In silico methods in the discovery of endocrine disrupting chemicals

In Silico Drug Design of Anti-Breast Cancer Agents

Cancer is a condition marked by abnormal cell proliferation that has the potential to invade or indicate other health issues. Human beings are affected by more than 100 different types of cancer. Some cancer promotes rapid cell proliferation, whereas others cause cells to divide and develop more slowly. Some cancers, such as leukemia, produce visible tumors, while others, such as breast cancer, do not. In this work, in silico investigations were carried out to investigate the binding mechanisms of four major analogs, which are marine sesquiterpene, sesquiterpene lactone, heteroaromatic chalcones, and benzothiophene against the target estrogen receptor-α for targeting breast cancer using Schrödinger suite 2021-4. The Glide module handled the molecular docking experiments, the QikProp module handled the ADMET screening, and the Prime MM-GB/SA module determined the binding energy of the ligands. The benzothiophene analog BT_ER_15f (G-score -15.922 Kcal/mol) showed the best binding activity against the target protein estrogen receptor-α when compared with the standard drug tamoxifen which has a docking score of -13.560 Kcal/mol. TRP383 (tryptophan) has the highest interaction time with the ligand, and hence it could act for a long time. Based on in silico investigations, the benzothiophene analog BT_ER_15f significantly binds with the active site of the target protein estrogen receptor-α. Similar to the outcomes of molecular docking, the target and ligand complex interaction motif established a high affinity of lead candidates in a dynamic system. This study shows that estrogen receptor-α targets inhibitors with better potential and low toxicity when compared to the existing market drugs, which can be made from a benzothiophene derivative. It may result in considerable activity and be applied to more research on breast cancer.

Review of in silico studies dedicated to the nuclear receptor family: Therapeutic prospects and toxicological concerns

Being in the center of both therapeutic and toxicological concerns, NRs are widely studied for drug discovery application but also to unravel the potential toxicity of environmental compounds such as pesticides, cosmetics or additives. High throughput screening campaigns (HTS) are largely used to detect compounds able to interact with this protein family for both therapeutic and toxicological purposes. These methods lead to a large amount of data requiring the use of computational approaches for a robust and correct analysis and interpretation. The output data can be used to build predictive models to forecast the behavior of new chemicals based on their in vitro activities. This atrticle is a review of the studies published in the last decade and dedicated to NR ligands in silico prediction for both therapeutic and toxicological purposes. Over 100 articles concerning 14 NR subfamilies were carefully read and analyzed in order to retrieve the most commonly used computational methods to develop predictive models, to retrieve the databases deployed in the model building process and to pinpoint some of the limitations they faced.

Biodegradable polymers and their nano-composites for the removal of endocrine-disrupting chemicals (EDCs) from wastewater: A review

Endocrine-disrupting chemicals (EDCs) target the endocrine system by interfering with the natural hormones in the body leading to adverse effects on human and animal health. These chemicals have been identified as major polluting agents in wastewater effluents. Pharmaceuticals, personal care products, industrial compounds, pesticides, dyes, and heavy metals are examples of substances that could be considered endocrine active chemicals. In humans, these chemicals could cause obesity, cancer, Alzheimer's disease, autism, reproductive abnormalities, and thyroid problems. While in wildlife, dysfunctional gene expression could lead to the feminization of some aquatic organisms, metabolic diseases, cardiovascular risk, and problems in the reproductive system as well as its levels of hatchability and vitellogenin. EDCs could be effectively removed from wastewater using advanced technologies such as reverse osmosis, membrane treatment, ozonation, advanced oxidation, filtration, and biodegradation. However, adsorption has been proposed as a more promising and sustainable method for water treatment than any other reported technique. Increased attention has been paid to biodegradable polymers and their nano-composites as promising adsorbents for the removal of EDCs from wastewater. These polymers could be either natural, synthetic, or a combination of both. This review presents a summary of the most relevant cases where natural and synthetic biodegradable polymers have been used for the successful removal of EDCs from wastewater. It demonstrates the effectiveness of these polymers as favorable adsorbents for novel wastewater treatment technologies. Hitherto, very limited work has been published on the use of both natural and synthetic biodegradable polymers to remove EDCs from wastewater, as most of the studies focused on the utilization of only one type, either natural or synthetic. Therefore, this review could pave the way for future exploration of biodegradable polymers as promising and sustainable adsorbents for the removal of various types of pollutants from wastewater.

Autopsy, thanatopraxy, cemeteries and crematoria as hotspots of toxic organic contaminants in the funeral industry continuum

The occurrence and health risks of toxic organic contaminants (TOCs) in the funeral industry are relatively under-studied compared to other industries. An increasing body of literature reports TOCs including emerging contaminants in the funeral industry, but comprehensive reviews of the evidence are still lacking. Hence, evidence was analysed to address the proposition that, the funeral industry constitutes several hotspot reservoirs of a wide spectrum of TOCs posing ecological and human health risks. TOCs detected include embalming products, persistent organic pollutants, synthetic pesticides, pharmaceuticals, personal care products and illicit drugs. Human cadavers, solid wastes, wastewaters and air-borne particulates from autopsy, thanatopraxy care facilities (mortuaries, funeral homes), cemeteries and crematoria are hotspots of TOCs. Ingestion of contaminated water, and aquatic and marine foods constitutes non-occupational human exposure, while occupational exposure occurs via inhalation and dermal intake. Risk factors promoting exposure to TOCs include unhygienic burial practices, poor solid waste and wastewater disposal, and weak and poorly enforced regulations. The generic health risks of TOCs are quite diverse, and include; (1) genotoxicity, endocrine disruption, teratogenicity and neurodevelopmental disorders, (2) development of antimicrobial resistance, (3) info-disruption via biomimicry, and (4) disruption of ecosystem functions and trophic interactions. Barring formaldehyde and inferential evidence, the epidemiological studies linking TOCs in the funeral industry to specific health outcomes are scarce. The reasons for the lack of evidence, and limitations of current health risk assessment protocols are discussed. A comprehensive framework for hazard identification, risk assessment and mitigation (HIRAM) in the funeral industry is proposed. The HIRAM includes regulatory, surveillance and control systems such as prevention and removal of TOCs. Future directions on the ecotoxicology of mixtures, behaviour, and health risks of TOCs are highlighted. The opportunities presented by emerging tools, including isotopic labelling, genomics, big data analytics (e.g., machine learning), and in silico techniques in toxicokinetic modelling are highlighted.

The 'thanato-resistome' - The funeral industry as a potential reservoir of antibiotic resistance: Early insights and perspectives

The funeral industry is a potential reservoir of antibiotic resistance. The occurrence, human exposure and health risks of antibiotic resistance in the funeral industry were examined. The funeral industry harbours antibiotic resistance to multiple common and last-resort antibiotics, hence constitutes the 'thanato-resistome'. Hydrological processes, air-borne particulates and vectors disseminate antibiotic resistance, while horizontal gene transfer circulates antibiotic resistance among resistomes, forming a complex network. Ingestion, inhalation of air-borne particulates, dermal intake and clothes of workers contribute to human exposure. Human health risks include; development of drug resistance in previously susceptible pathogens, and increased morbidity and mortality caused by increased pathogenicity and outbreaks of multi-drug resistant infections. Ecological risks include the proliferation of resistant organisms at the expense of susceptible ones, thereby disrupting ecosystem structure and function, including biogeochemical cycles. Barring inferential data, quantitative evidence linking antibiotic resistance to human infections is weak. This reflects the lack of systematic quantitative studies, rather than the absence of such health risks. Quantitative risk assessment is constrained by lack of quantitative data on antibiotic resistance in various reservoirs and exposure routes. A framework for risk assessment and mitigation is proposed. Finally, ten hypotheses and emerging tools such as genomics, in silico techniques and big data analytics are highlighted.

Natural and synthetic retinoid X receptor ligands and their role in selected nuclear receptor action

Important key players in the regulatory machinery within the cells are nuclear retinoid X receptors (RXRs), which compose heterodimers in company with several diverse nuclear receptors, playing a role as ligand inducible transcription factors. In general, nuclear receptors are ligand-activated, transcription-modulating proteins affecting transcriptional responses in target genes. RXR molecules forming permissive heterodimers with disparate nuclear receptors comprise peroxisome proliferator-activated receptors (PPARs), liver X receptors (LXRs), farnesoid X receptor (FXR), pregnane X receptor (PXR) and constitutive androstan receptor (CAR). Retinoid receptors (RARs) and thyroid hormone receptors (TRs) may form conditional heterodimers, and dihydroxyvitamin D₃ receptor (VDR) is believed to form nonpermissive heterodimer. Thus, RXRs are the important molecules that are involved in control of many cellular functions in biological processes and diseases, including cancer or diabetes. This article summarizes both naturally occurring and synthetic ligands for nuclear retinoid X receptors and describes, predominantly in mammals, their role in molecular mechanisms within the cells. A focus is also on triorganotin compounds, which are high affinity RXR ligands, and finally, we present an outlook on human microbiota as a potential source of RXR activators. Nevertheless, new synthetic rexinoids with better retinoid X receptor activity and lesser side effects are highly required.

Occurrence, behaviour, and human exposure pathways and health risks of toxic geogenic contaminants in serpentinitic ultramafic geological environments (SUGEs): A medical geology perspective

Serpentinitic ultramafic geological environments (SUGEs) contain toxic geogenic contaminants (TGCs). Yet comprehensive reviews on the medical geology of SUGEs are still lacking. The current paper posits that TGCs occur widely in SUGEs, and pose human health risks. The objectives of the review are to: (1) highlight the nature, occurrence and behaviour of TGCs associated with SUGEs; (2) discuss the human intake pathways and health risks of TGCs; (4) identify the key risk factors predisposing human health to TGCs particularly in Africa; and (5) highlight key knowledge gaps and future research directions. TGCs of human health concern in SUGEs include chrysotile asbestos, toxic metals (Fe, Cr, Ni, Mn, Zn, Co), and rare earth elements. Human intake of TGCs occur via inhalation, and ingestion of contaminated drinking water, wild foods, medicinal plants, animal foods, and geophagic earths. Occupational exposure may occur in the mining, milling, sculpturing, engraving, and carving industries. African populations are particularly at high risk due to: (1) widespread consumption of wild foods, medicinal plants, untreated drinking water, and geophagic earths; (2) weak and poorly enforced environmental, occupational, and public health regulations; and (3) lack of human health surveillance systems. Human health risks of chrysotile include asbestosis, cancers, and mesothelioma. Toxic metals are redox active, thus generate reactive oxygen species causing oxidative stress. Dietary intake of iron and geophagy may increase the iron overload among native Africans who are genetically predisposed to such health risks. Synergistic interactions among TGCs particularly chrysotile and toxic metals may have adverse human health effects. The occurrence of SUGEs, coupled with the several risk factors in Africa, provides a unique and ideal setting for investigating the relationships between TGCs and human health risks. A conceptual framework for human health risk assessment and mitigation, and future research direction are highlighted.

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.

Binding of iodinated contrast media (ICM) and their transformation products with hormone receptors: Are ICM the new EDCs?

Iodinated contrast media (ICM) have been detected at high concentrations (as high as about 3 μg/L) in surface water systems, and recently in fish brains and gonad. The mismatch between the polarity of ICM and the high lipid content of brain raises questions on whether their bioaccumulation is receptor-mediated. Furthermore, the structural similarity of ICM to the natural thyroid hormones thyroxine and triiodothyronine suggest potential binding of ICM to nuclear receptors in the endocrine system. Therefore, an in silico approach based on Surflex-Dock module of SYBYL was used to investigate the molecular docking of selected ICM (diatrizoic acid, iohexol, iopamidol, and iopromide). These ICM showed interaction with nuclear receptors that play key roles in endocrine regulation, including the androgen and estrogen receptors. Furthermore, the results indicate peroxisome proliferator-activated receptor gamma (PPARg) as one of the viable targets in the endocrine disrupting potential of ICM with higher Cscores for the ICM and iopromide transformation products than the reference ligand for the receptor. The data obtained from in silico calculations showed stronger binding of iohexol to the transthyretin-binding pocket compared to the natural hormones, thyroxine and triiodothyronine, suggesting the potential of ICM to act as endocrine disrupting chemicals (EDCs) in the environment.

Computational Drug Repurposing: Current Trends

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Biomedical discovery has been reshaped upon the exploding digitization of data which can be retrieved from a number of sources, ranging from clinical pharmacology to cheminformatics-driven databases. Now, supercomputing platforms and publicly available resources such as biological, physicochemical, and clinical data, can all be integrated to construct a detailed map of signaling pathways and drug mechanisms of action in relation to drug candidates. Recent advancements in computer-aided data mining have facilitated analyses of ‘big data’ approaches and the discovery of new indications for pre-existing drugs has been accelerated. Linking gene-phenotype associations to predict novel drug-disease signatures or incorporating molecular structure information of drugs and protein targets with other kinds of data derived from systems biology provide great potential to accelerate drug discovery and improve the success of drug repurposing attempts. In this review, we highlight commonly used computational drug repurposing strategies, including bioinformatics and cheminformatics tools, to integrate large-scale data emerging from the systems biology, and consider both the challenges and opportunities of using this approach. Moreover, we provide successful examples and case studies that combined various in silico drug-repurposing strategies to predict potential novel uses for known therapeutics.

Identification of the fungicide epoxiconazole by virtual screening and biological assessment as inhibitor of human 11β-hydroxylase and aldosterone synthase

Humans are constantly exposed to a multitude of environmental chemicals that may disturb endocrine functions. It is crucial to identify such chemicals and uncover their mode-of-action to avoid adverse health effects. 11β-hydroxylase (CYP11B1) and aldosterone synthase (CYP11B2) catalyze the formation of cortisol and aldosterone, respectively, in the adrenal cortex. Disruption of their synthesis by exogenous chemicals can contribute to cardio-metabolic diseases, chronic kidney disease, osteoporosis, and immune-related disorders. This study applied in silico screening and in vitro evaluation for the discovery of xenobiotics inhibiting CYP11B1 and CYP11B2. Several databases comprising environmentally relevant pollutants, chemicals in body care products, food additives and drugs were virtually screened using CYP11B1 and CYP11B2 pharmacophore models. A first round of biological testing used hamster cells overexpressing human CYP11B1 or CYP11B2 to analyze 25 selected virtual hits. Three compounds inhibited CYP11B1 and CYP11B2 with IC50 values below 3 μM. The most potent inhibitor was epoxiconazole (IC50 value of 623 nM for CYP11B1 and 113 nM for CYP11B2, respectively); flurprimidol and ancymidol were moderate inhibitors. In a second round, these three compounds were tested in human adrenal H295R cells endogenously expressing CYP11B1 and CYP11B2, confirming the potent inhibition by epoxiconazole and the more moderate effects by flurprimidol and ancymidol. Thus, the in silico screening, prioritization of chemicals for initial biological tests and use of H295R cells to provide initial mechanistic information is a promising strategy to identify potential endocrine disruptors inhibiting corticosteroid synthesis. A critical assessment of human exposure levels and in vivo evaluation of potential corticosteroid disrupting effects by epoxiconazole is required.

Overview of the effects of chemical mixtures with endocrine disrupting activity in the context of real-life risk simulation: An integrative approach (Review)

Research over the past years has indicated that chronic human exposure to very low doses of various chemical species in mixtures and administered via different routes (percutaneous, orally, etc.) should be the main focus of new biochemical and toxicological studies. Humans have daily contact with various chemicals, such as food additives, pesticides from fruits/vegetables, antibiotics (and other veterinary drugs) from meat, different types of preservatives from cosmetics, to name a few. Simultaneous exposure to this wide array of chemicals does not produce immediate effects, but summative effect/s over time that may be clinically manifested several years thereafter. Classical animal studies designed to test the toxic outcome of a single chemical are not suitable to assess, and then extrapolate to humans, the effects of a whole mixture of chemicals. Testing the aftermath of a combination of chemicals, at low doses, around or below the no observed adverse effect is stressed by many toxicologists. Thus, there is a need to reformulate the design of biochemical and toxicological studies in order to perform real-life risk simulation. This review discuss the potential use of computational methods as a complementary tool for in vitro and in vivo toxicity tests with a high predictive potential that could contribute to reduce animal testing, cost and time, when assessing the effects of chemical combinations. This review focused on the use of these methods to predict the potential endocrine disrupting activity of a mixture of chemicals.

Predicting estrogen receptor binding of chemicals using a suite of in silico methods - Complementary approaches of (Q)SAR, molecular docking and molecular dynamics

With the aim of obtaining reliable estimates of Estrogen Receptor (ER) binding for diverse classes of compounds, a weight of evidence approach using estimates from a suite of in silico models was assessed. The predictivity of a simple Majority Consensus of (Q)SAR models was assessed using a test set of compounds with experimental Relative Binding Affinity (RBA) data. Molecular docking was also carried out and the binding energies of these compounds to the ERα receptor were determined. For a few selected compounds, including a known full agonist and antagonist, the intrinsic activity was determined using low-mode molecular dynamics methods. Individual (Q)SAR model predictivity varied, as expected, with some models showing high sensitivity, others higher specificity. However, the Majority Consensus (Q)SAR prediction showed a high accuracy and reasonably balanced sensitivity and specificity. Molecular docking provided quantitative information on strength of binding to the ERα receptor. For the 50 highest binding affinity compounds with positive RBA experimental values, just 5 of them were predicted to be non-binders by the Majority QSAR Consensus. Furthermore, agonist-specific assay experimental values for these 5 compounds were negative, which indicates that they may be ER antagonists. We also showed different scenarios of combining (Q)SAR results with Molecular docking classification of ER binding based on cut-off values of binding energies, providing a rational combined strategy to maximize terms of toxicological interest.

Homology models of mouse and rat estrogen receptor-α ligand-binding domain created by in silico mutagenesis of a human template: molecular docking with 17ß-estradiol, diethylstilbestrol, and paraben analogs

Crystal structures exist for human, but not rodent, estrogen receptor-α ligand-binding domain (ERα-LBD). Consequently, rodent studies involving binding of compounds to ERα-LBD are limited in their molecular-level interpretation and extrapolation to humans. Because the sequences of rodent and human ERα-LBDs are > 95% identical, we expected their 3D structures and ligand binding to be highly similar. To test this hypothesis, we used the human ERα-LBD structure (PDB 3UUD) as a template to produce rat and mouse homology models. Employing the rodent models and human structure, we generated docking poses of 23 Group A ligands (17ß-estradiol, diethylstilbestrol, and 21 paraben analogs) in AutoDock Vina for interspecies comparisons. Ligand RMSDs (Å) (median, 95% CI) were 0.49 (0.21-1.82) (human-mouse) and 1.19 (0.22-1.82) (human-rat), well below the 2.0-2.5 Å range for equivalent docking poses. Numbers of interspecies ligand-receptor residue contacts were highly similar, with Sorensen Sc (%) = 96.8 (90.0-100) (human-mouse) and 97.7 (89.5-100) (human-rat). Likewise, numbers of interspecies ligand-receptor residue contacts were highly correlated: Pearson r = 0.913 (human-mouse) and 0.925 (human-rat). Numbers of interspecies ligand-receptor atom contacts were even more tightly correlated: r = 0.979 (human-mouse) and 0.986 (human-rat). Pyramid plots of numbers of ligand-receptor atom contacts by residue exhibited high interspecies symmetry and had Spearman r s = 0.977 (human-mouse) and 0.966 (human-rat). Group B ligands included 15 ring-substituted parabens recently shown experimentally to exhibit decreased binding to human ERα and to exert increased antimicrobial activity. Ligand efficiencies calculated from docking ligands into human ERα-LBD were well correlated with those derived from published experimental data (Pearson partial r p = 0.894 and 0.918; Groups A and B, respectively). Overall, the results indicate that our constructed rodent ERα-LBDs interact with ligands in like manner to the human receptor, thus providing a high level of confidence in extrapolations of rodent to human ligand-receptor interactions.

Computational study suggesting reconsideration of BPA analogues based on their endocrine disrupting potential estimated by binding affinities to nuclear receptors

Due to its endocrine disrupting nature Bisphenol-A (BPA), a chemical used in the plastic industry was placed under a ban which provided an incentive for its replacement by bisphenol and non-bisphenol based plasticizers. The use of bisphenol replacements in industry is increasing day by day. Therefore, it becomes prudent to put them under scrutiny. We studied the direct interaction of 45 BPA replacements and BPA with 12 nuclear receptors using an endocrine disruptome docking program (Kolšek et al., 2014b). Infact, the mechanism which could involve a direct interaction of ligands with nuclear receptors was taken into consideration. We found that the replacements, which were analogues of BPA, easily interacted with nuclear receptors due to the presence of phenyl moiety and their hydrophobic nature probably crucial for their endocrine disrupting potential. We therefore, strongly recommend reconsideration of BPA analogues in industries.

A combination of ternary classification models and reporter gene assays for the comprehensive thyroid hormone disruption profiles of 209 polychlorinated biphenyls

Computational toxicology is widely applied to screen tens and thousands of potential environmental endocrine disruptors (EDCs) for its great efficiency and rapid evaluation in recent years. Polychlorinated biphenyls (PCBs) with 209 congeners have not been comprehensively tested for their ability to interact with the thyroid receptor (TR), which is one of the most extensively studied targets related to the effects of EDCs. In this study, we aimed to determine the thyroid-disrupting mechanisms of 209 PCBs through the combination of a novel computational ternary classification model and luciferase reporter gene assay. The reporter gene assay was performed to examine the hormone activities of 22 PCBs via TR to classify their profiles as agonistic, antagonistic or inactive. Thus, six agonists, eleven antagonists and seven inactive chemicals against TR were identified in in vitro assays. Then, six relevant variables, including molecular structural descriptors and molecular docking scores, were selected for describing compounds. Machine learning methods (i.e., linear discriminant analysis (LDA) and support vector machines (SVM)) were used to build classification models. The optimal model was obtained by using SVM, with an accuracy of 88.24% in the training set, 80.0% in the test set and 75.0% in 10-fold cross-validation. The remaining 187 PCB congeners' hormone activities were predicted using the obtained models. Out of these PCBs, the SVM model predicted 38 agonists and 81 antagonists. The findings revealed that higher chlorinated PCBs tended to have TR-antagonistic activities, whereas lower chlorinated PCBs were agonists. This study provided a reference for further exploring PCBs' thyroid effect.

Virtual screening applications in short-chain dehydrogenase/reductase research

Several members of the short-chain dehydrogenase/reductase (SDR) enzyme family play fundamental roles in adrenal and gonadal steroidogenesis as well as in the metabolism of steroids, oxysterols, bile acids, and retinoids in peripheral tissues, thereby controlling the local activation of their cognate receptors. Some of these SDRs are considered as promising therapeutic targets, for example to treat estrogen-/androgen-dependent and corticosteroid-related diseases, whereas others are considered as anti-targets as their inhibition may lead to disturbances of endocrine functions, thereby contributing to the development and progression of diseases. Nevertheless, the physiological functions of about half of all SDR members are still unknown. In this respect, in silico tools are highly valuable in drug discovery for lead molecule identification, in toxicology screenings to facilitate the identification of hazardous chemicals, and in fundamental research for substrate identification and enzyme characterization. Regarding SDRs, computational methods have been employed for a variety of applications including drug discovery, enzyme characterization and substrate identification, as well as identification of potential endocrine disrupting chemicals (EDC). This review provides an overview of the efforts undertaken in the field of virtual screening supported identification of bioactive molecules in SDR research. In addition, it presents an outlook and addresses the opportunities and limitations of computational modeling and in vitro validation methods.

Integration of in silico methods and computational systems biology to explore endocrine-disrupting chemical binding with nuclear hormone receptors

Thousands of potential endocrine-disrupting chemicals present difficult regulatory challenges. Endocrine-disrupting chemicals can interfere with several nuclear hormone receptors associated with a variety of adverse health effects. The U.S. Environmental Protection Agency (U.S. EPA) has released its reviews of Tier 1 screening assay results for a set of pesticides in the Endocrine Disruptor Screening Program (EDSP), and recently, the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP) data. In this study, the predictive ability of QSAR and docking approaches is evaluated using these data sets. This study also presents a computational systems biology approach using carbaryl (1-naphthyl methylcarbamate) as a case study. For estrogen receptor and androgen receptor binding predictions, two commercial and two open source QSAR tools were used, as was the publicly available docking tool Endocrine Disruptome. For estrogen receptor binding predictions, the ADMET Predictor, VEGA, and OCHEM models (specificity: 0.88, 0.88, and 0.86, and accuracy: 0.81, 0.84, and 0.88, respectively) were each more reliable than the MetaDrug™ model (specificity 0.81 and accuracy 0.77). For androgen receptor binding predictions, the Endocrine Disruptome and ADMET Predictor models (specificity: 0.94 and 0.8, and accuracy: 0.78 and 0.71, respectively) were more reliable than the MetaDrug™ model (specificity 0.33 and accuracy 0.4). A consensus approach is proposed that reaches general agreement among the models (specificity 0.94 and accuracy 0.89). This study integrates QSAR, docking, and systems biology approaches as a virtual screening tool for use in risk assessment. As such, this systems biology pathways and network analysis approach provides a means to more critically assess the potential effects of endocrine-disrupting chemicals.

A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals

Endocrine-disrupting chemicals (EDCs), which can threaten ecological safety and be harmful to human beings, have been cause for wide concern. There is a high demand for efficient methodologies for evaluating potential EDCs in the environment. Herein an evaluation platform was developed using novel and statistically robust ternary models via different machine learning models (i.e., linear discriminant analysis, classification and regression tree, and support vector machines). The platform is aimed at effectively classifying chemicals with agonistic, antagonistic, or no estrogen receptor (ER) activities. A total of 440 chemicals from the literature were selected to derive and optimize the three-class model. One hundred and nine new chemicals appeared on the 2014 EPA list for EDC screening, which were used to assess the predictive performances by comparing the E-screen results with the predicted results of the classification models. The best model was obtained using support vector machines (SVM) which recognized agonists and antagonists with accuracies of 76.6% and 75.0%, respectively, on the test set (with an overall predictive accuracy of 75.2%), and achieved a 10-fold cross-validation (CV) of 73.4%. The external predicted accuracy validated by the E-screen assay was 87.5%, which demonstrated the application value for a virtual alert for EDCs with ER agonistic or antagonistic activities. It was demonstrated that the ternary computational model could be used as a faster and less expensive method to identify EDCs that act through nuclear receptors, and to classify these chemicals into different mechanism groups.

Dimorphic placental stress: A repercussion of interaction between endocrine disrupting chemicals (EDCs) and fetal sex

Placental homeostasis is critical for fetal development as it determines the health of mother and fetus during pregnancy and in later life. Interestingly even the fetus, in a sexually dimorphic manner, influences the pedantic growth and development of placenta. Although placenta is thought to act as a protective barrier against chemical exposures, certain endocrine disrupting chemicals (EDCs) that are circulating in mother's blood tend to cross placenta. These EDCs have been reported to cause changes in expression levels of certain genes, immunogenic factors and non-coding RNAs such as micro RNA (miRNA) and long non-coding RNA (lncRNA) leading to placental stress. We hypothesize that these changes in placenta occur in a sexually dimorphic manner as a result of interaction between EDC exposure and fetal sex. Therefore, we propose that the ability of placenta to respond and buffer EDC exposure depends on fetal sex and, hence the EDC associated disease susceptibility of one sex differs from the other.

Assessment of methods of detection of water estrogenicity for their use as monitoring tools in a process of estrogenicity removal

Methods of monitoring of estrogenicity in water were gathered, compared, and tested within the context of their practical use as measurement and design tools, in the development of a process of degradation of estrogenic endocrine disruptors. In this work, the focus was put on in vitro assays, with the use of analytical techniques as additional analysis when possible. Practically, from a literature review, four methods that seemed most suitable to practical use required in a process development were tested: the Yeast Estrogen Screen assay, the Lyticase-assisted Yeast Estrogen Screen assay (LYES), the MMV-LUC assay and the HPLC-UV analytical method. Dose-response curves in response to estrogenic standard 17β-estradiol were compared. Bisphenol A estrogenicity was measured by the methods as well. The model for the calculation of estradiol equivalents as measurements units was adapted. The methods were assessed in terms of ranges of detection, time of experiment, cost, ease of the experiment, reproducibility, etc. Based on that assessment, the LYES assay was selected and successfully applied to the monitoring of estrogenicity removal from 17β-estradiol and bisphenol A. More precisely, the bioassay allowed the acquisition of kinetic curves for a laboratory-scaled process of estrogenicity removal by immobilized enzymes in a continuous packed-bed reactor. The LYES assay was found to have a real methodological potential for scale-up and design of a treatment process. The HPLC-UV method showed good complementarity with the LYES assay for the monitoring of bisphenol A concentrations in parallel with estrogenicity, reporting no significant estrogenicity from degradation byproducts, among others.

Molecular mechanisms of endocrine and metabolic disruption: An in silico study on antitrypanosomal natural products and some derivatives

The VirtualToxLab is an in silico technology for estimating the toxic potential - endocrine and metabolic disruption, as well as aspects of carcinogenicity and cardiotoxicity - of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of currently 16 proteins, known or suspected to trigger adverse effects. The simulations are conducted at the atomic level and explicitly allow for a mechanistic interpretation of the results (in real-time 3D/4D), thereby complying with the Setubal principles put forward in 2002 for computational approaches to toxicology. Moreover, the underlying "ab-initio" protocol is independent from any training data and makes the approach universal with respect to the applicability domain. The VirtualToxLab runs in client-server mode and is freely available to academic and non-profit organizations. As the underlying technology yields a thermodynamic estimate of the binding affinity, the associated ligand-protein complexes have been challenged by molecular-dynamics simulations to probe their kinetic stability. Human African trypanosomiasis is a neglected tropical disease caused by two subspecies of Trypanosoma brucei. The control of this parasitic infection relies on a few chemotherapeutic agents, most of which were discovered decades ago and pose many challenges including adverse side effects, poor efficacy, and the occurrence of drug resistances. Natural products, on the other hand, offer a high potential for the discovery of new drug leads due to their chemical diversity. In this in silico study, we analyze a series of 89 natural products and derivatives displaying anti-trypanosomal activity for their potential to trigger adverse effects. Our results indicate a moderate potential for a number of those compounds to bind to nuclear receptors and thereby ease the development of endocrine disregulation. A few others would seem to inhibit enzymes of the cytochrome P450 family and, hence, sustain drug-drug interactions.

Steroids and endocrine disruptors--History, recent state of art and open questions

This introductory chapter provides an overview of the levels and sites at which endocrine disruptors (EDs) affect steroid actions. In contrast to the special issue of Journal of Steroid Biochemistry and Molecular Biology published three years ago and devoted to EDs as such, this paper focuses on steroids. We tried to point to more recent findings and opened questions. EDs interfere with steroid biosynthesis and metabolism either as inhibitors of relevant enzymes, or at the level of their expression. Particular attention was paid to enzymes metabolizing steroid hormones to biologically active products in target cells, such as aromatase, 5α-reductase and 3β-, 11β- and 17β-hydroxysteroid dehydrogenases. An important target for EDs is also steroid acute regulatory protein (StAR), responsible for steroid precursor trafficking to mitochondria. EDs influence receptor-mediated steroid actions at both genomic and non-genomic levels. The remarkable differences in response to various steroid-receptor ligands led to a more detailed investigation of events following steroid/disruptor binding to the receptors and to the mapping of the signaling cascades and nuclear factors involved. A virtual screening of a large array of EDs with steroid receptors, known as in silico methods (≡computer simulation), is another promising approach for studying quantitative structure activity relationships and docking. New data may be expected on the effect of EDs on steroid hormone binding to selective plasma transport proteins, namely transcortin and sex hormone-binding globulin. Little information is available so far on the effects of EDs on the major hypothalamo-pituitary-adrenal/gonadal axes, of which the kisspeptin/GPR54 system is of particular importance. Kisspeptins act as stimulators for hormone-induced gonadotropin secretion and their expression is regulated by sex steroids via a feed-back mechanism. Kisspeptin is now believed to be one of the key factors triggering puberty in mammals, and various EDs affect its expression and function. Finally, advances in analytics of EDs, especially those persisting in the environment, in various body fluids (plasma, urine, seminal fluid, and follicular fluid) are mentioned. Surprisingly, relatively scarce information is available on the simultaneous determination of EDs and steroids in the same biological material. This article is part of a Special Issue entitled 'Endocrine disruptors & steroids'.

Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases

Computational methods are well-established tools in the drug discovery process and can be employed for a variety of tasks. Common applications include lead identification and scaffold hopping, as well as lead optimization by structure-activity relationship analysis and selectivity profiling. In addition, compound-target interactions associated with potentially harmful effects can be identified and investigated. This review focuses on pharmacophore-based virtual screening campaigns specifically addressing the target class of hydroxysteroid dehydrogenases. Many members of this enzyme family are associated with specific pathological conditions, and pharmacological modulation of their activity may represent promising therapeutic strategies. On the other hand, unintended interference with their biological functions, e.g., upon inhibition by xenobiotics, can disrupt steroid hormone-mediated effects, thereby contributing to the development and progression of major diseases. Besides a general introduction to pharmacophore modeling and pharmacophore-based virtual screening, exemplary case studies from the field of short-chain dehydrogenase/reductase (SDR) research are presented. These success stories highlight the suitability of pharmacophore modeling for the various application fields and suggest its application also in futures studies.

Induction of the Estrogenic Marker Calbindn-D₉k by Octamethylcyclotetrasiloxane

Interrupting the hormonal balance of an organism by interfering with hormones and their target receptors gives rise to various problems such as developmental disorders. Collectively, these reagents are known as endocrine disruptors (EDs). Cyclic volatile methyl siloxanes (cVMSs) are a group of silicone polymers that including octamethylcyclotetrasiloxane (D4). In the present study, we examined the estrogenicity of D4 through in vitro and in vivo assays that employed calcium-binding protein 9K (calbindin-D9k; CaBP-9K) as a biomarker. For in vitro investigation, GH3 rat pituitary cells were exposed to vehicle, 17β-estradiol (E2), or D4 with/without ICI 182 780 (ICI). CaBP-9K and progesterone receptor (PR) both were up-regulated by E2 and D4 which were completely blocked by ICI. Transcription of estrogen receptor α (ER α) was decreased by E2 and D4 but increased by ICI. D4 was also administered to immature female rats for an uterotrophic (UT) assay and detection of CaBP-9K. Ethinyl estradiol (EE) or D4 was administered subcutaneously with or without ICI. Although uterine weight was not significant altered by D4, an effect thought to be due to cytochrome P450 (CYP), it induced CaBP-9K and PR gene expression. Based on these results we reveal that D4 has estrogenic potential proven under in vitro and in vivo experimental conditions.

A monograph on the remediation of hazardous phthalates

Phthalates or phthalic acid esters are a group of xenobiotic and hazardous compounds blended in plastics to enhance their plasticity and versatility. Enormous quantities of phthalates are produced globally for the production of plastic goods, whose disposal and leaching out into the surroundings cause serious concerns to the environment, biota and human health. Though in silico computational, in vitro mechanistic, pre-clinical animal and clinical human studies showed endocrine disruption, hepatotoxic, teratogenic and carcinogenic properties, usage of phthalates continues due to their cuteness, attractive chemical properties, low production cost and lack of suitable alternatives. Studies revealed that microbes isolated from phthalate-contaminated environmental niches efficiently bioremediate various phthalates. Based upon this background, this review addresses the enumeration of major phthalates used in industry, routes of environmental contamination, evidences for health hazards, routes for in situ and ex situ microbial degradation, bacterial pathways involved in the degradation, major enzymes involved in the degradation process, half-lives of phthalates in environments, etc. Briefly, this handy module would enable the readers, environmentalists and policy makers to understand the impact of phthalates on the environment and the biota, coupled with the concerted microbial efforts to alleviate the burden of ever increasing load posed by phthalates.

Computational study of binding affinity to nuclear receptors for some cosmetic ingredients

We studied the ingredients of cosmetic products as potential endocrine disruptors (ED) by in silico methods (docking). The structures of 14 human nuclear receptors have been retrieved from the protein data bank (PDB). We only considered the mechanism linked with direct binding to nuclear receptors with well-defined crystal structures. Predictions were performed using the Endocrine Disruptome docking program http://endocrinedisruptome.ki.si/ (Kolšek et al., 2013). 122 compounds were estimated to be possible endocrine disruptors bind to at least one of the receptors, 21 of them which are predicted to be probable toxicants for endocrine disruption as they bind to more than five receptors simultaneously. According to the literature survey and lack of experimental data it remains a challenge to prove or disprove the in silico results experimentally also for other potential endocrine disruptors.

LncRNA HOTAIR: A master regulator of chromatin dynamics and cancer

Non-coding RNAs (ncRNAs) are emerging classes of regulatory RNA that play key roles in various cellular and physiological processes such as in gene regulation, chromatin dynamics, cell differentiation, and development. NcRNAs are dysregulated in a variety of human disorders including cancers, neurological disorders, and immunological disorders. The mechanisms through which ncRNAs regulate various biological processes and human diseases still remain elusive. HOX antisense intergenic RNA (HOTAIR) is a recently discovered long non-coding RNA (lncRNA) that plays critical role in gene regulation and chromatin dynamics, appears to be misregulated in a variety of cancers. HOTAIR interacts with key epigenetic regulators such as histone methyltransferase PRC2 and histone demethylase LSD1 and regulates gene silencing. Here, we have reviewed recent advancements in understanding the functions and regulation of HOTAIR and its association with cancer and other diseases.

Computational toxicology, friend or foe?

Computational approaches offer the attraction of being both fast and cheap to run being able to process thousands of chemical structures in a few minutes. As with all new technology, there is a tendency for these approaches to be hyped up and claims of reliability and performance may be exaggerated. So just how good are these computational methods?

Reporter Cell Lines for the Characterization of the Interactions between Human Nuclear Receptors and Endocrine Disruptors

Endocrine-disrupting chemicals (EDCs) are exogenous substances interfering with hormone biosynthesis, metabolism, or action, and consequently causing disturbances in the endocrine system. Various pathways are activated by EDCs, including interactions with nuclear receptors (NRs), which are primary targets of numerous environmental contaminants. The main NRs targeted by environmental contaminants are the estrogen (ER α, β) and the androgen (AR) receptors. ERs and AR have pleiotropic regulatory roles in a diverse range of tissues, notably in the mammary gland, the uterus, and the prostate. Thus, dysfunctional ERs and AR signaling due to inappropriate exposure to environmental pollutants may lead to hormonal cancers and infertility. The pregnane X receptor (PXR) is also recognized by many environmental molecules. PXR has a protective role of the body through its ability to regulate proteins involved in the metabolism, the conjugation, and the transport of many exogenous and endogenous compounds. However, the permanent activation of this receptor by xenobiotics may lead to premature drug metabolism, the formation, and accumulation of toxic metabolites and defects in hormones homeostasis. The activity of other NRs can also be affected by environmental molecules. Compounds capable of inhibiting or activating the estrogen related (ERRγ), the thyroid hormone (TRα, β), the retinoid X receptors (RXRα, β, γ), and peroxisome proliferator-activated (PPAR α, γ) receptors have been identified and are highly suspected to promote developmental, reproductive, neurological, or metabolic diseases in humans and wildlife. In this review, we provide an overview of reporter cell lines established to characterize the human NR activities of a large panel of EDCs including natural as well as industrial compounds such as pesticides, plasticizers, surfactants, flame retardants, and cosmetics.

Mechanisms mediating environmental chemical-induced endocrine disruption in the adrenal gland

Humans are continuously exposed to hundreds of man-made chemicals that pollute the environment in addition to multiple therapeutic drug treatments administered throughout life. Some of these chemicals, known as endocrine disruptors (EDs), mimic endogenous signals, thereby altering gene expression, influencing development, and promoting disease. Although EDs are eventually removed from the market or replaced with safer alternatives, new evidence suggests that early-life exposure leaves a fingerprint on the epigenome, which may increase the risk of disease later in life. Epigenetic changes occurring in early life in response to environmental toxicants have been shown to affect behavior, increase cancer risk, and modify the physiology of the cardiovascular system. Thus, exposure to an ED or combination of EDs may represent a first hit to the epigenome. Only limited information is available regarding the effect of ED exposure on adrenal function. The adrenal gland controls the stress response, blood pressure, and electrolyte homeostasis. This endocrine organ therefore has an important role in physiology and is a sensitive target of EDs. We review herein the effect of ED exposure on the adrenal gland with particular focus on in utero exposure to the plasticizer di(2-ethylehyl) phthalate. We discuss the challenges associated with identifying the mechanism mediating the epigenetic origins of disease and availability of biomarkers that may identify individual or population risks.

Structural and functional profiling of environmental ligands for estrogen receptors

BACKGROUND

Individuals are exposed daily to environmental pollutants that may act as endocrine-disrupting chemicals (EDCs), causing a range of developmental, reproductive, metabolic, or neoplastic diseases. With their mostly hydrophobic pocket that serves as a docking site for endogenous and exogenous ligands, nuclear receptors (NRs) can be primary targets of small molecule environmental contaminants. However, most of these compounds are chemically unrelated to natural hormones, so their binding modes and associated hormonal activities are hardly predictable.

OBJECTIVES

We conducted a correlative analysis of structural and functional data to gain insight into the mechanisms by which 12 members of representative families of pollutants bind to and activate the estrogen receptors ERα and ERβ.

METHODS

We used a battery of biochemical, structural, biophysical, and cell-based approaches to characterize the interaction between ERs and their environmental ligands.

RESULTS

Our study revealed that the chemically diverse compounds bound to ERs via varied sets of protein-ligand interactions, reflecting their differential activities, binding affinities, and specificities. We observed xenoestrogens binding to both ERs-with affinities ranging from subnanomolar to micromolar values-and acting in a subtype-dependent fashion as full agonists or partial agonists/antagonists by using different combinations of the activation functions 1 and 2 of ERα and ERβ.

CONCLUSIONS

The precise characterization of the interactions between major environmental pollutants and two of their primary biological targets provides rational guidelines for the design of safer chemicals, and will increase the accuracy and usefulness of structure-based computational methods, allowing for activity prediction of chemicals in risk assessment.

EDCs DataBank: 3D-Structure database of endocrine disrupting chemicals

Endocrine disrupting chemicals (EDCs) are a group of compounds that affect the endocrine system, frequently found in everyday products and epidemiologically associated with several diseases. The purpose of this work was to develop EDCs DataBank, the only database of EDCs with three-dimensional structures. This database was built on MySQL using the EU list of potential endocrine disruptors and TEDX list. It contains the three-dimensional structures available on PubChem, as well as a wide variety of information from different databases and text mining tools, useful for almost any kind of research regarding EDCs. The web platform was developed employing HTML, CSS and PHP languages, with dynamic contents in a graphic environment, facilitating information analysis. Currently EDCs DataBank has 615 molecules, including pesticides, natural and industrial products, cosmetics, drugs and food additives, among other low molecular weight xenobiotics. Therefore, this database can be used to study the toxicological effects of these molecules, or to develop pharmaceuticals targeting hormone receptors, through docking studies, high-throughput virtual screening and ligand-protein interaction analysis. EDCs DataBank is totally user-friendly and the 3D-structures of the molecules can be downloaded in several formats. This database is freely available at http://edcs.unicartagena.edu.co.

OpenVirtualToxLab--a platform for generating and exchanging in silico toxicity data

The VirtualToxLab is an in silico technology for estimating the toxic potential--endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity--of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of currently 16 proteins, known or suspected to trigger adverse effects: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The toxic potential of a compound--its ability to trigger adverse effects--is derived from its computed binding affinities toward these very proteins: the computationally demanding simulations are executed in client-server model on a Linux cluster of the University of Basel. The graphical-user interface supports all computer platforms, allows building and uploading molecular structures, inspecting and downloading the results and, most important, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. Access to the VirtualToxLab is available free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations.

REACH and in silico methods: an attractive opportunity for medicinal chemists

REACH, the most ambitious chemical legislation in the world, provides unprecedented opportunities for medicinal chemists. Companies must report (eco)toxicological information about their chemicals, disseminated to the public domain by the European Chemicals Agency after their registration. The availability of this wealth of new toxicological data, together with the promotion of REACH of in silico methods, appoints medicinal chemists to a leading role in the regulatory hazard assessment process. In fact, Quantitative Structure-Activity Relation ship (QSAR) models and predictive toxicology have been applied in drug design and development for decades. Here, we discuss toxicological endpoints and areas where further development is needed to provide an enlightened appraisal of this attractive new opportunity.

Bisphenol-A and diethylstilbestrol exposure induces the expression of breast cancer associated long noncoding RNA HOTAIR in vitro and in vivo

Antisense transcript, long non-coding RNA HOTAIR is a key player in gene silencing and breast cancer and is transcriptionally regulated by estradiol. Here, we have investigated if HOTAIR expression is misregulated by bisphenol-A (BPA) and diethylstilbestrol (DES). Our findings demonstrate BPA and DES induce HOTAIR expression in cultured human breast cancer cells (MCF7) as well as in vivo in the mammary glands of rat. Luciferase assay showed that HOTAIR promoter estrogen-response-elements (EREs) are induced by BPA and DES. Estrogen-receptors (ERs) and ER-coregulators such as MLL-histone methylases (MLL1 and MLL3) bind to the HOTAIR promoter EREs in the presence of BPA and DES, modify chromatin (histone methylation and acetylation) and lead to gene activation. Knockdown of ERs down-regulated the BPA and DES-induced expression of HOTAIR. In summary, our results demonstrate that BPA and DES exposure alters the epigenetic programming of the HOTAIR promoters leading to its endocrine disruption in vitro and in vivo.

Endocrine disruption of oestrogen action and female reproductive tract cancers

Endocrine disrupting chemicals (EDC) are ubiquitous and persistent compounds that have the capacity to interfere with normal endocrine homoeostasis. The female reproductive tract is exquisitely sensitive to the action of sex steroids, and oestrogens play a key role in normal reproductive function. Malignancies of the female reproductive tract are the fourth most common cancer in women, with endometrial cancer accounting for most cases. Established risk factors for development of endometrial cancer include high BMI and exposure to oestrogens or synthetic compounds such as tamoxifen. Studies on cell and animal models have provided evidence that many EDC can bind oestrogen receptors and highlighted early life exposure as a window of risk for adverse lifelong effects on the reproductive system. The most robust evidence for a link between early life exposure to EDC and adverse reproductive health has come from studies on women who were exposed in utero to diethylstilbestrol. Demonstration that EDC can alter expression of members of the HOX gene cluster highlights one pathway that might be vulnerable to their actions. In summary, evidence for a direct link between EDC exposure and cancers of the reproductive system is currently incomplete. It will be challenging to attribute causality to any single EDC when exposure and development of malignancy may be separated by many years and influenced by lifestyle factors such as diet (a source of phytoestrogens) and adiposity. This review considers some of the evidence collected to date.