Exploration of endocrine-disrupting chemicals on estrogen receptor alpha by the agonist/antagonist differential-docking screening (AADS) method: 4-(1-adamantyl)phenol as a potent endocrine disruptor candidate

Risk assessment and environmental consequences of the use of the Allium-derived compound propyl-propane thiosulfonate (PTSO) in agrifood applications

The organosulfur compound propyl-propane thiosulfonate (PTSO), mainly found in Allium cepa, has a promising use in the agrifood industry. To confirm its safety for livestock, consumers, and environment, toxicological assessment is needed. In this regard, endocrine-disrupting chemicals (EDCs) are in the spotlight of research. Therefore, as part of the risk assessment of PTSO, in the present work, an in vivo study was performed in mice exposed to PTSO to investigate its potential reproductive toxicity considering fertility, genetic and endocrine endpoints. Five-weeks-old CD1 mice (80 males, 80 females) were exposed for 11 or 16 weeks (males or females, respectively) to different doses of PTSO (0, 14, 28 and 55 mg PTSO/kg b.w./day; 20 animals per group and sex) through the food pellets. No clinical observations or mortality and no changes in absolute organ weights and relative organ weights/body weight or brain ratios occurred during the study. The estrous cycle did not undergo any significant toxicologically relevant change. Most of the sex hormones displayed normal values. Some alterations in the expression of some genes related to reproduction is only observed in females, but they do not appear to have consequences in the development of sex organs. Docking results showed the impossibility of stable binding to estrogen and androgen receptors. Considering all the results obtained, the safe profile of PTSO can be confirmed for different agrifood applications at the conditions assayed.

Environmentally Relevant Concentrations of Carbamazepine Caused Endocrine-Disrupting Effects on Nontarget Organisms, Chinese Rare Minnows (Gobiocypris rarus)

In the present study, Chinese rare minnows (Gobiocypris rarus) were exposed to 1, 10, and 100 μg/L of carbamazepine (CBZ) under flow-through conditions for 28 d. A hepatic-specific custom microarray identified 111 and 71 differentially expressed genes in the livers of females and males, respectively, exposed to 100 μg/L of CBZ (ratio ≥ 2, p ≤ 0.05). The levels of five differentially expressed genes associated with the hypothalamic-pituitary-gonadal (HPG) axis were quantified by qPCR, and the results indicated the feasibility of screening endocrine-disrupting chemicals using a custom microarray. The mRNA levels of genes related to the HPG axis differed significantly in different organs of Chinese rare minnows (p < 0.05). Significant differences were observed in the 11-ketotestosterone and plasma vitellogenin levels in all treatments and in the 17β-estradiol (E2) levels in the 100 μg/L CBZ treatment. In contrast, the gonadosomatic index was significantly higher in females and slightly higher in males without significant differences. A pathological analysis determined that 10 and 100 μg/L of CBZ could lead to ova-testis in males and significantly promoted ovum maturation in females. Therefore, our results demonstrate that environmentally relevant concentrations of CBZ have homologous estrogenic activity and induce reproductive toxicity in Chinese rare minnows.

Discriminating Agonist from Antagonist Ligands of the Nuclear Receptors Using Different Chemoinformatics Approaches

Nuclear receptors (NRs) constitute an important class of therapeutic targets. During the last 4 years, we tackled the pharmacological profile assessment of NR ligands for which we constructed the NRLiSt BDB. We evaluated and compared the performance of different virtual screening approaches: mean of molecular descriptor distribution values, molecular docking and 3D pharmacophore models. The simple comparison of the distribution profiles of 4885 molecular descriptors between the agonist and antagonist datasets didn't provide satisfying results. We obtained an overall good performance with the docking method we used, Surflex-Dock which was able to discriminate agonist from antagonist ligands. But the availability of PDB structures in the "pharmacological-profile-to-predict-bound-state" (agonist-bound or antagonist-bound) and the availability of enough ligands of both pharmacological profiles constituted limits to generalize this protocol for all NRs. Finally, the 3D pharmacophore modeling approach, allowed us to generate selective agonist pharmacophores and selective antagonist pharmacophores that covered more than 99 % of the whole NRLiSt BDB. This study allowed a better understanding of the pharmacological modulation of NRs with small molecules and could be extended to other therapeutic classes.

Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations

Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.

Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores

Nuclear receptors (NRs) constitute an important class of therapeutic targets. We evaluated the performance of 3D structure-based and ligand-based pharmacophore models in predicting the pharmacological profile of NRs ligands using the NRLiSt BDB database. We could generate selective pharmacophores for agonist and antagonist ligands and we found that the best performances were obtained by combining the structure-based and the ligand-based approaches. The combination of pharmacophores that were generated allowed to cover most of the chemical space of the NRLiSt BDB datasets. By screening the whole NRLiSt BDB on our 3D pharmacophores, we demonstrated their selectivity towards their dedicated NRs ligands. The 3D pharmacophores herein presented can thus be used as a predictor of the pharmacological activity of NRs ligands.Graphical AbstractUsing a combination of structure-based and ligand-based pharmacophores, agonist and antagonist ligands of the Nuclear Receptors included in the NRLiSt BDB database could be separated.

2, 4-Dichloro-6-nitrophenol, a photonitration product of 2, 4-dichlorophenol, caused anti-androgenic potency in Chinese rare minnows (Gobiocypris rarus)

2,4-Dichloro-6-nitrophenol (DCNP) is an environmental transformation product of 2,4-dichlorophenol that has been identified as widespread in effluent wastewater, but little is known about its toxicity because this compound is not regulated. Therefore, to investigate the endocrine disruption potency of DCNP in Chinese rare minnows (Gobiocypris rarus), adult and juvenile fish were exposed to various concentrations of DCNP (2, 20, and 200 μg/L) for 28 d. After 28 d exposure, the plasma vitellogenin (VTG) levels were reduced in females while increased in males and juvenile fish considerably, as compared with the control. These results suggested that DCNP affects the HPG-axis in a sex-dependent way. Testosterone (T) levels in the plasma were significantly lower in adult and juvenile fish and were accompanied by an increased estradiol (E2)/T ratio. Histopathological observation revealed hypertrophy of the hepatocytes and nuclear pyknosis in the liver, the inhibition of spermatogenesis in the testes, and the degeneration of oocytes in the ovaries after DCNP exposure. The expression pattern of selected genes indicated that the nuclear receptor, steroidogenesis and gonadotropin regulation pathways were perturbed after DCNP exposure. Above all, our results demonstrated that DCNP clearly had anti-androgenic activity in both adult and juvenile fish and can therefore be considered as an endocrine-disrupting chemical.

Sequence to structure approach of estrogen receptor alpha and ligand interactions

Estrogen receptors (ERs) are steroid receptors located in the cytoplasm and on the nuclear membrane. The sequence similarities of human ERα, mouse ERα, rat ERα, dog ERα, and cat ERα are above 90%, but structures of ERα may different among species. Estrogen can be agonist and antagonist depending on its target organs. This hormone play roles in several diseases including breast cancer. There are variety of the relative binding affinity (RBA) of ER and estrogen species in comparison to 17β-estradiol (E2), which is a natural ligand of both ERα and ERβ. The RBA of the estrogen species are as following: diethyl stilbestrol (DES)>hexestrol>dienestrol>17β-estradiol (E2)>17-estradiol>moxestrol>estriol (E3)>4-OH estradiol>estrone-3-sulfate. Estrogen mimetic drugs, selective estrogen receptor modulators (SERMs), have been used as hormonal therapy for ER positive breast cancer and postmenopausal osteoporosis. In the postgenomic era, in silico models have become effective tools for modern drug discovery. These provide three dimensional structures of many transmembrane receptors and enzymes, which are important targets of de novo drug development. The estimated inhibition constants (Ki) from computational model have been used as a screening procedure before in vitro and in vivo studies.

Use of computational modeling approaches in studying the binding interactions of compounds with human estrogen receptors

Estrogens have a whole host of physiological functions in many human organs and systems, including the reproductive, cardiovascular, and central nervous systems. Many naturally-occurring compounds with estrogenic or antiestrogenic activity are present in our environment and food sources. Synthetic estrogens and antiestrogens are also important therapeutic agents. At the molecular level, estrogen receptors (ERs) mediate most of the well-known actions of estrogens. Given recent advances in computational modeling tools, it is now highly practical to use these tools to study the interaction of human ERs with various types of ligands. There are two common categories of modeling techniques: one is the quantitative structure activity relationship (QSAR) analysis, which uses the structural information of the interacting ligands to predict the binding site properties of a macromolecule, and the other one is molecular docking-based computational analysis, which uses the 3-dimensional structural information of both the ligands and the receptor to predict the binding interaction. In this review, we discuss recent results that employed these and other related computational modeling approaches to characterize the binding interaction of various estrogens and antiestrogens with the human ERs. These examples clearly demonstrate that the computational modeling approaches, when used in combination with other experimental methods, are powerful tools that can precisely predict the binding interaction of various estrogenic ligands and their derivatives with the human ERs.

Multi-conformer ensemble docking to difficult protein targets

Large-scale ensemble docking is investigated using five proteins from the Directory of Useful Decoys (DUD, dud.docking.org ) for which docking to crystal structures has proven difficult. Molecular dynamics trajectories are produced for each protein and an ensemble of representative conformational structures extracted from the trajectories. Docking calculations are performed on these selected simulation structures and ensemble-based enrichment factors compared with those obtained using docking in crystal structures of the same protein targets or random selection of compounds. Simulation-derived snapshots are found with improved enrichment factors that increase the chemical diversity of docking hits for four of the five selected proteins. A combination of all the docking results obtained from molecular dynamics simulation followed by selection of top-ranking compounds appears to be an effective strategy for increasing the number and diversity of hits when using docking to screen large libraries of chemicals against difficult protein targets.

A computational approach predicting CYP450 metabolism and estrogenic activity of an endocrine disrupting compound (PCB-30)

Endocrine disrupting chemicals influence growth and development through interactions with the hormone system, often through binding to hormone receptors such as the estrogen receptor. Computational methods can predict endocrine disrupting chemical activity of unmodified compounds, but approaches predicting activity following metabolism are lacking. The present study uses a well-known environmental contaminant, PCB-30 (2,4,6-trichlorobiphenyl), as a prototype endocrine disrupting chemical and integrates predictive (computational) and experimental methods to determine its metabolic transformation by cytochrome P450 3A4 (CYP3A4) and cytochrome P450 2D6 (CYP2D6) into estrogenic byproducts. Computational predictions suggest that hydroxylation of PCB-30 occurs at the 3- or 4-phenol positions and leads to metabolites that bind more strongly than the parent molecule to the human estrogen receptor alpha (hER-α). Gas chromatography-mass spectrometry experiments confirmed that the primary metabolite for CYP3A4 and CYP2D6 is 4-hydroxy-PCB-30, and the secondary metabolite is 3-hydroxy-PCB-30. Cell-based bioassays (bioluminescent yeast expressing hER-α) confirmed that hydroxylated metabolites are more estrogenic than PCB-30. These experimental results support the applied model's ability to predict the metabolic and estrogenic fate of PCB-30, which could be used to identify other endocrine disrupting chemicals involved in similar pathways.

Quantitative determination of bisphenol A from human saliva using bulk derivatization and trap-and-elute liquid chromatography coupled to electrospray ionization mass spectrometry

Endocrine disruptors cause adverse health effects as a result of their ability to shift the hormonal balance that is essential to the body. Bisphenol A (BPA) is an endocrine disruptor that has garnered much attention because of its presence in many consumer materials, which generates a significant risk for exposure. A method is presented for rapid detection of oral exposure to BPA directly from human saliva. Saliva was chosen because it serves as a noninvasive sampling route to detect BPA exposure; however, it is one of many complex biological matrices that have traditionally posed problems in quantitative analysis. Such analyses usually require extensive sample preparation to reduce interferences contributed by the sample matrix. Three validated methods are presented here that feature a streamlined sample-preparation strategy (bulk derivatization) prior to accurate and sensitive analysis by trap-and-elute liquid chromatography coupled to electrospray ionization mass spectrometry. Validated methods include standard addition calibration with variable injection volumes and multiple injection loading, as well as with incorporation of an internal standard. Reported limits of detection reached as low as 49.0 pg/ml (2.9 pg loaded on-column; equivalent to parts per trillion in saliva) among the presented methods with good accuracy and precision throughout. A proof-of-concept study is demonstrated to show that the final validated method has potential application to specific studies for trace-level BPA detection from real samples.