Epoxide hydrolase-catalyzed enantioselective conversion of  trans -stilbene oxide: Insights into the reaction mechanism from steady-state and pre-steady-state enzyme kinetics

Archelas, Alain; Zhao, Wei; Faure, Bruno; Iacazio, Gilles; Kotik, Michael

doi:10.1016/j.abb.2015.12.008

Cited by 6 publications

(4 citation statements)

References 34 publications

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“…3.4 Å between the center of the phenyl ring of the substrate and the proton in the H–C of Phe189). Previous computational studies have identified similar interactions to be present in the enzyme–substrate complex or in the alkyl–enzyme intermediate. ,,,,,,− …”

Section: Resultsmentioning

confidence: 99%

Quantum Chemical Modeling of Enantioconvergency in Soluble Epoxide Hydrolase

Lind

Himo

2016

ACS Catal.

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Soluble epoxide hydrolases (sEHs) catalyze the hydrolysis of epoxides to their corresponding vicinal diols. One property of a number of these enzymes is that they can catalyze the hydrolysis of some racemic substrates in an enantioconvergent one-enzyme fashion. Here, we have used the dispersion-corrected B3LYP-D3 density functional theory method to investigate the enantioconvergent conversion of styrene oxide (SO) by sEH from Solanum tuberosum (StEH1). A large cluster model of the active site, consisting of 279 atoms, is designed on the basis of the X-ray crystal structure of StEH1 in complex with the competitive inhibitor valpromide. Different substrate orientations of the two enantiomers of SO are examined, and the full reaction mechanisms for epoxide opening at the two carbons are calculated, including both the alkylation and hydrolysis half-reactions. The calculated overall reaction energy profiles show that the rate-determining step is associated with the dissociation of the covalent intermediate, which is the second step of the hydrolysis half-reaction. The calculations reproduce the experimentally observed regioselectivities for the two enantiomers of the substrate, in that both (S)-SO and (R)-SO are calculated to yield the same (R)-diol product. The obtained energy profiles indicate that the transition states for both the alkylation and hydrolysis half-reactions have to be taken into account in order to understand the stereochemical outcome of the reaction. The transition state structures are analyzed in detail, and several factors that contribute to the selectivity control are identified. In addition, the mechanistic scenario in which the active site His300 residue is in the protonated form is also considered and the implications on the energies and enantioselection are discussed. The current calculations demonstrate the applicability of the quantum chemical cluster methodology in reproducing and rationalizing experimental enantioselectivities, lending further support to its usefulness as a tool in asymmetric biocatalysis. The results presented here can be helpful in the rational engineering of sEHs to obtain variants with refined biocatalytic properties.

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Section: Resultsmentioning

confidence: 99%

Quantum Chemical Modeling of Enantioconvergency in Soluble Epoxide Hydrolase

Lind

Himo

2016

ACS Catal.

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“…The enantioselectivity of metagenome-derived EH Kau2 for racemic trans-stilbene oxide has been proposed to be due to differences in the rate of alkylation as well as the rate of hydrolysis. 39 Finally, in an alternative study of AnEH with para-substituted styrene oxide, 40 the origin of enantioselectivity was attributed to both a higher affinity and overall rate of catalysis as inferred from the experimental K M and V max values. The difficulty is that such experimental studies are unable to examine the origin of the enantioselectivity at an atomic level and as such the alternative mechanisms proposed are largely speculation.…”

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confidence: 99%

“…In contrast, the enantioselectivity of EH from Aspergillus niger ( An EH) for racemic styrene oxide and of rat microsomal EH for racemic glycidyl-4-nitrobenzoate was attributed to the rate of hydrolysis of the ester intermediate. The enantioselectivity of metagenome-derived EH Kau2 for racemic trans -stilbene oxide has been proposed to be due to differences in the rate of alkylation as well as the rate of hydrolysis . Finally, in an alternative study of An EH with para -substituted styrene oxide, the origin of enantioselectivity was attributed to both a higher affinity and overall rate of catalysis as inferred from the experimental K M and V max values.…”

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confidence: 99%

Effect of Binding on Enantioselectivity of Epoxide Hydrolase

Zaugg

Gumulya

Bodén

et al. 2018

J. Chem. Inf. Model.

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Molecular dynamics simulations and free energy calculations have been used to investigate the effect of ligand binding on the enantioselectivity of an epoxide hydrolase (EH) from Aspergillus niger. Despite sharing a common mechanism, a wide range of alternative mechanisms have been proposed to explain the origin of enantiomeric selectivity in EHs. By comparing the interactions of ( R)- and ( S)-glycidyl phenyl ether (GPE) with both the wild type (WT, E = 3) and a mutant showing enhanced enantioselectivity to GPE (LW202, E = 193), we have examined whether enantioselectivity is due to differences in the binding pose, the affinity for the ( R)- or ( S)- enantiomers, or a kinetic effect. The two enantiomers were easily accommodated within the binding pockets of the WT enzyme and LW202. Free energy calculations suggested that neither enzyme had a preference for a given enantiomer. The two substrates sampled a wide variety of conformations in the simulations with the sterically hindered and unhindered carbon atoms of the GPE epoxide ring both coming in close proximity to the nucleophilic aspartic acid residue. This suggests that alternative pathways could lead to the formation of a ( S)- and ( R)-diol product. Together, the calculations suggest that the enantioselectivity is due to kinetic rather than thermodynamic effects and that the assumption that one substrate results in one product when interpreting the available experimental data and deriving E-values may be inappropriate in the case of EHs.

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“…In contrast, the enantioselectivity of EH from Aspergillus niger (AnEH) for racemic styrene oxide [293] and of rat microsomal EH for racemic glycidyl-4-nitrobenzoate [294] was attributed to the rate of hydrolysis of the ester intermediate. The enantioselectivity of metagenome-derived EH Kau2 for racemic trans-stilbene oxide has been proposed to be due to differences in the rate of alkylation as well as the rate of hydrolysis [295]. Finally in an alternative study of AnEH with para-substituted styrene oxide [16], the origin of enantioselectivity was attributed to both a higher affinity and overall rate of catalysis as inferred from the experimental K M and V max values.…”

Section: Introductionmentioning

confidence: 99%

Computational modelling of enzymes: predicting and understanding the selectivity of an epoxide hydrolase

Zaugg¹

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Enzymes provide improved catalytic efficiency, renewability and higher selectivity compared to traditional chemical synthesis methods. Stereoselective enzymes in particular are highly desired within industry for the production of fine chemicals and drugs. Epoxide hydrolases (EH) are a family of enzymes whose selective properties facilitate the production of valuable intermediates used for the synthesis of many pharmaceuticals. There is a wealth of structural and biochemical data available for EHs, however the origin of their selectivity remains uncertain. Computational and statistical methods can aid in the design and discovery of selective enzymes and interpretation of the experimental data produced during their characterisation. This thesis focuses on the EH from the fungus Aspergillus niger (AnEH) and its aim is two-fold. The first aim is to explore and develop machine learning methods to predict selectivity enhancing mutations for AnEH. The second aim is to get insight into the mechanistic determinants of AnEH selectivity through molecular modelling methods. Publications during candidatureBook chapters • Zaugg J., Gumulya Y., Gillam E. M. J. and Bodén M. (2014) Computational tools for directed evolution: a comparison of prospective and retrospective strategies. Methods in Molecular Biology 1179:315-333 Contributions by others to the thesis Chapter 2 Zaugg J (candidate) and Bodén M researched and wrote the manuscript. Zaugg J, Bodén M, Gumulya Y and Gillam E edited the manuscript. Chapter 3 Zaugg J (candidate) carried out all computational experiments. Gumulya Y provided experimental data. Bodén M and Malde AK provided guidance in experimental design and analysis of results. Chapter 4 Zaugg J (candidate) carried out all computational experiments. Gumulya Y provided experimental data. Bodén M provided guidance in experimental design and analysis of results. Bodén M wrote much of the software (Bnkit) used for creating and training Bayesian networks. Wang Y developed code to allow specification of Dirichlet priors for Bayesian networks. Essebier A provided code for testing Bayesian networks. Chapter 6 Zaugg J (candidate) designed and carried out all computational experiments. Gumulya Y provided experimental data. Chapter 7 Zaugg J (candidate) carried out all computational experiments and designed the protocol used for docking of ligands. Malde AK and Mark AE provided guidance in the design and implementation of molecular dynamics simulations and free energy calculations and the analysis of results. Gumulya Y provided experimental data. Zaugg J, Gumulya Y, Bodén M, Mark AE and Malde AK wrote and edited the manuscript. IX Statement of parts of the thesis submitted to qualify for the award of another degree None. X Research Involving Human or Animal Subjects No animal or human subjects were involved in this research. XI Abstract I List of Figures XVI List of Tables XIX

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Epoxide hydrolase-catalyzed enantioselective conversion of trans -stilbene oxide: Insights into the reaction mechanism from steady-state and pre-steady-state enzyme kinetics

Cited by 6 publications

References 34 publications

Quantum Chemical Modeling of Enantioconvergency in Soluble Epoxide Hydrolase

Quantum Chemical Modeling of Enantioconvergency in Soluble Epoxide Hydrolase

Effect of Binding on Enantioselectivity of Epoxide Hydrolase

Computational modelling of enzymes: predicting and understanding the selectivity of an epoxide hydrolase

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