QSARs for predicting reductive transformation rate constants of halogenated aromatic hydrocarbons in anoxic sediment systems

Peijnenburg, Willie J.G.M.; Hart, Maarten J. 't; Hollander, Henri A. den; Meent, Dik van de; Verboom, Hans; Wolfe, N. Lee

doi:10.1002/etc.5620110304

Cited by 43 publications

(22 citation statements)

References 10 publications

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“…Apparently, the DhaA dehalogenase is not restricted to longer alkyl chains when the halogen atom is bromine instead of chlorine. It is well known that the carbon–bromine bond is weaker and more easily broken than the carbon–chlorine bond [28]. In addition, brominated compounds are more polarizable than the analogous chlorinated compounds.…”

Section: Resultsmentioning

confidence: 99%

Structure–specificity relationships for haloalkane dehalogenases

Damborský

Rorije

Jesenská

et al. 2001

Enviro Toxic and Chemistry

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A structural analysis of the substrate specificity of hydrolytic dehalogenases originating from three different bacterial isolates has been performed using the multiple computer-automated structure evaluation methodology. This methodology identifies structural fragments in substrate molecules that either activate or deactivate biological processes. The analysis presented in this contribution is based on newly measured dehalogenation data combined with data from the literature (91 substrates). The enzymes under study represent different specificity classes of haloalkane dehalogenases (haloalkane dehalogenase from Xanthobacter autotrophicus GJ10, Rhodococcus erythropolis Y2, and Sphingomonas paucimobilis UT26). Three sets of structural rules have been identified to explain their substrate specificity and to predict activity for untested substrates. Predictions of activity and inactivity based on the structural rules from this analysis were provided for those compounds that were not yet tested experimentally. Predictions were also made for the compounds with available experimental data not used for the model construction (i.e., the external validation set). Correct predictions were obtained for 28 of 30 compounds in the validation set. Incorrect predictions were noted for two substrates outside the chemical domain of the set of compounds for which the structural rules were generated. A mechanistic interpretation of the structural rules generated provided a fundamental understanding of the structure-specificity relationships for the family of haloalkane dehalogenases.

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Section: Resultsmentioning

confidence: 99%

Structure–specificity relationships for haloalkane dehalogenases

Damborský

Rorije

Jesenská

et al. 2001

Enviro Toxic and Chemistry

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“…17,1998 M.M. All geometries were optimized at the RHF and DFT (VWN functional; symmetry and relativistic corrections included) levels employing a 6-31G(d,p) basis set.…”

Section: Methodsmentioning

confidence: 99%

“…17,1998 M.M. Whereas 1,2,3,4-T 4 CDD is not an environmentally relevant dioxin congener, 2,3,7,8-T 4 CDD is produced by both natural and anthropogenic processes and is found in sediments.…”

Section: Homo-lumo Gapsmentioning

confidence: 99%

Molecular Orbital Calculations to Describe Microbial Reductive Dechlorination of Polychlorinated Dioxins

Lynam

Kutý

Damborský

et al. 1998

Environ Toxicol Chem

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Ab initio restricted Hartree Fock and density functional theory (DFT), as well as semiempirical Austin model 1 and parametrization method 3 molecular orbital calculations were carried out for a range of chlorinated dioxin molecules to obtain molecular descriptors such as HOMO–LUMO gaps (HOMO = highest occupied molecular orbital, LUMO = lowest unoccupied molecular orbital) and partial atomic charges. The HOMO–LUMO gap is an indicator of stability in a molecule: the larger the gap the greater the stability of the molecule toward further reaction. These calculations indicate that with increasing extent of chlorination, the gap decreases. The observed charge pattern shows that carbon atoms in the peri (1,4,6,9) ring positions have a partial negative charge while those in the lateral (2,3,7,8) position have a partial positive or small partial negative charge. The descriptors, from the more precise DFT method, were used to rationalize experimental observations of dechlorination of dioxins. Reductive dechlorination pathways from two different experimental studies were examined using partial charges and estimated Gibbs free energy of dechlorination. In both experimental studies, highly thermodynamically favorable and less thermodynamically favorable pathways were observed. For a given chlorinated dioxin, when more than one degradation pathway was possible, dechlorination in the most thermodynamically favored pathway occurred at the most positively charged carbon atom in the ring, which was usually a lateral carbon atom. These results are discussed in light of a possible mechanism for reductive dechlorination.

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“…Some authors, however, used anaerobic soil/sediment systems or mixed cultures from environmental waters 8. 23, 29, 30 Soil suspension experiments, however, are useful, as they represent the entire soil microflora, although it is an artificial system and is restricted to those species able to grow under the chosen conditions.…”

Section: Resultsmentioning

confidence: 99%

Quantitative structure–transformation relationships of phenylurea herbicides

Berger

Müller

Eing

2001

Pest Management Science

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Quantitative relationships between the structure of phenylurea herbicides and their transformation in different matrices have been developed. Experimental data on microbial transformation by pure and mixed cultures of soil micro-organisms in inoculated and native soil, as well as on chemical transformation by hydrolysis in sterile soil and water, were available from previous studies. Around 60 experimental or calculated descriptors were used. Quantum chemical calculations were performed with three different semi-empirical methods. Models developed with multiple linear regression were generally easier to interpret than those derived with partial least-squares projection to latent structures. Quite simple and interpretable models could be found to predict transformation rates by pure cultures from lipophilicity, by mixed cultures from adsorption distribution coefficients, and by chemical or enzymatic hydrolysis from electronic properties. Transformation in inoculated soil could not be predicted, but for native soil the use of a quantum chemical descriptor for reactivity (energy of LUMO) together with molar refraction resulted in a general model.

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QSARs for predicting reductive transformation rate constants of halogenated aromatic hydrocarbons in anoxic sediment systems

Cited by 43 publications

References 10 publications

Structure–specificity relationships for haloalkane dehalogenases

Structure–specificity relationships for haloalkane dehalogenases

Molecular Orbital Calculations to Describe Microbial Reductive Dechlorination of Polychlorinated Dioxins

Quantitative structure–transformation relationships of phenylurea herbicides

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