Quantitative structure-activity relationship (QSAR) studies for predicting activation of the ryanodine receptor type 1 channel complex (RyR1) by polychlorinated biphenyl (PCB) congeners

Predicted versus observed activity of PCB mixtures toward the ryanodine receptor

Non-dioxin-like polychlorinated biphenyls (NDL PCBs) alter the activity of the ryanodine receptor (RyR), and this activity is linked to developmental neurotoxicity. Most work to date has focused on the activity of single congeners rather than relevant mixtures. The current study assessed the RyR activity of single congeners or binary, tertiary, and complex PCB mixtures. Observed mixture activity was then compared to the expected activity calculated using the concentration addition (CA) model or a RyR-specific neurotoxic equivalency scheme (rNEQ). The predictions of the CA model were consistent with the observed activity of binary mixtures at the lower portion of the concentration-response curve, supporting the additivity of RyR1 active PCBs. Findings also show that minimally active congeners can compete for the RyR1 binding site, and congeners that do not activate the RyR1 do not interfere with the activity of a full agonist. Complex PCB mixtures that mimic PCB profiles detected in indoor air, fish tissue, and the serum of mothers and children activated the RyR1 and displayed similar efficacy and potency regardless of varying congener profiles. Neither the CA model nor the rNEQ perfectly predicted the observed activity of complex mixtures, but predictions were often within one magnitude of change from the observed response. Importantly, PCB mixtures approximating profiles found in environmental samples or human serum displayed RyR1 activity at concentrations reported in published research. The work presented will aid in the development of risk assessment platforms for NDL PCBs and similar compounds toward RyR1 activation and related neurotoxicity.

Predicted Versus Observed Activity of PCB Mixtures Toward the Ryanodine Receptor

Non-dioxin-like polychlorinated biphenyls (NDL PCBs) alter the activity of the ryanodine receptor (RyR), and this activity is linked to developmental neurotoxicity. Most work to date has focused on the activity of single congeners rather than relevant mixtures. The current study assessed the RyR activity of single congeners or binary, tertiary, and complex PCB mixtures. Observed mixture activity was then compared to the expected activity calculated using the concentration addition (CA) model or a RyR-specific neurotoxic equivalency scheme (rNEQ). The predictions of the CA model were consistent with the observed activity of binary mixtures at the lower portion of the concentration-response curve, supporting the additivity of RyR1 active PCBs. Findings also show that minimally active congeners can compete for the RyR1 binding site, and congeners that do not activate the RyR1 do not interfere with the activity of a full agonist. Complex PCB mixtures that mimic PCB profiles detected in indoor air, fish tissue, and the serum of mothers and children activated the RyR1 and displayed similar efficacy and potency regardless of varying congener profiles. Neither the CA model nor the rNEQ perfectly predicted the observed activity of complex mixtures, but predictions were often within one magnitude of change from the observed response. Importantly, PCB mixtures approximating profiles found in environmental samples or human serum displayed RyR1 activity at concentrations reported in published research. The work presented will aid in the development of risk assessment platforms for NDL PCBs, and similar compounds, towards RyR1 activation and related neurotoxicity.

A case study of neurodevelopmental risks from combined exposures to lead, methyl-mercury, inorganic arsenic, polychlorinated biphenyls, polybrominated diphenyl ethers and fluoride

We performed a mixture risk assessment (MRA) case study of dietary exposure to the food contaminants lead, methylmercury, inorganic arsenic (iAs), fluoride, non-dioxin-like polychlorinated biphenyls (NDL-PCBs) and polybrominated diphenyl ethers (PBDEs), all substances associated with declines in cognitive abilities measured as IQ loss. Most of these chemicals are frequently measured in human biomonitoring studies. A component-based, personalised modified reference point index (mRPI) approach, in which we expressed the exposures and potencies of our chosen substances as lead equivalent values, was applied to perform a MRA for dietary exposures. We conducted the assessment for four different age groups (toddlers, children, adolescents, and women aged 18-45 years) in nine European countries. Populations in all countries considered exceeded combined tolerable levels at median exposure levels. NDL-PCBs in fish, other seafood and dairy, lead in grains and fruits, methylmercury in fish and other seafoods, and fluoride in water contributed most to the combined exposure. We identified uncertainties for the likelihood of co-exposure, assessment group membership, endpoint-specific reference values (ESRVs) based on epidemiological (lead, methylmercury, iAs, fluoride and NDL-PCBs) and animal data (PBDE), and exposure data. Those uncertainties lead to a complex pattern of under- and overestimations, which would require probabilistic modelling based on expert knowledge elicitation for integration of the identified uncertainties into an overall uncertainty estimate. In addition, the identified uncertainties could be used to refine future MRA for cognitive decline.

Non-dioxin-like polychlorinated biphenyl neurotoxic equivalents found in environmental and human samples

Non-dioxin like polychlorinated biphenyls (NDL PCB) are recognized neurotoxicants with implications on altered neurodevelopment and neurodegeneration in exposed organisms. NDL PCB neurotoxic relative potency schemes have been developed for a single mechanism, namely activity toward the ryanodine receptor (RyR), or combined mechanisms including, but not limited to, alterations of RyR and dopaminergic pathways. We compared the applicability of the two neurotoxic equivalency (NEQ) schemes and applied each scheme to PCB mixtures found in environmental and human serum samples. A multiple mechanistic NEQ predicts higher neurotoxic exposure concentrations as compared to a scheme based on the RyR alone. Predictions based on PCB ortho categorization, versus homologue categorization, lead to a higher prediction of neurotoxic exposure concentrations, especially for the mMOA. The application of the NEQ schemes to PCB concentration data suggests that PCBs found in fish from US lakes represent a considerable NEQ exposure to fish consuming individuals, that indoor air of schools contained high NEQ concentrations representing an exposure concern when inhaled by children, and that levels already detected in the serum of adults and children may contribute to neurotoxicity. With further validation and in vivo exposure data the NEQ scheme would help provide a more inclusive measure of risk presented by PCB mixtures.

Integrating data gap filling techniques: A case study predicting TEFs for neurotoxicity TEQs to facilitate the hazard assessment of polychlorinated biphenyls

The application of toxic equivalency factors (TEFs) or toxic units to estimate toxic potencies for mixtures of chemicals which contribute to a biological effect through a common mechanism is one approach for filling data gaps. Toxic Equivalents (TEQ) have been used to express the toxicity of dioxin-like compounds (i.e., dioxins, furans, and dioxin-like polychlorinated biphenyls (PCBs)) in terms of the most toxic form of dioxin: 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD). This study sought to integrate two data gap filling techniques, quantitative structure-activity relationships (QSARs) and TEFs, to predict neurotoxicity TEQs for PCBs. Simon et al. (2007) previously derived neurotoxic equivalent (NEQ) values for a dataset of 87 PCB congeners, of which 83 congeners had experimental data. These data were taken from a set of four different studies measuring different effects related to neurotoxicity, each of which tested overlapping subsets of the 83 PCB congeners. The goals of the current study were to: (i) evaluate an alternative neurotoxic equivalent factor (NEF) derivations from an expanded dataset, relative to those derived by Simon et al. and (ii) develop QSAR models to provide NEF estimates for the large number of untested PCB congeners. The models used multiple linear regression, support vector regression, k-nearest neighbor and random forest algorithms within a 5-fold cross validation scheme and position-specific chlorine substitution patterns on the biphenyl scaffold as descriptors. Alternative NEF values were derived but the resulting QSAR models had relatively low predictivity (RMSE ∼0.24). This was mostly driven by the large uncertainties in the underlying data and NEF values. The derived NEFs and the QSAR predicted NEFs to fill data gaps should be applied with caution.

Authentication of synthetic environmental contaminants and their (bio)transformation products in toxicology: polychlorinated biphenyls as an example

Toxicological studies use "specialty chemicals" and, thus, should assess and report both identity and degree of purity (homogeneity) of the chemicals (or toxicants) under investigation to ensure that other scientists can replicate experimental results. Although detailed reporting criteria for the synthesis and characterization of organic compounds have been established by organic chemistry journals, such criteria are inconsistently applied to the chemicals used in toxicological studies. Biologically active trace impurities may lead to incorrect conclusions about the chemical entity responsible for a biological response, which in turn may confound risk assessment. Based on our experience with the synthesis of PCBs and their metabolites, we herein propose guidelines for the "authentication" of synthetic PCBs and, by extension, other organic toxicants, and provide a checklist for documenting the authentication of toxicants reported in the peer-reviewed literature. The objective is to expand guidelines proposed for different types of biomedical and preclinical studies to include a thorough authentication of specialty chemicals, such as PCBs and their derivatives, with the goal of ensuring transparent and open reporting of scientific results in toxicology and the environmental health sciences.

Early life exposure to air pollution particulate matter (PM) as risk factor for attention deficit/hyperactivity disorder (ADHD): Need for novel strategies for mechanisms and causalities

Epidemiological studies have demonstrated that air pollution particulate matter (PM) and adsorbed toxicants (organic compounds and trace metals) may affect child development already in utero. Recent studies have also indicated that PM may be a risk factor for neurodevelopmental disorders (NDDs). A pattern of increasing prevalence of attention deficit/hyperactivity disorder (ADHD) has been suggested to partly be linked to environmental pollutants exposure, including PM. Epidemiological studies suggest associations between pre- or postnatal exposure to air pollution components and ADHD symptoms. However, many studies are cross-sectional without possibility to reveal causality. Cohort studies are often small with poor exposure characterization, and confounded by traffic noise and socioeconomic factors, possibly overestimating the study associations. Furthermore, the mechanistic knowledge how exposure to PM during early brain development may contribute to increased risk of ADHD symptoms or cognitive deficits is limited. The closure of this knowledge gap requires the combined use of well-designed longitudinal cohort studies, supported by mechanistic in vitro studies. As ADHD has profound consequences for the children affected and their families, the identification of preventable risk factors such as air pollution exposure should be of high priority.

An Extended Structure-Activity Relationship of Nondioxin-Like PCBs Evaluates and Supports Modeling Predictions and Identifies Picomolar Potency of PCB 202 Towards Ryanodine Receptors

Nondioxin-like polychlorinated biphenyls (NDL PCBs) activate ryanodine-sensitive Ca²⁺channels (RyRs) and this activation has been associated with neurotoxicity in exposed animals. RyR-active congeners follow a distinct structure-activity relationship and a quantitative structure-activity relationship (QSAR) predicts that a large number of PCBs likely activate the receptor, which requires validation. Additionally, previous structural based conclusions have been established using receptor ligand binding assays but the impact of varying PCB structures on ion channel gating behavior is not understood. We used [³H]Ryanodine ([³H]Ry) binding to assess the RyR-activity of 14 previously untested PCB congeners evaluating the predictability of the QSAR. Congeners determined to display widely varying potency were then assayed with single channel voltage clamp analysis to assess direct influences on channel gating kinetics. The RyR-activity of individual PCBs assessed in in vitro assays followed the general pattern predicted by the QSAR but binding and lipid bilayer experiments demonstrated higher potency than predicted. Of the 49 congeners tested to date, tetra-ortho PCB 202 was found to be the most potent RyR-active congener increasing channel open probability at 200 pM. Shifting meta-substitutions to the para-position resulted in a > 100-fold reduction in potency as seen with PCB 197. Non-ortho PCB 11 was found to lack activity at the receptor supporting a minimum mono-ortho substitution for PCB RyR activity. These findings expand and support previous SAR assessments; where out of the 49 congeners tested to date 42 activate the receptor demonstrating that the RyR is a sensitive and common target of PCBs.

Structure-activity relationship of non-coplanar polychlorinated biphenyls toward skeletal muscle ryanodine receptors in rainbow trout (Oncorhynchus mykiss)

Research addressing the health impacts of polychlorinated biphenyls (PCBs) has primarily focused on the effects of coplanar, or dioxin-like (DL), congeners, which is especially true for research assessing impacts in fish species. Ortho substituted non-coplanar, termed non-dioxin-like (NDL), PCBs have received less attention. In mammals, NDL PCBs enhance the activity of ryanodine receptors (RyR), calcium release channels necessary for engaging excitation-contraction (EC) coupling in striated muscle. We utilized in vitro receptor binding analysis to determine whether NDL PCB congeners detected in aquatic environments alter the activity of RyR isoform 1 (RyR1) found in the skeletal muscle of rainbow trout. Congeners 52, 95, 136, and149 were the most efficacious leading to an increase in receptor activity that was approximately 250% greater than that found under solvent control conditions. Other environmentally relevant congeners, namely PCB 153, 151 and 101, which all contain two or more chlorines in the ortho-position, enhanced receptor activity by greater than 160% of baseline. The mono-ortho congeners or the non-ortho PCB 77 had negligible impact on the RyR1. When combined, in binary or environmentally relevant mixtures, congeners shown to enhance receptor activity appeared to display additivity and when the active PCB 95 was present with the non-active congener PCB 77 the impact on receptor activity was reduced from 250% to 230%. The important role of the RyR and the demonstrated additive nature of NDL congeners toward altering channel function calls for further investigation into the ecological implications of altered RyR function in fish with high PCB burdens.

The aqueous solubility of some herbicidal by-side toxic impurities: predicted data of the 399 chlorinated trans-azoxybenzene congeners

The quantitative structure - property relationship (QSPR) and the artificial neural networks (ANNs) methods were used to estimate aqueous solubility (log S and μg/L) of polychlorinated trans-azoxybenzenes (PCt-ABs). These QSPR and ANN models are 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 software and the semi-empirical quantum chemistry method for property parameterization (RM1) in the molecular orbital package (MOPAC) software. The predicted solubility of PCt-AOBs by RM1 and DFT models and depending on a congener varied within a homologue class between 47-19498 and 371-1738 μg/L for Mono-; 33-11481 and 7.9-3630 μg/L for Di-; 6.1-4786 and 4.7-12882 μg/L for Tri-; 1.3-1174 and 0.3-14791 μg/L for Tetra-; 0.4-646 and 0.1-38904 μg/L for Penta-; 0.1-155 and 0.2-63096 μg/L for Hexa-; 0.2-27 and 0.1-646 μg/L for Hepta-; < 0.1-6.2 and 0.8-282 μg/L for Octa-; 0.6-2.6 and 0.8-12 μg/L for NonaCt-AOBs; and 1.2 and 0.5 μg/L for DecaCt-AOB, respectively. Both computational models used were characterized by good predictive abilities and small errors, while calculations by RM1 method were highly competitive compared to a much more time-consuming and expensive method by DFT.

Estimation of K(OA) values of 209 polychlorinated trans-azobenzenes by PM6 and DFT methods

The octanol-air partition coefficients (K(OA)) of all 209 PCt-ABs were determined computationally to fill gaps on their environmentally relevant physical and chemical properties. These properties have been determined using two computational approaches: the semi-empirical quantum chemistry method for property parameterization (PM6) of the molecular orbital package (MOPAC) and density functional theory (DFT) method using B3LYP functional and 6-311++G** basis set in Gaussian 03 software and artificial neural network (ANN) predicting abilities. Both computational methods enabled estimation of log K(OA) partition coefficients of PCt-ABs with a similar accuracy and precision. The PM6 method compared to DFT was highly superior because it requires much less time, manpower and cost of hardware. The determined log K(OA) values of the investigated PCt-ABs for standard condition (25 °C) varied between 8.30 and 8.75 for Mono-; 8.71 and 9.92 for Di-; 9.58 and 10.72 for Tri-; 10.11 and 11.34 for Tetra-, 10.83 and 11.85 for Penta-; 11.24 and 12.36 for Hexa-; 11.87 and 12.66 for Hepta-; 12.31 and 12.97 for Octa-; 12.89 and 13.21 for Nona-Ct-ABs; and 13.17- and 13.49 for Deca-Ct-AB. PCt-ABs, in view of these log K(OA) values, can be classified as compounds of relatively low (Mono-, Di- and some of Tri- Ct-ABs with values of log K(OA) around 8 to 10) environmental mobility (most of Tri- to Nona-Ct-ABs and Deca-Ct-AB homologues with values of log K(OA) >10), and with a potential to be adsorbed by soil particles.

Estimation of the physicochemical properties of PCDD/Fs using three-dimensional holographic vector of atomic interaction field

Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) are a group of important persistent organic pollutants. In the present study, the three-dimensional holographic vector of atomic interaction field (3D-HoVAIF) method is used to describe the chemical structures of PCDD/Fs. After variable screening using a stepwise multiple regression (SMR) technique, the linear relationships among six physicochemical properties of PCDD/Fs and 3D-HoVAIF descriptors are built using a partial least-squares (PLS) regression model. The results show that the 3D-HoVAIF descriptors can be used to express the quantitative structure-property relationships of PCDD/Fs. The predictive capabilities of the models have also been confirmed by leave-one-out cross-validation. The optimum model has been used to estimate values for PCDD/Fs for which no experimental data on physicochemical properties are available. Supplemental materials are available for this article. Go to the publisher's online edition of Journal of Environmental Science and Health: Part A to view the free supplemental file.

Use of quantitative-structure property relationship (QSPR) and artificial neural network (ANN) based approaches for estimating the octanol-water partition coefficients of the 209 chlorinated trans-azobenzene congeners

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.

QSPR for prediction of subcooled vapor pressures (log PL) of polychlorinated trans-azobenzenes

In this study the values of subcooled vapor pressures (log P(L)) were estimated for 209 trans chloroazobenzenes (Ct-ABs) that fill some gaps in analytical and experimental data on these compounds. There are 209 chloro derivatives of trans azobenzenes that are relatively stable and more environmentally relevant than 209 chloro cis congeners. The calculations models were based on the Quantitative Structure-Property Relationship (QSPR) scheme using the semi-empirical method (PM6) in molecular package (MOPAC) software and density functional theory (DFT) method using B3LYP functional and 6-311++G** basis set) in Gaussian 03 software method and the artificial neural networks (ANNs) prediction. The values of log P(L) predicted by models used varied between -3.94 to -2.66 for Mono-; -4.85 to -2.97 for Di-; -5.18 to -3.17 for Tri-; -6.02 to -3.77 for Tetra-; -6.64 to -4.64 for Penta-; -7.36 to -4.76 for Hexa-; -7.54 to -5.79 for Hepta-; -7.75 to -6.64 for Octa-; -7.89 to -7.44 for Nona-Ct-Abs; and -8.09 and -8.13 for Deca-Ct-AB. Based on these values Ct-ABs can be grouped localized among relatively low (log P(L) -4 to -2) and low (log P(L) < -4) mobile Persistent Organic Pollutants (POPs). Both the calculation methods employed were characterized by similar prediction ability of subcooled vapor pressure values of Ct-ABs, while those of PM6 are much more efficient due to a cheaper hardware used and around 300-fold less time spent on calculations.

Prediction of subcooled vapor pressures (log PL) of 399 polychlorinated trans-azoxybenzenes by using the QSPR and ANN approach

Environmentally relevant partitioning properties such as the sub-cooled vapor pressures (log PL) have been predicted for 399 congeners of chloro-trans-azoxybenzene (C-t-AOBs) by two computational methods. The quantitative structure-property relationship (QSPR), an approach which is based on geometry optimalization and quantum-chemical structural descriptors in RM1 and DFT methods and artificial neural networks (ANNs), an approach that predicts abilities that give similar results of estimated log P(L) and the accuracy of the methods was also similar. The RM1 method was less time consuming and less costly compared to calculations by the DFT method. Estimated from the RM1 and DFT methods of log P(L) values of 399 Ct-AOBs varied between -1.98 to -0.93 and -1.83 to -0.79 for Mono-, 3.12 to -1.46 and -3.00 to -1.46 for Di-, -4.03 to -1.39 and -3.53 to -1.67 for Tri-, -4.75 to -2.33 and -4.59 to -1.91 for Tetra-, -5.37 to -2.59 and -5.42 to -2.09 for Penta-, -5.82 to -2.88 and -5.66 to -2.58 for Hexa-, -5.88 to -3.24 and -5.60 to -2.93 for Hepta-, -6.28 to -4.33 and -5.60 to -4.29 for Octa-, -6.54 to -5.28 and -5.66 to -4.93 for NonaCt-AOBs, and -6.59 and -5.61 for DecaCt-AOB. According to a common classification of environmental contaminants and by sub-cooled vapor pressure values, MonoCt-AOBs and a few of the Di- and TriCt-AOBs (log P(L)from -2 to 0) fall into the group of compounds that are relatively well mobile in the ambient environment, while most of the Di- to HeptaCt-AOBs (log P(L) < -4 to -2) mobility is relatively weak. Octa- and NonaCt-AOBs and DecaCt-AOB (log P(L) < -4) are also weak mobile contaminants.

QSPR models for prediction of the soil sorption coefficient (log KOC) values of 209 polychlorinated trans-azobenzenes (PCt-ABs)

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.

QSAR and ANN for the estimation of water solubility of 209 polychlorinated trans-azobenzenes

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.

N-octanol-water partition coefficients (log K(OW)) of 399 congeners of polychlorinated azoxybenzenes (PCAOBs) determined by QSPR- and ANN-based approach

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.