An in silico study on human carcinogenicity mechanism of polybrominated biphenyls exposure.

Polybrominated biphenyls (PBBs) are associated with an increased risk of thyroid cancer; however, relevant mechanistic studies are lacking. In this study, we investigated the mechanisms underlying PBB-induced human thyroid cancer. Molecular docking and molecular dynamics methods were employed to investigate the metabolism of PBBs by the cytochrome P450 enzyme under aryl hydrocarbon receptor mediation into mono- and di-hydroxylated metabolites. This was taken as the molecular initiation event. Subsequently, considering the interactions of PBBs and their metabolites with the thyroxine-binding globulin protein as key events, an adverse outcome pathway for thyroid cancer caused by PBBs exposure was constructed. Based on 2D quantitative structure activity relationship (2D-QSAR) models, the contribution of amino acid residues and binding energy were analyzed to understand the mechanism underlying human carcinogenicity (adverse effect) of PBBs. Hydrogen bond and van der Waals interactions were identified as key factors influencing the carcinogenic adverse outcome pathway of PBBs. Analysis of non-bonding forces revealed that PBBs and their hydroxylation products were predominantly bound to the thyroxine-binding globulin protein through hydrophobic and hydrogen bond interactions. The key amino acids involved in hydrophobic interactions were alanine 330, arginine 381 and lysine 270, and the key amino acids involved in hydrogen bond interactions were arginine 381 and lysine 270. This study provides valuable insights into the mechanisms underlying human health risk associated with PBBs exposure.

Risk mitigation strategy and mechanism analysis of neonicotinoid pesticides on earthworms.

Neonicotinoid insecticides (NNIs) are a new class of widely used insecticides with certain risks to non-target organisms, like earthworms. The gray correlation method was used to calculate the comprehensive risk effect value of acute toxicity (LC50) and bioaccumulation (logKow) of NNIs on earthworms. A comprehensive effects three-dimensional quantitative structure-activity relationship (3D-QSAR) model was constructed, using NNIs molecular structures and the comprehensive effect value as the independent and dependent variables, respectively. One of the representatives guadipyr (GUA) was selected as the template molecule for the molecular design and modification. A total of 63 NNIs alternatives were designed with a reduced comprehensive value higher than 10%, and as high as 42%. After screening, 15 NNIs alternatives were screened with decreased acute toxicity to earthworms, bioaccumulation effects and improved functional property. The calculated primary acute risk quotient of earthworms shows that the designed NNIs alternatives have lower earthworm risks (reduction of 70.48-99.99%). Results also found that the electronic, geometric and topological parameters of NNIs are the key descriptors that affect NNIs alternatives' toxicity. The number of hydrophobic interaction amino acid residues in NNIs molecules also contributes to the acute toxicity and the bioaccumulation of NNIs alternatives on earthworms. This study aims to design and screen functionally improved and environmentally friendly NNIs alternatives that have low risk to earthworms and provide theoretical methods and new ideas for the risk control and development of pesticides represented by NNIs.

In-silico analysis of atmospheric diffusion, crop planting degrading scheme, and health risk of dioxins from a domestic waste incineration plant.

Based on a domestic waste incineration power generation project, the dioxin emission from the waste incineration plant (WIP), phytoextraction and microbial degradation of dioxins, and dioxins human health risks reduction were investigated through in-silico methods. Based on the dioxins concentrations in soil (9.97 × 10-9-7.00 × 10-5ng/g) predicted by atmospheric dispersion model system and the Level-III fugacity model, planting schemes under different wind directions were designed considering the dioxin absorption capacity and the economic benefits for crops (i.e., barley, peanut, pea, maize and wheat). The dioxins in soils can be further degraded by five crops' rhizosphere microorganisms and fertilizers, simulated through molecular dynamic simulations. The enhanced degradation rates of dioxin by rhizosphere microorganisms of five crops reached 15.70 %-28.66 %. Finally, healthy dietary plans were developed to reduce the risk of dioxin exposure to the sensitive populations living around WIP. Results showed that the consumption of maize, fungus, mushroom and bamboo fungus could effectively reduce dioxins toxicity to humans by 58.13 %. The systematic approach developed in this study provided theoretical support for soil remediation and human health risk control of dioxins-contaminated sites.

A new perspective to improve the treatment of Lianhuaqingwen on COVID-19 and prevent the environmental health risk of medication.

Lianhuaqingwen (LH), one traditional Chinese medicine (TCM), has been used to treat the coronavirus disease 2019 (COVID-19), but its ecotoxicity with potential human health security has not been well investigated. To overcome such adverse effects and improve its medication efficacy, an intelligent multi-method integrated dietary scheme, screening, and performance evaluation approach was developed. Thirteen LH compounds were selected, and the main protease (Mpro) was used as the potential drug target. Resulted information showed that the more compounds of LH added, the higher medication efficacy obtained using multi-method integrated screening system, expert consultation method, and molecular dynamics simulation. Pharmacodynamic mechanism analysis showed that low total energy and polar surface area of LH active compound (i.e., ß-sitosterol) will contribute to the best therapeutic effect on COVID-19 using quantitative structure-activity relationships (QSAR) and sensitivity models. Additionally, when mild COVID-19 patients take LH with the optimum dietary scheme (i.e., ß-lactoglobulin, α-lactalbumin, vitamin A, vitamin B, vitamin C, carotene, and vitamin E), the medication efficacy were significantly improved (23.58%). Pharmacokinetics and toxicokinetics results showed that LH had certain human health risks and ecotoxicity. This study revealed the multi-compound interaction mechanism of LH treatment on COVID-19, and provided theoretical guidance for improving therapeutic effect, evaluating TCM safety, and preventing human health risk.

Human developmental toxicity mechanism of polybrominated biphenyl exposure and health risk regulation strategy for special populations.

Polybrominated biphenyls (PBBs) can bioaccumulate in nature and are toxic to humans. Long-time exposure to PBBs in pregnant women can lead to the birth of an infant with abnormal conditions. Hence, in this study, we used molecular docking, molecular dynamics, Taguchi experimental design, and fractional factorial experimental design to identify the developmental toxicity characteristics of 10 typical developmental toxic pollutants such as PBBs to which humans are frequently exposed. Furthermore, the correlation and sensitivity analyses of molecular developmental toxicity and structural parameters were performed. The molecular key structural parameters of the pollutants affecting human development were screened. Moreover, the supplementary food factors that could alleviate the developmental toxicity of pollutants were screened to develop supplementary food schemes to prevent or alleviate human developmental toxicity in the special population (e.g., pregnant women, infants) exposed to the pollutants. The results showed that the developmental toxicity was controlled by the main effects of the 10 pollutants. Among the 10 pollutants with developmental toxicity, the most significant pollutant with the main effects was PBB-153 (37.06%). In addition, the correlation and sensitivity analyses of the molecular developmental toxicity of the pollutants and structural parameters showed that the total energy value and infrared C-H vibration frequency of the pollutants were significantly correlated with human developmental toxicity. Accordingly, 15 supplementary food cofactors were selected for the Taguchi experiment design, among which the top seven cofactors were designed by fractional factorial analysis. The most significant cofactor that alleviated the developmental toxicity of PBB-153 exposure was the combination of carotene and docosahexaenoic acid (DHA), with an improvement of 17.28%. The combination of carotene and DHA significantly alleviated the effects of toxicity caused by most of the other pollutants, indicating that the selected supplementary food has certain universality. In this study, we developed a method to identify the characteristics of the developmental toxicity of pollutant exposure and developmental toxicity alleviation. Our study provided theoretical support for the regulation strategy of developmental toxicity caused by pollutants such as PBBs.

Establishment of a CoMFA Model Based on the Combined Activity of Bioconcentration, Long-Range Transport, and Highest Infrared Signal Intensity and Molecular Design of Environmentally Friendly PBB Derivatives.

In the current study, a comparative molecular field analysis (CoMFA) model with the combined activity of polybrominated biphenyls (PBBs) bioconcentration, long-range transport, and the highest infrared signal intensity (weight ratio of 5:4:1) was constructed based on the threshold method and was further evaluated and analyzed. PBB-153 derivatives with improved combined activity values of bioconcentration, long-range transport, and the highest infrared signals intensity were designed based on contour maps of the CoMFA model. The environmental stability and functionality of the derivatives were also evaluated. The constructed model showed good prediction ability, fitting ability, stability, and external prediction ability. The contribution rates of electrostatic and steric fields to the combined activity of PBBs were 53.4% and 46.6%, respectively. Four PBB-153 derivatives with significantly improved bioconcentration, long-range transport and the highest infrared signal intensity (the combined activity value of these three parameters decreased) were screened with good environmental stability and functionality. Results validated the accuracy and reliability, and ability of the generated model to realize the simultaneous modification of the three activities of the target molecule. The binding ability of the designed derivatives to food chain biodegradation enzymes increased, thereby verifying the improvement in the bioconcentration. The half-lives of the derivatives in air and their ability to be absorbed by the plants significantly improved compared to the target molecule, further showing that the long-range transport of derivatives was reduced. In addition, the introduction of the -NO group caused the N =O stretching vibration of the derivatives to increase the infrared signal intensity. The present model provides a theoretical design method for the molecular modification of environmentally friendly PBBs.

Optimal Allocation of Water Resources and Eco-Compensation Mechanism Model Based on the Interval-Fuzzy Two-Stage Stochastic Programming Method for Tingjiang River.

In this work, based on the upper line of water resources utilization and the bottom line of water environmental quality of "Three Lines, Single Project", a fuzzy optimization method was introduced into the Tingjiang River water resources optimal allocation and eco-compensation mechanism model, which is based on the interval two-stage (ITS) stochastic programming method. In addition, a Tingjiang River water resources allocation and eco-compensation mechanism model based on the interval fuzzy two-stage (IFTS) optimization method was also constructed. The objective functions of both models were to maximize the economic benefits of the Tingjiang River. The available water resources in the basin, the water environmental quality requirements, and regional development requirements were used as constraints, and under the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance, the water resources allocation plan of various sectors (industry, municipal, agriculture, and ecology) in the Tingjiang River was optimized, and an eco-compensation mechanism was developed. In this work, the uncertainty of the maximum available water resources in each region and the whole basin was considered. If the maximum available water resources were too high, it would lead to a large waste of water resources, whereas if the maximum available water resources were too low, regional economic development would be limited. Therefore, the above two parameters were set as fuzzy parameters in the optimization model construction in this work. The simulation results from the IFTS model showed that the amount of water available in the river basin directly affects the water usage by various departments, thereby affecting the economic benefits of the river basin and the amount of eco-compensation paid by the downstream areas. The average economic benefit of the Tingjiang River after the optimization of the IFTS model simulation was [3868.51, 5748.99] × 108 CNY, which is an increase of [1.67%, 51.9%] compared to the economic benefit of the basin announced by the government in 2018. Compared to the ITS model, the economic benefit interval of the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance was reduced by 28.54%, 44.9%, 31.49%, 40.37%, and 36.43%, respectively, which can improve the economic benefits of the basin and provide more accurate decision-making schemes. In addition, the IFTS simulation showed that the eco-compensation quota paid by downstream Guangdong Province to upstream Fujian Province is [28,116.4, 30,738.6] × 104 CNY, which is a reduction of [8461.404, 110,836] × 104 CNY compared to the 2018 compensation scheme of the government. Compared to the ITS model, the range of eco-compensation values was observed to increase by 9.94%, 54.81%, 15.85%, 50.31%, and 82.90%, respectively, under the five hydrological scenarios, which reduces the burden of ecological expenditure downstream and provides a broader decision-making space for decision-makers and thus enables improved decision-making efficiency. At the same time, after the optimization of the IFTS model, the additional water consumption of the second stage of the Tingjiang River during the extremely dry year decreased by 62.11% compared to the results of the ITS model. The additional water consumption of the industrial sector decreased by 68.39%, the municipal sector decreased by 59.27%, and in the first phase of water resources allocation for 14 districts and counties in the Tingjiang River, industrial and municipal sectors are the main two sectors. After introducing the fuzzy method into the IFTS model, the difference in the water consumption by these two sectors in the basin under different hydrological scenarios can be alleviated, and the waste of water resources caused by too low water allocation or excessive water allocation can be avoided. The national and local (the downstream region) eco-compensation quotas can be indirectly reduced, and the risk of water resources allocation and eco-compensation decision-making in the basin can be effectively reduced.

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.

A novel pharmacophore model on PAEs' estrogen and thyroid hormone activities using the TOPSIS and its application in molecule modification.

In the proposed model, the estrogen activity values and thyroid hormone activity values of PAEs molecules were normalized using the TOPSIS method by eliminating the dimension coefficients, and the comprehensive activity values of estrogen and thyroid hormone were obtained by analyzing the activity of each hormone and assigning the corresponding weight. The five pharmacophore models of hormone combined activity were constructed using the comprehensive activity values. Hypol 1 was the optimal pharmacophore model, showing good predictive power and significance. Then, the DBP, DNOP, and DMP molecules in environmental priority control pollutants were selected as the target molecules to perform common substitution reactions of hydrogen bond donor. Eleven PAEs derivative molecules with significantly reduced combined activity and single activity were screened. In analysis of the differences before and after modification of the docking parameters and amino acid residues before and after modification of PAEs and their derivatives, the reduced closeness between ligand and receptor leads to the decrease of thyroid hormones and estrogen activities. Moreover, the establishment of the models, not only shows that the PAEs hormone activity has certain linear relationships with the physical parameters of molecules but also shows that thyroid hormone activity and estrogen activity of PAEs is consistent with the hormone combined activity. The results confirmed the feasibility of the modified PAEs modification scheme with reduced combined activities of hormones, providing an important theoretical method for the construction of the pharmacophore model of combined activities of hormones and the study of PAEs derivative molecules.

A Double-Activity (Green Algae Toxicity and Bacterial Genotoxicity) 3D-QSAR Model Based on the Comprehensive Index Method and Its Application in Fluoroquinolones' Modification.

The comparative molecular similarity index analysis (CoMSIA) model of double-activity quinolones targeting green algae toxicity and bacterial genotoxicity (8:2) was constructed in this paper on the basis of the comprehensive index method. The contour maps of the model were analyzed for molecular modifications with high toxicities. In the CoMSIA model, the optimum number of components n was 7, the cross-validated q2 value was 0.58 (>0.5), the standard deviation standard error of estimate (SEE) was 0.02 (<0.95), F was 1265.33, and the non-cross-validated R2 value was 1 (>0.9), indicating that the model had a good fit and predicting ability. The scrambling stability test parameters Q2, cross-validated standard error of prediction (cSDEP), and dq2/dr2yy were 0.54, 0.25, and 0.8 (<1.2), respectively, indicating that the model had good stability. The external verification coefficient r2pred was 0.73 (>0.6), and standard error of prediction (SEP) was 0.17, indicating that the model had a good external prediction ability. The contribution rates of the steric fields, electrostatic fields, hydrophobic fields, hydrogen bond donor, and acceptor fields were 10.9%, 19.8%, 32.7%, 13.8%, and 22.8%, respectively. Large volume groups were selected for modification of ciprofloxacin (CIP), and the derivatives with increased double-activity characterization values were screened; the increase ratio ranged from 12.31-19.09%. The frequency of derivatives were positive and total energy, bioaccumulation, and environmental persistence was reduced, indicating that the CIP derivatives had good environmental stability and friendliness. Predicted values and CoMSIA model constructed of single activities showed that the CoMSIA model of double activities had accuracy and reliability. In addition, the total scores of the derivatives docking with the D1 protein, ferredoxin-NADP (H) reductases (FNRs), and DNA gyrase increased, indicating that derivatives can be toxic to green algae by affecting the photosynthesis of green algae. The mechanism behind the bactericidal effect was also explained from a molecular perspective.