In Silico Predictions of Endocrine Disruptors Properties

QSAR: Using the Past to Study the Present

Quantitative structure-activity relationships (QSAR) is a method for predicting the physical and biological properties of small molecules; it is in use in industry and public services. However, as any scientific method, it is challenged by more and more requests, especially considering its possible role in assessing the safety of new chemicals. To answer the question whether QSAR, by exploiting available knowledge, can build new knowledge, the chapter reviews QSAR methods in search of a QSAR epistemology. QSAR stands on tree pillars, i.e., biological data, chemical knowledge, and modeling algorithms. Usually the biological data, resulting from good experimental practice, are taken as a true picture of the world; chemical knowledge has scientific bases; so if a QSAR model is not working, blame modeling. The role of modeling in developing scientific theories, and in producing knowledge, is so analyzed. QSAR is a mature technology and is part of a large body of in silico methods and other computational methods. The active debate about the acceptability of the QSAR models, about the way to communicate them, and the explanation to provide accompanies the development of today QSAR models. An example about predicting possible endocrine-disrupting chemicals (EDC) shows the many faces of modern QSAR methods.

In silico models for the screening of human transthyretin disruptors

The use of New Approach Methodologies (NAMs), such as Quantitative Structure-Activity Relationship (QSAR) models, is highly recommended by international regulations to speed up hazard and risk assessment of Endocrine Disruptors, which are known to be linked to a wide spectrum of severe diseases on humans and wildlife. A very sensitive target for these chemicals is the thyroid hormone system, which plays a key role in regulating metabolic and cognitive functions. Several chemicals have been demonstrated to compete with the thyroid hormone thyroxine (T4) for binding to human thyroid hormone distributor protein transthyretin (hTTR). In this work, we generated three new datasets composed by T4-hTTR competing potencies of more than 200 heterogeneous chemicals measured by three different in vitro assays. These datasets were used for the development of new regression QSAR models. The best models were thoroughly validated by internal and external validation procedures. The mechanistic interpretation of the selected molecular descriptors provided information on structural features which are relevant to characterise hTTR binders, such as the presence of hydroxylated and halogenated aromatic rings. PCA analysis was used to rank the studied chemicals according to their increasing T4-hTTR competing potency. Hydroxylated and halogenated bicyclic aromatic compounds are ranked as the strongest hTTR binders. The new QSARs are useful to screen potential Thyroid Hormone System-Disrupting Chemicals (THSDCs), and to support the identification of sustainable alternatives to hazardous chemicals.

In silico analysis of endocrine-disrupting potential of triclosan, bisphenol A, and their analogs and derivatives

Owning to the increasing body of evidence about the ubiquitous exposure to endocrine disruptors (EDCs), particularly bisphenol A (BPA), and associated health effects, BPA has been gradually substituted with insufficiently tested structural analogs. The unmanaged excessive use of antimicrobial agents such as triclosan (TCS) during the COVID-19 outbreak has also raised concerns about its possible interferences with hormonal functions. The similarity of BPA and estradiol, as well as TCS and non-steroidal estrogens, imply that endocrine-disrupting properties of their analogs could be predicted based on the chemical structure. Hence, this study aimed to evaluate the endocrine-disrupting potential of BPA substitutes as well as TCS derivatives and degradation/biotransformation metabolites, in comparison to BPA and TCS based on their molecular properties, computational predictions of pharmacokinetics and binding affinities to nuclear receptors. Based on the obtained results several under-researched BPA analogs exhibited higher binding affinities for nuclear receptors than BPA. Notable analogs included compounds detected in receipts (DD-70, BTUM-70, TGSA, and BisOPP-A), along with a flame retardant, BDP. The possible health hazards linked to exposure to TCS and its mono-hydroxylated metabolites were also found. Further research is needed in order to elucidate the health impacts of these compounds and promote better regulation practices.

Exposure and potential risks of thirteen endocrine- disrupting chemicals in pharmaceuticals and personal care products for breastfed infants in China

Ingestion of breast milk represents the primary exposure pathway for endocrine-disrupting chemicals (EDCs) in newborns. To elucidate the associated risks, it is essential to quantify EDC levels in both breast milk and infant urine. This study measured the concentrations of 13 EDCs, including parabens (methyl paraben (MP), ethyl paraben (EP), propyl paraben (PP), iso-propyl paraben, butyl paraben, and iso-butyl paraben), bisphenols (bisphenol A (BPA), bisphenol F, bisphenol S, bisphenol AF, and bisphenol Z), triclosan (TCS), and triclocarban, in breast milk and infant urine to assess their potential health effects and endocrine disruption risks. In total, 1 014 breast milk samples were collected from 20 cities across China, along with 144 breast milk samples and 134 urine samples from a mother-infant cohort in Hangzhou. The EDCs were detected using ultra-high-performance liquid chromatography-triple quadrupole mass spectrometry. Endocrine-disrupting potency was evaluated using a predictive method based on EDC affinity for 15 hormone receptor proteins. The toxicological priority index (ToxPi), incorporating population exposure data, was employed to assess health risks associated with exposure to multiple EDCs. Among the 13 EDCs, MP, EP, PP, BPA, and TCS were detected in over 50 % of breast milk samples, with the highest median concentrations observed for MP (0.37 ng/mL), EP (0.29 ng/mL), and BPA (0.17 ng/mL). Across the 20 cities, 0 %-40 % of infants had a hazard index (HI) exceeding 1. Based on affinity prediction analysis and estimated exposure, cumulative endocrine disruption risk intensity was ranked as MP > TCS > BPA > EP > PP. This research highlights the extensive exposure of Chinese infants to EDCs, offering a detailed analysis of their varying endocrine disruption potencies and underscoring the significant health risks associated with EDCs in breast milk.

Novel dihydropyrimidines as promising EGFR & HER2 inhibitors: Insights from experimental and computational studies

Dihydropyrimidines are widely recognized for their diverse biological properties and are often synthesized by the Biginelli reactions. In this backdrop, a novel series of Biginelli dihydropyrimidines were designed, synthesized, purified, and analyzed by FT-IR, 1H NMR, 13C NMR, and mass spectrometry. Anticancer activity against MCF-7 breast cancer cells was evaluated as part of their cytotoxicity in comparison with the normal Vero cells. The cytotoxicity of dihydropyrimidines ranges from moderate to significant. Among the 38 dihydropyrimidines screened, compounds 16, 21, and 39 exhibited significant cytotoxicity. These 3 compounds were subjected to flow cytometry studies and EGFRwt Kinase inhibition assay using lapatinib as a standard. The study included evaluation for the inhibition of EGFR and HER2 expression at five different concentrations. At a concentration of 1000 nM compound 21 showed 98.51 % and 96.79 % inhibition of EGFR and HER2 expression. Moreover, compounds 16, 21 and 39 significantly inhibited EGFRwt activity with IC50 = 69.83, 37.21 and 76.79 nM, respectively. In addition, 3D-QSAR experiments were conducted to elucidate Structure activity relationships in a 3D grid space by comparing the experimental and predicted cytotoxic activities. Molecular docking studies were performed to validate the results by in silico method. All together, we developed a new series of Biginelli dihydropyrimidines as dual EGFR/HER2 inhibitors.

Probabilistic risk assessment of endocrine disrupting pesticides in Iran

The chronic dietary risk assessment for 34 pesticides suspected of acting as endocrine disrupters in Iran was assessed by comparing TMDI with the Acceptable Daily Intakes (ADI). Of 34 investigated endocrine-disrupting pesticides (EDPs), 6 had TMDI > ADI. In addition, potential non-carcinogenic and carcinogenic health risk assessments were evaluated using Monte Carlo simulation. HQ in wheat was 17.40 and 20.29 in adults and children, respectively. Due to dimethoate residue in wheat, HQ was 2.78, and for fenitrothion residue, 3.22. HI was 21.22 for adults and 24.76 for children in wheat, more than 1. Total Carcinogenic risk (TCR) due to EDPs residues was 6.40 × 10-5 in apples, in citrus fruits 5.97 × 10-5, 3.33 × 10-5 in cucumber, 5.30 × 10-5 in lettuce, in potato was 2.36 × 10-5, in rice was 1.61 × 10-5, 1.78 × 10-5 in tomato, and due to epoxiconazole residues in wheat was 3.18 × 10-5, more than acceptable limit 1.0 × 10-6. Therefore, consumers were at significant risk of carcinogenesis.Abbreviations: PCBs: polychlorinated biphenyls; BPA: Bisphenol A; ED: Endocrine Disrupting; EDCs: Endocrine Disrupting Chemicals; EDPs: Endocrine Disrupting Pesticides; ADI: Acceptable Daily Intake; TMDI: Theoretical Maximum Daily Intake; FAO: Food and Agriculture Organization; WHO: World Health Organization; MRL: Maximum Residue Limit; HQ: Hazard Quotient; HI: Hazard Index; CR: Cancer Risk; TCR: Total Cancer Risk; PPP: plant protection products.

Thyroid dysfunction caused by exposure to environmental endocrine disruptors and the underlying mechanism: A review

Thyroid disease has been rapidly increasing, but its causes remain unclear. At present, many studies have focused on the relationship between environmental endocrine disruptors (EEDs) and the pathogenesis of thyroid disease. Herein, we summarize such studies exploring the effects of exposure to common EEDs on thyrotoxicosis, finding that EEDs appear to contribute to the pathogenesis of thyroid-related diseases such as thyroid cancer, goiter, thyroiditis, hyperthyroidism, and hypothyroidism. To explore this causative effect in detail, we have analyzed the following three aspects of how EEDs are believed to exert their impacts on the occurrence and development of thyroid disease: (1) damage to the thyroid tissue structure, including disrupted mitochondria and the stratification of thyroid follicular epithelial cells; (2) disruption of thyroid hormone signaling, including thyroid hormone synthesis and secretion disorders, destruction of normal function of the hypothalamus-pituitary-thyroid axis, disturbed estrogen signaling in the body, alterations to the level of thyroid-stimulating hormone, inhibition of the release of thyroglobulin from thyroid cells, and reductions in the levels of sodium iodide co-transporters, thyroid peroxidase, deiodinase, and transthyretin; and (3) molecular mechanisms underlying the disruption of thyroid function, including competitive binding to T3 and T4 receptors, disturbance of the hypothalamic-pituitary-thyroid axis, activation of the ERK and Akt pathways, oxidative stress, regulation of the expression of the proto-oncogene k-Ras, tumor suppressor gene PTEN, and thyroid TSHR gene, and induction of autophagy in thyroid cells. Overall, this article reviews how EEDs can affect the occurrence and development of thyroid disease via multiple routes, thus providing new ideas to intervene for the prevention, diagnosis, treatment, and prognosis of thyroid disease.

Comparison of photoinduced and electrochemically induced degradation of venlafaxine

The European Union requires environmental monitoring of the antidepressant drug venlafaxine. Advanced oxidation processes provide a remedy against the spread of micropollutants. In this study, the photoinduced and electrochemical decompositions of venlafaxine were investigated in terms of mechanism and efficacy using high-performance liquid chromatography coupled to high-resolution multifragmentation mass spectrometry. Kinetic analysis, structure elucidation, matrix variation, and radical scavenging indicated the dominance of a hydroxyl-mediated indirect mechanism during photodegradation and hydroxyl and direct electrochemical oxidation for electrochemical degradation. Oxidants, sulfate, and chloride ions acted as accelerants, which reduced venlafaxine half-lives from 62 to 25 min. Humic acid decelerated degradation during ultra-violet irradiation up to 50%, but accelerated during electrochemical oxidation up to 56%. In silico quantitative structure activity relationship analysis predicted decreased environmental hazard after advanced oxidation process treatment. In general, photoirradiation proved more efficient due to faster decomposition and slightly less toxic transformation products. Yet, matrix effects would have to be carefully evaluated when potential applications as a fourth purification stage were to be considered.

Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders

An abnormal hormonal activity or exposure to endocrine-disrupting chemicals (EDCs) can cause endocrine system malfunction. Among the many interactions EDCs can affect is the disruption of estrogen signalling, which can lead to adverse health effects such as cancer, osteoporosis, neurodegenerative diseases, cardiovascular disease, insulin resistance, and obesity. Knowing which chemical can act as an EDC is a significant advantage and a practical necessity. New Approach Methodologies (NAM) computational models offer a quick and cost-effective solution for preliminary hazard assessment of chemicals without animal testing. Therefore, a machine learning approach was used to investigate the relationships between estrogen receptor (ER) activity and chemical structure to identify chemicals that can interact with ER. For this purpose, the consolidated in vitro assay data from ToxCast/Tox21 projects was used for developing Random Forest classification models for ER binding, agonists, and antagonists. The overall classification prediction accuracy reaches up to 82%, depending on whether the model predicted agonists, antagonists, or compounds that bind to the active site. Given the imbalance in endocrine disruption data, the derived models are good candidates for deprioritising chemicals and reducing animal testing. The interpretation of theoretical molecular descriptors of the models was consistent with the molecular interactions known in the ligand binding pocket. The estimated class probabilities enabled the analysis of the applicability domain of the developed models and the assessment of the predictions' reliability, followed by the guidelines for interpreting prediction results. The models are openly accessible and useable at QsarDB.org (http://dx.doi.org/10.15152/QDB.259) according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles.

Research advances in identification procedures of endocrine disrupting chemicals

Endocrine disrupting chemicals (EDCs) are increasingly concerned substance endangering human health and environment. However, there is no unified standard for identifying chemicals as EDCs, which is also controversial internationally. In this review, the procedures for EDC identification in different organizations/countries were described. Importantly, three aspects to be considered in identifying chemical substances as EDCs were summarized, which were mechanistic data, animal experiments, and epidemiological information. The relationships between them were also discussed. To elaborate more clearly on these three aspects of evidence, scientific data on some chemicals including bisphenol A, 1,2-dibromo-4-(1,2 dibromoethyl) cyclohexane and perchlorate were collected and evaluated. Altogether, the above three chemicals were assessed for interfering with hormones and elaborated their health hazards from macroscopic to microscopic. This review is helpful for standardizing the identification procedure of EDCs.

Systems bioengineering approaches for developmental toxicology

Developmental toxicology is the field of study that examines the effects of chemical and physical agents on developing organisms. By using principles of systems biology and bioengineering, a systems bioengineering approach could be applied to study the complex interactions between developing organisms, the environment, and toxic agents. This approach would result in a holistic understanding of the effects of toxic agents on organisms, by considering the interactions between different biological systems and the impacts of toxicants on those interactions. It would be useful in identifying key biological pathways and mechanisms affected by toxic agents, as well as in the development of predictive models to assess potential risks of exposure to toxicants during development. In this review, we discuss the relevance of systems bioengineering to the field of developmental toxicity and provide up-to-date examples that illustrate the use of engineering principles for this application.

New Approach Methodologies for the Endocrine Activity Toolbox: Environmental Assessment for Fish and Amphibians

Multiple in vivo test guidelines focusing on the estrogen, androgen, thyroid, and steroidogenesis pathways have been developed and validated for mammals, amphibians, or fish. However, these tests are resource-intensive and often use a large number of laboratory animals. Developing alternatives for in vivo tests is consistent with the replacement, reduction, and refinement principles for animal welfare considerations, which are supported by increasing mandates to move toward an "animal-free" testing paradigm worldwide. New approach methodologies (NAMs) hold great promise to identify molecular, cellular, and tissue changes that can be used to predict effects reliably and more efficiently at the individual level (and potentially on populations) while reducing the number of animals used in (eco)toxicological testing for endocrine disruption. In a collaborative effort, experts from government, academia, and industry met in 2020 to discuss the current challenges of testing for endocrine activity assessment for fish and amphibians. Continuing this cross-sector initiative, our review focuses on the current state of the science regarding the use of NAMs to identify chemical-induced endocrine effects. The present study highlights the challenges of using NAMs for safety assessment and what work is needed to reduce their uncertainties and increase their acceptance in regulatory processes. We have reviewed the current NAMs available for endocrine activity assessment including in silico, in vitro, and eleutheroembryo models. New approach methodologies can be integrated as part of a weight-of-evidence approach for hazard or risk assessment using the adverse outcome pathway framework. The development and utilization of NAMs not only allows for replacement, reduction, and refinement of animal testing but can also provide robust and fit-for-purpose methods to identify chemicals acting via endocrine mechanisms. Environ Toxicol Chem 2023;42:757-777. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Novel Thiosemicarbazone Quantum Dots in the Treatment of Alzheimer's Disease Combining In Silico Models Using Fingerprints and Physicochemical Descriptors

Searching for thiosemicarbazone derivatives with the potential to inhibit acetylcholinesterase for the treatment of Alzheimer's disease (AD) is an important current goal. The QSAR_KPLS, QSAR_ANN, and QSAR_SVR models were constructed using binary fingerprints and physicochemical (PC) descriptors of 129 thiosemicarbazone compounds screened from a database of 3791 derivatives. The R ² and Q ² values for the QSAR_KPLS, QSAR_ANN, and QSAR_SVR models are greater than 0.925 and 0.713 using dendritic fingerprint (DF) and PC descriptors, respectively. The in vitro pIC₅₀ activities of four new design-oriented compounds N1, N2, N3, and N4, from the QSAR_KPLS model using DFs, are consistent with the experimental results and those from the QSAR_ANN and QSAR_SVR models. The designed compounds N1, N2, N3, and N4 do not violate Lipinski-5 and Veber rules using the ADME and BoiLED-Egg methods. The binding energy, kcal mol^-1, of the novel compounds to the 1ACJ-PDB protein receptor of the AChE enzyme was also obtained by molecular docking and dynamics simulations consistent with those predicted from the QSAR_ANN and QSAR_SVR models. New compounds N1, N2, N3, and N4 were synthesized, and the experimental in vitro pIC₅₀ activity was determined in agreement with those obtained from in silico models. The newly synthesized thiosemicarbazones N1, N2, N3, and N4 can inhibit 1ACJ-PDB, which is predicted to be able to cross the barrier. The DFT B3LYP/def-SV(P)-ECP quantization calculation method was used to calculate E _HOMO and E _LUMO to account for the activities of compounds N1, N2, N3, and N4. The quantum calculation results explained are consistent with those obtained in in silico models. The successful results here may contribute to the search for new drugs for the treatment of AD.

Bioremediation of Endocrine Disrupting Chemicals- Advancements and Challenges

Endocrine Disrupting Chemicals (EDCs), major group of recalcitrant compounds, poses a serious threat to the health and future of millions of human beings, and other flora and fauna for years to come. A close analysis of various xenobiotics undermines the fact that EDC is structurally diverse chemical compounds generated as a part of anthropogenic advancements as well as part of their degradation. Regardless of such structural diversity, EDC is common in their ultimate drastic effect of impeding the proper functioning of the endocrinal system, basic physiologic systems, resulting in deregulated growth, malformations, and cancerous outcomes in animals as well as humans. The current review outlines an overview of various EDCs, their toxic effects on the ecosystem and its inhabitants. Conventional remediation methods such as physico-chemical methods and enzymatic approaches have been put into action as some form of mitigation measures. However, the last decade has seen the hunt for newer technologies and methodologies at an accelerated pace. Genetically engineered microbial degradation, gene editing strategies, metabolic and protein engineering, and in-silico predictive approaches - modern day's additions to our armamentarium in combating the EDCs are addressed. These additions have greater acceptance socially with lesser dissonance owing to reduced toxic by-products, lower health trepidations, better degradation, and ultimately the prevention of bioaccumulation. The positive impact of such new approaches on controlling the menace of EDCs has been outlaid. This review will shed light on sources of EDCs, their impact, significance, and the different remediation and bioremediation approaches, with a special emphasis on the recent trends and perspectives in using sustainable approaches for bioremediation of EDCs. Strict regulations to prevent the release of estrogenic chemicals to the ecosystem, adoption of combinatorial methods to remove EDC and prevalent use of bioremediation techniques should be followed in all future endeavors to combat EDC pollution. Moreover, the proper development, growth and functioning of future living forms relies on their non-exposure to EDCs, thus remediation of such chemicals present even in nano-concentrations should be addressed gravely.

Hyperandrogenism and Polycystic ovary syndrome: Effects in pregnancy and offspring development

Polycystic ovary syndrome (PCOS) is one of the major endocrine disorders affecting women of reproductive age. Its etiology remains unclear. It is suggested that environmental factors, and particularly the intrauterine environment, play key roles in PCOS development. Besides the role of androgens in PCOS pathogenesis, exposure to endocrine disruptors, as is Bisphenol A, could also contribute to its development. Although PCOS is considered one of the leading causes of ovarian infertility, many PCOS patients can get pregnant. Some of them by natural conception and others by assisted reproductive technique treatments. As hyperandrogenism (one of PCOS main features) affects ovarian and uterine functions, PCOS women, despite reaching pregnancy, could present high-risk pregnancies, including implantation failure, an increased risk of gestational diabetes, preeclampsia, and preterm birth. Moreover, hyperandrogenism may also be maintained in these women during pregnancy. Therefore, as an altered uterine milieu, including hormonal imbalance, could affect the developing organisms, monitoring these patients throughout pregnancy and their offspring development is highly relevant. The present review focuses on the impact of androgenism and PCOS on fertility issues and pregnancy-related outcomes and offspring development. The evidence suggests that the increased risk of pregnancy complications and adverse offspring outcomes of PCOS women would be due to the factors involved in the syndrome pathogenesis and the related co-morbidities. A better understanding of the involved mechanisms is still needed and could contribute to a better management of these women and their offspring. This article is categorized under: Reproductive System Diseases > Molecular and Cellular Physiology Reproductive System Diseases > Environmental Factors.

ER/AR Multi-Conformational Docking Server: A Tool for Discovering and Studying Estrogen and Androgen Receptor Modulators

The prediction of the estrogen receptor (ER) and androgen receptor (AR) activity of a compound is quite important to avoid the environmental exposures of endocrine-disrupting chemicals. The Estrogen and Androgen Receptor Database (EARDB, http://eardb.schanglab.org.cn/) provides a unique collection of reported ERα, ERβ, or AR protein structures and known small molecule modulators. With the user-uploaded query molecules, molecular docking based on multi-conformations of a single target will be performed. Moreover, the 2D similarity search against known modulators is also provided. Molecules predicted with a low binding energy or high similarity to known ERα, ERβ, or AR modulators may be potential endocrine-disrupting chemicals or new modulators. The server provides a tool to predict the endocrine activity for compounds of interests, benefiting for the ER and AR drug design and endocrine-disrupting chemical identification.

Integrated Genomic and Bioinformatics Approaches to Identify Molecular Links between Endocrine Disruptors and Adverse Outcomes

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.

Interspecies Differences in Activation of Peroxisome Proliferator-Activated Receptor γ by Pharmaceutical and Environmental Chemicals

Endocrine disrupting chemicals (EDCs) are able to deregulate the hormone system, notably through interactions with nuclear receptors (NRs). The mechanisms of action and biological effects of many EDCs have mainly been tested on human and mouse but other species such as zebrafish and xenopus are increasingly used as a model to study the effects of EDCs. Among NRs, peroxisome proliferator-activated receptor γ (PPARγ) is a main target of EDCs, for which most experimental data have been obtained from human and mouse models. To assess interspecies differences, we tested known human PPARγ ligands on reporter cell lines expressing either human, mouse, zebrafish, or xenopus PPARγ. Using these cell lines, we were able to highlight major interspecies differences. Known hPPARγ pharmaceutical ligands modulated hPPARγ and mPPARγ activities in a similar manner, while xPPARγ was less responsive and zfPPARγ was not modulated at all by these compounds. On the contrary, human liver X receptor (hLXR) ligands GW 3965 and WAY-252623 were only active on zfPPARγ. Among environmental compounds, several molecules activated the PPARγ of the four species similarly, e.g., phthalates (MEHP), perfluorinated compounds (PFOA, PFOS), and halogenated derivatives of BPA (TBBPA, TCBPA), but some of them like diclofenac and the organophosphorus compounds tri-o-tolyl phosphate and triphenyl phosphate were most active on zfPPARγ. This study confirms or shows for the first time the h, m, x, and zfPPARγ activities of several chemicals and demonstrates the importance of the use of species-specific models to study endocrine and metabolism disruption by environmental chemicals.

Exposure to Melamine cyanuric acid in adolescent mice caused emotional disorder and behavioral disorder

Melamine cyanuric acid (MCA) is a flame retardant linked by hydrogen bonds between melamine and cyanuric acid. MCA is used in an excellent series of phosphorus and nitrogen flame retardants. MCA can harm the kidney, liver, testis, and spleen cells. However, the effects of MCA on the emotions and behaviour of adolescent mice have not yet been investigated. In this article, male mice were exposed to MCA at 10, 20, and 40 mg/kg for four weeks. MCA exposure resulted in enhanced mouse locomotor and nocturnal activity. We also observed anxiety-like and depression-like behaviours. Moreover, after MCA exposure, the serum concentrations of thyroid-related hormones were changed, and the mRNA levels were affected. In short, MCA exposure can cause behavioural and emotion disorders.

Predicting Potential Endocrine Disrupting Chemicals Binding to Estrogen Receptor α (ERα) Using a Pipeline Combining Structure-Based and Ligand-Based in Silico Methods

The estrogen receptors α (ERα) are transcription factors involved in several physiological processes belonging to the nuclear receptors (NRs) protein family. Besides the endogenous ligands, several other chemicals are able to bind to those receptors. Among them are endocrine disrupting chemicals (EDCs) that can trigger toxicological pathways. Many studies have focused on predicting EDCs based on their ability to bind NRs; mainly, estrogen receptors (ER), thyroid hormones receptors (TR), androgen receptors (AR), glucocorticoid receptors (GR), and peroxisome proliferator-activated receptors gamma (PPARγ). In this work, we suggest a pipeline designed for the prediction of ERα binding activity. The flagged compounds can be further explored using experimental techniques to assess their potential to be EDCs. The pipeline is a combination of structure based (docking and pharmacophore models) and ligand based (pharmacophore models) methods. The models have been constructed using the Environmental Protection Agency (EPA) data encompassing a large number of structurally diverse compounds. A validation step was then achieved using two external databases: the NR-DBIND (Nuclear Receptors DataBase Including Negative Data) and the EADB (Estrogenic Activity DataBase). Different combination protocols were explored. Results showed that the combination of models performed better than each model taken individually. The consensus protocol that reached values of 0.81 and 0.54 for sensitivity and specificity, respectively, was the best suited for our toxicological study. Insights and recommendations were drawn to alleviate the screening quality of other projects focusing on ERα binding predictions.

A Comparative Study of Human and Zebrafish Pregnane X Receptor Activities of Pesticides and Steroids Using In Vitro Reporter Gene Assays

The nuclear receptor pregnane X receptor (PXR) is a ligand-dependent transcription factor that regulates genes involved in xenobiotic metabolism in mammals. Many studies suggest that PXR may play a similar role in fish. The interaction of human PXR (hPXR) with a variety of structurally diverse endogenous and exogenous chemicals is well described. In contrast, little is known about the zebrafish PXR (zfPXR). In order to compare the effects of these chemicals on the PXR of these two species, we established reporter cell lines expressing either hPXR or zfPXR. Using these cellular models, we tested the hPXR and zfPXR activity of various steroids and pesticides. We provide evidence that steroids were generally stronger activators of zfPXR while pesticides were more potent on hPXR. In addition, some chemicals (econazole nitrate, mifepristone, cypermethrin) showed an antagonist effect on zfPXR, whereas no antagonist chemical has been identified for hPXR. These results confirm significant differences in the ability of chemicals to modulate zfPXR in comparison to hPXR and point out that zfPXR assays should be used instead of hPXR assays for evaluating the potential risks of chemicals on aquatic species.

Piperazine-substituted derivatives of favipiravir for Nipah virus inhibition: What do in silico studies unravel?

Favipiravir is found to show excellent in-vitro inhibition activity against Nipah virus. To explore the structure-property relationship of Favipiravir, in silico designing of a series of piperazine substituted Favipiravir derivatives are attempted and computational screening has been done to evaluate its bimolecular interactions with Nipah virus. The geometrical features of all the molecules have been addressed from Density Functional Theory calculations. Chemical reactivity descriptor analysis was carried out to understand various reactivity parameters. The drug-likeness properties were estimated by a detailed ADMET study. The binding ability and the mode of binding of these derivatives into the Nipah virus are obtained from molecular docking studies. Our calculations show greater binding ability for the designed inhibitors compared to that of the experimentally reported molecule. Overall, the present work proves to offers new insights and guidelines for synthetic chemists to develop new drugs using piperazine substituted Favipiravir in the treatment of Nipah virus.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s42452-020-04051-9.

Binary and multi-class classification for androgen receptor agonists, antagonists and binders

Androgens and androgen receptor regulate a variety of biological effects in the human body. The impaired functioning of androgen receptor may have different adverse health effects from cancer to infertility. Therefore, it is important to determine whether new chemicals have any binding activity and act as androgen agonists or antagonists before commercial use. Due to the large number of chemicals that require experimental testing, the computational methods are a viable alternative. Therefore, the aim of the present study was to develop predictive QSAR models for classifying compounds according to their activity at the androgen receptor. A large data set of chemicals from the CoMPARA project was used for this purpose and random forest classification models have been developed for androgen binding, agonistic, and antagonistic activity. In addition, a unique effort has been made for multi-class approach that discriminates between inactive compounds, agonists and antagonists simultaneously. For the evaluation set, the classification models predicted agonists with 80% of accuracy and for the antagonists' and binders' the respective metrics were 72% and 78%. Combining agonists, antagonists and inactive compounds into a multi-class approach added complexity to the modelling task and resulted to 64% prediction accuracy for the evaluation set. Considering the size of the training data sets and their imbalance, the achieved evaluation accuracy is very good. The final classification models are available for exploring and predicting at QsarDB repository (https://doi.org/10.15152/QDB.236).

The GOLIATH Project: Towards an Internationally Harmonised Approach for Testing Metabolism Disrupting Compounds

The purpose of this project report is to introduce the European "GOLIATH" project, a new research project which addresses one of the most urgent regulatory needs in the testing of endocrine-disrupting chemicals (EDCs), namely the lack of methods for testing EDCs that disrupt metabolism and metabolic functions. These chemicals collectively referred to as "metabolism disrupting compounds" (MDCs) are natural and anthropogenic chemicals that can promote metabolic changes that can ultimately result in obesity, diabetes, and/or fatty liver in humans. This project report introduces the main approaches of the project and provides a focused review of the evidence of metabolic disruption for selected EDCs. GOLIATH will generate the world's first integrated approach to testing and assessment (IATA) specifically tailored to MDCs. GOLIATH will focus on the main cellular targets of metabolic disruption-hepatocytes, pancreatic endocrine cells, myocytes and adipocytes-and using an adverse outcome pathway (AOP) framework will provide key information on MDC-related mode of action by incorporating multi-omic analyses and translating results from in silico, in vitro, and in vivo models and assays to adverse metabolic health outcomes in humans at real-life exposures. Given the importance of international acceptance of the developed test methods for regulatory use, GOLIATH will link with ongoing initiatives of the Organisation for Economic Development (OECD) for test method (pre-)validation, IATA, and AOP development.

The EDCMET Project: Metabolic Effects of Endocrine Disruptors

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.

Experimental Approaches for Characterizing the Endocrine-Disrupting Effects of Environmental Chemicals in Fish

Increasing industrial and agricultural activities have led to a disturbing increase of pollutant discharges into the environment. Most of these pollutants can induce short-term, sustained or delayed impacts on developmental, physiological, and behavioral processes that are often regulated by the endocrine system in vertebrates, including fish, thus they are termed endocrine-disrupting chemicals (EDCs). Physiological impacts resulting from the exposure of these vertebrates to EDCs include abnormalities in growth and reproductive development, as many of the prevalent chemicals are capable of binding the receptors to sex steroid hormones. The approaches employed to investigate the action and impact of EDCs is largely dependent on the specific life history and habitat of each species, and the type of chemical that organisms are exposed to. Aquatic vertebrates, such as fish, are among the first organisms to be affected by waterborne EDCs, an attribute that has justified their wide-spread use as sentinel species. Many fish species are exposed to these chemicals in the wild, for either short or prolonged periods as larvae, adults, or both, thus, studies are typically designed to focus on either acute or chronic exposure at distinct developmental stages. The aim of this review is to provide an overview of the approaches and experimental methods commonly used to characterize the effects of some of the environmentally prevalent and emerging EDCs, including 17 α-ethinylestradiol, nonylphenol, BPA, phthalates, and arsenic; and the pervasive and potential carriers of EDCs, microplastics, on reproduction and growth. In vivo and in vitro studies are designed and employed to elucidate the direct effects of EDCs at the organismal and cellular levels, respectively. In silico approaches, on the other hand, comprise computational methods that have been more recently applied with the potential to replace extensive in vitro screening of EDCs. These approaches are discussed in light of model species, age and duration of EDC exposure.