Perturbation of Nuclear Hormone Receptors by Endocrine Disrupting Chemicals: Mechanisms and Pathological Consequences of Exposure

Hall, Julie M.; Greco, Callie W.

doi:10.3390/cells9010013

Cited by 39 publications

(29 citation statements)

References 221 publications

(235 reference statements)

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“…The mean numbers of active and inactive chemicals were, respectively, 120.9 ± 124. 1 In addition, the highest and lowest numbers of the active chemicals were, respectively, 683 and 2 in Tra, 684 and 6 in Val, and 170 and 2 in Test (Table S1). The molecular images derived from the 3D chemical structures were generated using the DeepSnap approach at different angles along the x-, y-, and z-axes, i.e., (176 • , 176 • , 176 • ).…”

Section: Resultsmentioning

confidence: 99%

“…Many chemical substances have potential harmful effects, causing the perturbation of endocrine homeostasis by interfering with various nuclear receptors (NRs) of hormones [ 1 , 2 , 3 , 4 , 5 ]. In the disruption of hormone pathways, structurally diverse groups of chemicals are known to interact primarily with ligand–NR bindings, which have the ability to substitute for natural ligands, ultimately resulting in proliferative, reproductive, and metabolic disorders [ 6 , 7 , 8 , 9 , 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

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Molecular Image-Based Prediction Models of Nuclear Receptor Agonists and Antagonists Using the DeepSnap-Deep Learning Approach with the Tox21 10K Library

Matsuzaka

Uesawa

2020

Molecules

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The interaction of nuclear receptors (NRs) with chemical compounds can cause dysregulation of endocrine signaling pathways, leading to adverse health outcomes due to the disruption of natural hormones. Thus, identifying possible ligands of NRs is a crucial task for understanding the adverse outcome pathway (AOP) for human toxicity as well as the development of novel drugs. However, the experimental assessment of novel ligands remains expensive and time-consuming. Therefore, an in silico approach with a wide range of applications instead of experimental examination is highly desirable. The recently developed novel molecular image-based deep learning (DL) method, DeepSnap-DL, can produce multiple snapshots from three-dimensional (3D) chemical structures and has achieved high performance in the prediction of chemicals for toxicological evaluation. In this study, we used DeepSnap-DL to construct prediction models of 35 agonist and antagonist allosteric modulators of NRs for chemicals derived from the Tox21 10K library. We demonstrate the high performance of DeepSnap-DL in constructing prediction models. These findings may aid in interpreting the key molecular events of toxicity and support the development of new fields of machine learning to identify environmental chemicals with the potential to interact with NR signaling pathways.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Molecular Image-Based Prediction Models of Nuclear Receptor Agonists and Antagonists Using the DeepSnap-Deep Learning Approach with the Tox21 10K Library

Matsuzaka

Uesawa

2020

Molecules

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“…The number of EDCs has markedly increased over the past 60 years. Humans are constantly exposed to hundreds of EDCs mainly through air, water, and food [1][2][3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Human Health Consequences of Endocrine-Disrupting Chemicals

Heshmati¹

2021

Environmental Issues and Sustainable Development

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Daily use of chemicals is an essential part of modern life. Endocrine-disrupting chemicals (EDCs) are a heterogeneous group of exogenous chemicals or chemical mixtures that interfere with the action of hormones and consequently cause adverse effects to humans and wildlife. The number of EDCs has markedly increased over the past 60 years. Humans are constantly exposed to hundreds of EDCs mainly through air, water, and food. Exposure to EDCs (in utero or lifetime) may be a significant component of the environmental origin of several medical conditions. The developing fetus and neonate are more sensitive than adults to perturbation by EDCs. The prenatal damage can cause adverse consequences later in life (developmental origins of adult disease). In many cases, the damage is irreversible. There is also a possibility of transgenerational effects. By interfering with hormonal functions, EDCs can contribute to a variety of dysfunctions and diseases including obesity, diabetes, reproductive disorders, and cancers. Information on long-term effects of chronic, low-dose exposure to EDCs is relatively limited. EDCs represent a global threat for human health and cause a high cost for the society. Promoting public knowledge and initiating preventive measures will help minimizing the health and economic consequences of EDCs for future generations.

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“…The effects of hormones are mediated mainly through interactions with their cognate receptors, such as ligand-inducible, transcription-modulating nuclear receptors (NRs) [32][33][34]. In addition to the classical steroid hormone receptors, among the most interesting candidates for ED and MDC effects are the so-called xenobiotic sensors, proteins specialized in sensing the chemical environment and typically involved in the activation of detoxification processes (for reviews, see [33][34][35][36]). Many NRs are well-known targets of several xenobiotics, including EDs and as they have also been shown to be involved in the regulation of cellular energy homeostasis, changes in their activity may underlie many adverse metabolic effects of MDCs [35] (Table 1).…”

Section: Introductionmentioning

confidence: 99%

“…Metabolism disrupting chemicals (MDCs), their nuclear receptors (NRs) and other transcription factor targets, epigenetic modifications, and mitochondrial effects[27,[33][34][35][36][37][38][39]46,47].…”

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confidence: 99%

The EDCMET Project: Metabolic Effects of Endocrine Disruptors

Küblbeck

Vuorio

Niskanen

et al. 2020

IJMS

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Endocrine disruptors (EDs) are defined as chemicals that mimic, block, or interfere with hormones in the body’s endocrine systems and have been associated with a diverse array of health issues. The concept of endocrine disruption has recently been extended to metabolic alterations that may result in diseases, such as obesity, diabetes, and fatty liver disease, and constitute an increasing health concern worldwide. However, while epidemiological and experimental data on the close association of EDs and adverse metabolic effects are mounting, predictive methods and models to evaluate the detailed mechanisms and pathways behind these observed effects are lacking, thus restricting the regulatory risk assessment of EDs. The EDCMET (Metabolic effects of Endocrine Disrupting Chemicals: novel testing METhods and adverse outcome pathways) project brings together systems toxicologists; experimental biologists with a thorough understanding of the molecular mechanisms of metabolic disease and comprehensive in vitro and in vivo methodological skills; and, ultimately, epidemiologists linking environmental exposure to adverse metabolic outcomes. During its 5-year journey, EDCMET aims to identify novel ED mechanisms of action, to generate (pre)validated test methods to assess the metabolic effects of Eds, and to predict emergent adverse biological phenotypes by following the adverse outcome pathway (AOP) paradigm.

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Perturbation of Nuclear Hormone Receptors by Endocrine Disrupting Chemicals: Mechanisms and Pathological Consequences of Exposure

Cited by 39 publications

References 221 publications

Molecular Image-Based Prediction Models of Nuclear Receptor Agonists and Antagonists Using the DeepSnap-Deep Learning Approach with the Tox21 10K Library

Molecular Image-Based Prediction Models of Nuclear Receptor Agonists and Antagonists Using the DeepSnap-Deep Learning Approach with the Tox21 10K Library

Human Health Consequences of Endocrine-Disrupting Chemicals

The EDCMET Project: Metabolic Effects of Endocrine Disruptors

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