Polychlorinated trans-azobenzenes (PCt-ABs) are less studied a highly toxic impurity in 2,3-dichloroaniline (2,3-D) and some herbicides and are compounds of environmental relevance lacking experimental physical and chemical properties data. In this study, to fulfill gaps on environmentally relevant partitioning properties of PCABs, the values of water solubility (μg/L and log S) have been determined for 209 congeners of chloro-trans-azobenzene (Ct-AB) by means of quantitative structure - property relationship (QSPR) approach and artificial neural networks (ANN) predictive ability. The quantitative structure - property relationship (QSPR) approach used based on geometry optimalization and quantum-chemical structural descriptors, which were computed on the level of density functional theory (DFT) using B3LYP functional and 6-311++G** basis set in Gaussian 03 and the semi-empirical quantum chemistry method for property parameterization (PM6) in the molecular orbital package (MOPAC) software. The predicted solubility of PCt-ABs by PM6 and DFT models and depending on a congener within a homologue class varied between 1995-11481 and 5370-15135 μg/L for mono-; 170-5495 and 138-9332 μg/L for di-; 36-1950 and 209-5248 μg/L for tri-; 15-794 and 41-3715 μg/L for tetra-; 5.5-209 and 39-1259 μg/L for penta-; 1.8-98 and 3.5-1096 μg/L for hexa-; 1.5-34 and 4.7-214 μg/L for hepta-; 0.71-6.2 and 0.76-26 μg/L for octa-; 0.83-1.7 and 0.69-1.2 μg/L for nonaCt-ABs; and between 0.36 and 0.04 μg/L for decaCt-AB, respectively. The calculations by PM6 were highly efficient and inexpensive compared to these by DFT, while both models gave data of similar accuracy.
Polychlorinated trans-azoxybenzenes (PCt-AOBs) consist a group of 399 theoretically possible congeners, which are toxicologically and environmentally relevant compounds. Some of PCt-AOBs have been identified as by-side impurity in technical grade 3,4-dichloroaniline (3,4-DCA), and also in derived of this chemical pesticides such as Diuron, Linuron or Propanil. In this study 31 quantum-chemical descriptors were in silico generated and used to characterize all 399 PCt-AOBs. Further, the basic thermodynamic and quantum-chemical property data matrix of PCt-AOBs made was interpreted with an aid of the Principal Component Analysis (PCA). The PCA of these data matrix created a three-dimensional model that explained 77.31% (63.79% + 8.87% + 4.65%) of the total variance. Polarizability, molecular weight, logarithm of the n-octanol/water partition coefficient, molecular refraction, valence molecular index, kappa index, molecular connectivity index, thermal capacity and entropy were the best positively correlated descriptors, which all are connected with molecular shape and size of the molecules. They all are explained by the first principal component (PC1), while energy of the highest occupied molecular orbital, Gibbs free energy in gas phase, standard heat of formation, the total particle energy and thermal energy were negatively correlated. The PC2 depended on polarizability vector Z and energy of the lowest unoccupied molecular orbital, while the PC3 was negatively impacted by the most positive partial charge on atoms. The congeners of trans-PCAOBs substituted with chlorine at positions 2' (ortho position) are non-planar. 119 Congeners of trans-chloroazoxybenzene (Ct-AOB) could be classified amongst stereoisomers (analogues) to highly toxic and environmentally persistent 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD). Data obtained after PCA were further used to create Fractional Factorial Design of PCt-AOBs and eight congeners, i.e., 2',3'-DiCt-AOB (no. 11), 2,2',5-TrCt-AOB (no. 32), 3',4'-DiCt-AOB (no. 24), 2,4,5-TrCt-AOB (no. 58), 2,2',3,4',5,5'-HeCt-AOB (no. 271), 2,2',3',4',5,5',6'-HpCt-AOB (no. 360), 2,3,3',4,4',5',6-HpCt-AOB (no. 364) and 2,2',3,3',4',5',6'-HpCt-AOB (no. 337), which probably are the best describers of the whole group, could be assigned.
Polychlorinated azobenzenes (PCABs) can be found as contaminant by products in 3,4-dichloroaniline and its derivatives and in the herbicides Diuron, Linuron, Methazole, Neburon, Propanil and SWEP. Trans congeners of PCABs are physically and chemically more stable and so are environmentally relevant, when compared to unstable cis congeners. In this study, to fulfill gaps on environmentally relevant partitioning properties of PCABs, the values of n-octanol/water partition coefficients (log K(OW)) have been determined for 209 congeners of chloro-trans-azobenzene (Ct-AB) by means of quantitative structure-property relationship (QSPR) approach and artificial neural networks (ANN) predictive ability. The QSPR methods used based on geometry optimalization and quantum-chemical structural descriptors, which were computed on the level of density functional theory (DFT) using B3LYP functional and 6-311++G basis set in Gaussian 03 and of the semi-empirical quantum chemistry method (PM6) of the molecular orbital package (MOPAC). Polychlorinated dibenzo-p-dioxins (PCDDs), -furans (PCDFs) and -biphenyls (PCBs), to which PCABs are related, were reference compounds in this study. An experimentally obtained data on physical and chemical properties of PCDD/Fs and PCBs were reference data for ANN predictions of log K(OW) values of Ct-ABs in this study. Both calculation methods gave similar results in term of absolute log K(OW) values, while the models generated by PM6 are considered highly efficient in time spent, when compared to these by DFT. The estimated log K(OW) values of 209 Ct-ABs varied between 5.22-5.57 and 5.45-5.60 for Mono-, 5.56-6.00 and 5.59-6.07 for Di-, 5.89-6.56 and 5.91-6.46 for Tri-, 6.10-7.05 and 6.13-6.80 for Tetra-, 6.43-7.39 and 6.48-7.14 for Penta-, 6.61-7.78 and 6.98-7.42 for Hexa-, 7.41-7.94 and 7.34-7.86 for Hepta-, 7.99-8.17 and 7.72-8.20 for Octa-, 8.35-8.42 and 8.10-8.62 for NonaCt-ABs, and 8.52-8.60 and 8.81-8.83 for DecaCt-AB. These log K(OW) values shows that Ct-ABs are compounds of relatively low environmental mobility (log K(OW) > 4.5) and of significant bioaccumulation potential.
The values of the soil sorption coefficient (K(OC)) have been computed for 209 environmentally relevant trans polychlorinated azobenzenes (PCABs) lacking experimental partitioning data. The quantitative structure-property relationship (QSPR) approach and artificial neural networks (ANN) predictive ability used in models based on geometry optimalization and quantum-chemical structural descriptors, which were computed on the level of density functional theory (DFT) using B3LYP functional and 6-311++G** basis set and of the semi-empirical quantum chemistry method for property parameterization (PM6) of the molecular orbital package (MOPAC). An experimentally available data on physical and chemical properties of PCDD/Fs and PCBs were used as reference data for the QSPR models and ANNs predictions in this study. Both calculation methods gave similar results in term of absolute log K(OC) values, while the PM6 model generated in the MOPAC was a much more efficient compared to the DFT model in GAUSSIAN. The estimated values of log K(OC) varied between 4.93 and 5.62 for mono-, 5.27 and 7.46 for di-, 6.46 and 8.09 for tri-, 6.65 and 9.11 for tetra-, 6.75 and 9.68 for penta-, 6.44 and 10.24 for hexa-, 7.00 and 10.36 for hepta-, 7.09 and 9.82 octa-, 8.94 and 9.71 for nona-Ct-ABs, and 9.26 and 9.34 for deca-Ct-AB. Because of high log K(OC) values PCt-ABs could be classified as compounds with high affinity to the particles of soil, sediments and organic matter.
Polychlorinated azoxybenzenes (PCAOBs) theoretically consist of 798 congeners with 399 in cis and 399 in trans configuration. PCAOBs in trans configuration are largerly planar compounds and some are highly toxic and environmentally relevant compared to cis congeners. Trans-PCAOBs can be found as by-side products in 3,4-dichloroaniline and some herbicides. To fulfill gaps in physical and chemical properties of PCAOBs, the values of log K(OW) were determined for 399 congeners of t-CAOB using a computational approach. We used the semi-empirical RM1 in MOPAC and DFT B3LYP in Gaussian 03 methods, artificial neural net (ANN) predictions, and the standardized variables with and without the normal varimax rotation. The models created predicted the values of log K(OW) of all 399 chlorinated derivatives of trans-azoxybenzenes (C-t-AOBs). The values of log K(OW) of C-t-AOBs varied between 5.08 and 5.42 for Mono-, 5.16 and 5.96 for Di-, 5.79 and 6.73 for Tri-, 6.26 and 7.18 for Tetra-, 6.65 and 7.54 for Penta-, 7.13 and 7.94 for Hexa-, 7.20 and 8.20 for Hepta-, 7.96 and 8.32 for Octa-, 8.32 and 8.43 for Nonachloro-t-AOBs and 8.55 and 8.97 for Decachloro-t-AOB. These log K(OW) values were similar per chloro-t-AOB congener and independent of the calculation method. C-t-AOBs have log K(OW) values above 4.5, and what relates to contaminants of low or very low environmentally mobility but a high predilection to the soil and sediment particles and with potential for bioaccumulation. The models that used the standardized variables had smallest errors and higher correlation coefficients compared to the models that based on the normal varimax rotation of standardized structural descriptors. In light of these data, the semi-empirical RM1 calculations in MOPAC software and followed by ANN were a much less time consuming and less expensive compared to the DFT B3LYP method.
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