Quantitative relationship between chromatographic retentions and molecular structures of polychlorinated dibenzo-p-dioxins (PCDDs)

Liang, Xinmiao; Wang, W.; Wu, Wenbo; Schramm, Karl‐Werner; Henkelmann, Bernhard; Kettrup, A.

doi:10.1016/s0045-6535(99)00469-5

Cited by 14 publications

(6 citation statements)

References 21 publications

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“…Many attempts have been made to model the physicochemical properties and bioactivities of PCDDs by utilizing QSPR and Quantitative Structure -Activity Relationship (QSAR) techniques [10 -14]. For instance, Liang et al reported a quantitative relationship between chromatographic retentions and molecular structures of PCDDs [15].…”

Section: Introductionmentioning

confidence: 99%

QSPR Study on the Aqueous Solubility (−lgS_w) and n‐Octanol/Water Partition Coefficients (lgK_ow) of Polychlorinated Dibenzo‐p‐dioxins (PCDDs)

Yang

Wang

et al. 2007

QSAR Comb. Sci.

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Optimized calculation of 75 Polychlorinated Dibenzo-p-dioxins (PCDDs) and their parent compound DD was carried out at B3LYP/6-31G* level with GAUSSIAN 98 program. The structural parameters identified with the Theoretical Linear Solvation Energy Relationship (TLSER) model were employed as theoretical descriptors in the Quantitative Structure -Property Relationship (QSPR) models derived to predict the aqueous solubility (À lgS w ) and n-octanol/water partition coefficients (lgK ow ) of PCDDs. The regression model obtained to predict À lgS w contains only one variable: the mean molecular polarizability (a). The best fitted equation for the correlation between À lgS w and a of 12 PCDDs was À lgS w ¼ À 3.6425 þ 0.0693a with r 2 as 0.9776, Standard Deviation (SD) as 0.30, and suggesting high accuracy of the À lgS w predicting model. At the same time, there exists high correlation (r 2 ¼ 0.8862) between n-octanol/water partition coefficients (lgK ow ) and the mean molecular polarizability (a), and the SD is small. The mean molecular polarizability (a) is the only theoretical descriptor used in the QSPR model derived to predict lgK ow .

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Section: Introductionmentioning

confidence: 99%

QSPR Study on the Aqueous Solubility (−lgS_w) and n‐Octanol/Water Partition Coefficients (lgK_ow) of Polychlorinated Dibenzo‐p‐dioxins (PCDDs)

Yang

Wang

et al. 2007

QSAR Comb. Sci.

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“…In the past significant work has been done for QSRR [1,2] researches, for retention index predictions, separation condition selections and retention mechanism exploration [3] . For example, QSRR models [4][5][6][7][8][9][10] were established by introducing such descriptors as molecular geometrical characteristics, topological structures and diversities of physicochemical parameters. However, it was difficult to construct QSRR model for organic and biological molecules because they were based on 2D structures without considering interactions among compounds, fixed phase and fluxion phase.…”

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confidence: 99%

Three-dimensional holographic vector of atomic interaction field for quantitative structure-retention relationship of purine bases

et al. 2006

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A newly developed descriptor, threedimensional holographic vector of atomic interaction field (3D-HoVAIF), was used to describe the chemical structures of purine bases. After variable screening by stepwise multiple regression (SMR) technique, a partial least square (PLS) regression model was built with 3D-HoVAIF. The model was satisfactory comparing to reference since correlation coefficients of molecular modeling ( ), cross-validation ( ) and standard deviation of estimation (SD) were 0.966, 0.860 and 0.112, respectively, showing that the model had favorable estimation and prediction capabilities. It was illustrated that information related to retention data of purine bases could preferably be expressed by 3D-HoVAIF with definite physicochemical meanings and easy structural interpretation for purine bases. It was illustrated that 3D-HoVAIF was to preferably express retention data of purine bases and had definite physicochemical significance. So 3D-HoVAIF was a useful structural expression technique for quantitative structure activity (or property or retention) relationships (QSAR/QSPR/QSRR) study, such as structural characterization and chromatographic retention prediction. 2 cum R 2 cum Q Keywords: three-dimensional holographic vector of atomic interaction field (3D-HoVAIF), quantitative structure-retention relationship (QSRR), purine bases.It is necessary to introduce structural descriptors when creating quantitative structure-retention relationship. In the past significant work has been done for QSRR [1,2] researches, for retention index predictions, separation condition selections and retention mechanism exploration [3] . For example, QSRR models [4][5][6][7][8][9][10] were established by introducing such descriptors as molecular geometrical characteristics, topological structures and diversities of physicochemical parameters. However, it was difficult to construct QSRR model for organic and biological molecules because they were based on 2D structures without considering interactions among compounds, fixed phase and fluxion phase. Under such circumstances, 3D descriptors have been gradually developed in structural representation. Recently, there have been only few reports on 3D descriptors. Gramatica [11] used weighted holistic invariant molecular index (WHIM) proposed by Todeschini [12][13][14] to calculate chromatogram retention index of polychlorobiphenyl and Luo [15] used comparative molecular field analysis (CoMFA) proposed by Cramer [16] to calculate purine bases' capacity factor. Since WHIM index arises from rotation and translation of constants via weighted transform of physical variables, the calculation process is too intricate to be generalized. While CoMFA requires a series of complex procedures, such as overlap of molecular steric structure and configuration, partition of spatial grids, control of variable amounts and selection of potential probes. Combinating advantages of both 3D methods in explicit, accurate and explainable representation and 2D methods in easy and quick characterization, 3D...

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confidence: 99%

“…However, given the large number of potential contaminants and the lack of analytical standards, predictive tools are needed to assist researchers in screening environmental samples for novel compounds. Several models have been developed to predict relative GC retention times (GC-RRTs) of individual halogenated organic contaminant classes, such as those for PCBs, [4][5][6] PCDEs, 7 PCDDs, 4,8 PCDFs, 4,9,10 and PBDDs, 11 yet no further attempts have been made to develop a predictive GC-RRT model for more than one contaminant class after such an approach was successfully demonstrated by Ong and Hites. 4 The objective of this work was to identify a set of easily calculated variables that could be successfully used as descriptors in a predictive GC-RRT model for each of the following individual halogenated contaminant classes: PBDEs, PCDEs, PCBs, PCNs, PCDDs, PCDFs, PBDDs, PBDFs, and organochlorine pesticides.…”

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confidence: 99%

Development of a Multiple-Class High-Resolution Gas Chromatographic Relative Retention Time Model for Halogenated Environmental Contaminants

Rayne

Ikonomou

2003

Anal. Chem.

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A predictive model for the relative gas chromatographic retention times (GC-RRTs) of the following nine classes of halogenated environmental contaminants was developed: polybrominated diphenyl ethers (PBDEs); polychlorinated diphenyl ethers (PCDEs); polychlorinated biphenyls (PCBs); polychlorinated naphthalenes (PCNs); polychlorinated dibenzo-p-dioxins (PCDDs); polychlorinated dibenzofurans (PCDFs); polybrominated dibenzo-p-dioxins (PBDDs); polybrominated dibenzofurans (PBDFs); and organochlorine pesticides. MOPAC calculated physicochemical properties and structural descriptors in the model include molecular weight, square root of the number of halogen substituents, ionization potential, dipole moment, and the number of ortho, meta, and para halogen substituents. Using these variables, individual models for each of the contaminant classes were combined into a multiple class model incorporating the GC-RRTs of the 375 compounds of interest. The individual and multiclass GC-RRT models had acceptable fits between observed and predicted GC-RRTs (r2 = 0.9741-0.9990 for PBDEs, PCDEs, PCBs, PCNs, PCDD/Fs, and PBDD/Fs; r2 = 0.9250 for pesticides; and r2 = 0.9631 for the multiclass model) over a wide range of retention times and molecular structures. The combined model was tested on known GC-RRTs of hydroxylated PCBs and chlorinated phenoxyphenols and provided satisfactory results, demonstrating the strength of the model in predicting GC-RRT windows for contaminant classes not used in constructing the model. Such models will be useful in predicting the GC retention characteristics of novel environmental contaminants and their degradation products, for which analytical standards may not be available.

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Quantitative relationship between chromatographic retentions and molecular structures of polychlorinated dibenzo-p-dioxins (PCDDs)

Cited by 14 publications

References 21 publications

QSPR Study on the Aqueous Solubility (−lgS_w) and n‐Octanol/Water Partition Coefficients (lgK_ow) of Polychlorinated Dibenzo‐p‐dioxins (PCDDs)

QSPR Study on the Aqueous Solubility (−lgS_w) and n‐Octanol/Water Partition Coefficients (lgK_ow) of Polychlorinated Dibenzo‐p‐dioxins (PCDDs)

Three-dimensional holographic vector of atomic interaction field for quantitative structure-retention relationship of purine bases

Development of a Multiple-Class High-Resolution Gas Chromatographic Relative Retention Time Model for Halogenated Environmental Contaminants

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Quantitative relationship between chromatographic retentions and molecular structures of polychlorinated dibenzo-p-dioxins (PCDDs)

Cited by 14 publications

References 21 publications

QSPR Study on the Aqueous Solubility (−lgSw) and n‐Octanol/Water Partition Coefficients (lgKow) of Polychlorinated Dibenzo‐p‐dioxins (PCDDs)

QSPR Study on the Aqueous Solubility (−lgSw) and n‐Octanol/Water Partition Coefficients (lgKow) of Polychlorinated Dibenzo‐p‐dioxins (PCDDs)

Three-dimensional holographic vector of atomic interaction field for quantitative structure-retention relationship of purine bases

Development of a Multiple-Class High-Resolution Gas Chromatographic Relative Retention Time Model for Halogenated Environmental Contaminants

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Product

Resources

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QSPR Study on the Aqueous Solubility (−lgS_w) and n‐Octanol/Water Partition Coefficients (lgK_ow) of Polychlorinated Dibenzo‐p‐dioxins (PCDDs)

QSPR Study on the Aqueous Solubility (−lgS_w) and n‐Octanol/Water Partition Coefficients (lgK_ow) of Polychlorinated Dibenzo‐p‐dioxins (PCDDs)