QSARs for congener-specific toxicity of polyhalogenated dibenzo-p-dioxins with DFT and WHIM theory

Molecular Polarization Potential as a Molecular Descriptor to Predict Biological Activity of Dioxins and Dibenzofurans

Molecular interaction potential (MIP) maps are a powerful tool to develop structure-activity relationships of a series of compounds. In the present study we have studied the effect of molecular polarization on the description of the toxicity of a series of dioxins and benzofurans using their MIPs. Specifically, we have used principal component analysis in an exploratory way to understand the common structural features that describe the toxicity of these molecules through the analysis of their MIPs and each of their components, i.e.; molecular electrostatic and polarization potentials. Moreover, we have developed a predictive model using PLS that permits to evaluate the toxicity of compounds belonging to any of the families of compounds studied in the present work on the basis of their molecular electrostatic and interaction potentials.

Comparative antioxidant status in freshwater fish Carassius auratus exposed to eight imidazolium bromide ionic liquids: a combined experimental and theoretical study

Imidazolium bromide ionic liquids such as 1-alkyl-3-methylimidazolium bromides ([AMIm]Br) and 1-alkyl-2,3-dimethylimidazolium bromides ([AMMIm]Br) are common-use organic salts. However, data on comparative toxicological effects of these ILs are lacking for fish. In this study, a combined experimental and theoretical approach was applied to compare and analyze the effects of these ILs on biochemical biomarkers in liver of Carassius auratus treated with different concentrations (2 and 20mg/L) for 3 and 16d. Changes in the activities of superoxide dismutase, catalase, glutathione peroxidase, and in the levels of reduced glutathione and malondialdehyde were detected, indicating that these ILs exhibit potential biotoxicity. The integrated biomarker response (IBR) index suggested that 1-hexyl-3-methylimidazolium bromide ([HMIm]Br), 1-octyl-3-methylimidazolium bromide ([OMIm]Br), 1-hexyl-2,3-dimethylimidazolium bromide ([HMMIm]Br), and 1-octyl-2,3-dimethylimidazolium bromide ([OMMIm]Br) showed the highest biotoxicity under different concentrations or exposure time, while 1-ethyl-3-methylimidazolium bromide ([EMIm]Br) always showed the least stressful power towards the test organism. Quantum chemical calculations (electronic parameters, frontier molecular orbitals, and Wiberg bond order) were also conducted to interpret the experimental results. Notably, some descriptors were correlated with the toxicity order. In addition, theoretical calculations provided some valuable information on metabolic pathways of these ILs, which may help to get better understanding on their environmental behavior and fate. In general, the toxicological determination and analysis of these ILs were performed with a combined experimental and theoretical method, which may contribute to the future ecotoxicological studies.

Complementary PLS and KNN algorithms for improved 3D-QSDAR consensus modeling of AhR binding

Multiple validation techniques (Y-scrambling, complete training/test set randomization, determination of the dependence of R2test on the number of randomization cycles, etc.) aimed to improve the reliability of the modeling process were utilized and their effect on the statistical parameters of the models was evaluated. A consensus partial least squares (PLS)-similarity based k-nearest neighbors (KNN) model utilizing 3D-SDAR (three dimensional spectral data-activity relationship) fingerprint descriptors for prediction of the log(1/EC50) values of a dataset of 94 aryl hydrocarbon receptor binders was developed. This consensus model was constructed from a PLS model utilizing 10 ppm x 10 ppm x 0.5 Å bins and 7 latent variables (R2test of 0.617), and a KNN model using 2 ppm x 2 ppm x 0.5 Å bins and 6 neighbors (R2test of 0.622). Compared to individual models, improvement in predictive performance of approximately 10.5% (R2test of 0.685) was observed. Further experiments indicated that this improvement is likely an outcome of the complementarity of the information contained in 3D-SDAR matrices of different granularity. For similarly sized data sets of Aryl hydrocarbon (AhR) binders the consensus KNN and PLS models compare favorably to earlier reports. The ability of 3D-QSDAR (three dimensional quantitative spectral data-activity relationship) to provide structural interpretation was illustrated by a projection of the most frequently occurring bins on the standard coordinate space, thus allowing identification of structural features related to toxicity.

Toxicity assessment on three direct dyes (D-BLL, D-GLN, D-3RNL) using oxidative stress bioassay and quantum parameter calculation

Textile dyes and dye industrial effluents are widely known for esthetic and toxicity problems. The toxicity of three direct dyes, Direct Blending Rebine (D-BLL), Direct Blending Scarlet (D-GLN), and Direct Blending Yellow (D-3RNL), were examined by the antioxidase and lipid peroxide index. Fish (Carassius auratus) were exposed to 100mg/L test compounds or injected with 200μg/kg corresponding dyes, and then samples of liver were collected at different times (0.5, 1, 3, 5, 7, 10, 13, 17 and 22d ) for analysis of superoxide dismutase (SOD), catalase (CAT), and contents of malondialdehyde (MDA). There is an obvious difference between two poisoning conditions and results indicated injection pattern have a more sensitive response. Besides, SOD, CAT and MDA levels displayed different variation trend following the prolonged duration, implying that dye metabolism generated less toxic or more active substance. The comparison among their intensity of enzyme inhibition showed that the toxicity order is D-BLL>D-GLN>D-3RNL. Additionally, three direct dye molecules were optimized based on the quantum mechanical charge density of a solute molecule interacting with a continuum description of the solvent (SMD) of Self-consistent Reaction Field Theory (SCRF) on B3LYP/LAN2BM level and the stable configurations were obtained. Wiberg bond orders were analyzed and atom in molecule (AIM) 2000 program was employed to estimate the interaction between atoms. The possible degradation pathways and toxicities were speculated based on the computations. The calculation is consistent with the experimental results and analysis.

A DFT-based QSAR study of the toxicity of quaternary ammonium compounds on Chlorella vulgaris

The DFT-based descriptors were used to derive the quantitative structure-activity relationship (QSAR) models enabling the calculated quantum chemistry parameters to be correlated to the toxicity of quaternary ammonium compounds (QACs) on green alga Chlorella vulgaris. DFT/B3LYP level of theory with the 6-31G(d) basis set was applied to calculate a set of quantum chemistry descriptors for 11 QACs. The partial least squares (PLS) analysis implemented in Simca-P was employed to obtain the QSAR models. The optimal PLS model with the cumulative cross-validated regression coefficient (Q(cum)(2)=0.893) and the correlation coefficient between observed values and fitted values (R=0.975) explained 95.3% of the variance of the independent variables and 92.8% of the variance of the dependent variable. The results of this investigation show that alkyl chain lengths (CL), polarizability tense (alpha(zz)), the most positive net atomic charges on a hydrogen atom (q(H)(+)) and entropy (S(o)) are the major descriptors in governing the log(1/EC(50)) values of the QACs.