clinical studies, treat cancer, inflammation, and attenuate the side effects of drugs and industrial pollutants.

In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs

Historically, identifying carcinogens has relied primarily on tumor studies in rodents, which require enormous resources in both money and time. In silico models have been developed for predicting rodent carcinogens but have not yet found general regulatory acceptance, in part due to the lack of a generally accepted protocol for performing such an assessment as well as limitations in predictive performance and scope. There remains a need for additional, improved in silico carcinogenicity models, especially ones that are more human-relevant, for use in research and regulatory decision-making. As part of an international effort to develop in silico toxicological protocols, a consortium of toxicologists, computational scientists, and regulatory scientists across several industries and governmental agencies evaluated the extent to which in silico models exist for each of the recently defined 10 key characteristics (KCs) of carcinogens. This position paper summarizes the current status of in silico tools for the assessment of each KC and identifies the data gaps that need to be addressed before a comprehensive in silico carcinogenicity protocol can be developed for regulatory use.

Development and Validation of a UPLC-MS/MS Method for Ultra-Trace Level Determination of Acyl Chloride Potential Genotoxic Impurity in Mezlocillin

3-Chlorocarbonyl-1-methanesulfonyl-2-imidazolidinone (CMI) is a critical intermediate used in the synthesis of mezlocillin drug substance and also a potential genotoxic impurity with acyl chloride moiety. The content of CMI in mezlocillin should be <0.16 ppm to avoid the carcinogenicity and mutagenicity threats to patients. Therefore, a workable determination of CMI was critically crucial for ensuring the safety of mezlocillin drug products. However, the conventional HPLC method is insufficient for detection limits at ppm or lower levels. Besides, the high activity of acyl chloride also raises a challenge to the direct measurement of CMI. Thus, we explored a simple esterification approach, which converts CMI into methyl 3-(methylonyl)-2-oxoimidazolidine-1-carboxylate completely by optimizing the reaction temperature and time. Furthermore, the selected reaction monitoring model of triple quadrupole mass spectrometer optimized by the Box-Behnken design significantly enhanced the sensitivity of ultra-trace level determination. The limit of detection and limit of quantification of the method were reached 0.014 and 0.02 ppm, respectively, in the following validation study. A sensitive and specific ultra-performance liquid chromatography tandem mass spectrometry method for ultra-trace level determination of acyl chloride potential genotoxic impurity in mezlocillin drug substance has been successfully established in this study, which will provide a practical quality control tool of mezlocillin.

A risk classification strategy for migrants of food contact material combined with three (Q)SAR tools in silico

The chemical constituents in food contact materials (FCMs) may transfer into food during the contact, which may pose potential risk to humans. So, it is important to evaluate the safety of FCMs. Due to the advantages of cost-effectiveness and high throughput, (Q)SAR tools have been gradually used for risk assessment. In this work, a risk classification strategy for migrants of food contact materials combined with three (Q)SAR tools was developed based on a single endpoint (Mutagenicity) assessment and risk matrix approach, respectively. 419 migrants existing in a self-built toxicology database beneficial from Python crawler technology were evaluated. 5 toxic hazard ranks and 4 risk ranks were obtained for single endpoint assessment and risk matrix respectively, with 21 substances assigned as Toxic hazard Class I and 43 substances assigned as RISK Ⅰ which need the highest safety concern. Besides, for the Toxic hazard Class I substances assessed by the single endpoint, 19 of them were confirmed experimentally, and all of them were overlapped in the RISK Ⅰ substances, which suggests the effectiveness and reliability of this strategy.

Towards prevention of ischemia-reperfusion kidney injury: Pre-clinical evaluation of 6-chromanol derivatives and the lead compound SUL-138✰

Acute kidney injury (AKI) is a global healthcare burden attributable to high mortality and staggering costs of dialysis. The underlying causes of AKI include hypothermia and rewarming (H/R), ischemia/reperfusion (I/R), mitochondrial dysfunction and reactive oxygen species production. Inspired by the mechanisms conferring organ protection in hibernating hamster, 6-chromanol derived compounds were developed to address the need of effective prevention and treatment of AKI. Here we report on the pre-clinical screening of 6-chromanol leads that confer protection during I/R to select compounds with favorable profiles for clinical testing in AKI. A library of 6-chromanols (n = 63) was screened in silico for pharmacochemical properties and druggability. Selected compounds (n = 15) were screened for the potency to protect HEK293 cells from H/R cell death and subjected to a panel of in vitro safety assays. Based on these parameters, SUL-138 was selected as the lead compound and was found to safeguard kidney function and decrease renal injury after I/R in rats. The compound was without cardiovascular or respiratory effects in vivo. SUL-138 pharmacokinetics of control animals (mouse, rat) and those undergoing I/R (rat) was identical, showing a two-phase elimination profile with terminal half-life of about 8 h. Collectively, our phenotype-based screening approach led to the identification of 3 candidates for pre-clinical studies (5%, 3/64). SUL-138 emerged from this small-scale library of 6-chromanols as a novel prophylactic for AKI. The presented efficacy and safety data provide a basis for future development and clinical testing. SECTION ASSIGNMENTS: : Drug discovery and translational medicine, renal, metabolism SIGNIFICANCE STATEMENT: : Based on in silico druggability parameters, a 63 compound 6-chromanol library was narrowed down to 15 compounds. These compounds were subjected to phenotypical screening of cell survival following hypothermia damage and hit compounds were identified. After subsequent assessment of in vivo efficacy, toxicity, pharmacokinetics, and cardiovascular and respiratory safety, SUL-138 emerged as a lead compound that prevented kidney injury after ischemia/reperfusion and demonstrated a favorable pharmacokinetic profile unaffected by renal ischemia.

Bacterial mutagenicity test data: collection by the task force of the Japan pharmaceutical manufacturers association

Background

Ames test is used worldwide for detecting the bacterial mutagenicity of chemicals. In silico analyses of bacterial mutagenicity have recently gained acceptance by regulatory agencies; however, current in silico models for prediction remain to be improved. The Japan Pharmaceutical Manufacturers Association (JPMA) organized a task force in 2017 in which eight Japanese pharmaceutical companies had participated. The purpose of this task force was to disclose a piece of pharmaceutical companies’ proprietary Ames test data.

Results

Ames test data for 99 chemicals of various chemical classes were collected for disclosure in this study. These chemicals are related to the manufacturing process of pharmaceutical drugs, including reagents, synthetic intermediates, and drug substances. The structure-activity (mutagenicity) relationships are discussed in relation to structural alerts for each chemical class. In addition, in silico analyses of these chemicals were conducted using a knowledge-based model of Derek Nexus (Derek) and a statistics-based model (GT1_BMUT module) of CASE Ultra. To calculate the effectiveness of these models, 89 chemicals for Derek and 54 chemicals for CASE Ultra were selected; major exclusions were the salt form of four chemicals that were tested both in the salt and free forms for both models, and 35 chemicals called “known” positives or negatives for CASE Ultra. For Derek, the sensitivity, specificity, and accuracy were 65% (15/23), 71% (47/66), and 70% (62/89), respectively. The sensitivity, specificity, and accuracy were 50% (6/12), 60% (25/42), and 57% (31/54) for CASE Ultra, respectively. The ratio of overall disagreement between the CASE Ultra “known” positives/negatives and the actual test results was 11% (4/35). In this study, 19 out of 28 mutagens (68%) were detected with TA100 and/or TA98, and 9 out of 28 mutagens (32%) were detected with either TA1535, TA1537, WP2uvrA, or their combination.

Conclusion

The Ames test data presented here will help avoid duplicated Ames testing in some cases, support duplicate testing in other cases, improve in silico models, and enhance our understanding of the mechanisms of mutagenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41021-021-00206-1.

In silico assessment of genotoxicity. Combinations of sensitive structural alerts minimize false negative predictions for all genotoxicity endpoints and can single out chemicals for which experimentation can be avoided

Genotoxicity assessment of chemicals has a crucial role in most regulations. Due to labor, time, cost, and animal welfare issues, attention is being given to (Q)SAR methods. A strategic application of alternative methods is to first use a sequence of conservative (very sensitive) (Q)SARs and/or in vitro models to arrive at the conclusion that no further testing is necessary for negatives, and to use mechanistically based, Weight-Of-Evidence approach to evaluate the chemicals showing positive results. The ICH M7 guideline to detect DNA-reactive impurities in drugs follows these lines (recommending solely (Q)SAR in step 1). However, ICH M7 focuses only on Ames test. Here a large database of more than 6000 chemicals positive in at least one endpoint (in vitro gene mutations or chromosomal aberrations, in vivo micronucleus, aneugenicity) were analyzed with structural alerts implemented in the OECD QSAR Toolbox, resulting in maximum 3% false negatives. These promising results indicate that it may be possible to extend the approach to the whole range of genotoxicity endpoints required by regulations. Since structural alerts may generate false positives, cautious follow-up of positives is recommended (with e.g., statistically based QSARs, read across of similar chemicals, expert judgement, and experimentation when necessary).

Chlorpyrifos pesticide promotes oxidative stress and increases inflammatory states in BV-2 microglial cells: A role in neuroinflammation

The exposure to environmental stressors, such as organophosphate (OP) pesticides, has been associated with the development of neurodegenerative diseases. Chlorpyrifos (CPF) is the worldwide most used OP pesticide and one of the most hazardous pesticides as it can cross the blood-brain barrier. Since studies evaluating the effects of CPF on brain immune cells are scarce, this research investigated the oxidative and inflammatory responses of CPF exposure in murine microglial cells. BV-2 cells were exposed to different concentrations of CPF pesticide (0.3-300 μM). CPF induced activation of microglial cells, confirmed by Iba-1 and CD11b marking, and promoted microglial proliferation and cell cycle arrest at S phase. Moreover, CPF exposure increased oxidative stress production (NO, MDA, and O₂∙), and upregulated pro-inflammatory cytokines (IL-1β and NLRP3) genes expression in BV-2 cells. Overall, data showed that CPF exposure, at the lowest concentrations, acted by promoting pro-oxidative and pro-inflammatory states in microglial cells. These results provide important information on the potential role of microglial activation in CPF-induced neuroinflammation and add to the expanding knowledge on the neurotoxicity of OP.

Toxic effects of substituted p-benzoquinones and hydroquinones in in vitro bioassays are altered by reactions with the cell assay medium

Substituted para-benzoquinones and hydroquinones are ubiquitous transformation products that arise during oxidative water treatment of phenolic precursors, for example through ozonation or chlorination. The benzoquinone structural motive is associated with mutagenicity and carcinogenicity, and also with induction of the oxidative stress response through the Nrf2 pathway. For either endpoint, toxicological data for differently substituted compounds are scarce. In this study, oxidative stress response, as indicated by the AREc32 in vitro bioassay, was induced by differently substituted para-benzoquinones, but also by the corresponding hydroquinones. Bioassays that indicate defense against genotoxicity (p53RE-bla) and DNA repair activity (UmuC) were not activated by these compounds. Stability tests conducted under incubation conditions, but in the absence of cell lines, showed that tested para-benzoquinones reacted rapidly with constituents of the incubation medium. Compounds were abated already in phosphate buffer, but even faster in biological media, with reactions attributed to amino- and thiol-groups of peptides, proteins, and free amino acids. The products of these reactions were often the corresponding substituted hydroquinones. Conversely, differently substituted hydroquinones were quantitatively oxidized to p-benzoquinones over the course of the incubation. The observed induction of the oxidative stress response was attributed to hydroquinones that are presumably oxidized to benzoquinones inside the cells. Despite the instability of the tested compounds in the incubation medium, the AREc32 in vitro bioassay could be used as an unspecific sum parameter to detect para-benzoquinones and hydroquinones in oxidatively treated waters.

COSMOS next generation - A public knowledge base leveraging chemical and biological data to support the regulatory assessment of chemicals

The COSMOS Database (DB) was originally established to provide reliable data for cosmetics-related chemicals within the COSMOS Project funded as part of the SEURAT-1 Research Initiative. The database has subsequently been maintained and developed further into COSMOS Next Generation (NG), a combination of database and in silico tools, essential components of a knowledge base. COSMOS DB provided a cosmetics inventory as well as other regulatory inventories, accompanied by assessment results and in vitro and in vivo toxicity data. In addition to data content curation, much effort was dedicated to data governance - data authorisation, characterisation of quality, documentation of meta information, and control of data use. Through this effort, COSMOS DB was able to merge and fuse data of various types from different sources. Building on the previous effort, the COSMOS Minimum Inclusion (MINIS) criteria for a toxicity database were further expanded to quantify the reliability of studies. COSMOS NG features multiple fingerprints for analysing structure similarity, and new tools to calculate molecular properties and screen chemicals with endpoint-related public profilers, such as DNA and protein binders, liver alerts and genotoxic alerts. The publicly available COSMOS NG enables users to compile information and execute analyses such as category formation and read-across. This paper provides a step-by-step guided workflow for a simple read-across case, starting from a target structure and culminating in an estimation of a NOAEL confidence interval. Given its strong technical foundation, inclusion of quality-reviewed data, and provision of tools designed to facilitate communication between users, COSMOS NG is a first step towards building a toxicological knowledge hub leveraging many public data systems for chemical safety evaluation. We continue to monitor the feedback from the user community at support@mn-am.com.

In vivo and in vitro mutagenicity of perillaldehyde and cinnamaldehyde

BACKGROUND

Perillaldehyde and cinnamaldehyde are natural substances found in plants that are used as flavoring ingredients. Due to the α,β-unsaturated aldehydes in their structures, these compounds are expected to be DNA reactive. Indeed, several reports have indicated that perillaldehyde and cinnamaldehyde show positive in in vitro and in vivo genotoxicity tests. However, their genotoxic potentials are currently disputed. To clarify the mutagenicity of perillaldehyde and cinnamaldehyde, we conducted in silico quantitative structure-activity relationship (QSAR) analysis, in vitro Ames tests, and in vivo transgenic rodent gene mutation (TGR) assays.

RESULTS

In Ames tests, perillaldehyde was negative and cinnamaldehyde was positive; these respective results were supported by QSAR analysis. In TGR assays, we treated Muta™ Mice with perillaldehyde and gpt-delta mice with cinnamaldehyde up to the maximum tested doses (1000 mg/kg/day). There was no increase in gene mutations in the liver, glandular stomach, or small intestine following all treatments except the positive control (N-ethyl-N-nitrosourea at 100 mg/kg/day).

CONCLUSIONS

These data clearly show no evidence of in vivo mutagenic potentials of perillaldehyde and cinnamaldehyde (administered up to 1000 mg/kg/day) in mice; however, cinnamaldehyde is mutagenic in vitro.

Assessing the impact of expert knowledge on ICH M7 (Q)SAR predictions. Is expert review still needed?

The ICH M7 (R1) guideline recommends the use of complementary (Q)SAR models to assess the mutagenic potential of drug impurities as a state-of-the-art, high-throughput alternative to empirical testing. Additionally, it includes a provision for the application of expert knowledge to increase prediction confidence and resolve conflicting calls. Expert knowledge, which considers structural analogs and mechanisms of activity, has been valuable when models return an indeterminate (equivocal) result or no prediction (out-of-domain). A retrospective analysis of 1002 impurities evaluated in drug regulatory applications between April 2017 and March 2019 assessed the impact of expert review on (Q)SAR predictions. Expert knowledge overturned the default predictions for 26% of the impurities and resolved 91% of equivocal predictions and 75% of out-of-domain calls. Of the 261 overturned default predictions, 15% were upgraded to equivocal or positive and 79% were downgraded to equivocal or negative. Chemical classes with the most overturns were primary aromatic amines (46%), aldehydes (45%), Michael-reactive acceptors (37%), and non-primary alkyl halides (33%). Additionally, low confidence predictions were the most often overturned. Collectively, the results suggest that expert knowledge continues to play an important role in an ICH M7 (Q)SAR prediction workflow and triaging predictions based on chemical class and probability can improve (Q)SAR review efficiency.