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Keywords = Molecular Initiating Event (MIE)

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24 pages, 5520 KiB  
Review
Drug-Induced Fatty Liver Disease (DIFLD): A Comprehensive Analysis of Clinical, Biochemical, and Histopathological Data for Mechanisms Identification and Consistency with Current Adverse Outcome Pathways
by Ernesto López-Pascual, Ivan Rienda, Judith Perez-Rojas, Anna Rapisarda, Guillem Garcia-Llorens, Ramiro Jover and José V. Castell
Int. J. Mol. Sci. 2024, 25(10), 5203; https://doi.org/10.3390/ijms25105203 - 10 May 2024
Cited by 12 | Viewed by 6606
Abstract
Drug induced fatty liver disease (DIFLD) is a form of drug-induced liver injury (DILI), which can also be included in the more general metabolic dysfunction-associated steatotic liver disease (MASLD), which specifically refers to the accumulation of fat in the liver unrelated to alcohol [...] Read more.
Drug induced fatty liver disease (DIFLD) is a form of drug-induced liver injury (DILI), which can also be included in the more general metabolic dysfunction-associated steatotic liver disease (MASLD), which specifically refers to the accumulation of fat in the liver unrelated to alcohol intake. A bi-directional relationship between DILI and MASLD is likely to exist: while certain drugs can cause MASLD by acting as pro-steatogenic factors, MASLD may make hepatocytes more vulnerable to drugs. Having a pre-existing MASLD significantly heightens the likelihood of experiencing DILI from certain medications. Thus, the prevalence of steatosis within DILI may be biased by pre-existing MASLD, and it can be concluded that the genuine true incidence of DIFLD in the general population remains unknown. In certain individuals, drug-induced steatosis is often accompanied by concomitant injury mechanisms such as oxidative stress, cell death, and inflammation, which leads to the development of drug-induced steatohepatitis (DISH). DISH is much more severe from the clinical point of view, has worse prognosis and outcome, and resembles MASH (metabolic-associated steatohepatitis), as it is associated with inflammation and sometimes with fibrosis. A literature review of clinical case reports allowed us to examine and evaluate the clinical features of DIFLD and their association with specific drugs, enabling us to propose a classification of DIFLD drugs based on clinical outcomes and pathological severity: Group 1, drugs with low intrinsic toxicity (e.g., ibuprofen, naproxen, acetaminophen, irinotecan, methotrexate, and tamoxifen), but expected to promote/aggravate steatosis in patients with pre-existing MASLD; Group 2, drugs associated with steatosis and only occasionally with steatohepatitis (e.g., amiodarone, valproic acid, and tetracycline); and Group 3, drugs with a great tendency to transit to steatohepatitis and further to fibrosis. Different mechanisms may be in play when identifying drug mode of action: (1) inhibition of mitochondrial fatty acid β-oxidation; (2) inhibition of fatty acid transport across mitochondrial membranes; (3) increased de novo lipid synthesis; (4) reduction in lipid export by the inhibition of microsomal triglyceride transfer protein; (5) induction of mitochondrial permeability transition pore opening; (6) dissipation of the mitochondrial transmembrane potential; (7) impairment of the mitochondrial respiratory chain/oxidative phosphorylation; (8) mitochondrial DNA damage, degradation and depletion; and (9) nuclear receptors (NRs)/transcriptomic alterations. Currently, the majority of, if not all, adverse outcome pathways (AOPs) for steatosis in AOP-Wiki highlight the interaction with NRs or transcription factors as the key molecular initiating event (MIE). This perspective suggests that chemical-induced steatosis typically results from the interplay between a chemical and a NR or transcription factors, implying that this interaction represents the primary and pivotal MIE. However, upon conducting this exhaustive literature review, it became evident that the current AOPs tend to overly emphasize this interaction as the sole MIE. Some studies indeed support the involvement of NRs in steatosis, but others demonstrate that such NR interactions alone do not necessarily lead to steatosis. This view, ignoring other mitochondrial-related injury mechanisms, falls short in encapsulating the intricate biological mechanisms involved in chemically induced liver steatosis, necessitating their consideration as part of the AOP’s map road as well. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Hepatotoxicity—2nd Edition)
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21 pages, 2675 KiB  
Article
Structural Insights into Neonicotinoids and N-Unsubstituted Metabolites on Human nAChRs by Molecular Docking, Dynamics Simulations, and Calcium Imaging
by Karin Grillberger, Eike Cöllen, Claudia Immacolata Trivisani, Jonathan Blum, Marcel Leist and Gerhard F. Ecker
Int. J. Mol. Sci. 2023, 24(17), 13170; https://doi.org/10.3390/ijms241713170 - 24 Aug 2023
Cited by 6 | Viewed by 2711
Abstract
Neonicotinoid pesticides were initially designed in order to achieve species selectivity on insect nicotinic acetylcholine receptors (nAChRs). However, concerns arose when agonistic effects were also detected in human cells expressing nAChRs. In the context of next-generation risk assessments (NGRAs), new approach methods (NAMs) [...] Read more.
Neonicotinoid pesticides were initially designed in order to achieve species selectivity on insect nicotinic acetylcholine receptors (nAChRs). However, concerns arose when agonistic effects were also detected in human cells expressing nAChRs. In the context of next-generation risk assessments (NGRAs), new approach methods (NAMs) should replace animal testing where appropriate. Herein, we present a combination of in silico and in vitro methodologies that are used to investigate the potentially toxic effects of neonicotinoids and nicotinoid metabolites on human neurons. First, an ensemble docking study was conducted on the nAChR isoforms α7 and α3β4 to assess potential crucial molecular initiating event (MIE) interactions. Representative docking poses were further refined using molecular dynamics (MD) simulations and binding energy calculations using implicit solvent models. Finally, calcium imaging on LUHMES neurons confirmed a key event (KE) downstream of the MIE. This method was also used to confirm the predicted agonistic effect of the metabolite descyano-thiacloprid (DCNT). Full article
(This article belongs to the Special Issue Pesticides Exposure and Toxicity)
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15 pages, 882 KiB  
Review
Oxidative Stress and Lung Fibrosis: Towards an Adverse Outcome Pathway
by Patrudu Makena, Tatiana Kikalova, Gaddamanugu L. Prasad and Sarah A. Baxter
Int. J. Mol. Sci. 2023, 24(15), 12490; https://doi.org/10.3390/ijms241512490 - 6 Aug 2023
Cited by 27 | Viewed by 4363
Abstract
Lung fibrosis is a progressive fatal disease in which deregulated wound healing of lung epithelial cells drives progressive fibrotic changes. Persistent lung injury due to oxidative stress and chronic inflammation are central features of lung fibrosis. Chronic cigarette smoking causes oxidative stress and [...] Read more.
Lung fibrosis is a progressive fatal disease in which deregulated wound healing of lung epithelial cells drives progressive fibrotic changes. Persistent lung injury due to oxidative stress and chronic inflammation are central features of lung fibrosis. Chronic cigarette smoking causes oxidative stress and is a major risk factor for lung fibrosis. The objective of this manuscript is to develop an adverse outcome pathway (AOP) that serves as a framework for investigation of the mechanisms of lung fibrosis due to lung injury caused by inhaled toxicants, including cigarette smoke. Based on the weight of evidence, oxidative stress is proposed as a molecular initiating event (MIE) which leads to increased secretion of proinflammatory and profibrotic mediators (key event 1 (KE1)). At the cellular level, these proinflammatory signals induce the recruitment of inflammatory cells (KE2), which in turn, increase fibroblast proliferation and myofibroblast differentiation (KE3). At the tissue level, an increase in extracellular matrix deposition (KE4) subsequently culminates in lung fibrosis, the adverse outcome. We have also defined a new KE relationship between the MIE and KE3. This AOP provides a mechanistic platform to understand and evaluate how persistent oxidative stress from lung injury may develop into lung fibrosis. Full article
(This article belongs to the Special Issue Advances in Lung Injury, Regeneration, and Fibrosis)
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10 pages, 909 KiB  
Article
Nuclear Receptor and Stress Response Pathways Associated with Antineoplastic Agent-Induced Diarrhea
by Mashiro Okunaka, Daisuke Kano and Yoshihiro Uesawa
Int. J. Mol. Sci. 2022, 23(20), 12407; https://doi.org/10.3390/ijms232012407 - 17 Oct 2022
Cited by 7 | Viewed by 2257
Abstract
In severe cases, antineoplastic agent-induced diarrhea may be life-threatening; therefore, it is necessary to determine the mechanism of toxicity and identify the optimal management. The mechanism of antineoplastic agent-induced diarrhea is still unclear but is often considered to be multifactorial. The aim of [...] Read more.
In severe cases, antineoplastic agent-induced diarrhea may be life-threatening; therefore, it is necessary to determine the mechanism of toxicity and identify the optimal management. The mechanism of antineoplastic agent-induced diarrhea is still unclear but is often considered to be multifactorial. The aim of this study was to determine the molecular initiating event (MIE), which is the initial interaction between molecules and biomolecules or biosystems, and to evaluate the MIE specific to antineoplastic agents that induce diarrhea. We detected diarrhea-inducing drug signals based on adjusted odds ratios using the Food and Drug Administration Adverse Event Reporting System. We then used the quantitative structure-activity relationship platform of Toxicity Predictor to identify potential MIEs that are specific to diarrhea-inducing antineoplastic agents. We found that progesterone receptor antagonists were potential MIEs associated with diarrhea. The findings of this study may help improve the prediction and management of antineoplastic agent-induced diarrhea. Full article
(This article belongs to the Special Issue Cytotoxicity on Pharmaceutical Interactions in Chemotherapy)
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21 pages, 1574 KiB  
Article
Providing Biological Plausibility for Exposure–Health Relationships for the Mycotoxins Deoxynivalenol (DON) and Fumonisin B1 (FB1) in Humans Using the AOP Framework
by Annick D. van den Brand, Lola Bajard, Inger-Lise Steffensen, Anne Lise Brantsæter, Hubert A. A. M. Dirven, Jochem Louisse, Ad Peijnenburg, Sophie Ndaw, Alberto Mantovani, Barbara De Santis and Marcel J. B. Mengelers
Toxins 2022, 14(4), 279; https://doi.org/10.3390/toxins14040279 - 13 Apr 2022
Cited by 11 | Viewed by 5439
Abstract
Humans are chronically exposed to the mycotoxins deoxynivalenol (DON) and fumonisin B1 (FB1), as indicated by their widespread presence in foods and occasional exposure in the workplace. This exposure is confirmed by human biomonitoring (HBM) studies on (metabolites of) these mycotoxins in human [...] Read more.
Humans are chronically exposed to the mycotoxins deoxynivalenol (DON) and fumonisin B1 (FB1), as indicated by their widespread presence in foods and occasional exposure in the workplace. This exposure is confirmed by human biomonitoring (HBM) studies on (metabolites of) these mycotoxins in human matrices. We evaluated the exposure–health relationship of the mycotoxins in humans by reviewing the available literature. Since human studies did not allow the identification of unequivocal chronic health effects upon exposure to DON and FB1, the adverse outcome pathway (AOP) framework was used to structure additional mechanistic evidence from in vitro and animal studies on the identified adverse effects. In addition to a preliminary AOP for DON resulting in the adverse outcome (AO) ‘reduced body weight gain’, we developed a more elaborated AOP for FB1, from the molecular initiating event (MIE) ‘inhibition of ceramide synthases’ leading to the AO ‘neural tube defects’. The mechanistic evidence from AOPs can be used to support the limited evidence from human studies, to focus FB1- and DON-related research in humans to identify related early biomarkers of effect. In order to establish additional human exposure–health relationships in the future, recommendations are given to maximize the information that can be obtained from HBM. Full article
(This article belongs to the Special Issue Human Biomonitoring and Risk Assessment of Mycotoxins)
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18 pages, 1808 KiB  
Article
Prediction of the Neurotoxic Potential of Chemicals Based on Modelling of Molecular Initiating Events Upstream of the Adverse Outcome Pathways of (Developmental) Neurotoxicity
by Domenico Gadaleta, Nicoleta Spînu, Alessandra Roncaglioni, Mark T. D. Cronin and Emilio Benfenati
Int. J. Mol. Sci. 2022, 23(6), 3053; https://doi.org/10.3390/ijms23063053 - 11 Mar 2022
Cited by 22 | Viewed by 5262
Abstract
Developmental and adult/ageing neurotoxicity is an area needing alternative methods for chemical risk assessment. The formulation of a strategy to screen large numbers of chemicals is highly relevant due to potential exposure to compounds that may have long-term adverse health consequences on the [...] Read more.
Developmental and adult/ageing neurotoxicity is an area needing alternative methods for chemical risk assessment. The formulation of a strategy to screen large numbers of chemicals is highly relevant due to potential exposure to compounds that may have long-term adverse health consequences on the nervous system, leading to neurodegeneration. Adverse Outcome Pathways (AOPs) provide information on relevant molecular initiating events (MIEs) and key events (KEs) that could inform the development of computational alternatives for these complex effects. We propose a screening method integrating multiple Quantitative Structure–Activity Relationship (QSAR) models. The MIEs of existing AOP networks of developmental and adult/ageing neurotoxicity were modelled to predict neurotoxicity. Random Forests were used to model each MIE. Predictions returned by single models were integrated and evaluated for their capability to predict neurotoxicity. Specifically, MIE predictions were used within various types of classifiers and compared with other reference standards (chemical descriptors and structural fingerprints) to benchmark their predictive capability. Overall, classifiers based on MIE predictions returned predictive performances comparable to those based on chemical descriptors and structural fingerprints. The integrated computational approach described here will be beneficial for large-scale screening and prioritisation of chemicals as a function of their potential to cause long-term neurotoxic effects. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Specific Target Organ Toxicity)
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24 pages, 659 KiB  
Review
Integrated Genomic and Bioinformatics Approaches to Identify Molecular Links between Endocrine Disruptors and Adverse Outcomes
by Jacopo Umberto Verga, Matthew Huff, Diarmuid Owens, Bethany J. Wolf and Gary Hardiman
Int. J. Environ. Res. Public Health 2022, 19(1), 574; https://doi.org/10.3390/ijerph19010574 - 5 Jan 2022
Cited by 9 | Viewed by 4592
Abstract
Exposure to Endocrine Disrupting Chemicals (EDC) has been linked with several adverse outcomes. In this review, we examine EDCs that are pervasive in the environment and are of concern in the context of human, animal, and environmental health. We explore the consequences of [...] Read more.
Exposure to Endocrine Disrupting Chemicals (EDC) has been linked with several adverse outcomes. In this review, we examine EDCs that are pervasive in the environment and are of concern in the context of human, animal, and environmental health. We explore the consequences of EDC exposure on aquatic life, terrestrial animals, and humans. We focus on the exploitation of genomics technologies and in particular whole transcriptome sequencing. Genome-wide analyses using RNAseq provides snap shots of cellular, tissue and whole organism transcriptomes under normal physiological and EDC perturbed conditions. A global view of gene expression provides highly valuable information as it uncovers gene families or more specifically, pathways that are affected by EDC exposures, but also reveals those that are unaffected. Hypotheses about genes with unknown functions can also be formed by comparison of their expression levels with genes of known function. Risk assessment strategies leveraging genomic technologies and the development of toxicology databases are explored. Finally, we review how the Adverse Outcome Pathway (AOP) has exploited this high throughput data to provide a framework for toxicology studies. Full article
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17 pages, 3941 KiB  
Article
Novel QSAR Models for Molecular Initiating Event Modeling in Two Intersecting Adverse Outcome Pathways Based Pulmonary Fibrosis Prediction for Biocidal Mixtures
by Myungwon Seo, Chong Hak Chae, Yuno Lee, Ha Ryong Kim and Jongwoon Kim
Toxics 2021, 9(3), 59; https://doi.org/10.3390/toxics9030059 - 16 Mar 2021
Cited by 10 | Viewed by 6874
Abstract
The adverse outcome pathway (AOP) was introduced as an alternative method to avoid unnecessary animal tests. Under the AOP framework, an in silico methods, molecular initiating event (MIE) modeling is used based on the ligand-receptor interaction. Recently, the intersecting AOPs (AOP 347), including [...] Read more.
The adverse outcome pathway (AOP) was introduced as an alternative method to avoid unnecessary animal tests. Under the AOP framework, an in silico methods, molecular initiating event (MIE) modeling is used based on the ligand-receptor interaction. Recently, the intersecting AOPs (AOP 347), including two MIEs, namely peroxisome proliferator-activated receptor-gamma (PPAR-γ) and toll-like receptor 4 (TLR4), associated with pulmonary fibrosis was proposed. Based on the AOP 347, this study developed two novel quantitative structure-activity relationship (QSAR) models for the two MIEs. The prediction performances of different MIE modeling methods (e.g., molecular dynamics, pharmacophore model, and QSAR) were compared and validated with in vitro test data. Results showed that the QSAR method had high accuracy compared with other modeling methods, and the QSAR method is suitable for the MIE modeling in the AOP 347. Therefore, the two QSAR models based on the AOP 347 can be powerful models to screen biocidal mixture related to pulmonary fibrosis. Full article
(This article belongs to the Section Exposome Analysis and Risk Assessment)
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16 pages, 1396 KiB  
Article
Molecular Modelling Study of the PPARγ Receptor in Relation to the Mode of Action/Adverse Outcome Pathway Framework for Liver Steatosis
by Ivanka Tsakovska, Merilin Al Sharif, Petko Alov, Antonia Diukendjieva, Elena Fioravanzo, Mark T. D. Cronin and Ilza Pajeva
Int. J. Mol. Sci. 2014, 15(5), 7651-7666; https://doi.org/10.3390/ijms15057651 - 5 May 2014
Cited by 38 | Viewed by 9106
Abstract
The comprehensive understanding of the precise mode of action and/or adverse outcome pathway (MoA/AOP) of chemicals has become a key step toward the development of a new generation of predictive toxicology tools. One of the challenges of this process is to test the [...] Read more.
The comprehensive understanding of the precise mode of action and/or adverse outcome pathway (MoA/AOP) of chemicals has become a key step toward the development of a new generation of predictive toxicology tools. One of the challenges of this process is to test the feasibility of the molecular modelling approaches to explore key molecular initiating events (MIE) within the integrated strategy of MoA/AOP characterisation. The description of MoAs leading to toxicity and liver damage has been the focus of much interest. Growing evidence underlines liver PPARγ ligand-dependent activation as a key MIE in the elicitation of liver steatosis. Synthetic PPARγ full agonists are of special concern, since they may trigger a number of adverse effects not observed with partial agonists. In this study, molecular modelling was performed based on the PPARγ complexes with full agonists extracted from the Protein Data Bank. The receptor binding pocket was analysed, and the specific ligand-receptor interactions were identified for the most active ligands. A pharmacophore model was derived, and the most important pharmacophore features were outlined and characterised in relation to their specific role for PPARγ activation. The results are useful for the characterisation of the chemical space of PPARγ full agonists and could facilitate the development of preliminary filtering rules for the effective virtual ligand screening of compounds with PPARγ full agonistic activity. Full article
(This article belongs to the Special Issue Proteins and Protein-Ligand Interactions)
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