Screening of high production volume chemicals for estrogen receptor binding activity (II) by the MultiCASE expert system

A structurally and functionally diverse and cross-validated quantitative structure-activity knowledge database generated by the MultiCASE expert system was used to screen 2526 high production volume chemicals (HPVCs) for their estrogen receptor binding activity. 73 HPVCs were found to contain structural features or biophores that have been documented as having the ability to bind to the estrogen receptor. Potential chemicals were ranked according to their quantitatively predicted ER binding potential and the details of the biophores found in them are discussed.     

QSAR modeling of bioconcentration factors in fish based on fragment constants and structural correction factors

The quantitative structure-activity relationship between the BCF and fragment constant of organic chemicals was studied using a database containing 337 experimental BCF values. The database covered a large variety of chemicals ranging from the very hydrophobic to the very hydrophilic with logKow values between 0.39 and 8.60. The structural features affecting the BCFs were identified and evaluated during a preliminary modeling. A final linear multivariate regression model was derived that was able to account for as much as 98.0% of the variation in the experimental BCF values. The mean absolute error for the final model was 0.315 log-units. In addition, the predictability and robustness of the model was also evaluated.     

QSAR MODELING OF BIOCONCENTRATION FACTORS IN FISH BASED ON FRAGMENT CONSTANTS AND STRUCTURAL CORRECTION FACTORS

The quantitative structure-activity relationship between the BCF and fragment constant of organic chemicals was studied using a database containing 337 experimental BCF values. The database covered a large variety of chemicals ranging from the very hydrophobic to the very hydrophilic with logKow values between 0.39 and 8.60. The structural features affecting the BCFs were identified and evaluated during a preliminary modeling. A final linear multivariate regression model was derived that was able to account for as much as 98.0% of the variation in the experimental BCF values. The mean absolute error for the final model was 0.315 log-units. In addition, the predictability and robustness of the model was also evaluated.     

Perfluorinated compounds affect the function of sex hormone receptors

Perfluorinated compounds (PFCs) are a large group of chemicals used in different industrial and commercial applications. Studies have suggested the potential of some PFCs to disrupt endocrine homeostasis, increasing the risk of adverse health effects. This study aimed to elucidate mechanisms behind PFC interference with steroid hormone receptor functions. Seven PFCs [perfluorohexane sulfonate (PFHxS), perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA), perfluorononanoate (PFNA), perfluorodecanoate (PFDA), perfluoroundecanoate (PFUnA), and perfluorododecanoate (PFDoA)] were analyzed in vitro for their potential to affect estrogen receptor (ER) and androgen receptor (AR) transactivity as well as aromatase enzyme activity. The PFCs were assessed as single compounds and in an equimolar mixture. PFHxS, PFOS and PFOA significantly induced the ER transactivity, whereas PFHxS, PFOS, PFOA, PFNA and PFDA significantly antagonized the AR activity in a concentration-dependent manner. Moreover, PFDA weakly decreased the aromatase activity at a high test concentration. A mixture effect more than additive was observed on AR function. We conclude that five of the seven PFCs possess the potential in vitro to interfere with the function of the ER and/or the AR. The observed mixture effect emphasizes the importance of considering the combined action of PFCs in future studies to assess related health risks.     

First report on development of quantitative interspecies structure-carcinogenicity relationship models and exploring discriminatory features for rodent carcinogenicity of diverse organic chemicals using OECD guidelines

Different regulatory agencies in food and drug administration and environmental protection worldwide are employing quantitative structure-activity relationship (QSAR) models to fill the data gaps related with properties of chemicals affecting the environment and human health. Carcinogenicity is a toxicity endpoint of major concern in recent times. Interspecies toxicity correlations may provide a tool for estimating sensitivity towards toxic chemical exposure with known levels of uncertainty for a diversity of wildlife species. In this background, we have developed quantitative interspecies structure-carcinogenicity correlation models for rat and mouse [rodent species according to the Organization for Economic Cooperation and Development (OECD) guidelines] based on the carcinogenic potential of 166 organic chemicals with wide diversity of molecular structures, spanning a large number of chemical classes and biological mechanisms. All the developed models have been assessed according to the OECD principles for the validation of QSAR models. Consensus predictions for carcinogenicity of the individual compounds are presented here for any one species when the data for the other species are available. Informative illustrations of the contributing structural fragments of chemicals which are responsible for specific carcinogenicity endpoints are identified by the developed models. The models have also been used to predict mouse carcinogenicities of 247 organic chemicals (for which rat carcinogenicities are present) and rat carcinogenicities of 150 chemicals (for which mouse carcinogenicities are present). Discriminatory features for rat and mouse carcinogenicity values have also been explored.     

Photolysis of estrone generates estrogenic photoproducts with higher activity than the parent compound

In the present study, we aimed to evaluate the effect of UV-visible irradiation on the estrogenicity of an estrone aqueous solution by using chemical analysis associated with an in vitro bioassay and in silico analysis. An estrone aqueous solution was irradiated with an UV-visible high-pressure mercury lamp. By using the MELN in vitro cellular bioassay, based on the induction of a luciferase reporter gene upon the activation of the estrogen receptor by chemicals, we showed that the estrogenic potency of the solution increased after irradiation. High-performance liquid chromatography fractionation of the photolyzed solution followed by in vitro testing of fractions allowed the quantitation of the estrogenic potency of each fraction. Nine photoproducts were detected and characterized by liquid chromatography-mass spectrometry coupling. The observed estrogenic activity is mediated by mono- and multi-hydroxylated photoproducts; it is influenced by the position of hydroxyl groups on the steroidal skeleton. In addition, a structure-activity analysis of the hydroxylated photoproducts confirmed their ability to act as estrogen receptor ligands.     

Development of an immuno-immobilized androgen receptor assay (IRA) and its application for the characterization of the receptor binding affinity of different pesticides

Pesticides are synthetic chemicals used not only for improving food and feed production but also for the protection of materials and of human health and well-being. Some of these substances are suspected for adverse effects attributable to an interaction with the endocrine system of vertebrates by mimicking or inhibiting endogenous hormones. One of the biological targets important in this relation is the androgen receptor (AR). To be able to screen environmental samples for the presence of compounds which might interfere with androgen action, we aimed to develop a receptor assay based on recombinant human AR (rhAR). We herein describe an rhAR assay in which the receptor is immobilized in microtiter plates via a specific antibody. The assay can be used for high throughput screening of chemicals spread into the environment. 29 of the most recommended pesticides of the Federal Country Hessen, Germany, were tested for their ability to displace [3H]-DHT bound to the rhAR. This evaluation included the major part of the most common herbicides, insecticides and fungicides and covered three potential groups of endocrine disrupting chemicals. For 28 of the substances evaluated, the relative binding affinity to the rhAR was below 0.1% when compared to dihydrotestosterone (DHT) (100%), only fentinacetate exhibited an affinity of 1.42%. An exchange assay indicated that the binding inhibition was reversible. In consequence, fentinacetate seems to be a hormonally active substance which may be present in vegetables or fish, but also on clothing. We conclude that further investigations on this compound and its metabolites are necessary.     

Antiestrogenic activity of anthropogenic and natural chemicals

A number of natural and man-made chemicals possess antiestrogenic activity, i.e. they antagonize a broad spectrum of estrogen-induced responses in vertebrates. Examples of antiestrogens include dioxin, furan and PCB congeners, certain PAHs, pesticides and indol-3-carbinol derivatives. Major mechanisms of antiestrogenicity are antagonistic action of chemicals at the estrogen receptor, or binding of chemicals to the arylhydrocarbon (Ah) receptor and subsequent interaction with estrogen-responsive genes. Toxicological consequences resulting from antiestrogenic activity have not been conclusively demonstrated to date, although antiestrogenic compounds could critically affect sensitive reproductive and developmental processes.     

Structure-activity relationship assessment of four perfluorinated chemicals using a prolonged zebrafish early life stage test

Perfluorinated compounds (PFCs) are a group of anthropogenic chemicals containing diverse functional groups and chain lengths. They are known to be persistent and bioaccumulative explaining their worldwide environmental presence. The toxicological information on these chemicals is still incomplete and insufficient to assess their environmental impact and structure-activity relationship. In the present study, the developmental effects of PFOS (perfluorooctane sulfonate, C8), PFOA (perfluorooctanoic acid, C8), PFBS (perfluorobutane sulfonate, C4) and PFBA (perfluorobutanoic acid, C4) were evaluated in zebrafish embryos (Danio rerio). The different chain lengths and functional groups of the selected chemicals made it possible to determine the structure-activity relationship of these compounds. PFCs with longer chain lengths (C8) tend to be more toxic than PFCs with shorter chain lengths (C4). Comparison based on the functional groups of compounds with the same chain length indicates that PFCs with a sulfonate group have a larger toxic potential than the ones with a carboxyl group. Furthermore, exposure to the different PFCs resulted in some general effects, such as deformations of the tail and an uninflated swim bladder, as well as in more specific effects which might be related to the structure of the tested chemicals. Oedemas and effects on length could only be detected in 8-carbon PFCs while malformations of the head were a more specific action of the sulfonated PFCs. Effects on hatching rate and success were found in PFOA exposed embryos and heart rates were affected after exposure to PFOS, PFOA and PFBS.     

4-Alkylphenols and related chemicals show similar effect on the function of human and rat estrogen receptor alpha in reporter gene assay

Alkylphenols (APs) are widely used as important industrial materials and have attracted lots of attention because of their potential estrogenic activities. In this study, we developed human estrogen receptor alpha (hERalpha) and rat estrogen receptor alpha (rERalpha) mediated reporter gene assays and compared the estrogenic activity of APs and related chemicals based on the two ERalpha. Human breast cancer cell line MCF-7 was co-transfected with Gal4-fused hERalpha and corresponding reporter plasmid; African green monkey kidney cell line CV-1 was co-transfected with rERalpha and reporter gene. Both assays showed acceptable response to natural estrogen 17beta-estradiol (E2) with EC50 of 0.16 nM and 4.7 nM. Then the estrogenic activity of 4-APs, 4-phenylphenol and bisphenol-A were evaluated and compared with the effects of E2. The data suggested that test APs and related chemicals possessed weakly estrogenic activity and the activity of test APs increased with the increase of substituent size. This structure-activity relationship helped to infer the activity of chemicals with similar feature. Furthermore, test APs showed similar effect on the function of hERalpha and rERalpha. This consistency helped to extrapolate in vivo rodent data to human being when performing risk assessment of endocrine disruptors.     

QSAR modeling with the electrotopological state indices: predicting the toxicity of organic chemicals

A quantitative structure-activity relationship model, based on the atom-type electrotopological state (E-state) indices, for the prediction of toxicity to fathead minnow for a diverse set of 140 organic chemicals is presented. Multiple linear regression and artificial neural network techniques were employed in the modeling of experimental toxicity (-logLC(50)) values ranging from 0.85 to 6.09. For the training set of 130 organic compounds a linear regression model with r(2)=0.84 and s=0.36 was obtained with 14 atom-type E-state indices. For the test set of 10 compounds, the corresponding statistics were r(2)=0.83 and s=0.47, respectively. Neural networks gave a significant improvement using the same set of parameters, and the standard deviations were s=0.31 for the training set and s=0.30 for the test set when an artificial neural network with five neurons in the hidden layer was used. The results clearly show that accurate models can be rapidly calculated for the prediction of toxicity for a diverse set of organic chemicals using easily calculated parameters.     

Estrogenicity and acute toxicity of selected anilines using a recombinant yeast assay

Suspected estrogen modulators include industrial organic chemicals (i.e., xenoestrogens), and have been shown to consist of alkylphenols, bisphenols, biphenylols, and some hydroxy-substituted polycyclic aromatic hydrocarbons. The most prominent structural feature identified to be important for estrogenic activity is a polar group capable of donating hydrogen bonds (i.e., hydroxyl) on an aromatic system. The present study was undertaken to explore the estrogenic activity and acute toxicity of chemicals containing a weaker hydrogen bond donor group on aromatic systems, i.e., the amino substituent. There is a great deal of chemical similarity between aromatic amines (anilines) and aromatic alcohols (phenols). The chemicals chosen for the current study contained an amino-substituted benzene ring with hydrophobic constituents varying in size and shape. Thus, 37 substituted aromatic amines were assayed for estrogenic activity EC50 and acute toxicity LC50 using the Saccharomyces cerevisiae recombinant yeast assay. While the EC50 of 17-beta-estradiol occurs at the 10(-10) range, the aniline with the greatest activity had an EC50 of 10(-6) M. Thus, anilines, in general, are capable only of very weak estrogenic activity in this assay. A comparison of estrogenic potency between the present group of anilines and a set of previously tested analogous phenols indicated that anilines are consistently less estrogenic than phenols. A comparison of hazard indices (EC50/LC50) of these chemicals revealed that, for the vast majority of anilines, the EC50 and LC50 were in the same order of magnitude. More specifically, estrogenic activity of para-substituted alkylanilines increases with alkyl group size up to 5 carbons in length, after which the acute toxicity of the larger alkyl-substituents precluded the ability of the compound to induce the estrogenic response.     

Prediction of mixture toxicity with its total hydrophobicity

Based on the C18 Empore disk/water partition coefficient of a mixture, quantitative structure-activity relationships (QSARs) are presented, which are used to predict the toxicity of mixed halogenated benzenes to P. phosphoreum. The predicted toxicity of 10 other related mixtures based on the QSAR model, agree well with the observed data with r2 = 0.973, SE = 0.113 and F = 287.785 at a level of significance P < 0.0001. The joint effect of these chemicals is simple similar action and the toxicity of the mixtures can be predicted from total hydrophobicity and is independent of hydrophobicity of the components or the ratio of the individual chemicals.     

Investigation of structural requirements for inhibitory activity at the rat and housefly picrotoxinin binding sites in ionotropic GABA receptors using DISCOtech and CoMFA

A number of widely diverse compounds that show inhibitory activities at the picrotoxinin binding sites in housefly and rat GABA receptors were investigated by using the distance comparison technique (DISCOtech) and comparative molecular field analysis (CoMFA) methods to explore the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds. These compounds consist of three diverse types of noncompetitive GABA receptor antagonists, i.e., trioxabicyclooctanes and their derivatives, picrodendrins and related terpenoids, and fipronil and its analogs. For investigation of the structural requirements for inhibitory activity at the picrotoxinin binding site of GABA receptor, DISCOtech pharmacophore models containing one center of hydrophobic ring and two hydrogen bond acceptor atoms for both housefly-head and rat-brain GABA receptors were constructed, respectively. In particular, the interacting areas in housefly receptors appear to be wider than that in rat receptors, the differences between rat and housefly receptor models implicate the selectivity of noncompetitive GABA receptor antagonists. In addition, corresponding CoMFA models with good statistical indices (r(2)>0.9 and q(2)>0.5) were also obtained. These models can be used as guidance for the development of new compounds with high activities and selectivities.     

QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes

The safety assessment process of chemicals requires information on their mutagenic potential. The experimental determination of mutagenicity of a large number of chemicals is tedious and time and cost intensive, thus compelling for alternative methods. We have established local and global QSAR models for discriminating low and high mutagenic compounds and predicting their mutagenic activity in a quantitative manner in Salmonella typhimurium (TA) bacterial strains (TA98 and TA100). The decision treeboost (DTB)-based classification QSAR models discriminated among two categories with accuracies of >96% and the regression QSAR models precisely predicted the mutagenic activity of diverse chemicals yielding high correlations (R ²) between the experimental and model-predicted values in the respective training (>0.96) and test (>0.94) sets. The test set root mean squared error (RMSE) and mean absolute error (MAE) values emphasized the usefulness of the developed models for predicting new compounds. Relevant structural features of diverse chemicals that were responsible and influence the mutagenic activity were identified. The applicability domains of the developed models were defined. The developed models can be used as tools for screening new chemicals for their mutagenicity assessment for regulatory purpose.

     

Multivariate toxicity profiles and QSAR modeling of non-dioxin-like PCBs--an investigation of in vitro screening data from ultra-pure congeners

The non-dioxin-like PCBs (NDL-PCBs) found in food and human samples have a complex spectrum of adverse effects, but lack a detailed risk assessment. The toxicity profiles of 21 carefully selected PCBs (19 NDL-PCBs) were identified by in vitro screening in 17 different assays on specific endpoints related to neurotoxicity, endocrine disruption and tumor promotion. To ensure that the test results were not affected by polychlorinated dioxins, dibenzofurans or DL-PCB contaminants, the NDL-PCB congeners were thoroughly purified before testing. Principal component analysis (PCA) was used to derive general toxicity profiles from the in vitro screening data. The toxicity profiles indicated different structure-activity relationships (SAR) and distinct mechanisms of action. The analysis also indicated that the NDL-PCBs could be divided into two groups. The first group included generally smaller, ortho-substituted congeners, comprising PCB 28, 47, 51, 52, 53, 95, 100, 101, 104 and 136, with PCB 95, 101 and 136 as generally being most active. The second group comprising PCB 19, 74, 118, 122, 128, 138, 153, 170, 180 and 190 had lower biological activity in many of the assays, except for three endocrine-related assays. The most abundant congeners, PCB 138, 153, 170, 180 and 190, cluster in the second group, and thereby show similar SAR. Two quantitative structure-activity relationship (QSAR) models could be developed that added information to the SAR and could aid in risk assessments of NDL-PCBs. The QSAR models predicted a number of congeners as active and among these e.g., PCB 18, 25, 45 and 49 have been found in food or human samples.     

Modeling transport and deposition of contaminants to ecosystems of concern: a case study for the Laurentian Great Lakes

Transfer efficiency (TE) is introduced as a model output that can be used to characterize the relative ability of chemicals to be transported in the environment and deposited to specific target ecosystems. We illustrate this concept by applying the Berkeley-Trent North American contaminant fate model (BETR North America) to identify organic chemicals with properties that result in efficient atmospheric transport and deposition to the Laurentian Great Lakes. By systematically applying the model to hypothetical organic chemicals that span a wide range of environmental partitioning properties, we identify combinations of properties that favor efficient transport and deposition to the Lakes. Five classes of chemicals are identified based on dominant transport and deposition pathways, and specific examples of chemicals in each class are identified and discussed. The role of vegetation in scavenging chemicals from the atmosphere is assessed, and found to have a negligible influence on transfer efficiency to the Great Lakes. Results indicate chemicals with octanol-water (K(ow)) and air-water (K(aw)) partition coefficients in the range of 10(5)-10(7) and 10(-4)-10(-1) combine efficient transport and deposition to the Great Lakes with potential for biaccumulation in the aquatic food web once they are deposited. A method of estimating the time scale for atmospheric transport and deposition process is suggested, and the effects of degrading reactions in the atmosphere and meteorological conditions on transport efficiency of different classes of chemicals are discussed. In total, this approach provides a method of identifying chemicals that are subject to long-range transport and deposition to specific target ecosystems as a result of their partitioning and persistence characteristics. Supported by an appropriate contaminant fate model, the approach can be applied to any target ecosystem of concern.