Assessment of hydroxylated metabolites of polychlorinated biphenyls as potential xenoestrogens: a QSAR comparative analysis∗

In silico exploration of hydroxylated polychlorinated biphenyls as estrogen receptor β ligands by 3D-QSAR, molecular docking and molecular dynamics simulations

Hydroxylated polychlorinated biphenyls (HO-PCBs), as the major metabolites of PCBs, have been reported to act as estrogen receptor β (ERβ) agonists. However, the chemical-biological interactions governing their activities toward ERβ have not been elucidated. Therefore, three dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations, to the best of our knowledge, for the first time were performed to explore the correlation between the structures and activities. The best 3D-QSAR model presented higher predictive ability (R²_cv=0.543, R²_pred=0.5793/R²_cv=0.543, R²_pred=0.6795) based on comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA), respectively. At the same time, the derived contour maps indicated the important structural features required for improving the activity. Furthermore, molecular docking studies and MD simulations predicted the binding mode and the interactions between the ligand and the receptor. All the results would lead to a better understanding of the specific mechanism of HO-PCBs on estrogen receptor β (ERβ).Communicated by Ramaswamy H. Sarma.

In-Silico QSAR Modelling of Predicted Rho Kinase Inhibitors Against Cardio Vascular Diseases

BACKGROUND

Rho-kinase is an essential downstream target of GTP-binding protein RhoA, and plays a crucial role in the calcium-sensitization pathway. Rho-kinase pathway is critically involved in phosphorylation state of myosin light chain, leading to increased contraction of smooth muscles. Inhibition of this pathway has turned out to be a promising target for several indications such as cardiovascular diseases, glaucoma and inflammatory diseases.

METHODS

The present work focuses on a division-based 2D quantitative structure-activity relationship (QSAR) analysis along with a docking study to predict structural features that may be essential for the enhancement of selectivity and potency of the target compounds. Furthermore, a set of indoles and azaindoles were also projected based on the regression equation as novel developments. Molecular docking was applied for exploring the binding sites of the newly predicted set of compounds with the receptor.

RESULTS

Results of the docked conformations suggested that introduction of non-bulky and substituted groups in the hinge region of ROCK-II ATP binding pocket would improve the activity by decreasing the bulkiness or length of the compounds.

CONCLUSION

ADME studies were performed to ascertain the novelty and drug-like properties of the designed molecules, respectively.

QSAR and Molecular Modeling Studies on a Series of Pyrrolidine Analogs Acting as BACE-1 Inhibitors

Background:

β-Site amyloidal precursor protein (APP) cleavage enzyme (BACE-1) is reported as prime cause for progession of Alzheimer’s disease (AD). It is a form of dementia characterized by degeneration of neurones in brain. Therefore, attempts have been made to find potent inhibitors of this enzyme.

Methods:

The paper presents an division-based 2D quantitative structure-activity relationship (QSAR) study on a series of BACE-1 inhibitors to analyse the structural features that may be important to increase the potency of the compounds.

Results:

The study led to predict some potential leads for the development of potent inhibitors of BACE-1. One of the molecule with pyrrolidine and pyrrolidinone substitutions exhibited drugreceptor interactions comparable with reference drug.

Conclusion:

The hydrogen-bond interactions between the molecules and the receptor basically control the BACE-1 inhibition activity of the compounds.

Sources and toxicities of phenolic polychlorinated biphenyls (OH-PCBs)

Polychlorinated biphenyls (PCBs), a group of 209 congeners that differ in the number and position of chlorines on the biphenyl ring, are anthropogenic chemicals that belong to the persistent organic pollutants (POPs). For many years, PCBs have been a topic of interest because of their biomagnification in the food chain and their environmental persistence. PCBs with fewer chlorine atoms, however, are less persistent and more susceptible to metabolic attack, giving rise to chemicals characterized by the addition of one or more hydroxyl groups to the chlorinated biphenyl skeleton, collectively known as hydroxylated PCBs (OH-PCBs). In animals and plants, this biotransformation of PCBs to OH-PCBs is primarily carried out by cytochrome P-450-dependent monooxygenases. One of the reasons for infrequent detection of lower chlorinated PCBs in serum and other biological matrices is their shorter half-lives, and their metabolic transformation, resulting in OH-PCBs or their conjugates, such as sulfates and glucuronides, or macromolecule adducts. Recent biomonitoring studies have reported the presence of OH-PCBs in human serum. The occurrence of OH-PCBs, the size of this group (there are 837 mono-hydroxyl PCBs alone), and their wide spectra of physical characteristics (pKa's and log P's ranging over 5 to 6 orders of magnitude) give rise to a multiplicity of biological effects. Among those are bioactivation to electrophilic metabolites that can form covalent adducts with DNA and other macromolecules, interference with hormonal signaling, inhibition of enzymes that regulate cellular concentrations of active hormones, and interference with the transport of hormones. This new information creates an urgent need for a new perspective on these often overlooked metabolites.

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.

Concentrations and patterns of hydroxylated polybrominated diphenyl ethers and polychlorinated biphenyls in arctic foxes (Vulpes lagopus) from Svalbard

Concentrations and patterns of hydroxylated (OH) polybrominated diphenyl ethers (PBDEs) and polychlorinated biphenyls (PCBs) were investigated in liver from arctic foxes (Vulpes lagopus) sampled from Svalbard 1997-2011 (n = 100). The most important OH-PBDE in the arctic foxes was 6-OH-BDE47 detected in 24% of the samples. Relationships between 6-OH-BDE47, δ(13)C and BDE47 suggest that 6-OH-BDE47 residues in arctic foxes are related to marine dietary input, while the relative importance of the metabolic/natural origin of this compound remains unclear. 4-OH-CB187 and 4-OH-CB146 were the main OH-PCBs among the analyzed compounds. The OH-PCB pattern in the present arctic foxes indicates that arctic foxes have a capacity to biotransform a wide range of PCBs of different structures. Formation and retention of OH-PCBs was tightly related to PCB exposure. Furthermore, ΣOH-PCB concentrations were four times higher in the leanest compared to the fattest foxes. Concentrations of 4-OH-CB187 and 4-OH-CB146 among the highest contaminated arctic foxes were similar to the previously reported concentrations for polar bears. Given the high endocrine disruptive potential of OH-PCBs, we suggest that endocrine system may be affected by the relatively high OH-PCB residues in the Svalbard arctic fox population.

3D QSAR studies of hydroxylated polychlorinated biphenyls as potential xenoestrogens

Mono-hydroxylated polychlorinated biphenyls (OH-PCBs) are found in human biological samples and lack of data on their potential estrogenic activity has been a source of concern. We have extended our previous in silico 2D QSAR study through the application of advance techniques such as docking and 3D QSAR to gain insights into their estrogen receptor (ERα) binding. The results support our earlier findings that the hydroxyl group is the most important feature on the compounds; its position, orientation and surroundings in the structure are influential for the binding of OH-PCBs to ERα. This study has also revealed the following additional interactions that influence estrogenicity of these chemicals (a) the aromatic interactions of the biphenyl moieties with the receptor, (b) hydrogen bonding interactions of the p-hydroxyl group with key amino acids ARG394 and GLU353, (c) low or no electronegative substitution at para-positions of the p-hydroxyl group, (d) enhanced electrostatic interactions at the meta position on the B ring, and (e) co-planarity of the hydroxyl group on the A ring. In combination the 2D and 3D QSAR approaches have led us to the support conclusion that the hydroxyl group is the most important feature on the OH-PCB influencing the binding to estrogen receptors, and have enhanced our understanding of the mechanistic details of estrogenicity of this class of chemicals. Such in silico computational methods could serve as useful tools in risk assessment of chemicals.

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.

Occupational risk factors for prostate cancer in an area of former coal, iron, and steel industries in Germany. Part 2: results from a study performed in the 1990s

Currently, there is no established occupational risk factor for prostate cancer. However, in the 1980s, a hospital-based case-control study in the greater Dortmund area showed an elevated risk for hard coal miners and, based on few cases, for painters and varnishers. Therefore, approximately 10 yr later, a similar study regarding prostate cancer was performed in this area. In total, 292 patients with prostate cancer who underwent radical prostatectomy and 313 controls who underwent transurethral resection of a benign prostatic hyperplasia were investigated by questionnaire. All of them were operated on between 1995 and 1999. This study showed a decreased risk for prostate cancer in hard coal miners (odds ratio [OR] = 0.67, 95% confidence interval [CI] = 0.44-1.03). Occupational exposures related to an elevated risk for prostate cancer were exposures to combustion products (20% cases vs. 11% controls), colorants and dyes (19 vs. 13%), and cutting fluids (8 vs. 6%). The different prostate cancer risks for underground coal miners in two studies with a time interval of approximately 10 yr are striking. Factors to be discussed are the introduction of prostate-specific antigen (PSA) screening for prostate cancer and investigation of cases that underwent radical prostatectomy, where the disease in general is locally confined. Working conditions in the local underground coal mines improved over time but did not change markedly in the period of interest. In essence, the present study does not corroborate an elevated prostate cancer risk in former underground hard coal miners from the greater Dortmund area.

Green Tea Catechin, EGCG, Suppresses PCB 102-Induced Proliferation in Estrogen-Sensitive Breast Cancer Cells

The persistence of polychlorinated biphenyls (PCBs) in the environment is of considerable concern since they accumulate in human breast tissue and may stimulate the growth of estrogen-sensitive tumors. Studies have shown that EGCG from green tea can modify estrogenic activity and thus may act as a cancer chemopreventive agent. In the present study, we evaluated the individual and combined effects of PCB 102 and EGCG on cell proliferation using an estrogen-sensitive breast cancer cell line MCF-7/BOS. PCB 102 (1-10 μM) increased cell proliferation in a dose-dependent manner. Furthermore, the proliferative effects of PCB 102 were mediated by ERα and could be abrogated by the selective ERα antagonist MPP. EGCG (10-50 μM) caused a dose-dependent inhibition of PCB 102-induced cell proliferation, with nearly complete inhibition at 25 μM EGCG. The antiproliferative action of EGCG was mediated by ERβ and could be blocked by the ERβ-specific inhibitor PHTPP. In conclusion, EGCG suppressed the proliferation-stimulating activity of the environmental estrogen PCB 102 which may be helpful in the chemoprevention of breast cancer.

Prediction of the endocrine disruption profile of pesticides

Numerous manmade chemicals released into the environment can interfere with normal, hormonally regulated biological processes to adversely affect the development and reproductive functions of living species. Various in vivo and in vitro tests have been designed for detecting endocrine disruptors, but the number of chemicals to test is so high that to save time and money, (quantitative) structure-activity relationship ((Q)SAR) models are increasingly used as a surrogate for these laboratory assays. However, most of them focus only on a specific target (e.g. estrogenic or androgenic receptor) while, to be more efficient, endocrine disruption modelling should preferentially consider profiles of activities to better gauge this complex phenomenon. In this context, an attempt was made to evaluate the endocrine disruption profile of 220 structurally diverse pesticides using the Endocrine Disruptome simulation (EDS) tool, which simultaneously predicts the probability of binding of chemicals on 12 nuclear receptors. In a first step, the EDS web-based system was successfully applied to 16 pharmaceutical compounds known to target at least one of the studied receptors. About 13% of the studied pesticides were estimated to be potential disruptors of the endocrine system due to their high predicted affinity for at least one receptor. In contrast, about 55% of them were unlikely to be endocrine disruptors. The simulation results are discussed and some comments on the use of the EDS tool are made.

Prediction of mutagenicity and carcinogenicity using in silico modelling: A case study of polychlorinated biphenyls

In silico modelling is an important alternative method for the evaluation of properties of chemical compounds. Basically, two concepts are used in its applications: QSAR modelling for endpoint predictions, and grouping (categorization) of large groups of chemicals. In the presented report we address both of these concepts. As a case study we present the results on a set of polychlorinated biphenyls (PCBs) and some of their metabolites. Their mutagenicity and carcinogenic potency were evaluated with CAESAR and T.E.S.T. models, which are freely available over the internet. We discuss the value and reliability of the predictions, the applicability domain of models and the ability to create prioritized groupings of PCBs as a category of chemicals.