Anaerobic Dehalogenation of Chloroanilines by Dehalococcoides mccartyi Strain CBDB1 and Dehalobacter Strain 14DCB1 via Different Pathways as Related to Molecular Electronic Structure.

Dehalococcoides mccartyi strain CBDB1 and Dehalobacter strain 14DCB1 are organohalide-respiring microbes of the phyla Chloroflexi and Firmicutes, respectively. Here, we report the transformation of chloroanilines by these two bacterial strains via dissimilar dehalogenation pathways and discuss the underlying mechanism with quantum chemically calculated net atomic charges of the substrate Cl, H, and C atoms. Strain CBDB1 preferentially removed Cl doubly flanked by two Cl or by one Cl and NH2, whereas strain 14DCB1 preferentially dechlorinated Cl that has an ortho H. For the CBDB1-mediated dechlorination, comparative analysis with Hirshfeld charges shows that the least-negative Cl discriminates active from nonactive substrates in 14 out of 15 cases and may represent the preferred site of primary attack through cob(I)alamin. For the latter trend, three of seven active substrates provide strong evidence, with partial support from three of the remaining four substrates. Regarding strain 14DCB1, the most positive carbon-attached H atom discriminates active from nonactive chloroanilines in again 14 out of 15 cases. Here, regioselectivity is governed for 10 of the 11 active substrates by the most positive H attached to the highest-charge (most positive or least negative) aromatic C carrying the Cl to be removed. These findings suggest the aromatic ring H as primary site of attack through the supernucleophile Co(I), converting an initial H bond to a full electron transfer as start of the reductive dehalogenation. For both mechanisms, one- and two-electron transfer to Cl (strain CBDB1) or H (strain 14DCB1) are compatible with the presently available data. Computational chemistry research into reaction intermediates and pathways may further aid in understanding the bacterial reductive dehalogenation at the molecular level.

In Silico Investigation of the Thyroid Hormone Activity of Hydroxylated Polybrominated Diphenyl Ethers.

Polybrominated diphenyl ethers (PBDEs) have been shown to have a disruptive effect on the thyroid hormone system, and one possible mechanism is the direct binding of their hydroxylated metabolites (HO-PBDEs) to thyroid hormone receptors (TRs). However, the experimental data on the thyroid hormone activity of HO-PBDEs are limited, and the molecular interaction mechanism remains unclear, impeding the ecological risk assessment for these widespread contaminants. In the present research, a quantum chemical approach was developed to predict the thyroid hormone activity of HO-PBDEs using the electronic structure parameters of neutral molecules. The ab initio HF/6-31G** algorithm was employed to optimize the molecular geometry and to calculate local molecular parameters regarding effective energy and electron transfer amount. The mechanistic analysis shows that the ability of the hydroxyl oxygen and hydrogen atom to donate or accept additional electron charges is an important property affecting the chemical activity of the thyroid hormone. The derived regression model was shown to have a good statistical performance and could be used to predict the thyroid hormone activity of other HO-PBDE congeners for which experimental measurements are not possible or are restricted. Therefore, the model has the potential to be a useful tool in the application of integrated testing strategies.

Anaerobic microbial transformation of halogenated aromatics and fate prediction using electron density modeling.

Halogenated homo- and heterocyclic aromatics including disinfectants, pesticides and pharmaceuticals raise concern as persistent and toxic contaminants with often unknown fate. Remediation strategies and natural attenuation in anaerobic environments often build on microbial reductive dehalogenation. Here we describe the transformation of halogenated anilines, benzonitriles, phenols, methoxylated, or hydroxylated benzoic acids, pyridines, thiophenes, furoic acids, and benzenes by Dehalococcoides mccartyi strain CBDB1 and environmental fate modeling of the dehalogenation pathways. The compounds were chosen based on structural considerations to investigate the influence of functional groups present in a multitude of commercially used halogenated aromatics. Experimentally obtained growth yields were 0.1 to 5 × 10(14) cells mol(-1) of halogen released (corresponding to 0.3-15.3 g protein mol(-1) halogen), and specific enzyme activities ranged from 4.5 to 87.4 nkat mg(-1) protein. Chlorinated electron-poor pyridines were not dechlorinated in contrast to electron-rich thiophenes. Three different partial charge models demonstrated that the regioselective removal of halogens is governed by the least negative partial charge of the halogen. Microbial reaction pathways combined with computational chemistry and pertinent literature findings on Co(I) chemistry suggest that halide expulsion during reductive dehalogenation is initiated through single electron transfer from B12Co(I) to the apical halogen site.

Predicting Michael-acceptor reactivity and toxicity through quantum chemical transition-state calculations.

The electrophilic reactivity of Michael acceptors is an important determinant of their toxicity. For a set of 35 α,ß-unsaturated aldehydes, ketones and esters with experimental rate constants of their reaction with glutathione (GSH), k(GSH), quantum chemical transition-state calculations of the corresponding Michael addition of the model nucleophile methane thiol (CH(3)SH) have been performed at the B3LYP/6-31G** level, focusing on the 1,2-olefin addition pathway without and with initial protonation. Inclusion of Boltzmann-weighting of conformational flexibility yields intrinsic reaction barriers ΔE(‡) that for the case of initial protonation correctly reflect the structural variation of k(GSH) across all three compound classes, except that they fail to account for a systematic (essentially incremental) decrease in reactivity upon α-substitution. By contrast, the reduction in k(GSH) through ß-substitution is well captured by ΔE(‡). Empirical correction for the α-substitution effect yields a high squared correlation coefficient (r(2) = 0.96) for the quantum chemical prediction of log k(GSH), thus enabling an in silico screening of the toxicity-relevant electrophilicity of α,ß-unsaturated carbonyls. The latter is demonstrated through application of the calculation scheme for a larger set of 46 Michael-acceptor aldehydes, ketones and esters with experimental values for their toxicity toward the ciliates Tetrahymena pyriformis in terms of 50% growth inhibition values after 48 h exposure (EC(50)). The developed approach may add in the predictive hazard evaluation of α,ß-unsaturated carbonyls such as for the European REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) Directive, enabling in particular an early identification of toxicity-relevant Michael-acceptor reactivity.

Prediction of michael-type acceptor reactivity toward glutathione.

A model has been developed to predict the kinetic rate constants (k(GSH)) of α,ß-unsaturated Michael acceptor compounds for their reaction with glutathione (GSH). The model uses the local charge-limited electrophilicity index ω(q) [Wondrousch, D., et al. (2010) J. Phys. Chem. Lett. 1, 1605-1610] at the ß-carbon atom as a descriptor of reactivity, a descriptor for resonance stabilization of the transition state, and one for steric hindrance at the reaction sites involved. Overall, the Michael addition model performs well (r² = 0.91; rms = 0.34). It includes various classes of compounds with double and triple bonds, linear and cyclic systems, and compounds with and without substituents in the α-position. Comparison of experimental and predicted rate constants demonstrates even better performance of the model for individual classes of compounds (e.g., for aldehydes, r² = 0.97 and rms = 0.15; for ketones, r² = 0.95 and rms = 0.35). The model also allows for the prediction of the RC50 values from the Schultz chemoassay, the accuracy being close to the interlaboratory experimental error. Furthermore, k(GSH) and associated RC50 values can be predicted in cases where experimental measurements are not possible or restricted, for example, because of low solubility or high volatility. The model has the potential to provide information to assist in the assessment and categorization of toxicants and in the application of integrated testing strategies.

Modeling and predicting pKa values of mono-hydroxylated polychlorinated biphenyls (HO-PCBs) and polybrominated diphenyl ethers (HO-PBDEs) by local molecular descriptors.

Hydroxylated polychlorinated biphenyls (HO-PCBs) and polybrominated diphenyl ethers (HO-PBDEs) are attracting considerable concerns because of their multiple endocrine-disrupting effects and wide existence in environment and organisms. The hydroxyl groups enable these chemicals to be ionizable, and dissociation constant, pKa, becomes an important parameter for investigating their environmental behavior and biological activities. In this study, a new pKa prediction model was developed using local molecular descriptors. The dataset contains 21 experimental pKa values of HO-PCBs and HO-PBDEs. The optimized geometries by ab initio HF/6-31G(∗∗) algorithm were used to calculate the site-specific molecular readiness to accept or donate electron charges. The developed model obtained good statistical performance, which significantly outperformed commercial software ACD and SPARC. Mechanism analysis indicates that pKa values increase with the charge-limited donor energy EQocc on hydroxyl oxygen atom and decrease with the energy-limited acceptor charge QEvac on hydroxyl hydrogen atom. The regression model was also applied to calculate pKa values for all 837 mono-hydroxylated PCBs and PBDEs in each class, aiming to provide basic data for the ecological risk assessment of these chemicals.