In silico study on hydroxylated polychlorinated biphenyls as androgen receptor antagonists

Development and Validation of Predictive Quantitative Structure-Activity Relationship Models for Estrogenic Activities of Hydroxylated Polychlorinated Biphenyls

Disruption of the endocrine system by hydroxylated polychlorinated biphenyls (OH-PCBs) is hypothesized, among other potential mechanisms, to be mediated via nuclear receptor binding. Due to the high cost and lengthy time required to produce high-quality experimental data, empirical data to support the nuclear receptor binding hypothesis are in short supply. In the present study, two quantitative structure-activity relationship models were developed for predicting the estrogenic activities of OH-PCBs. Findings revealed that model I (for the estrogen receptor α dataset) contained five two-dimensional (2D) descriptors belonging to the classes autocorrelation, Burden modified eigenvalues, chi path, and atom type electrotopological state, whereas model II (for the estrogen receptor β dataset) contained three 2D and three 3D descriptors belonging to the classes autocorrelation, atom type electrotopological state, and Radial Distribution Function descriptors. The internal and external validation metrics reported for models I and II indicate that both models are robust, reliable, and suitable for predicting the estrogenic activities of untested OH-PCB congeners. Environ Toxicol Chem 2023;42:823-834. © 2023 SETAC.

An adjusted 3D-QSAR model for the combined activity of fluoroquinolones photodegradation and microbial degradation assisted by dynamic simulation and its application in molecular modification

This study developed a comprehensive characterization method for the combined degradation effect of modified fluoroquinolones (FQs) photodegradation and microbial degradation. A combination of revised 3D-QSAR model, molecular docking, path simulation inference, pharmacokinetics, molecular dynamics (MD) simulation and toxicokinetics simulation was used to construct a systematic environment-friendly drug screening system. Five derivatives were screened with significantly improved combined degradation effect (over 20%) and functional characteristics and human health parameters through combined model verification, functional and human health risk assessment. The simulation path of photo- and microbial-degradation of gatifloxacin and new gatifloxacin molecules was derived, and the reaction energy barrier was also calculated. The ratio of the total rate-determining steps change rate of the decreased energy barrier (14.10%:26.30%) was consistent with the ratio of the increased degradation performance predicted by the model (22.87%:19.77%), demonstrating the reliability of revised 3D-QSAR model and it could be applied in molecular modification. MD and toxicokinetics simulation were used to predict the binding energy and aquatic toxicity between photo- and microbial-degradation products and the degradation enzymes, which further to screen the degradation pathways with low potential environmental risks. The findings will be helpful to screen environment-friendly drug and develop appropriate strategies for its risk management.

Identification and regulation of ecotoxicity of polychlorinated naphthalenes to aquatic food Chain (green algae-Daphnia magna-fish)

Polychlorinated naphthalenes (PCNs) are widely distributed in the aquatic environment and can be transmitted through the food chain, which can amplify their toxic effects on human. To inhibit their transmission in the trophic level, this study aimed to predict the joint toxicity mechanism of polychlorinated naphthalenes (PCNs) to the key organisms and control scheme of its toxicity in the aquatic food chain (green algae-Daphnia magna-fish). The toxic effect grade and mode of action (MoA) of PCNs on the food chain were first predicted to guide the establishment of toxic mechanism model. QSAR models were constructed to quantify the mechanism of aquatic toxicity due to PCNs. The results showed the PCN compounds studied were highly toxic at all the trophic levels of the aquatic food chain. The binding ability of PCNs to the aquatic organisms was the main factor causing the toxicity of PCNs in the food chain, followed by electronic parameters E_HOMO and E_LUMO. Moreover, the binding ability between PCNs and food chain receptors was related to the molecular hydrophobicity, the hydrophobicity can be changed by adjusting the ability of PCNs to be adsorbed by sediment and their chlorine substituents, while the effect of PCNs electronic parameters (E_HOMO and E_LUMO) can be adjusted by their solvation effect. In addition, the macro-control scheme of PCN-based aquatic toxicity mechanism was established, and the molecular dynamics (MD) simulation confirmed its effectiveness and accessibility. The MD simulation showed the inhibition effect of nutrition-grade toxicity in the food chain was significant when the external stimulation conditions of solvation, anaerobic dechlorination and molecular adsorption were improved, with the decrease range of 66.26-263.16%, 198.93-323.98% and 189.24-549.48%, respectively. This work reveals new insights into the mechanism of PCNs joint toxicity to aquatic ecosystem food chain and develop appropriate strategies for its ecological risk management.

Combined remediation of polychlorinated naphthalene-contaminated soil under multiple scenarios: An integrated method of genetic engineering and environmental remediation technology

This study explored the types of polychlorinated naphthalene (PCN)-contaminated soil and determined the practicable scheme of combined remediation using an integrated method of genetic engineering and environmental remediation technology. A multi-scenario comprehensive evaluation system of a plant-microbial combined bioremediation of PCN-contaminated soil was established using the intelligent integration of analytic hierarchy process and formula evaluation methods based on the current situation of PCN contamination in China, which showed the bioremediation of PCN-contaminated soil by the plant-microbial system could be divided into four scenarios. QSAR models were constructed to quantify the remediation mechanism that electronic parameter ∆E was the key factor changing the efficiency of combined bioremediation. Moreover, the macro-control scheme of PCN-contaminated soil was established, which indicated that four new multifunctional proteins promoted the absorption, degradation, and mineralization of PCNs in specific soil pollution types significantly, were obtained through cross gene recombination. The molecular dynamics (MD) simulation results showed the efficiency of the plant-microbial combined bioremediation were increased by 15.45% (Scenario 1, 2, 3) and 20.02% (Scenario 4) under the optimal regulation scheme. The findings will be helpful to realize the regional control of PCN-contaminated soil.

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.

Environmentally Friendly Quinolones Design for a Two-Way Choice between Biotoxicity and Genotoxicity through Double-Activity 3D-QSAR Model Coupled with the Variation Weighting Method

Quinolone (QN) antibiotics are widely used, which lead to their accumulation in soil and toxic effects on ryegrass in pasture. In this study, we employed ryegrass as the research object and selected the total scores of 29 QN molecules docked with two resistant enzyme structures, superoxide dismutase (SOD, PDB ID: 1B06) and proline (Pro, PPEP-2, PDB ID: 6FPC), as dependent variables. The structural parameters of QNs were used as independent variables to construct a QN double-activity 3D-QSAR model for determining the biotoxicity on ryegrass by employing the variation weighting method. This model was constructed to determine modification sites and groups for designing QNs molecules. According to the 3D contour map of the model, by considering enrofloxacin (ENR) and sparfloxacin (SPA) as examples, 23 QN derivatives with low biotoxicity were designed, respectively. The functional properties and environmental friendliness of the QN derivatives were predicted through a two-way selection between biotoxicity and genotoxicity before and after modification; four environmentally friendly derivatives with low biotoxicity and high genotoxicity were screened out. Mixed toxicity index and molecular dynamics methods were used to verify the combined toxicity mechanism of QNs on ryegrass before and after modification. By simulating the combined pollution of ENR and its derivatives in different soils (farmland, garden, and woodland), the types of combined toxicity were determined as partial additive and synergistic. Binding energies were calculated using molecular dynamics. The designed QN derivatives with low biotoxicity, high genotoxicity, and environmental friendliness can highly reduce the combined toxicity on ryegrass and can be used as theoretic reserves to replace QN antibiotics.

Environmentally Friendly Fluoroquinolone Derivatives with Lower Plasma Protein Binding Rate Designed Using 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation

Comparative molecular similarity index analysis (CoMSIA) was used to establish a three-dimensional quantitative structure–activity relationship (3D-QSAR) model with structural parameters of quinolones as the independent variables and plasma protein binding rate (logf_b) as the dependent variable to predict the logf_b values of remaining quinolones in this study. In addition, the mono-substituted and bis-substituted reaction schemes that significantly influenced the plasma protein binding rate of quinolones were determined through an analysis of the 3D-QSAR contour maps. It was found that the replacement of small groups, hydrophobic groups, electronegative groups, or hydrogen bond acceptor groups at the substitution sites significantly reduce the logf_b values of quinolone derivatives. Furthermore, the mechanism of decrease in binding rate between trovafloxacin (TRO) derivatives and plasma protein was revealed qualitatively and quantitatively based on molecular docking and molecular dynamics simulation. After modification of the target molecule, 11 TRO derivatives with low plasma protein binding rates were screened (reduced by 0.50–24.18%). Compared with the target molecule, the molecular genotoxicity and photodegradability of the TRO derivatives was higher (genotoxicity increased by 4.89–21.36%, and photodegradability increased by 9.04–20.56%), and their bioconcentration was significantly lower (by 36.90–61.41%).

Enhanced Biodegradation of Phthalic Acid Esters' Derivatives by Plasticizer-Degrading Bacteria (Burkholderia cepacia, Archaeoglobus fulgidus, Pseudomonas aeruginosa) Using a Correction 3D-QSAR Model

A phthalic acid ester’s (PAEs) comprehensive biodegradability three-dimensional structure-activity relationship (3D-QSAR) model was established, to design environmentally friendly PAE derivatives, which could be simultaneously degraded by plasticizer-degrading bacteria, such as Burkholderia cepacia, Archaeoglobus fulgidus, and Pseudomonas aeruginosa. Only three derivatives of diethyl phthalate (DEP (DEP-27, DEP-28 and DEP-29)) were suited for their functionality and environmental friendliness, which had an improved stability in the environment and improved the characteristics (bio-toxicity, bioaccumulation, persistence, and long-range migration) of the persistent organic pollutants (POPs). The simulation inference of the microbial degradation path before and after DEP modification and the calculation of the reaction energy barrier exhibited the energy barrier for degradation being reduced after DEP modification and was consistent with the increased ratio of comprehensive biodegradability. This confirmed the effectiveness of the comparative molecular similarity index analysis (CoMSIA) model of the PAE’s comprehensive biodegradability. In addition, a molecular dynamics simulation revealed that the binding of the DEP-29 derivative with the three plasticizer-degradation enzymes increased significantly. DEP-29 could be used as a methyl phthalate derivative that synergistically degrades with microplastics, providing directional selection and theoretical designing for plasticizer replacement.

Environment-friendly PCN derivatives design and environmental behavior simulation based on a multi-activity 3D-QSAR model and molecular dynamics

A multi-activity three-dimensional quantitative structure-activity relationship (3D-QSAR) model was established based on the comprehensive evaluation index (CEI) of polychlorinated naphthalenes (PCNs). The CEI values were calculated using the vector analysis method in combination with the following parameters: biological toxicity (predicted by logEC₅₀), bioconcentration (predicted by logK_ow), long-distance migration (predicted by logP_L), and biodegradation (predicted by total-score). Additionally, sixty-four CN-70 derivatives with lower CEI values were designed, among which three derivatives with reduced CEI values were selected for verification based on an evaluation of their persistent organic pollutant properties and practicability. Finally, an environmental behavior simulation was conducted via molecular dynamics simulation aided by the Taguchi experimental design by considering the degradation characteristics of the three aforementioned CN-70 derivatives as an example. Only two of the selected CN-70 derivatives were observed to be more easily degraded when compared with the CN-70 molecule (ascending range: 11.57 %-13.57 %) in a real-world setting, which was consistent with the biodegradability prediction results (ascending range: 14.94 %-22.49 %) obtained through the molecular docking studies. The multi-activity 3D-QSAR model established in this study overcame the limitations of generating molecular designs based on single-effect models from the source because it focused on the multiple effects of the pollutants.

Integration of Fuzzy Matter-Element Method and 3D-QSAR Model for Generation of Environmentally Friendly Quinolone Derivatives

The environmental pollution of quinolone antibiotics (QAs) has caused rising public concern due to their widespread usage. In this study, Gaussian 09 software was used to obtain the infrared spectral intensity (IRI) and ultraviolet spectral intensity (UVI) of 24 QAs based on the Density Functional Theory (DFT). Rather than using two single-factor inputs, a fuzzy matter-element method was selected to calculate the combined effects of infrared and ultraviolet spectra (CI). The Comparative Molecular Field Analysis (CoMFA) was then used to construct a three-dimensional quantitative structure–activity relationship (3D-QSAR) with QAs’ molecular structure as the independent variable and CI as the dependent variable. Using marbofloxacin and levofloxacin as target molecules, the molecular design of 87 QA derivatives was carried out. The developed models were further used to determine the stability, functionality (genetic toxicity), and the environmental effects (bioaccumulation, biodegradability) of these designed QA derivatives. Results indicated that all QA derivatives are stable in the environment with their IRI, UVI, and CI enhanced. Meanwhile, the genetic toxicity of the 87 QA derivatives increased by varying degrees (0.24%–29.01%), among which the bioaccumulation and biodegradability of 43 QA derivatives were within the acceptable range. Through integration of fuzzy matter-element method and 3D-QSAR, this study advanced the QAs research with the enhanced CI and helped to generate the proposed environmentally friendly quinolone derivatives so as to aid the management of this class of antibiotics.

Fuzzy Comprehensive Evaluation Assistant 3D-QSAR of Environmentally Friendly FQs to Reduce ADRs

Most studies on adverse drug reactions (ADRs) of fluoroquinolones (FQs) have focused on the mechanisms of single ADRs, and no quantitative structure–activity relationship (QSAR) method studies have been carried out that combine several ADRs of FQs. In this study, an improved three-dimensional (3D) QSAR method was established using fuzzy comprehensive evaluation. This method could simultaneously consider three common ADRs of FQs using molecular parameters. The improved method could comprehensively predict three ADRs of FQs and provide direction for the development of new drugs with lower ADRs than the originals. According to the improved method, 48 derivatives with lower ADRs (decreased by 4.86% to 50.92%) were designed from pazufloxacin. Three derivatives with a higher genotoxicity, higher photodegradation, and lower bioconcentration than pazufloxacin were selected using the constructed QSAR methods of the FQs. Finally, three traditional 3D-QSAR methods of single ADR were constructed to validate the improved method. The improved method was reasonable, with a relative error range of 0.96% to 4.30%. This study provides valuable reference data and will be useful for the development of strategies to produce new drugs with few ADRs. In the absence of complementary biological studies of these adverse drug reactions, the results reported here may be quite divergent from those found in humans or experimental animals in vivo. One major reason for this is that many adverse drug reactions are dependent upon enzyme-catalyzed metabolic activation (toxication) or on non-enzymatic conversion to toxic products and are not due to the parent drug moiety.

Quantitative structure-property relationship (QSPR) models for predicting the physicochemical properties of polychlorinated biphenyls (PCBs) using deep belief network

Octanol/water partition coefficient (log P), octanol/air partition coefficient (log K_OA) and bioconcentration factor (log BCF) are important physiochemical properties of organic substances. Quantitative structure-property relationship (QSPR) models are a promising alternative method of reducing and replacing experimental steps in determination of log P, log K_OA and log BCF. In the current study, we propose a new QSPR model based on a deep belief network (DBN) to predict the physicochemical properties of polychlorinated biphenyls (PCBs). The prediction accuracy of the proposed model was compared to the results of previous reported models. The predictive ability of the DBN model, validated with a test set, is clearly superior to the other models. All results showed that the proposed model is robust and satisfactory, and can effectively predict the physiochemical properties of PCBs without highly reliable experimental values.

The identification of the metabolites of chlorothalonil in zebrafish (Danio rerio) and their embryo toxicity and endocrine effects at environmentally relevant levels

Chlorothalonil is a broad spectrum fungicide with high annual production and environmental contamination. Despite its high consumption, studies regarding the potential ecological risks of chlorothalonil, especially its metabolites, to aquatic organisms are still limited. In this study, we selected the zebrafish (Danio rerio) as the in vivo model and first identified the metabolite (4-hydroxychlorothalonil) of chlorothalonil in zebrafish by tandem quadrupole/orthogonal-acceleration time-of-flight (Q-TOF). Then, the in vivo and in vitro models were applied to comprehensively estimate the embryo toxicity and potential endocrine effect of chlorothalonil and 4-hydroxychlorothalonil. The data from zebrafish embryo toxicity showed that the lowest observed effect concentrations of both chlorothalonil and 4-hydroxychlorothalonil were 50 μg/L after 96 h of exposure. The mortality rate of the 4-hydroxychlorothalonil was 2.6-fold higher than that of the parent compound at the concentration of 50 μg/L. Dual-luciferase reporter gene assays indicated that both chlorothalonil and 4-hydroxychlorothalonil exerted estrogen receptor α (ERα) agonist activity with REC₂₀ values of 2.4 × 10^-8 M and 3.6 × 10^-8 M, respectively. However, only 4-hydroxychlorothalonil exhibited both thyroid receptor β (TRβ) agonistic and antagonistic activities. Lastly, we employed molecular docking to predict the binding affinity of chlorothalonil and 4-hydroxychlorothalonil with ERα or TRβ. The results revealed that the potential endocrine effect of chlorothalonil and 4-hydroxychlorothaloni might be attributed to the different binding affinities with the receptors. In conclusion, our studies revealed that 4-hydroxychlorothalonil exhibited potent endocrine-disrupting effects compared to its parent compound, chlorothalonil. The results provided here remind us that the assessment of the potential ecological and health risks of the metabolites of fungicides in addition to their parent compounds should arouse great concerns.

The neurotoxicity of DE-71: effects on neural development and impairment of serotonergic signaling in zebrafish larvae

The underlying mechanism of polybrominated diphenyl ether (PBDE)-induced neurotoxicity is still a major concern due to its ubiquitous nature and persistence. Here, zebrafish embryos (2 h postfertilization, hpf) were exposed to different concentrations of the commercial PBDE mixture DE-71 (0-100 µg l^-1 ) until 120 hpf, and the impact on neural development and serotonergic system was investigated. The in vivo results revealed significantly reduced transcription of genes involved in neurogenesis (fgf8, shha, wnt1), and contents of proteins in neuronal morphogenesis (myelin basic protein, synapsin IIa), suggesting an impairment of neural development in zebrafish embryos. Further results demonstrated a reduction of 5-hydroxytryptamine neuron and a dose-dependent decrease of whole-body serotonin levels, as well as the transcription of genes involved in serotonergic synthesis (tph1, tph2, trhr) and neurotransmission (serta/b, htr1aa/b). In addition, we predicted possible targets of PBDEs by molecular docking, and the results indicated that PBDE congeners showed high binding affinities with fibroblast growth factor 8 other than SHH and HTR1B. Taken together, this study demonstrated that PBDE exposure during embryogenesis could damage neural development and cause impairment of the serotonergic system as secondary effects in the zebrafish larvae. Copyright © 2016 John Wiley & Sons, Ltd.

Molecular docking and 3D-QSAR studies on the glucocorticoid receptor antagonistic activity of hydroxylated polychlorinated biphenyls

The glucocorticoid receptor (GR) antagonistic activities of hydroxylated polychlorinated biphenyls (HO-PCBs) were recently characterised. To further explore the interactions between HO-PCBs and the GR, and to elucidate structural characteristics that influence the GR antagonistic activity of HO-PCBs, molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed. Comparative molecular similarity indices analysis (CoMSIA) was performed using both ligand- and receptor-based alignment schemes. Results generated from the receptor-based model were found to be more satisfactory, with q(2) of 0.632 and r(2) of 0.931 compared with those from the ligand-based model. Some internal validation strategies (e.g. cross-validation analysis, bootstrapping analysis and Y-randomisation) and an external validation method were used respectively to further assess the stability and predictive ability of the derived model. Graphical interpretation of the model provided some insights into the structural features that affected the GR antagonistic activity of HO-PCBs. Molecular docking studies revealed that some key residues were critical for ligand-receptor interactions by forming hydrogen bonds (Glu540) and hydrophobic interactions with ligands (Ile539, Val543 and Trp577). Although CoMSIA sometimes depends on the alignment of the molecules, the information provided is beneficial for predicting the GR antagonistic activities of HO-PCB homologues and is helpful for understanding the binding mechanisms of HO-PCBs to GR.

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q(2)) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825-0.969 (>0.5), the correlation coefficient (r(2)) obtained was in the range of 0.957-1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070-0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3'-, 5- and 6- positions, which could reduce the PCB migration ability. These results are expected to be beneficial in predicting logKOA values of PCB homologues and derivatives and in providing a theoretical foundation for further elucidation of the global migration behaviour of PCBs.

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.