Xiaoxiang Wang

Molecular docking, molecular dynamics simulation, and structure-based 3D-QSAR studies on estrogenic activity of hydroxylated polychlorinated biphenyls

Hydroxylated polychlorinated biphenyls (HO-PCBs), major metabolites of PCBs, have been reported to present agonist or antagonist interactions with estrogen receptor α (ERα) and induce ER-mediated responses. In this work, a multistep framework combining molecular docking, molecular dynamics (MD) simulations, and structure-based three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed to explore the influence of structural features on the estrogenic activities of HO-PCBs, and to investigate the molecular mechanism of ERα-ligand interactions. The CoMSIA (comparative molecular similarity indices analysis) model was developed from the conformations obtained from molecular docking. The model exhibited statistically significant results as the cross-validated correlation coefficient q² was 0.648, the non-cross-validated correlation coefficient r² was 0.968, and the external predictive correlation coefficient r(pred)² was 0.625. The key amino acid residues were identified by molecular docking, and the detailed binding modes of the compounds with different activities were determined by MD simulations. The binding free energies correlated well with the experimental activity. An energetic analysis, MM-GBSA energy decomposition, revealed that the van der Waals interaction was the major driving force for the binding of compounds to ERα. The hydrogen bond interactions between the ligands and residue His524 help to stabilize the conformation of ligands at the binding pocket. These results are expected to be beneficial to predict estrogenic activities of other HO-PCB congeners and helpful for understanding the binding mechanism of HO-PCBs and ERα.

Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β

Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q²) was 0.571 and non-cross-validation correlation coefficient (r²) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results.

In silico investigations of anti-androgen activity of polychlorinated biphenyls

Polychlorinated biphenyls (PCBs) have attracted great concern as global environmental pollutants and representative endocrine disruptors. In this work, a molecular model study combining three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations was performed to explore the structural requirement for the anti-androgen activities of PCBs and to reveal the binding mode between the PCBs and androgen receptor (AR). The best comparative molecular similarity indices analysis (CoMSIA) model, obtained from receptor-based alignment, shows leave-one-out cross-validated correlation coefficient (q(2)) of 0.665 and conventional correlation coefficient (R(2)) of 0.945. The developed model has a highly predictive ability in both internal and external validation. Furthermore, the interaction mechanisms of PCBs to AR were analyzed by molecular docking and MD simulation. Molecular docking indicated that all the PCBs in the data set docked in a hydrophobic pocket. The Binding free energies calculated by Molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) not only exhibited a good correlation with the experimental activity, but also could explain the activity difference of the studied compounds. The binding free energy decomposition analysis indicates that the van der Waals interaction is the major driving force for the binding process.

Molecular docking, molecular dynamics simulation, and structure-based 3D-QSAR studies on the aryl hydrocarbon receptor agonistic activity of hydroxylated polychlorinated biphenyls.

The binding interactions between hydroxylated polychlorinated biphenyls (HO-PCBs) and the aryl hydrocarbon receptor (AhR) are suspected of causing toxic effects. To understand the binding mode between HO-PCBs and AhR, and to explore the structural characteristics that influence the AhR agonistic activities of HO-PCBs, the combination of molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR), and molecular dynamics (MD) simulations was performed. Using molecular docking, the HO-PCBs were docked into the binding pocket of AhR, which was generated by homology modeling. Comparative molecular similarity index analysis (CoMSIA) models were subsequently developed from three different alignment rules. The optimum 3D-QSAR model showed good predictive ability (q(2)=0.583, R(2)=0.913) and good mechanism interpretability. The statistical reliability of the CoMSIA model was also validated. In addition, molecular docking and MD simulations were applied to explore the binding modes between the ligands and AhR. The results obtained from this study may lead to a better understanding of the interaction mechanism between HO-PCBs and AhR.

Docking and CoMSIA studies on steroids and non-steroidal chemicals as androgen receptor ligands

While some synthetic chemicals have been demonstrated to disrupt normal endocrine function by binding to the androgen receptor (AR), the mechanism by which ligands bind to the ligand binding domain (LBD) remained unclear. In this study, docking and comparative molecular similarity index analysis (CoMSIA) were performed to study the AR ligand binding mechanism of steroids and non-steroidal chemicals. The obtained docking conformations and predictive CoMSIA models (r(pred)(2)values as 0.842 and 0.554) indicated the primary interaction site and key residues in the binding process. The major factors influence the binding affinity of steroids and non-steroidal chemicals were electrostatic and hydrophobic interactions, respectively. The results indicated that besides amino-acid residues Gln711, Arg752 and Thr877 which have previously been reported to be important in binding ligands, Leu701 and Leu704 are also important. Residues Val746, Met749 and Phe764 are crucial only for steroids, while Met742 and Met787 are important only for non-steroidal chemicals. This knowledge of key interactions and important amino-acid residues governing ligands to the AR allow better prediction of potency of AR agonists so that their potential to disrupt AR-mediated pathways and to design less potent alternatives.

Distribution of perfluorooctane sulfonate isomers and predicted risk of thyroid hormonal perturbation in drinking water.

We documented the distribution of seven perfluorooctane sulfonate (PFOS) isomers in drinking water in Jiangsu Province, China. Compared to the 30% proportion of branched PFOS in technical PFOS, the levels of branched PFOS in drinking water increased to 31.8%-44.6% of total PFOS. Because of previous risk assessment without considering the PFOS isomer profile and the toxicity of individual PFOS isomers, here we performed a new health risk assessment of PFOS for thyroid hormonal perturbation in drinking water with the contribution from individual PFOS isomers. The risk quotients (RQs) of individual PFOS isomers indicated that linear PFOS contributed most to the risk among all the target PFOS isomers (83.0%-90.2% of the total PFOS RQ), and that risk from 6m-PFOS (5.2%-11.9% of the total PFOS RQ) was higher than that from other branched PFOS isomers. We found that the risks associated with PFOS in drinking water would be overestimated by 10.0%-91.7% if contributions from individual PFOS isomers were not considered. The results revealed that the PFOS isomer profile and the toxicity of individual PFOS isomers were important factors in health risk assessment of PFOS and should be considered in the future risk assessments.

Molecular modeling and molecular dynamics simulation studies on the interactions of hydroxylated polychlorinated biphenyls with estrogen receptor-β.

Endocrine-disrupting chemicals have attracted great concern. As major metabolites of polychlorinated biphenyls (PCBs), hydroxylated polychlorinated biphenyls (HO-PCBs) may disrupt estrogen hormone status because of their structural similarity to estrogen endogenous compounds. However, interactions between HO-PCBs and estrogen receptors (ERs) are not fully understood. In the present work, a molecular modeling study combining molecular docking, molecular dynamics simulations, and binding free energy calculations was performed to characterize the interactions of three HO-PCBs (4′-HO-PCB50, 2′-HO-PCB65, and 4′-HO-PCB69) having much different estrogenic activities with ERβ. Docking results showed that binding between ligands and ERβ was stabilized by hydrogen bond and hydrophobic interactions. The binding free energies of three ligands with ERβ were calculated, and further binding free energy decomposition analysis indicated that the dominating driving force of the binding between the ligands and ERβ was the van der Waals interaction. Some key residues, such as Leu298, Phe356, Gly472, His475, and Leu476, played important roles in ligand–receptor interactions by forming hydrophobic and hydrogen bond interactions with ligands. The results may be beneficial to increase understanding of the interactions between HO-PCBs and ERβ.

A high-throughput, computational system to predict if environmental contaminants can bind to human nuclear receptors

Some pollutants can bind to nuclear receptors (NRs) and modulate their activities. Predicting interactions of NRs with chemicals is required by various jurisdictions because these molecular initiating events can result in adverse, apical outcomes, such as survival, growth or reproduction. The goal of this study was to develop a high-throughput, computational method to predict potential agonists of NRs, especially for contaminants in the environment or to which people or wildlife are expected to be exposed, including both persistent and pseudo-persistent chemicals. A 3D-structure database containing 39 human NRs was developed. The database was then combined with AutoDock Vina to develop a System for Predicting Potential Effective Nuclear Receptors (SPEN), based on inverse docking of chemicals. The SPEN was further validated and evaluated by experimental results for a subset of 10 chemicals. Finally, to assess the robustness of SPEN, its ability to predict potentials of 40 chemicals to bind to some of the most studied receptors was evaluated. SPEN is rapid, cost effective and powerful for predicting binding of chemicals to NRs. SPEN was determined to be useful for screening chemicals so that pollutants in the environment can be prioritized for regulators or when considering alternative compounds to replace known or suspected contaminants with poor environmental profiles.

The impact of dissolved oxygen on sulfate radical-induced oxidation of organic micro-pollutants: A theoretical study

Sulfate radical (SO4.-)-induced oxidation is an important technology in advanced oxidation processes (AOPs) for the removal of pollutants. To date, few studies have assessed the effects of dissolved oxygen (DO) on the SO4.--induced oxidation of organic micro-pollutants. In the present work, a quantum chemical calculation was used to investigate the influence of the external oxygen molecule on the Gibbs free energy (Gpollutant) and HOMO-LUMO gap (ΔE) of 15 organic micro-pollutants representing four chemical categories. Several thermodynamic and statistical models were combined with the data from the quantum chemical calculation to illustrate the impact of DO on the oxidation of organic micro-pollutants by SO4.-. Results indicated that the external oxygen molecule increased Gpollutant of all studied chemicals, which implies DO has the potential to decrease the energy barrier of the SO4.--induced oxidation and shift the chemical equilibrium of the reaction towards the side of products. From the perspective of kinetics, DO can accelerate the oxidation by decreasing ΔE of organic micro-pollutants. In addition, changes of Gpollutant and ΔE of the SO4.--induced oxidation were both significantly different between open-chain and aromatic chemicals, and these differences were partially attributed to the difference of polarizability of these two types of chemicals. Furthermore, we revealed that all changes of Gpollutant and ΔE induced by DO were dependent on the DO content. Our study emphasizes the significance of DO on the oxidation of organic micro-pollutants by SO4.-, and also provides a theoretical method to study the effect of components in wastewater on removal of organic pollutants in AOPs.