An integrated "4-phase" approach for setting endocrine disruption screening priorities--phase I and II predictions of estrogen receptor binding affinity

Recent legislation mandates the US Environmental Protection Agency (EPA) to develop a screening and testing program for potential endocrine disrupting chemicals (EDCs), of which xenoestrogens figure prominently. Under the legislation, a large number of chemicals will undergo various in vitro and in vivo assays for their potential estrogenicity, as well as other hormonal activities. There is a crucial need for priority setting before this strategy can be effectively implemented. Here we report an integrated computational approach to priority setting using estrogen receptor (ER) binding as an example. This approach rationally integrates different predictive computational models into a "Four-Phase" scheme so that it can effectively identify potential estrogenic EDCs based on their predicted ER relative binding affinity (RBA). The system has been validated using an in-house ER binding assay dataset for 232 chemicals that was designed to have both broad structural diversity and a wide range of binding affinities. When applied to 58,000 chemicals identified by Walker et al. as candidates for endocrine disruption screening, some 9100 chemicals were predicted to bind to ER. Of these, only 3600 were expected to bind to ER at RBA values up to 100,000-fold less than that of 17beta-estradiol. The method ruled out 83% of the chemicals as non-binders with a very low rate of false negatives. We believe that the same integrated scheme will be equally applicable to endpoints of other endocrine disrupting mechanisms, e.g. androgen receptor binding.     

Comparative molecular field analysis (CoMFA) model using a large diverse set of natural, synthetic and environmental chemicals for binding to the androgen receptor

A large number of natural, synthetic and environmental chemicals are capable of disrupting the endocrine systems of experimental animals, wildlife and humans. These so-called endocrine disrupting chemicals (EDCs), some mimic the functions of the endogenous androgens, have become a concern to the public health. Androgens play an important role in many physiological processes, including the development and maintenance of male sexual characteristics. A common mechanism for androgen to produce both normal and adverse effects is binding to the androgen receptor (AR). In this study, we used Comparative Molecular Field Analysis (CoMFA), a three-dimensional quantitative structure-activity relationship (3D-QSAR) technique, to examine AR-ligand binding affinities. A CoMFA model with r2 = 0.902 and q2 = 0.571 was developed using a large training data set containing 146 structurally diverse natural, synthetic, and environmental chemicals with a 10(6)-fold range of relative binding affinity (RBA). By comparing the binding characteristics derived from the CoMFA contour map with these observed in a human AR crystal structure, we found that the steric and electrostatic properties encoded in this training data set are necessary and sufficient to describe the RBA of AR ligands. Finally, the CoMFA model was challenged with an external test data set; the predicted results were close to the actual values with average difference of 0.637 logRBA. This study demonstrates the utility of this CoMFA model for real-world use in predicting the AR binding affinities of structurally diverse chemicals over a wide RBA range.     

A reactivity pattern for discrimination of ER agonism and antagonism based on 3-D molecular attributes

Various models have been developed to predict the relative binding affinity (RBA) of chemicals to estrogen receptors (ER). These models can be used to prioritize chemicals for further tiered biological testing to assess the potential for endocrine disruption. One shortcoming of models predicting RBA has been the inability to distinguish potential receptor antagonism from agonism, and hence in vivo response. It has been suggested that steroid receptor antagonists are less compact than agonists; thus, ER binding of antagonists may prohibit proper alignment of receptor protein helices preventing subsequent transactivation. The current study tests the theory of chemical bulk as a defining parameter of antagonism by employing a 3-D structural approach for development of reactivity patterns for ER antagonists and agonists. Using a dataset of 23 potent ER ligands (16 agonists, 7 antagonists), molecular parameters previously found to be associated with ER binding affinity, namely global ( E HOMO ) and local (donor delocalizabilities and charges) electron donating ability of electronegative sites and steric distances between those sites, were found insufficient to discriminate ER antagonists from agonists. However, parameters related to molecular bulk, including solvent accessible surface and negatively charged Van der Waal's surface, provided reactivity patterns that were 100% successful in discriminating antagonists from agonists in the limited data set tested. The model also shows potential to discriminate pure antagonists from partial agonist/antagonist structures. Using this exploratory model it is possible to predict additional chemicals for their ability to bind but inactivate the ER, providing a further tool for hypothesis testing to elucidate chemical structural characteristics associated with estrogenicity and anti-estrogenicity.     

A reactivity pattern for discrimination of ER agonism and antagonism based on 3-D molecular attributes

Various models have been developed to predict the relative binding affinity (RBA) of chemicals to estrogen receptors (ER). These models can be used to prioritize chemicals for further tiered biological testing to assess the potential for endocrine disruption. One shortcoming of models predicting RBA has been the inability to distinguish potential receptor antagonism from agonism, and hence in vivo response. It has been suggested that steroid receptor antagonists are less compact than agonists; thus, ER binding of antagonists may prohibit proper alignment of receptor protein helices preventing subsequent transactivation. The current study tests the theory of chemical bulk as a defining parameter of antagonism by employing a 3-D structural approach for development of reactivity patterns for ER antagonists and agonists. Using a dataset of 23 potent ER ligands (16 agonists, 7 antagonists), molecular parameters previously found to be associated with ER binding affinity, namely global (E(HOMO)) and local (donor delocalizabilities and charges) electron donating ability of electronegative sites and steric distances between those sites, were found insufficient to discriminate ER antagonists from agonists. However, parameters related to molecular bulk, including solvent accessible surface and negatively charged Van der Waal's surface, provided reactivity patterns that were 100% successful in discriminating antagonists from agonists in the limited data set tested. The model also shows potential to discriminate pure antagonists from partial agonist/antagonist structures. Using this exploratory model it is possible to predict additional chemicals for their ability to bind but inactivate the ER, providing a further tool for hypothesis testing to elucidate chemical structural characteristics associated with estrogenicity and anti-estrogenicity.     

QSAR models using a large diverse set of estrogens

Endocrine disruptors (EDs) have a variety of adverse effects in humans and animals. About 58,000 chemicals, most having little safety data, must be tested in a group of tiered assays. As assays will take years, it is important to develop rapid methods to help in priority setting. For application to large data sets, we have developed an integrated system that contains sequential four phases to predict the ability of chemicals to bind to the estrogen receptor (ER), a prevalent mechanism for estrogenic EDs. Here we report the results of evaluating two types of QSAR models for inclusion in phase III to quantitatively predict chemical binding to the ER. Our data set for the relative binding affinities (RBAs) to the ER consists of 130 chemicals covering a wide range of structural diversity and a 6 orders of magnitude spread of RBAs. CoMFA and HQSAR models were constructed and compared for performance. The CoMFA model had a r2 = 0.91 and a q2LOO = 0.66. HQSAR showed reduced performance compared to CoMFA with r2 = 0.76 and q2LOO = 0.59. A number of parameters were examined to improve the CoMFA model. Of these, a phenol indicator increased the q2LOO to 0.71. When up to 50% of the chemicals were left out in the leave-N-out cross-validation, the q2 remained significant. Finally, the models were tested by using two test sets; the q2pred for these were 0.71 and 0.62, a significant result which demonstrates the utility of the CoMFA model for predicting the RBAs of chemicals not included in the training set. If used in conjunction with phases I and II, which reduced the size of the data set dramatically by eliminating most inactive chemicals, the current CoMFA model (phase III) can be used to predict the RBA of chemicals with sufficient accuracy and to provide quantitative information for priority setting.     

Holographic QSAR of environmental estrogens

Environmental endocrine disrupting chemicals(EDCs) or environmental estrogens pose severe healthhazard to wildlife and humans. They are believed to bethe main cause of the weakening activity and secretionof sex hormone, sperm declination, abnormal repro-d…     

Densitometry determination of oestrogenic EDCs with gold nanoparticle-modified oestrogen response element assay

Oestrogen receptor binding assay is an important approach to screen oestrogenic endocrine disruptors. But it is often expensive and radioactive pollution has existed. In order to screening endocrine disrupting chemicals (EDCs) without a radioactive label, we developed a new high-throughout method using gold nanoparticle technology. The assay is based on the competition binding between the oestrogenic EDCs in the sample and 17β-estradiol-BSA to the oestrogen receptor. The signal is from specific binding of gold nanoparticles labelled ERE to the ligand-receptor complex. The result showed that as little as 100?pg?L^?1 of 17β-estradiol could be detected with a linear range from 100?pg?L^?1 to 1?µg?L^?1 (R ²?=?0.9764). The concentrations of oestrogenic EDCs in environmental sample determined by our method and by the cell (MCF-7) proliferation were not significantly different. The result presented led us to conclude that this method is an ideal screening method which is reliable, low-cost, rapid, high-throughout and could be performed on microplates or chips.     

Effects-based chemical category approach for prioritization of low affinity estrogenic chemicals

Regulatory agencies are charged with addressing the endocrine disrupting potential of large numbers of chemicals for which there is often little or no data on which to make decisions. Prioritizing the chemicals of greatest concern for further screening for potential hazard to humans and wildlife is an initial step in the process. This paper presents the collection of in vitro data using assays optimized to detect low affinity estrogen receptor (ER) binding chemicals and the use of that data to build effects-based chemical categories following QSAR approaches and principles pioneered by Gilman Veith and colleagues for application to environmental regulatory challenges. Effects-based chemical categories were built using these QSAR principles focused on the types of chemicals in the specific regulatory domain of concern, i.e. non-steroidal industrial chemicals, and based upon a mechanistic hypothesis of how these non-steroidal chemicals of seemingly dissimilar structure to 17ß-estradiol (E2) could interact with the ER via two distinct binding types. Chemicals were also tested to solubility thereby minimizing false negatives and providing confidence in determination of chemicals as inactive. The high-quality data collected in this manner were used to build an ER expert system for chemical prioritization described in a companion article in this journal.     

Screening of endocrine disrupting chemicals using a surface plasmon resonance sensor.

Because concern over endocrine disrupting reactions caused by chemicals to humans and animals is growing, a rapid and reliable screening assay for endocrine disrupting chemicals is required. We have developed an in vitro screening assay based on a hormone receptor mechanism using a surface plasmon resonance (SPR) sensor. The interaction between an estrogen receptor alpha (ER) and an estrogen response element (ERE) is monitored in real time, when ER is injected over the SPR sensor chip on which a DNA fragment containing ERE is immobilized. In the presence of a chemical with estrogenic activity, the ER-ERE interaction is enhanced and the kinetic parameters are altered. We have validated the assay in terms of its specificity, dose dependency, optimal reaction conditions and reproducibility. It has been shown that the assay is very reliable as a rapid and quantitative screening method to judge the estrogenic activities of chemicals.     

Molecular recognition of endocrine disruptors by synthetic and natural 17β-estradiol receptors: a comparative study

A β-estradiol receptor binding mimic was synthesised using molecular imprinting. Bulk polymers and spherical polymer nanoparticles based on methacrylic acid and ethylene glycol dimethacrylate as the functional monomer and crosslinker, respectively, were prepared in acetonitrile. The selectivity was evaluated by radioligand binding assays. The imprinted polymers were very specific to β-estradiol since the control polymers bound virtually none of the radioligand. The bulk polymer was then employed to screen endocrine disrupting chemicals. Structurally related steroids like α-estradiol, estrone and ethynylestradiol showed, respectively, 14.0, 5.0 and 0.7% of relative binding to the β-estradiol polymer, whereas most unrelated chemicals did not bind at all. These results are compared to those obtained with a bioassay using stably transfected yeast cells in culture bearing the human estrogen receptor. The receptor was activated by several estrogen-like chemicals and to a lesser extent by some structurally related chemicals. Figure A molecularly imprinted polymer that was a synthetic receptor for beta-estradiol was used for the screening of endocrine disrupting chemicals that are structurally related or unrelated to beta-estradiol. The results were compared with the recognition of the compounds by the biological estrogen receptor expressed in yeast cells. Related steroids like alpha-estradiol, estrone and ethynylestradiol showed significant binding to the beta-estradiol imprinted polymer, whereas most unrelated chemicals did not bind. The biological receptor was activated by several estrogen-like chemicals, and to a lesser extent by some structurally related chemicals     

Development of a nanomechanical biosensor for analysis of endocrine disrupting chemicals

A nanomechanical transducer is developed to detect and screen endocrine disrupting chemicals (EDCs) combining fluidic sample injection and delivery with bioreceptor protein functionalized microcantilevers (MCs). The adverse affects of EDCs on the endocrine system of humans, livestock, and wildlife provides strong motivation for advances in analytical detection and monitoring techniques. The combination of protein receptors, which include estrogen receptor alpha (ER-alpha) and estrogen receptor beta (ER-beta), as well as monoclonal antibodies (Ab), with MC systems employing modified nanostructured surfaces provides for excellent nanomechanical response sensitivity and the inherent selectivity of biospecific receptor-EDC interactions. The observed ranking of binding interaction of the tested EDCs with ER-beta is diethylstilbestrol (DES) > 17-beta-estradiol > 17-alpha-estradiol > 2-OH-estrone > bisphenol A > p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) with measurements exhibiting intra-day RSDs of about 3%. A comparison of responses of three EDCs, which include 17-beta-estradiol, 17-alpha-estradiol, and 2-OH-estrone, with ER-beta and ER-alpha illustrates which estrogen receptor subtype provides the greatest sensitivity. Antibodies specific to a particular EDC can also be used for analyte specific screening. Calibration plots for a MC functionalized with anti-17-beta-estradiol Ab show responses in the range of 1 x 10(-11) through 1 x 10(-7) M for 17-beta-estradiol with a linear portion extending over two orders of magnitude in concentration.     

环境水体中酚类EDCs前处理技术及分析方法研究进展

环境内分泌干扰物(EDCs)是指干扰生物体内保持自身平衡和调节发育过程中天然激素的合成、分泌、运输、代谢、结合、反应、消除等生物过程的外源性化学物质,这类物质的存在会干扰人类和野生动物的内分泌系统,带来生殖障碍、发育异常、免疫功能减弱等问题。EDCs,尤其是使用最为广泛的酚类EDCs,在水环境中的污染特征研究已是当前科学界和公众共同关注的热点问题之一。环境样品基质非常复杂,使得痕量酚类EDCs的分析检测难度较大。该文对近年来环境水体中酚类EDCs的分析方法进行了综述,分别对样品前处理与检测分析技术进行了介绍,其中前处理技术包括样品萃取、样品净化和样品衍生化,检测分析技术包括化学分析和仪器分析。最后对酚类分析方法进行了展望。     

卵黄蛋白原的分离测定及其在环境内分泌干扰物质筛选中的应用

环境内分泌干扰物的存在直接威胁野生动物的生存和人类的健康，对其作用机制及筛选方法的研究，已经成为环境科学研究的热点领域。近年来，卵黄蛋白原作为环境内分泌干扰物的“生物标志物”，得到了较深入的研究。本文讨论了卵黄蛋白原的分离测定方法及其在内分泌干扰物筛选中应用的最新进展，为建立更有效的卵黄蛋白分离测定方法及发展新的环境内分泌干扰物筛选技术提供参考。     

Laccase-Mediated Transformations of Endocrine Disrupting Chemicals Abolish Binding Affinities to Estrogen Receptors and Their Estrogenic Activity in Zebrafish

Endocrine disrupting chemicals (EDCs) are known to mainly affect aquatic organisms, producing negative effects in aquaculture. Transformation of the estrogenic compounds 17??-estradiol (E2), bisphenol-A (BPA), nonylphenol (NP), and triclosan (TCS) by laccase of Coriolopsis gallica was studied. Laccase is able to efficiently transform them into polymers. The estrogenic activity of the EDCs and their laccase transformation products was evaluated in vitro as their affinity for the human estrogen receptor alpha (hER??) and for the ligand binding domain of zebrafish (Danio rerio) estrogen receptor alpha (zfER??LBD). E2, BPA, NP, and TCS showed higher affinity for the zfER??LBD than for hER??. After laccase treatment, no affinity was found, except a marginal affinity of E2 products for the zfER??LBD. Endocrine disruption studies in vivo on zebrafish were performed using the induction of vitellogenin 1 as a biomarker (VTG1 mRNA levels). The use of enzymatic bioreactors, containing immobilized laccase, efficiently eliminates the endocrine activity of BPA and TCS, and significantly reduces the effects of E2. The potential use of enzymatic reactors to eliminate the endocrine activity of EDCs in supply water for aquaculture is discussed.     

Novel method for evaluation of chemicals based on ligand-dependent recruitment of GFP labeled coactivator to estrogen receptor displayed on bacterial magnetic particles

We established a novel method to evaluate endocrine disrupting chemicals (EDCs) by assembling the estrogen receptor-ligand binding domain (ERLBD) and GFP labeled coactivator on magnetic nanoparticles. EDC can promote or inhibit coactivator recruitment to the ligand-ERLBD complex. ERLBD was displayed on the surface of nano-sized bacterial magnetic particles (BacMPs) produced by the magnetic bacterium, Magnetospirillum magneticum AMB-1. Our method resulted in 38 molecules of ERLBD molecules on a BacMPs with diameter of 75 nm. Furthermore, ligand-dependent recruitment assays of GFP labeled coactivator to ERLBD-BacMPs was performed by measuring the fluorescence intensity. 17β-estradiol (E2), estriol, diethylstilbestrol, zeralenone (full agonist), octylphenol (partial agonist) and ICI 182,780 (antagonist) were evaluated by this method. Full agonists tested showed increased fluorescence with increasing agonist concentration. Octylphenol had lower fluorescence intensity than E2. ICI 182,780 did not produce any fluorescence. The method developed in this study can evaluate the estrogenic potential of chemicals by discriminating whether they are an ER full agonist, partial agonist, or antagonist. Finally, this method is amenable adaptation into a high throughput format by using automated magnetic separation.     

Novel Detection Method of Endocrine Disrupting Chemicals Utilizing Liposomes as Cell Membrane Model

Abstract

A novel detection method of endocrine disrupting chemicals (EDCs) is proposed. Liposomes encapsulating fluorescence dye was prepared as a cell membrane model and applied to detect EDCs. Leakages of dye from liposomes were observed after their exposure to EDCs. Fluorescence intensity increased significantly when the liposomes were exposed to 5 ppm EDCs. The increases showed a good correlation with EDCs' dipole moment. Therefore, polarizability is suggested as one of the factors of the liposome-EDC interaction. At lower than 5 ppm, the increases depended on EDCs' concentration. The tendency of the results was in accordance with reported estrogenic activity of EDCs.     

Trends in sensitive electrochemical sensors for endocrine disruptive compounds

The endocrine system that provides communication and maintains homeostasis, is an important part of the body. Any defects or disruptions that affect the endocrine system may cause serious problems in the actions and functions of the body. Endocrine disruptive chemicals (EDCs) are exogenous chemicals or mixtures of chemicals that affects normal functions of the endocrine system by interfering with endogenous hormones and hormonal pathways and disrupting homeostasis. Numerous compounds are considered as endocrine disruptors such as bisphenols (BPs), phthalates, pesticides etc. and they are widely used for industrial purposes in many commercial products. Therefore, human exposure is almost inevitable. Besides that, EDCs may cause environmental pollution and are found in surface waters, wastewater, soil etc. To prevent exposure and hazardous effect, there are legislative regulations including restrictions and prohibitions of the use of EDCs. Due to these reasons; it is crucial to develop highly sensitive, low-cost, easy-to-use, and rapid sensors for the determination of EDCs in commercial and environmental samples. Although there are mostly chromatographic and spectrometric methods for the EDCs monitoring, electrochemistry surpasses them with advantageous properties such as easy application procedure, high sensitivity, very low limit of detection (LOD) values and low-cost.In this review, major groups of EDCs will be explained with their recent and novel electrochemical sensor applications for their detection in commercial and environmental samples.     

Quantification of steroids and endocrine disrupting chemicals in rat ovaries by LC-MS/MS for reproductive toxicology assessment

Reproductive function is controlled by a finely tuned balance of androgens and estrogens. Environmental toxicants, notably endocrine disrupting chemicals (EDCs), appear to be involved in the disruption of hormonal balance in several studies. To further describe the effects of selected EDCs on steroid secretion in female rats, we aim to simultaneously investigate the EDC concentration and the sex hormone balance in the ovaries. Therefore, an effective method has been developed for the quantification of the sex steroid hormones (testosterone, androstenedione, estradiol, and estrone) and four endocrine disrupting chemicals (bisphenol A, atrazine, and the active metabolites of methoxychlor and vinclozolin) in rat ovaries. The sample preparation procedure is based on the so-called "quick, easy, cheap, effective, rugged, and safe" approach, and an analytical method was developed to quantify these compounds with low detection limits by liquid chromatography coupled with a tandem mass spectrometer. This analytical method, applied to rat ovary samples following subacute EDC exposure, revealed some new findings for toxicological evaluation. In particular, we showed that EDCs with the same described in vitro mechanisms of action have different effects on the gonadal steroid balance. These results highlight the need to develop an integrative evaluation with the simultaneous measurement of EDCs and numerous steroids for good risk assessment.