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Abstract: The individual toxicities of Cu and 11 nitroaromatic compounds to Photobacterium phosphoreum were determined. The toxicity was expressed as the concentrations causing a 50% inhibition of bioluminescence after 15min exposure (IC50). To evaluate the joint effect between the metal ion and the 11 nitroaromatic compounds, the joint toxicity of Cu and 11 nitroaromatic compounds were measured at different Cu concentrations (0.2IC50, 0.5IC50 and 0.8IC50), respectively. The result shows that the binary joint effect between Cu and nitroaromatic compounds is mainly simple addition at the low Cu concentration (0.2IC50). However, an antagonism effect, 55% and 64%, was observed between Cu and 11 nitroaromatic compounds for Cu at medium and high concentrations (0.5IC50 and 0.8IC50). Quantitative structure–activity relationship (QSAR) analysis was performed to study the joint toxicity for the 11 nitroaromatic compounds. The result shows that the toxicity of nitroaromatic compounds is related to descriptors of Connolly solvent-excluded volume (CSEV) and dipolarity/polarizability (S) at low Cu concentration. On the other hand, the toxicity is related to Connolly accessible area (CAA) at medium and high Cu concentrations. The result indicates that different QSAR models on complex mixtures need to be developed to assess the ecological risk in real environments. Using single toxic data to evaluate the toxic effect of mixtures may result in wrong conclusions. [Copyright &y& Elsevier]

Quantitative structure-activity relationships (OSARs) for the toxicity of substituted phenols, anilines and nitrobenzenes to algae (Scenedesmus obliquus) have been studied. Chemicals were divided into polar narcotics and electrophiles based on structure criteria according to the toxicity mechanisms of action. A good relationship between the toxicity and octanol/water partition coefficient (logP) was observed for the polar narcotic compounds. The results confirmed that hydrophobicity is the determining physicochemical parameter in modelling narcotics. However, no statistically significant mono-parametric QSAR models could be made from descriptors calculated in this study for all the compounds. In order to investigate the mechanisms of toxic action and develop OSAR models for all compounds, Abraham solvation descriptors were calculated from the program of Pharma-Algorithms. Stepwise regression produced a three-parameter QSAR model (polarizability/dipolarity, hydrogen-bond basicity and molecular volume) with a good statistical fit for all the compounds studied, which had square of the correlation coefficient R²=0.83. We have also developed an interpretable QSAR model by using parameter of logP, which represents the bio-uptake process, and polarizability/dipolarity (8), which represents the irteraction of chemicals with the acceptor micromolecules (target receptor) at the active site. No hydrogen-bond interaction was observed between the chemicals and receptor micromolecules. [ABSTRACT FROM AUTHOR]

Cellular exposure to xenobiotic human-made products will lead to oxidative stress that gives rise to DNA damage, as well as chemical or mechanical damage. Distinguishing the chemicals that will induce oxidative stress and predicting their toxicity is necessary. In the present study, 4270 compounds in the ARE- bla assay were investigated to predict active and inactive compounds by using simple algorithms, namely, recursive partitioning (RP) and binomial logistic regression, and to develop the quantitative structure–activity relationship (QSAR) models of chemicals that activate the ARE pathway to induce oxidative stress and exert toxic effects on cells. A decision tree based on scaffold-based fragments obtained through RP analysis showed the best identification accuracy. However, the overall identification accuracy of this model for active compounds was unsatisfactory due to limited fragments. Furthermore, a binomial logistic regression model was developed from 638 active compounds and 3632 inactive chemicals. The model with a cutoff of 0.15 could predict chemicals that were active or inactive with the prediction accuracy of 69.1%. Its area under the receiver operating characteristic (ROC) curve metric (AUROC) was 0.762, which indicated the acceptable predictive ability of this model. The parameters nBM (number of multiple bonds) and H% (percentage of H atom) played dominant roles in the prediction of the activity (inactive or active) of chemicals. A global QSAR model was developed to predict the toxicity of active chemicals. However, the model displayed an unsatisfactory result with R 2 = 0.316 and R 2 ext = 0.090. Active chemicals were then classified on the basis of structure. A total of 79 compounds with carbon chains could be predicted with acceptable performance by using a QSAR model with six descriptors (R 2 = 0.722, R 2 ext = 0.798, Q 2 Loo = 0.654, Q 2 Boot = 0.755, Q 2 ext = 0.721). The simple models established here contribute to efforts on identification compounds inducing oxidative stress and provide the scientific basis for risk assessment to organisms in the environment. • Simple algorithms are applied to identify chemicals causing oxidative stress. • Binomial logistic regression model can predict active and inactive compounds. • A linear model on active compounds with carbon chains is established. • The structural factors of compounds ascribing to oxidative stress are discussed. [ABSTRACT FROM AUTHOR]

Abstract The hydrated electron (e aq −)-based reduction processes are promising for removing organic pollutants in water engineering systems. The reductive kinetics, especially the second order rate constants ( k e aq − ) of e aq − with organic compounds, is important for evaluating and modeling the advanced reduction processes. In this study, the k e aq − values for aliphatic compounds and phenyl-based compounds are, for the first time, modeled by the quantitative structure-activity relationship (QSAR) method. The structural features governing the reactivity of two classes of organic compounds toward e aq − were revealed, and the energy of the lowest unoccupied molecular orbital (E LUMO) , one-electron reduction potential (E RED) and polarizability (α) were found to be the important molecular parameters in both two models. The built QSAR models provide robust predictive tools for estimating the removal of emerging pollutants using e aq − during wastewater treatment processes. Additionally, quantum chemical calculations were employed to probe into the mechanism and feasibility of the single electron transfer (SET) pathway in the e aq −-based reduction process. The thermodynamic investigation suggests that the compounds with electron-withdrawing groups tend to possess higher k e aq − and lower Gibbs free energy (Δ G SET) and Gibbs free energies of activation (∆ ‡ G SET ∘) than the ones with electron-donating groups, indicating the SET process occurs more readily. It is also found that the refractory halogenated compounds can achieve dehalogenation via the SET pathway. Graphical abstract Image 1 Highlights • We developed QSAR models to predict e aq − reaction rate constants ( k e aq − ). • E LUMO is the most important molecular parameter governing the reactivity with e aq −. • Compounds with electron withdrawing groups possess higher reactivities with e aq −. • Compounds with electron withdrawing groups have lower Δ ‡ G S E T ° , Δ G SET and Δ H SET. [ABSTRACT FROM AUTHOR]

Insecticides are widely used in crop protection against insects and frequently detected in aquatic environment. Photolysis kinetics are directly related with exposure assessment and risk assessment. However, the photolysis mechanism of neonicotinoid insecticides with different structures has not been studied and compared systematically in the literature. In this paper, the photolysis rate constants in water were determined for eleven insecticides under irradiation of simulated sunlight. At the same time, the photolysis mechanism and effect of dissolved organic matter (DOM) on their photolysis were studied. The results showed that photolysis rates of eleven insecticides vary in a large range. The photolysis rates of nitro-substituted neonicotinoids and butenolide insecticide are much faster than that of cyanoimino-substituted neonicotinoids and sulfoximine insecticide. The ROS scavenging activity assays reveal that direct photolysis dominates the degradation of seven insecticides and, on the other hand, self-sensitized photolysis dominates four insecticides. The shading-effect from DOM can reduce the direct photolysis rates, on the other hand, ROSs generated by triplet-state DOM (3DOM*) can also accelerate photolysis of insecticides. According to the photolytic products identified from HPLC-MS, these eleven insecticides have different photolysis pathways. Six insecticides are degraded from the removal of nitro group from their parent compounds and four insecticides are degraded through ·OH reaction or singlet oxygen (1O 2) reaction. QSAR (quantitative structure-activity relationship) analysis showed that photolysis rate was directly related to the energy gap between the highest occupied molecular orbital to the lowest unfilled molecular orbital (E gap = E LUMO − E HOMO) and dipole moment (δ). These two descriptors reflect the chemical stability and reactivity of insecticides. The pathways developed from identified products and the molecular descriptors of QSAR models can well verify the photolysis mechanisms of eleven insecticides. [Display omitted] • The photolysis rate constants have been measured for eleven neonicotinoid insecticides. • The direct photolysis dominates the degradation of seven out of eleven insecticides. • Addition of ROS scavengers can significantly decrease photolysis rates of four insecticides. • Photolysis mechanisms have been verified from the photolysis pathways for eleven insecticides. • QSAR models reflect the photolysis mechanisms of eleven insecticides. [ABSTRACT FROM AUTHOR]

• A significant interspecies correlation equation has been developed between tadpole and worm toxicities. • A theoretical equation has been developed to explain the QSAR models. • Insecticides and fungicides can be classified as specifically-acting compounds to both tadpoles and worms. • Worms are more sensitive than tadpoles for reactive compounds because of their polar property. • Ionic compounds exhibit low toxicity to tadpoles and worms because of their poor bio-uptake potential. Insecticides, fungicides, dinitrobenzenes, resorcinols, phenols and anilines are widely used in agricultural and industrial productions. However, their modes of toxic action are unclear in some nontarget organisms, such as worms and tadpoles. In this study, acute toxicity data was experimentally collected for Limnodrilus hoffmeisteri worms and Rana chensinensis tadpoles, respectively. Interspecies correlation and excess toxicity were calculated to determine modes of action (MOAs) between the two species for class-based compounds. The result showed that, although the interspecies correlation of toxicity between the tadpoles and worms is significant with a coefficient of determination (R2) of 0.83, tadpoles are more sensitive than the worms and toxicity values between these two species are not identical with an overall 0.43 log unit difference. Regression analysis revealed that the toxicity of nonpolar narcotics or baseline compounds is linearly related to hydrophobicity for both the tadpoles and worms and the two baseline models are parallel, suggesting that these nonpolar narcotics share the same MOA between the two species. The difference of baseline toxicities between the two species is attributed to differences in bioconcentration factors. Analysis of the excess toxicity calculated from the toxicity ratio (TR) suggested that phenols and anilines can be classified as polar narcotics, not only to fish, but also to the tadpoles and worms. These compounds are more toxic than the baseline compounds and quantitative structure-activity relationship (QSAR) models show that their toxicity is linearly related to chemical hydrophobicity and polarity. Analysis of the excess toxicity reveals that aminophenols and resorcinols can be classified as reactive compounds, and insecticides and fungicides can be classified as specifically-acting compounds for both species. These compounds exhibited significantly greater toxic effect to both the tadpoles and worms. QSAR models have been developed to describe the toxic mechanisms for nonpolar narcotics, polar narcotics, reactive chemicals and specifically-acting compounds, and a theoretical equation has been derived to explain the effect of bio-uptake and interaction of the chemical with target receptors for both tadpole and worm toxicity. Our study reveals that tadpole toxicity can be estimated from worm toxicity data and the two species can serve as surrogates for each other in the safety evaluation of organic pollutants. [ABSTRACT FROM AUTHOR]

Mitochondria are significant targets in cells for many environmental chemicals. Mitochondrial damage and dysfunction can lead to apoptosis and death of fish. The objectives of this study were to compare the modes of action (MOAs) between fish, cell and mitochondrial toxicity. To achieve the goal, toxicity correlation, excess toxicity and quantitative structure–activity relationship (QSAR) were investigated between these three toxicity endpoints for a wide range of compounds. Results showed that fish toxicity is well correlated to cytotoxicity, but overall fish toxicity is relatively greater than the cytotoxicity. On the other hand, fish or cell toxicity is poorly related to mitochondrial toxicity, suggesting some compounds share same toxic mechanism but some not. The excess toxicity calculated from toxicity ratio (TR) shows that specifically-acting compounds in cytotoxicity, such as insecticides, fungicides, herbicides, dyes and medications used to treat cancer, depression, heart failure and blood pressure, are active compounds in mitochondrial toxicity. However, the less inert compounds identified in fish and cell toxicity exhibit greatly mitochondrial toxicity. QSAR models reveal that fish or cell toxicity is closely related to the chemical hydrophobicity, ionization, energy of lowest unoccupied molecular orbital, hydrogen bonding potential and stability. These descriptors reflect chemical bio-uptake, reactivity and interaction with target receptors. On the other hand, binomial model reveals that mitochondrial toxicity is closely related to the chemical hydrophobicity and polarizability/dipolarity, indicating bio-uptake and Van der Waals interaction play key roles in mitochondrial toxicity. Theoretical equations have been used to explain the toxicity correlation, excess toxicity and QSAR for fish, cell and mitochondrial toxicity. Above results suggest that cytotoxicity can serve as a surrogate for fish toxicity and be used in the safety evaluation of organic pollutants in aqueous environment, but not mitochondrial toxicity, although some compounds share same modes of action between fish or cell toxicity and mitochondrial toxicity. [Display omitted] • Fish toxicity is closely related to cytotoxicity, but not mitochondrial toxicity. • QSAR or binomial models are developed for fish, cell and mitochondrial toxicity. • Many pesticides and medications exhibit excess toxicity to fish, cell and mitochondria. • Phenols and anilines exhibit significant toxicity to mitochondria, but not to fish and cells. • Theoretical equations can well explain toxicity correlation, excess toxicity and QSAR. [ABSTRACT FROM AUTHOR]