Combinatorial × Computational × Cheminformatics (C3) Approach to Characterization of Congeneric Libraries of Organic Pollutants

Quantitative and semiquantitative analyses of hexa-mix-chlorinated/brominated benzenes in fly ash, soil and air using gas chromatography-high resolution mass spectrometry assisted with isotopologue distribution computation

Hexa-mix-chlorinated/brominated benzenes (HXBs), a group of newly found analogues of hexachlorobenzene (HCB) and hexabromobenzene (HBB), may exhibit similar environmental risks and toxicities as HCB and HBB, and therefore possess high interests in environmental and toxicological research. Yet information regarding HXBs in the environment remains scarce. In this study, we developed an isotope dilution method for quantitative and semiquantitative determination of five HXBs in fly ash, soil and air using gas chromatography high resolution mass spectrometry (GC-HRMS) in multiple ion detection mode. The samples were Soxhlet-extracted and purified with multilayer composite silica gel-alumina columns, followed by GC-HRMS detection. Identification of HXBs was conducted by the comparison between theoretical and detected mass spectra using paired-samples T test and cosine similarity analysis. Two HXBs (C₆BrCl₅ and C₆Br₄Cl₂) with reference standards were quantitatively determined while the rest three (C₆Br₂Cl₄, C₆Br₃Cl₃ and C₆Br₅Cl) without reference standards were semiquantitatively analyzed by sharing the calibration curves of C₆BrCl₅ and C₆Br₄Cl₂ in cooperation with isotopologue distribution computation. The accuracies for C₆BrCl₅ and C₆Br₄Cl₂ were 87.3-107.8% with relative standard deviations (RSD) of 2.8-5.0%. The method limits of quantification of the HXBs were 0.10 ng/g in fly ash and soil samples and 0.09 pg/m³ in ambient air samples. The recoveries ranged from 42.7% to 102.1% with RSD of 3.7-13.9%. This method has been successfully applied to the analysis of the HXBs in the environmental samples. The total concentrations of HXBs in the fly ash, soil and ambient air samples were 19.48 ng/g, 10.44 ng/g and 5.13 pg/m³, respectively, which accounted for 10.6%, 0.4% and 10.8% of the corresponding total concentrations of HCB and HBB. This study provides a reference method for quantitative and/or semiquantitative analyses of novel mix-halogenated organic compounds, and sheds light on the full picture of HXBs pollution in the environment.

Modeling adsorption of brominated, chlorinated and mixed bromo/chloro-dibenzo-p-dioxins on C60 fullerene using Nano-QSPR

Many technological implementations in the field of nanotechnology have involved carbon nanomaterials, including fullerenes such as the buckminsterfullerene, C60. The unprecedented properties of such organic nanomaterials (in particular their large surface area) gained extensive attention for their potential use as organic pollutant sorbents. Sorption interactions can be very hazardous and useful at the same time. This work investigates the influence of halogenation by bromine and/or chlorine in dibenzo-p-dioxins on their sorption ability on the C60 fullerene surface. Halogenated dibenzo-p-dioxins (PXDDs, where X = Br or Cl) are ever-present in the environment and accidently produced in many technological processes in only approximately known quantities. If all combinatorial Br and/or Cl dioxin substitution possibilities are present in the environment, the experimental characterization and investigation of sorbent effectiveness is more than difficult. In this work, we have developed a quantitative structure-property relationship (QSPR) model (R2 = 0.998), predicting the adsorption energy [kcal/mol] for 1,701 PXDDs adsorbed on C60 (PXDD@C60). Based on the QSPR model reported herein, we concluded that the lowest energy PXDD@C60 complexes are those that the World Health Organization (WHO) considers to be less dangerous with respect to the aryl hydrocarbon receptor (AhR) toxicity mechanism. Therefore, the effectiveness of fullerenes as sorbent agents may be underestimated as sorption could be less effective for toxic congeners than previously believed.

Modeling bioconcentration factor (BCF) using mechanistically interpretable descriptors computed from open source tool "PaDEL-Descriptor"

Predictive regression-based models for bioconcentration factor (BCF) have been developed using mechanistically interpretable descriptors computed from open source tool PaDEL-Descriptor ( http://padel.nus.edu.sg/software/padeldescriptor/ ). A data set of 522 diverse chemicals has been used for this modeling study, and extended topochemical atom (ETA) indices developed by the present authors' group were chosen as the descriptors. Due to the importance of lipohilicity in modeling BCF, XLogP (computed partition coefficient) was also tried as an additional descriptor. Genetic function approximation followed by multiple linear regression algorithm was applied to select descriptors, and subsequent partial least squares analyses were performed to establish mathematical equations for BCF prediction. The model generated from only ETA indices shows importance of seven descriptors in model development, while the model generated from ETA descriptors along with XlogP shows importance of four descriptors in model development. In general, BCF depends on lipophilicity, presence of heteroatoms, presence of halogens, fused ring system, hydrogen bonding groups, etc. The developed models show excellent statistical qualities and predictive ability. The developed models were used also for prediction of an external data set available from the literature, and good quality of predictions (R (2) pred = 0.812 and 0.826) was demonstrated. Thus, BCF can be predicted using ETA and XlogP descriptors calculated from open source PaDEL-Descriptor software in the context of aquatic chemical toxicity management.