Relationship between the binding free energy and PCBs' migration, persistence, toxicity and bioaccumulation using a combination of the molecular docking method and 3D-QSAR

Polychlorinated biphenyl congeners in water canals and their relationships with water quality parameters: Insights into their risk assessment

Water pollution with pesticides is one of the most important environmental problems. Polychlorinated biphenyls (PCBs) reach water bodies via agricultural discharge. The aim of this study was to determine the contamination of different water bodies with PCB congeners, and detect the correlation between water quality parameters and seasonal distribution of these PCBs. The results indicated that water canals of AlGharbiah showed the highest ranges of temperature, total dissolved solids (TDS) in spring, and dissolved oxygen (DO) in autumn, while AlQaliobiah water bodies witnessed the highest pH and electrical conductivity (EC) ranges in summer. The highest range of a PCB congener was that of PCB44 (7.96-118.29 µg/g) in sediment samples of Giza, followed by its range (18.01-85.44 µgL-1) in surface water of AlQaliobiah. We found a potential cancer risk from dermal contact with all the investigated PCBs. Principal component analysis (PCA) showed positive correlations between most PCBs and each of EC and TDS, and a negative correlation with DO. While the correlation between PCBs and each of temperature and pH varied according to the geographic location of the governorate. In conclusion, the investigated water canals were contaminated with PCBs, which posed a potential cancer risk and deteriorated water quality.

Paradox of 'ideal correlations': improved model for air half-life of persistent organic pollutants

The persistence of organic pollutants is an important environmental property due to the extended possibility to have an impact of corresponding substances. In many cases, the experimental values of the thousands of contaminants are missing. The object of the study is novel computational modelling for air pollutions. Quantitative structure-property relationship (QSPR) for air half-life has been built using the Monte Carlo method with applying the index of ideality of correlation (IIC). The basis of the predictive model of air half-life is the representation of the molecular structure by simplifying molecular input-line entry system (SMILES) and numerical data on the above endpoint (expressed by hours) converted to a decimal logarithm. The statistical quality of the model has been checked up with different validation metrics and is quite good. Paradoxically, the improvement of the statistical quality via the IIC for the validation set is done in detriment to the training set. The new model has performed better than those obtained previously on the same set of compounds, for the prediction of new compounds in the validation set. Some semi-quantitative indicators for the mechanistic interpretation of the model are suggested.

Functional modification of HHCB: Strategy for obtaining environmentally friendly derivatives

Galaxolide (HHCB), one of the most widely used synthetic musks in personal care products (PCPs), has been recognized as an emerging contaminant with potential human health concerns. To overcome such adverse effects, a systematic molecular design, screening and performance evaluation approach was developed to generate functionally improved and environmentally friendly HHCB derivatives. Among the 90 designed HHCB derivatives, 15 were screened with improved functional properties (i.e., odor stability and intensity) and less environmental impacts (i.e., lower bio-toxicity, bio-accumulation ability, and mobility) using 3D-QSAR models and density functional theory methods. Their human health risks were then assessed by toxicokinetic analysis, which narrowed the candidates to four. Derivative 7, the designed molecule with the least dermal adsorption potential, was evaluated for its interaction with other PCPs additives (i.e., anti-photosensitivity materials and moisturizer) and such impacts on human health risks using molecular docking and molecular dynamic simulation. The environmental fate of Derivative 7 after transformation (i.e., photodegradation, biotransformation, and chlorination) was also discussed. Biotransformation and chlorination were recognized as optimum options for Derivative 7 mitigation. This study provided the theoretical basis for the design of functionally improved and environmentally friendly HHCB alternatives and advanced the understanding of their environmental behaviors and health risks.

The challenge of micropollutants in surface water of the Yangtze River

The Yangtze River, the third largest river and supporting nearly one-third of Chinese population, has been severely polluted in recent decades. Among the numerous pollutants, organic micropollutants, as one kind of important emerging contaminants, are currently key contaminants of concern. However, few studies have focused on their mixture environmental impacts, especially for the complex environmental mixtures. In the current study, four categories of organic micropollutants, including 16 polycyclic aromatic hydrocarbons (PAHs), 32 polychlorinated biphenyls (PCBs), 27 organochlorine pesticides (OCPs) and 20 pharmaceutical and personal care products (PPCPs) are analyzed in 10 study sites on the Yangtze River. Subsequently, comprehensive risk assessment for micropollutant mixtures was conducted by risk quotient based on the sum of PEC/PNEC values (RQ_MEC/PNEC) and risk quotient based on the toxic units (RQ_STU). The mixture risk evaluation based on the detected environmental concentrations indicates that micropollutant mixtures in surface water of the Yangtze River exhibited relative high risks for aquatic organisms. The observed results revealed that mixture risk assessments have to consider the complexity of environmental samples; PCBs dominated main mixture risks in the upper stream; PAHs contributed major comprehensive risks in the middle stream; and OCPs were the key micropollutants in the downstream. The outcomes of the present study here can serve for pollution control in the Yangtze River, which provide the scientific underpinnings and regulatory reference for risk management and river protection.

Toward a Computational Ecotoxicity Assay

Thousands of anthropogenic chemicals are released into the environment each year, posing potential hazards to human and environmental health. Toxic chemicals may cause a variety of adverse health effects, triggering immediate symptoms or delayed effects over longer periods of time. It is thus crucial to develop methods that can rapidly screen and predict the toxicity of chemicals to limit the potential harmful impacts of chemical pollutants. Computational methods are being increasingly used in toxicity predictions. Here, the method of molecular docking is assessed for screening potential toxicity of a variety of xenobiotic compounds, including pesticides, pharmaceuticals, pollutants, and toxins derived from the chemical industry. The method predicts the binding energy of pollutants to a set of carefully selected receptors under the assumption that toxicity in many cases is related to interference with biochemical pathways. The strength of the applied method lies in its rapid generation of interaction maps between potential toxins and the targeted enzymes, which could quickly yield molecular-level information and insight into potential perturbation pathways, aiding in the prioritization of chemicals for further tests. Two scoring functions are compared: Autodock Vina and the machine-learning scoring function RF-Score-VS. The results are promising, although hampered by the accuracy of the scoring functions. The strengths and weaknesses of the docking protocol are discussed, as well as future directions for improving the accuracy for the purpose of toxicity predictions.

Degradation mechanism of biphenyl and 4-4'-dichlorobiphenyl cis-dihydroxylation by non-heme 2,3 dioxygenases BphA: A QM/MM approach

Biphenyl 2,3-dioxygenase (BphA), a Rieske-type and first enzyme in the aerobic degradation process, plays a key role in the metabolizing process of biphenyl/polychlorinated biphenyl aromatic pollutants in the environment. To understand the catalytic mechanism of biphenyl 2,3-dioxygenase, the conversions leading to the cis-diols are investigated by means of quantum mechanics/molecular mechanics (QM/MM) method. A hydroperoxo-iron (III) species is involved in the enzyme-catalyzed reaction. Herein, we explored the direct reaction mechanism of hydroperoxo-iron (III) species with biphenyl and 4-4'-dichlorobiphenyl. The reaction process involves an epoxide intermediate, it could develop into a carbocation intermediate, and ultimately evolve into a cis-diol product. The important roles of several residues during the dioxygenation process were highlighted. This study may provide theoretical support for further directed mutations and enzymatic engineering of BphA, as well as promote the development of degrading environmentally persistent biphenyl/polychlorinated biphenyl aromatic contaminants.