QSARs for the toxicity of polychlorinated dibenzofurans through DFT-calculated descriptors of polarizabilities, hyperpolarizabilities and hyper-order electric moments (original) (raw)
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Toxicity analysis of polychlorinated dibenzofurans through global and local electrophilicities
2006
Toxicity of polychlorinated dibenzofurans are correlated with global and local electrophilicities calculated through DFT/6-31G(d) method with B3LYP functionals using both Mulliken and Hirshfeld population analysis schemes. An excellent correlation is observed between the experimental binding affinity values of 31 polychlorinated dibenzofurans with AhR receptors and a linear combination of global and local electrophilicity values. Motivation. To verify the importance of global and local electrophilicities in analyzing toxicity within a QSAR parlance. Method. Calculation ω and + k ω of 31 polychlorinated dibenzofurans using Becke's three parameter hybrid density functional, B3LYP, with 6-31G(d) basis set and Mulliken and Hirshfeld population analysis schemes. Results. A linear relation between the experimental binding affinities (50 pIC) of polychlorinated biphenyls with biosystems and a linear combination of global and local electrophilicity values is observed. Conclusions. The global and local electrophilicities together can explain the toxicities of polychlorinated dibenzofurans. The beautiful correlation between the binding affinity of these toxins with biosystems and a linear combination of global and local electrophilicity values confirms the importance of charge transfer in analyzing the origin of toxicity.
Density Functional Theory (B3LYP/6-31G*) Study of Toxicity of Polychlorinated Dibenzofurans
International Journal of Computational and Theoretical Chemistry, 2017
Quantitative Structure Toxicity Relationship (QSTR) study was applied to a dataset of 35 polychlorinated dibenzofurans (PCDFs) to investigate the relationship between toxicities of the compounds and their structures by employing Density Functional Theory (DFT) (B3LYP/6-31G*) method to compute their quantum molecular descriptors. The model was built using Genetic Function Algorithm (GFA) approach. The model (N= 24, Friedman LOF = 0.361, squared correlation coefficient (R 2) = 0.963, R 2 adj = 0.955, cross-validation correlation coefficient (Q 2) = 0.889, external prediction ability (R 2 pred) = 0.8286, P-value of optimization at P 95% ˂ 0.05) of the best statistical significance was selected. The accuracy of the model was evaluated through Leave one out (LOOV) cross-validation, external validation using test set molecules, Y-randomization and applicability domain techniques. The results of the present study are expected to be useful to the environmental regulatory agencies locally and internationally in the area of environmental risk assessment of toxicity of Polychlorinated dibenzofurans (PCDFs) and other related Polychlorinated aromatic compounds/ pollutants that fall within the model's applicability domain.
New QSAR models for polyhalogenated aromatics
Environmental Toxicology and Chemistry, 1994
Electronic properties of polychlorinated dibenzo p dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), poly chlorinated biphenyls (PCBs), and polychlorinated diphenyl ethers (PCDEs) were calculated using the semi-empirical AM 1 method The calculated electronic descriptorsthe energy of the lowest unoccupied molecular orbital (ELUMO), the energy of the highest occupied molecular orbital (EHOMO), the ELUMO-EHOMO gap (@), and molecular polarizability-are related to the Ah re ceptor binding affinity values of PCDDs, PCDFs, and PCBs and immunotoxicity values for PCDEs The quantitative structure activity relationships (QSARs) based on chlorine substitution patterns were also constructed, and they proved to be very predictive for Ah receptor binding Significant correlations of the electronic factors were found between the dE and Ah receptor binding affinities for PCDDs, PCDFs, and PCBs and for immunotoxicity of PCDEs A combination of descriptors EL,,, and the total number of chlorine atoms attached to a molecule (nci) gives significant correlation for the Ah receptor binding of PCDFs and for immunotoxicity of PCDEs Hydrophobicity values taken from the literature were shown to be nonsignificant for toxicity prediction of these polychlorinated compounds
Toxicology Letters, 2012
Polybrominated diphenyl ethers (PBDEs) are experimentally indicated to be capable of binding to the cytosolic aryl hydrocarbon receptor (AhR) and show a weak or moderate toxicity. However, little is yet known about the AhR-mediated toxicology. To fully evaluate the structural effects of PBDE ligand on AhR binding affinity and toxicity, quantitative structure-activity relationships (QSARs) were developed by PLS analysis. In this study, a simple but potent QSAR that was qualified with much better or comparable performance of prediction was optimally established for PBDE toxicity. With QSAR analysis, the AhR binding property was carefully described to reflect the origin of AhR binding affinity. Besides the effects from topological characters, the dispersion and electrostatic interactions were of indispensability for AhR binding affinity whereas the dispersion was further suggested to be dominant. The structural requirement for AhR binding affinity and toxicity was also investigated. As was similarly observed for polychlorinated biphenyls (PCBs), the preferential bromination at para-and meta (particularly 3,3-)-sites was confirmed as a key determinant to improve the AhR binding affinity and the toxicity of PBDEs.
Environmental Toxicology and Chemistry, 1993
A multivariate characterization of the 136 tetra-to octa-chloro-substituted dibenzo-pdioxins (PCDDs) and dibenzofurans (PCDFs) is reported. By principal component analysis (PCA) of a battery of physicochemical descriptors, an overview of similarities and differences between congener groups and substitution patterns is obtained. Available data for two biochemical end points, the induction of the enzymes aryl hydrocarbon hydroxylase (AHH) and ethoxy resorufin O-deethylase (EROD), were used to construct quantitative structure-activity relationships (QSARs) using partial least-squares projections with latent variables (PLS). By applying the principles of statistical experimental design to the orthogonal scores from the PCA, a set of PCDD and PCDF congeners is proposed for further biological and toxicological evaluations.
Journal of Chemical Information and Modeling, 2005
The quality of quantitative structure-activity relationship (QSAR) models depends on the quality of their constitutive elements including the biological activity, statistical procedure applied, and the physicochemical and structural descriptors. The aim of this study was to assess the comparative use of ab initio and semiempirical quantum chemical calculations for the development of toxicological QSARs applied to a large and chemically diverse data set. A heterogeneous collection of 568 organic compounds with 96 h acute toxicity measured to the fish fathead minnow (Pimephales promelas) was utilized. A total of 162 descriptors were calculated using the semiempirical AM1 Hamiltonian, and 121 descriptors were compiled using an ab initio (B3LYP/6-31G**) method. The QSARs were derived using multiple linear regression (MLR) and partial least squares (PLS) analyses. Statistically similar models were obtained using AM1 and B3LYP calculated descriptors supported by the use of the logarithm of the octanol-water partition coefficient (log K ow). The main difference between the models derived by both MLR and PLS with the two sets of quantum chemical descriptors was concentrated on the type of descriptors selected. It was concluded that for large-scale predictions, irrespective of the mechanism of toxic action, the use of precise but time-consuming ab initio methods does not offer considerable advantage compared to the semiempirical calculations and could be avoided.
2010
In the present study, the density functional B3LYP/6-311G** level of theory was used to compute and map the molecular surface electrostatic potentials of a group of substituted nitrobenzenes to identify common features related to their subsequent toxicities. Several statistical properties including potentials’ extrema (Vmin, Vmax), molecular volume, surface area, polar surface area, along with different energies were computed. A little linear correlation was revealed between Vmin and surface area, and systems’ toxicities. Another computations employed quantitative structure– property relationships model in CODESSA package to correlate toxicities with calculated descriptors. Statistically, the most significant correlation is a five-parameter equation with correlation coefficient, R values of 0.962, and the cross-validated correlation coefficient, RCV=0.950. The obtained models allowed us to reveal toxic activity of nitrobenzenes.
Toxicity analysis of benzidine through chemical reactivity and selectivity profiles: a DFT approach
2003
Chemical reactivity descriptors based on density functional theory are useful in analyzing the toxicities and in identifying the reactive sites of the molecular systems. In the present investigation the global reactivity profiles such as electronegativity, chemical hardness, polarizability, electrophilicity index and local selectivity profiles like condensed electrophilicity of benzidine are calculated using B3LYP/6-31G* including both Hartree-Fock and density functional theory based exchange functionals (B3LYP) in order to gain deeper insights into the toxic nature of this compound. Both global and local electrophilicity have been found to be adequate in explaining respectively the overall toxicity and the most probable site of reactivity. Interaction between benzidine and nucleic acid (NA) base/selected base pairs and Aryl Hydrocarbon Hydroxylase (AHH) receptors are determined using Parr's formula. The charge transfer involved in the formation of adducts is also qualitatively studied. The results revealed that benzidine acts as an electron-donating agent in their interaction with biomolecules. The planarity and electron affinity are the criteria influencing the toxic nature of benzidine.
Journal of Molecular Structure: THEOCHEM, 2006
Optimized calculations of 76 polychlorinated dibenzo-p-dioxins and 136 polychlorinated dibenzo-furans were carried out at the B3LYP/6-31G* level in GAUSSIAN 98 program. Based on the theoretical linear solvation energy relationship (TLSER) model, the obtained structural parameters were taken as theoretical descriptors to establish a novel QSPR model for predicting aqueous solubility (KlgS w ) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzo-furans. The new model of KlgS w achieved in this work contains two variables, dipole moment of the molecules (m) and the polarizability (a), of which R 2 Z0.9403, SDZ0.40. And the results of cross-validation test (q 2 Z0.9153) and method validation also showed that the model of this study exhibited optimum stability and better predictive power than semi-empirical method. q Journal of Molecular Structure: THEOCHEM 766 (2006) 25-33 www.elsevier.com/locate/theochem 0166-1280/$ -see front matter q