Anionic Phenolic Compounds Bind Stronger with Transthyretin than Their Neutral Forms: Nonnegligible Mechanisms in Virtual Screening of Endocrine Disrupting Chemicals

Identification of Hydrocarbon Sulfonates as Previously Overlooked Transthyretin Ligands in the Environment

Incidences of thyroid disease, which has long been hypothesized to be partially caused by exposure to thyroid hormone disrupting chemicals (TDCs), have rapidly increased in recent years. However, known TDCs can only explain a small portion (∼1%) of in vitro human transthyretin (hTTR) binding activities in environmental samples, indicating the existence of unknown hTTR ligands. In this study, we aimed to identify the major environmental hTTR ligands by employing protein Affinity Purification with Nontargeted Analysis (APNA). hTTR binding activities were detected in all 11 indoor dust and 9 out of 10 sewage sludge samples by the FITC-T4 displacement assay. By using APNA, 31 putative hTTR ligands were detected including perfluorooctanesulfonate (PFOS). Two of the most abundant ligands were identified as hydrocarbon surfactants (e.g., dodecyl benzenesulfonate). Moreover, another abundant ligand was surprisingly identified as a disulfonate fluorescent brightener, 4,4'-bis(2-sulfostyryl)biphenyl sodium (CBS). CBS was validated as a nM-affinity hTTR ligand with an IC50 of 345 nM. In total, hydrocarbon surfactants and fluorescent brighteners explain 1.92-17.0 and 5.74-54.3% of hTTR binding activities in dust and sludge samples, respectively, whereas PFOS only contributed <0.0001%. Our study revealed for the first time that hydrocarbon sulfonates are previously overlooked hTTR ligands in the environment.

Environmental health risks induced by interaction between phthalic acid esters (PAEs) and biological macromolecules: A review

As a kind of compounds abused in industry productions, phthalic acid esters (PAEs) cause serious problems in natural environment. PAEs pollution has penetrated into environmental media and human food chain. This review consolidates the updated information to assess the occurrence and distribution of PAEs in each transmission section. It is found that micrograms per kilogram of PAEs are exposed to humans through daily diets. After entering the human body, PAEs often undergo the metabolic process of hydrolysis to monoesters phthalates and conjugation process. Unfortunately, in the process of systemic circulation, PAEs will interact with biological macromolecules in vivo under the action of non-covalent binding, which is also the essence of biological toxicity. The interactions usually operate in the following pathways: (a) competitive binding; (b) functional interference; and (c) abnormal signal transduction. While the non-covalent binding forces mainly contain hydrophobic interaction, hydrogen bond, electrostatic interaction, and π interaction. As a typical endocrine disruptor, the health risks of PAEs often start with endocrine disorder, further leading to metabolic disruption, reproductive disorders, and nerve injury. Besides, genotoxicity and carcinogenicity are also attributed to the interaction between PAEs and genetic materials. This review also pointed out that the molecular mechanism study on biological toxicity of PAEs are deficient. Future toxicological research should pay more attention to the intermolecular interactions. This will be beneficial for evaluating and predicting the biological toxicity of pollutants at molecular scale.

Potential Disrupting Effects of Wastewater-Derived Disinfection Byproducts on Chinese Rare Minnow (Gobiocypris rarus) Transthyretin: An In Vitro and In Silico Study

The available information about whether wastewater-derived disinfection byproducts (DBPs) could elicit potential endocrine-related detrimental effects on aquatic organisms was scarce. Herein, the potential disrupting effects and underlying binding mechanism of 14 wastewater-derived aliphatic and aromatic DBPs and 12 other substances on Chinese rare minnow (Gobiocypris rarus) transthyretin (CrmTTR) were tested and revealed by in vitro and in silico methods. The amino acid sequences of CrmTTR were determined, and the recombinant CrmTTR with a molecular mass of 66.3 kDa was expressed and purified. In vitro assay results indicated that eight selected aromatic DBPs exhibited detectable CrmTTR disrupting ability. Meanwhile, six aliphatic DBPs were not CrmTTR binders. Molecular modeling results implied that hydrophobic hydrogen bonds and/or ionic pair interactions were non-negligible. Four binary classification models with high classification performance were constructed. A significant positive linear relationship was observed for the binding affinity data from CrmTTR and human TTR (n = 18, r = 0.922, p < 0.0001). However, the binding affinity for 13 out of 18 tested compounds with CrmTTR was higher than that with human TTR. All the results highlighted that some wastewater-derived DBPs may be potential disruptors on the aquatic organism endocrine system, and interspecies variation should not be neglected in future determination of the potential endocrine disrupting effects of wastewater-derived DBPs.

Thyroid hormone activities of neutral and anionic hydroxylated polybrominated diphenyl ethers to thyroid receptor β: A molecular dynamics study

Hydroxylated polybrominated diphenyl ethers (OH-PBDEs) have been identified as the strong endocrine disrupting chemicals to humans, which show structural similarity with endogenous thyroid hormones (THs) and thus disrupt the functioning of THs through competitive binding with TH receptors (TRs). Although previous studies have reported the hormone activities of some OH-PBDEs on TH receptor β (TRβ), the interaction mechanism remains unclear. Furthermore, hydroxyl dissociation of OH-PBDEs may alter their TR disrupting activities, which has not yet been investigated in depth. In this work, we selected 18 OH-PBDEs with neutral and anionic forms and performed molecular dynamics (MD) simulations to estimate their binding interactions with the ligand binding domain (LBD) of TRβ. The results demonstrate that most of OH-PBDEs have stronger binding affinities to TRβ-LBD than their anionic counterparts, and the hydroxyl dissociation of ligands differentiate the major driving force for their binding. More Br atoms in OH-PBDEs can result in stronger binding potential with TRβ-LBD. Moreover, 5 hydrophobic residues, including Met313, Leu330, Ile276, Leu346, and Phe272, are identified to have important contributions to bind OH-PBDEs. These results clarify the binding mechanism of OH(O^-)-PBDEs to TRβ-LBD at the molecular level, which can provide a solid theoretical basis for accurate assessment of TH disrupting effects of these chemicals.

Biodegradation of anionic polyacrylamide by manganese peroxidase: docking, virtual mutation based on affinity, QM/MM calculation and molecular dynamics simulation

Manganese peroxidase (Mn P) is capable of effectively degrading anionic polyacrylamide (HPAM). However, the interaction of Mn P with HPAM at molecular level is lacking until now. Here, the HPAM model compounds, HPAM-2, HPAM-3, HPAM-4, and HPAM-5, were selected to reveal their binding mechanisms with Mn P. The results showed that the most suitable substrate for Mn P was HPAM-5, and the main reason for MnP-HPAM-5 with maximal affinity was strong hydrogen bond. LYS96 was the important key residue in all complexes, and the number of key residue was largest in MnP-HPAM-5. The optimal THR27ILE mutant may enhance the affinity of Mn P to HPAM-4. The stability of Mn P binding to HPAM-4 was the optimal. These results were helpful in designing highly efficient Mn P against HPAM to protect the ecological environment.

Human transthyretin binding affinity of halogenated thiophenols and halogenated phenols: An in vitro and in silico study

Serious harmful effects have been reported for thiophenols, which are widely used industrial materials. To date, little information is available on whether such chemicals can elicit endocrine-related detrimental effects. Herein the potential binding affinity and underlying mechanism of action between human transthyretin (hTTR) and seven halogenated-thiophenols were examined experimentally and computationally. Experimental results indicated that the halogenated-thiophenols, except for pentafluorothiophenol, were powerful hTTR binders. The differentiated hTTR binding affinity of halogenated-thiophenols and halogenated-phenols were observed. The hTTR binding affinity of mono- and di-halo-thiophenols was higher than that of corresponding phenols; while the opposite relationship was observed for tri- and penta-halo-thiophenols and phenols. Our results also confirmed that the binding interactions were influenced by the degree of ligand dissociation. Molecular modeling results implied that the dominant noncovalent interactions in the molecular recognition processes between hTTR and halogenated-thiophenols were ionic pair, hydrogen bonds and hydrophobic interactions. Finally, a model with acceptable predictive ability was developed, which can be used to computationally predict the potential hTTR binding affinity of other halogenated-thiophenols and phenols. Taken together, our results highlighted that more research is needed to determine their potential endocrine-related harmful effects and appropriate management actions should be taken to promote their sustainable use.

Investigating the molecular mechanism of hydroxylated bromdiphenyl ethers to inhibit the thyroid hormone sulfotransferase SULT1A1

Hydroxylated bromodiphenyl ethers (OH-BDEs) have raised great concern due to their potential endocrine disrupting effects on humans. In vitro experiments have indicated OH-BDEs can inhibit the activity of thyroid hormone (TH) sulfotransferases (SULTs); however, the molecular mechanism has not been investigated in depth. In this work, we employed 17 OH-BDEs with five or fewer Br atoms, and performed integrated computational simulations to unravel the possible inhibition mechanism of OH-BDEs on human SULT1A1. The molecular docking results demonstrate that OH-BDEs form hydrogen bonds with residues Lys106 and His108, and the neutral OH-BDEs show comparable binding energies with their anionic counterparts. The further hybrid quantum mechanical/molecular mechanical (QM/MM) calculations unravel a metabolic mechanism of OH-BDEs comprised by proton abstraction and sulfation steps. This mechanism is involved in the SULT1A1 inhibition by some OH-BDEs comprised of three or fewer Br atoms, while other OH-BDEs likely only form ternary complexes to competitively inhibit SULT1A1 activity. Moreover, the effect of the hydroxyl group of OH-BDEs on SULT1A1 inhibition potential follows the order of ortho-OH BDE > meta-OH BDE > para-OH BDE. These results provide an insight into the inhibition mechanism of OH-BDEs to SULT1A1 at the molecular level, which are beneficial in illuminating the molecular initiating events involved in the TH disruption of OH-BDEs.

Binding interactions of halo-benzoic acids, halo-benzenesulfonic acids and halo-phenylboronic acids with human transthyretin

The anionic form-dependent binding interaction of halo-phenolic substances with human transthyretin (hTTR) has been observed previously. This indicates that ionizable compounds should be the primary focus in screening potential hTTR disruptors. Here, the potential binding potency of halo-benzoic acids, halo-benzenesulfonic acids/sulfates and halo-phenylboronic acids with hTTR was determined and analyzed by competitive fluorescence displacement assay integrated with computational methods. The laboratorial results indicated that the three test groups of model compounds exhibited a distinct binding affinity to hTTR. All the tested halo-phenylboronic acids, some of the tested halo-benzoic acids and halo-benzenesulfonic acids/sulfates were shown to be inactive with hTTR. Other halo-benzoic acids and halo-benzenesulfonic acids/sulfates were moderate and/or weak hTTR binders. The binding affinity of halo-benzoic acids and halo-benzenesulfonic acids/sulfates with hTTR was similar. The low distribution ability of the model compounds from water to hTTR may be the reason why they exhibited the binding potency observed with hTTR. By introducing other highly hydrophobic compounds, we observed that the binding affinity between compounds and hTTR increased with increasing molecular hydrophobicity. Those results indicated that the highly hydrophobic halo-benzoic acids and halo-benzenesulfonic acids/sulfates may be high-priority hTTR disruptors. Finally, a binary classification model was constructed employing three predictive variables. The sensitivity (S_n), specificity (S_p), predictive accuracy (Q) values of the training set and validation set were >0.83, indicating that the model had good classification performance. Thus, the binary classification model developed here could be used to distinguish whether a given ionizable compound is a potential hTTR binder or not.

In silico study for inhibiting thyroid hormone sulfotransferase activity by halogenated phenolic chemicals

Thyroid hormones (THs) are essential to proper growth and development of human bodies. Inhibiting the sulfation metabolism of THs has been demonstrated to be an important way for some environmental pollutants, such as halogenated phenolic compounds, to interfere THs homeostasis, thereby causing health problems. However, the important property characteristics that govern the sulfation inhibition of these chemicals are not well understood, and the experimental data on inhibition potential is limited. In this work, an in silico approach was developed to investigate the structure-activity relationship for their sulfotransferases (SULTs) inhibition. A series of quantum chemical descriptors that quantify the electronic and energy properties of 22 halogenated phenolic compounds have been calculated to establish a predictive model and analyzed their corresponding contributions to SULTs inhibition. Density functional theory (DFT) B3LYP/6-31G** has been employed to optimize molecular geometries to obtain a total of 15 descriptors for every compound. The implementation of linear regression shows three descriptors that represent molecular mass, positive charges on hydrogen atoms, and energy of frontier orbitals strongly correlate with SULTs inhibition potential. This indicates molecular size, hydrogen-bond strength, and nucleophilic-electrophilic reactivity may play important roles in SULTs inhibition. The derived regression model has good statistical performance (r² = 0.84, rms = 0.35), and different validation strategies indicate it can serve as an efficient predictive tool for other chemicals in application domain but with no experimental data, consequently assisting in their THs sulfation inhibition and health risk assessment.

Development of liposome/water partition coefficients predictive models for neutral and ionogenic organic chemicals

Membrane/water partition coefficient (K_m/w) is a vital parameter used to characterize the membrane permeability of compounds. Considering the K_m/w value is difficult to observe experimentally for real biological membranes, liposome/water partition coefficient (K_lip/w) is employed to approximate K_m/w. Here, quantitative structure property relationship (QSPR) models for logK_lip/w of the neutral organic chemicals and the neutral form of ionogenic organic chemicals (IOCs) (logK_{lip/w-neutral}), ionic form of IOCs (logK_lip/w-ionic), the speciation-corrected liposome-water distribution ratios at a pH = 7.40 (logD_{lip/w-(pH=7.40)}) were developed. In the modeling, two modeling methods (multiple linear regressions (MLR) and k-nearest neighbor (kNN)) were used. The predictive variables employed here could be calculated from the molecular structure directly. For logK_{lip/w-neutral} and logD_{lip/w-(pH=7.40)}, the logK_OW and logD_OW-based, non-logK_OW and non-logD_OW-based kNN-QSPR and MLR-QSPR models were developed, respectively. The evaluation results implied that the predictive performance of kNN-QSPR models is better than that of MLR-QSPR models. For logK_lip/w-ionic, only one acceptable MLR-QSPR model was developed for cation and anion, respectively. The model quality of the derived models was evaluated following the OECD QSPR models validation guideline. The determination coefficient (R²), leave-one-out cross validation Q² (Q²_LOO) and bootstrapping coefficient (Q²_BOOT), the external validation coefficient (Q²_EXT) of all the models met the acceptable criteria (Q² > 0.600, R² > 0.700); while the root-mean-square error (RMSE) range from 0.351 to 0.857. All the results implied that the models had good goodness-of-fit, robustness and predictive ability. Therefore, the developed models could be used to fill the data gap for substances within the applicability domain on their missing logK_{lip/w-neutral}, logK_lip/w-ionic, logD_{lip/w-(pH=7.40)} values.

Emerging Polar Phenolic Disinfection Byproducts Are High-Affinity Human Transthyretin Disruptors: An in Vitro and in Silico Study

Phenolic disinfection byproducts (phenolic-DBPs) have been identified in recent years. However, the toxicity data for phenolic-DBPs are scarce, hampering their risk assessment and the development of regulations on the acceptable concentration of phenolic-DBPs in water. In this study, the binding potency and underlying interaction mechanism between human transthyretin (hTTR) and five groups of representative phenolic-DBPs (2,4,6-trihalo-phenols, 2,6-dihalo-4-nitrophenols, 3,5-dihalo-4-hydroxybenzaldehydes, 3,5-dihalo-4-hydroxybenzoic acids, halo-salicylic acids) were determined and probed by competitive fluorescence displacement assay integrated with in silico methods. Experimental results implied that 2,4,6-trihalo-phenols, 2,6-dihalo-4-nitrophenols, and 3,5-dihalo-4-hydroxybenzaldehydes have a high binding affinity with hTTR. The hTTR binding potency of the chemicals with electron-withdrawing groups on their molecular structures were higher than that with electron-donor groups. Molecular modeling methods were used to decipher the binding mechanism between model compounds and hTTR. The results documented that ionic pair, hydrogen bonding and hydrophobic interactions were dominant interactions. Finally, a mechanism-based model for predicting the hTTR binding affinity was developed. The determination coefficient ( R²), leave-one-out cross validation Q² ( Q_LOO²), bootstrapping coefficient ( Q_BOOT²), external validation coefficient ( Q_EXT²) and concordance correlation coefficient ( CCC) of the developed model met the acceptable criteria ( Q² > 0.600, R² > 0.700, CCC > 0.850), implying that the model had good goodness-of-fit, robustness, and external prediction performances. All the results indicated that the phenolic-DBPs have the hTTR disrupting effects, and further studies are needed to investigate their other mechanism of endocrine disruption.

Development of chicken and fish muscle protein - Water partition coefficients predictive models for ionogenic and neutral organic chemicals

Muscle protein was one of critical accumulation protein for anthropogenic chemicals. However, few predictive models were constructed for muscle protein up to now. In addition, some ionizable chemicals classes e.g. sulfonates were not successfully modeled in previously models, indicating considerable work would be needed. The major objective of this study was to develop quantitative structure-activity relationship (QSAR) models for predicting the muscle protein-water partition coefficient (logK_MP/w) of chicken and fish. In the modeling, the n-octanol/water distribution coefficient (logD), functional groups, atom-centred fragments and chemical form adjusted descriptors were used to construct the models. The application domain of the derived models was defined by the Euclidean distance-based method and Williams plot. The modeling results indicated that the determination coefficient (R²), leave-one out cross validation Q² (Q²_LOO) and bootstrapping coefficient (Q²_BOOT) of the QSAR models for chicken and fish were 0.882 and 0.929, 0.844 and 0.906, 0.779 and 0.792, respectively, implying the models had good goodness-of-fit and robustness. The coefficient determination (R²_EXT) and external validation coefficient (Q²_EXT) of the validation set for the two models were 0.874 and 0.937, 0.869 and 0.915, respectively, indicating the models had good predictive ability. The predictor variables selected to construct the logK_MP/w models of chicken and fish included logD, the function groups, and the fraction of the ionized species (δ_I). Considering the molecular descriptors used here can be calculated from their molecular structures directly, the developed models could be easily used to fill the logK_MP/w data gap for other chemicals within the applicability domain.

Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors

The partition coefficients between bovine serum albumin (BSA) and water (K_BSA/w) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logK_BSA/w. However, it was found that the conventional descriptors are inappropriate for modeling logK_BSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K_BSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logK_BSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (V_s-adj^-), the chemical form adjusted molecular dipole moment (dipolemoment_adj), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logK_BSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs.

Different binding mechanisms of neutral and anionic poly-/perfluorinated chemicals to human transthyretin revealed by In silico models

Chemical forms-dependent binding interactions between phenolic compounds and human transthyretin (hTTR) have been elaborated previously. However, it is not known whether the binding interactions between ionizable halogenated alphatic compounds and hTTR also have the same manner. In this study, poly-/perfluorinated chemicals (PFCs) were selected as model compounds and molecular dynamic simulation was performed to investigate the binding mechanisms between PFCs and hTTR. Results show the binding interactions between the halogenated aliphatic compounds and hTTR are related to the chemical forms. The ionized groups of PFCs can form electrostatic interactions with the -NH⁺₃ groups of Lys 15 residues in hTTR and form hydrogen bonds with the residues of hTTR. By analyzing the molecular orbital energies of PFCs, we also found that the anionic groups (nucleophile) in PFCs could form electron donor - acceptor interactions with the -NH⁺₃ groups (electrophile) in Lys 15. The aforementioned orientational interactions make the ionized groups of the PFCs point toward the entry port of the binding site. The roles of fluorine atoms in the binding interactions were also explored. The fluorine atoms can influence the binding interactions via inductive effects. Appropriate molecular descriptors were selected to characterize these interactions, and two quantitative structure-activity relationship models were developed.

Understanding the microscopic binding mechanism of hydroxylated and sulfated polybrominated diphenyl ethers with transthyretin by molecular docking, molecular dynamics simulations and binding free energy calculations

Polybrominated diphenyl ethers (PBDEs), one typical type of persistent environmental contaminant, have toxicological effects such as disrupting thyroid homeostasis in the human body. The high binding affinities of hydroxylated metabolites of PBDEs (OH-PBDEs) with transthyretin (TTR) were considered to be one major reason for their extraordinary capacity of passing through the blood-brain barrier via competitive thyroid hormone (T4) transport protein binding. Recent findings showed that sulfated PBDEs can be formed in human liver cytosol as phase-II metabolites. However, experimentally determined data for the TTR binding potential of the sulfated PBDEs are still not available. Therefore, molecular docking and molecular dynamics (MD) simulations were employed in the present study to probe the molecular basis of TTR interacting with hydroxylated and sulfated PBDEs at the atomic level. The docking scores of LeDock were used to construct the structure-based predictive model. The calculated results showed that the sulfated PBDEs have stronger affinity for TTR than the corresponding OH-PBDEs. Further analysis of structural characteristics based on MD simulations indicated that upon the binding of PBDE metabolites, the stability of TTR was enhanced and the dissociation rate of the tetrameric protein structure was potentially decreased. Subsequent binding free energy calculations implied that van der Waals interactions are the dominant forces for the binding of these metabolites of PBDEs at the T4 site of TTR. The residues Ser117/Ser117' and Lys15/Lys15' were identified, by both residue energy decomposition and computational alanine-scanning mutagenesis methods, as key residues which play an important role in determining the binding orientations of the -OSO₃^- group of sulfated PBDEs by formation of either hydrogen bonds or electrostatic interactions, respectively. In general, the combination of docking calculations with MD simulations provided a theoretically toxicological assessment for the metabolites of PBDEs, deep insight into the recognition mechanism of TTR for these compounds, and thus more comprehensive understanding of the thyroid-related toxic effects of PBDEs as well.

Development of predictive models for predicting binding affinity of endocrine disrupting chemicals to fish sex hormone-binding globulin

Disturbing the transport process is a crucial pathway for endocrine disrupting chemicals (EDCs) exerting disrupting endocrine function. However, this mechanism has not received enough attention compared with that of hormones receptors and synthetase. Recently, we have explored the interaction between EDCs and sex hormone-binding globulin of human (hSHBG). In this study, interactions between EDCs and sex hormone-binding globulin of eight fish species (fSHBG) were investigated by employing classification methods and quantitative structure-activity relationships (QSAR). In the modeling, the relative binding affinity (RBA) of a chemical with 17β-estradiol binding to fSHBG was selected as the endpoint. Classification models were developed for two fish species, while QSAR models were established for the other six fish species. Statistical results indicated that the models had satisfactory goodness of fit, robustness and predictive ability, and that application domain covered a large number of endogenous and exogenous steroidal and non-steroidal chemicals. Additionally, by comparing the log RBA values, it was found that the same chemical may have different affinities for fSHBG from different fish species, thus species diversity should be taken into account. However, the affinity of fSHBG showed a high correlation for fishes within the same Order (i.e., Salmoniformes, Cypriniformes, Perciformes and Siluriformes), thus the fSHBG binding data for one fish species could be used to extrapolate other fish species in the same Order.

Predicting anti-androgenic activity of bisphenols using molecular docking and quantitative structure-activity relationships

Both in vivo and in vitro assay indicated that bisphenols can inhibit the androgen receptor. However, the underlying antagonistic mechanism is unclear. In this study, molecular docking was employed to probe the interaction mechanism between bisphenols and human androgen receptor (hAR). The binding pattern of ligands in hAR crystal structures was also analyzed. Results show that hydrogen bonding and hydrophobic interactions are the dominant interactions between the ligands and hAR. The critical amino acid residues involved in forming hydrogen bonding between bisphenols and hAR is Asn 705 and Gln 711. Furthermore, appropriate molecular structural descriptors were selected to characterize the non-bonded interactions. Stepwise multiple linear regressions (MLR) analysis was employed to develop quantitative structure-activity relationship (QSAR) models for predicting the anti-androgenic activity of bisphenols. Based on the QSAR development and validation guideline issued by OECD, the goodness-of-fit, robustness and predictive ability of constructed QSAR model were assessed. The model application domain was characterized by the Euclidean distance and Williams plot. The mechanisms of the constructed model were also interpreted based on the selected molecular descriptors i.e. the number of hydroxyl groups (nROH), the most positive values of the molecular surface potential (Vs,max) and the lowest unoccupied molecular orbital energy (ELUMO). Finally, based on the model developed, the data gap for other twenty-six bisphenols on their anti-androgenic activity was filled. The predicted results indicated that the anti-androgenic activity of seven bisphenols was higher than that of bisphenol A.

Rational Selection of the 3D Structure of Biomacromolecules for Molecular Docking Studies on the Mechanism of Endocrine Disruptor Action

Molecular modeling has become an essential tool in predicting and simulating endocrine disrupting effects of chemicals. A key prerequisite for successful application of molecular modeling lies in the correctness of 3D structure for biomacromolecules to be simulated. To date, there are several databases that can provide the experimentally-determined 3D structures. However, commonly, there are many challenges or disadvantageous factors, e.g., (a) lots of 3D structures for a given biomacromolecular target in the protein database; (b) the quality variability for those structures; (c) belonging to different species; (d) mutant amino acid residue in key positions, and so on. Once an inappropriate 3D structure of a target biomacromolecule was selected in molecular modeling, the accuracy and scientific nature of the modeling results could be inevitably affected. In this article, based on literature survey and an analysis of the 3D structure characterization of biomacromolecular targets belonging to the endocrine system in protein databases, six principles were proposed to guide the selection of the appropriate 3D structure of biomacromolecules. The principles include considering the species diversity, the mechanism of action, whether there are mutant amino acid residues, whether the number of protein chains is correct, the degree of structural similarity between the ligand in 3D structure and the target compounds, and other factors, e.g., the experimental pH conditions of the structure determined process and resolution.

Development of classification model and QSAR model for predicting binding affinity of endocrine disrupting chemicals to human sex hormone-binding globulin

Disturbing the transport process is a crucial pathway for endocrine disrupting chemicals (EDCs) to disrupt endocrine function. However, this mechanism has not gotten enough attention, compared with that of hormone receptors and synthetase up to now, especially for the sex hormone transport process. In this study, we selected sex hormone-binding globulin (SHBG) and EDCs as a model system and the relative competing potency of a chemical with testosterone binding to SHBG (log RBA) as the endpoints, to develop classification models and quantitative structure-activity relationship (QSAR) models. With the classification model, a satisfactory model with nR09, nR10 and RDF155v as the most relevant variables was screened. Statistic results indicated that the model had the sensitivity, specificity, accuracy of 86.4%, 80.0%, 84.4% and 85.7%, 87.5%, 86.2% for the training set and validation set, respectively, highlighting a high classification performance of the model. With the QSAR model, a satisfactory model with statistical parameters, specifically, an adjusted determination coefficient (Radj(2)) of 0.810, a root mean square error (RMSE) of 0.616, a leave-one-out cross-validation squared correlation coefficient (QLOO(2)) of 0.777, a bootstrap method (QBOOT(2)) of 0.756, an external validation coefficient (Qext(2)) of 0.544 and a RMSEext of 0.859, were obtained, which implied satisfactory goodness of fit, robustness and predictive ability. The applicability domain of the current model covers a large number of structurally diverse chemicals, especially a few classes of nonsteroidal compounds.

Toward rational design of amines for CO2 capture: Substituent effect on kinetic process for the reaction of monoethanolamine with CO2

Amines have been considered as promising candidates for post-combustion CO2 capture. A mechanistic understanding for the chemical processes involved in the capture and release of CO2 is important for the rational design of amines. In this study, the structural effects of amines on the kinetic competition among three typical products (carbamates, carbamic acids and bicarbonate) from amines+CO2 were investigated, in contrast to previous thermodynamic studies to tune the reaction of amines with CO2 based on desirable reaction enthalpy and reaction stoichiometry. We used a quantum chemical method to calculate the activation energies (Ea) for the reactions of a range of substituted monoethanolamines with CO2 covering three pathways to the three products. The results indicate that the formation of carbamates is the most favorable, among the three considered products. In addition, we found that the Ea values for all pathways linearly correlate with pKa of amines, and more importantly, the kinetic competition between carbamate and bicarbonate absorption pathways varies with pKa of the amines, i.e. stronger basicity results in less difference in Ea. These results highlight the importance of the consideration of kinetic competition among different reaction pathways in amine design.

Modeling and predicting pKa values of mono-hydroxylated polychlorinated biphenyls (HO-PCBs) and polybrominated diphenyl ethers (HO-PBDEs) by local molecular descriptors

Hydroxylated polychlorinated biphenyls (HO-PCBs) and polybrominated diphenyl ethers (HO-PBDEs) are attracting considerable concerns because of their multiple endocrine-disrupting effects and wide existence in environment and organisms. The hydroxyl groups enable these chemicals to be ionizable, and dissociation constant, pKa, becomes an important parameter for investigating their environmental behavior and biological activities. In this study, a new pKa prediction model was developed using local molecular descriptors. The dataset contains 21 experimental pKa values of HO-PCBs and HO-PBDEs. The optimized geometries by ab initio HF/6-31G(∗∗) algorithm were used to calculate the site-specific molecular readiness to accept or donate electron charges. The developed model obtained good statistical performance, which significantly outperformed commercial software ACD and SPARC. Mechanism analysis indicates that pKa values increase with the charge-limited donor energy EQocc on hydroxyl oxygen atom and decrease with the energy-limited acceptor charge QEvac on hydroxyl hydrogen atom. The regression model was also applied to calculate pKa values for all 837 mono-hydroxylated PCBs and PBDEs in each class, aiming to provide basic data for the ecological risk assessment of these chemicals.

Human sex hormone-binding globulin binding affinities of 125 structurally diverse chemicals and comparison with their binding to androgen receptor, estrogen receptor, and α-fetoprotein

One endocrine disruption mechanism is through binding to nuclear receptors such as the androgen receptor (AR) and estrogen receptor (ER) in target cells. The concentration of a chemical in serum is important for its entry into the target cells to bind the receptors, which is regulated by the serum proteins. Human sex hormone-binding globulin (SHBG) is the major transport protein in serum that can bind androgens and estrogens and thus change a chemical's availability to enter the target cells. Sequestration of an androgen or estrogen in the serum can alter the chemical elicited AR- and ER-mediated responses. To better understand the chemical-induced endocrine activity, we developed a competitive binding assay using human pregnancy plasma and measured the binding to the human SHBG for 125 structurally diverse chemicals, most of which were known to bind AR and ER. Eighty seven chemicals were able to bind the human SHBG in the assay, whereas 38 chemicals were nonbinders. Binding data for human SHBG are compared with that for rat α-fetoprotein, ER and AR. Knowing the binding profiles between serum and nuclear receptors will improve assessment of a chemical's potential for endocrine disruption. The SHBG binding data reported here represent the largest data set of structurally diverse chemicals tested for human SHBG binding. Utilization of the SHBG binding data with AR and ER binding data could enable better evaluation of endocrine disrupting potential of chemicals through AR- and ER-mediated responses since sequestration in serum could be considered.

Synthesis, crystal structure and biological activity of 2-hydroxyethylammonium salt of p-aminobenzoic acid

p-Aminobenzoic acid (pABA) plays important roles in a wide variety of metabolic processes. Herein we report the synthesis, theoretical calculations, crystallographic investigation, and in vitro determination of the biological activity and phytotoxicity of the pABA salt, 2-hydroxyethylammonium p-aminobenzoate (HEA-pABA). The ability of neutral and anionic forms of pABA to interact with TIR1 pocket was investigated by calculation of molecular electrostatic potential maps on the accessible surface area, docking experiments, Molecular Dynamics and Quantum Mechanics/Molecular Mechanics calculations. The docking study of the folate precursor pABA, its anionic form and natural auxin (indole-3-acetic acid, IAA) with the auxin receptor TIR1 revealed a similar binding mode in the active site. The phytotoxic evaluation of HEA-pABA, pABA and 2-hydroxyethylamine (HEA) was performed on the model plant Arabidopsis thaliana ecotype Col 0 at five different concentrations. HEA-pABA and pABA acted as potential auxin-like regulators of root development in Arabidopsis thaliana (0.1 and 0.2 mM) and displayed an agravitropic root response at high concentration (2 mM). This study suggests that HEA-pABA and pABA might be considered as potential new regulators of plant growth.

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.

Designing quantitative structure activity relationships to predict specific toxic endpoints for polybrominated diphenyl ethers in mammalian cells

Polybrominated diphenyl ethers (PBDEs) are known as effective flame retardants and have vast industrial application in products like plastics, building materials and textiles. They are found to be structurally similar to thyroid hormones that are responsible for regulating metabolism in the body. Structural similarity with the hormones poses a threat to human health because, once in the system, PBDEs have the potential to affect thyroid hormone transport and metabolism. This study was aimed at designing quantitative structure-activity relationship (QSAR) models for predicting toxic endpoints, namely cell viability and apoptosis, elicited by PBDEs in mammalian cells. Cell viability was evaluated quantitatively using a general cytotoxicity bioassay using Janus Green dye and apoptosis was evaluated using a caspase assay. This study has thus modelled the overall cytotoxic influence of PBDEs at an early and a late endpoint by the Genetic Function Approximation method. This research was a twofold process including running in vitro bioassays to collect data on the toxic endpoints and modeling the evaluated endpoints using QSARs. Cell viability and apoptosis responses for Hep G2 cells exposed to PBDEs were successfully modelled with an r(2) of 0.97 and 0.94, respectively.