The quantum chemical cluster approach for modeling enzyme reactions

Siegbahn, Per E. M.; Himo, Fahmi

doi:10.1002/wcms.13

Cited by 262 publications

(347 citation statements)

References 83 publications

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Section: Introductionmentioning

confidence: 99%

“…In the QM cluster approach, the most important residues of the active site (typically 50-200 atoms) are cut out of the enzyme [1,2,3,4]. The geometries are normally optimised with a split-valence basis set and energies are calculated on these geometries using polarised triple-zeta basis sets.…”

Section: Introductionmentioning

confidence: 99%

“…The geometries are normally optimised with a split-valence basis set and energies are calculated on these geometries using polarised triple-zeta basis sets. Typically, hybrid density-functional QM methods are employed and recently the importance of dispersion corrections has been emphasized [3,10,11,12]. Zero-point energies are estimated from vibrational frequencies and sometimes also entropic and thermal effects.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, some atoms are often fixed in the geometry optimisations to ensure that the geometry remains close to that in protein crystal structures. On the other hand, this means that entropies can no longer be obtained [3].The other approach is to use QM for a central active-site model of a similar size (50-200 atoms) but include the rest of the enzyme, as well as a number of explicit water molecules, at the molecular mechanics (MM) level of theory. In this QM/MM approach, QM and MM energies and forces are added, ensuring that no terms are double-counted [5,6,7,8].…”

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confidence: 99%

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Effect of Geometry Optimizations on QM-Cluster and QM/MM Studies of Reaction Energies in Proteins

Sumner

Söderhjelm

Ryde

2013

J. Chem. Theory Comput.

120

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We have examined the effect of geometry optimisation on energies calculated with the quantum-mechanical (QM) cluster, the combined QM and molecular-mechanics (QM/MM), the big-QM approaches (very large single-point QM calculations taken from QM/MMoptimised structures, including all atoms within 4.5 Å of the minimal active site, all buried charged groups in the protein, and truncations moved at least three residues away from the active site). We study a simple proton-transfer reaction between His-79 and Cys-546 in the active site of [Ni,Fe] hydrogenase and optimise QM systems of 50 different sizes (56-362 atoms). Geometries optimised with QM/MM are stable and reliable, whereas QM-cluster optimisations give larger changes in the structures and sometimes lead to large distortions in the active site if some hydrogen-bond partners to the metal ligands are omitted. Keeping 2-3 atoms for each truncated residue (rather than one) fixed in the optimisation improves the results, but does not solve all problems for the QM-cluster optimisations. QM-cluster energies in vacuum and a continuum solvent are insensitive to the geometry optimisations with a mean absolute change upon the optimisations of only 4-7 kJ/mol. This shows that geometry optimisations do not improve the convergence of QM-cluster calculations -there is still a ~60 kJ/mol difference between calculations in which groups have been added to the QM system according to their distance to the active site or based on QM/MM free-energy components. QM/MM energies do not show such a difference, but they converge rather slowly with respect to the size of the QM system, although the convergence is improved by moving away truncations from the active site. The big-QM energies are stable over the 50 different optimised structures, 57±1 kJ/mol, although some smaller trends can be discerned. This shows that both QM-cluster geometries and energies should be interpreted with caution. Instead, we recommend QM/MM for geometry optimisations and energies calculated by the big-QM approach.Key Words: Quantum mechanical cluster calculations, QM/MM, geometry optimisation, density-functional theory, [Ni,Fe] hydrogenase. 2 IntroductionDuring the latest two decades, quantum mechanical (QM) calculations have been established as an important and powerful complement to experiments for the study of biochemical reactions [1,2,3,4,5,6,7,8]. In particular, it has been shown that QM calculations can give structures of active sites with an accuracy that is better than what is obtained in lowand medium-resolution crystal structures [9], and they can provide structures of transition states of putative enzyme reactions, which are hard to study experimentally. The calculations also give energies of the transition states and intermediates, which can be used to compare different putative reaction mechanisms.Two approaches are used for such calculations. In the QM cluster approach, the most important residues of the active site (typically 50-200 atoms) are cut out of the enzyme [1,2,3,4]. The geom...

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Effect of Geometry Optimizations on QM-Cluster and QM/MM Studies of Reaction Energies in Proteins

Sumner

Söderhjelm

Ryde

2013

J. Chem. Theory Comput.

120

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“…[11] Proponents of the cluster models argue that these environmental effects converge relatively quickly with respect to the size of the QM model, after approximately 200 atoms. [12] However, other studies have show significant dependence of relative energies on QM system size up to 500-1000 atoms, with QM/MM models converging faster than cluster models. [13,14] These effects remain even after geometry optimization.…”

Section: Introductionmentioning

confidence: 97%

Protein effects in non-heme iron enzyme catalysis: insights from multiscale models

Vedin

Lundberg

2016

J Biol Inorg Chem

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PostprintThis is the accepted version of a paper published in Journal of Biological Inorganic Chemistry. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination. Citation for the original published paper (version of record):Vedin, N P., Lundberg, M. (2016) Protein effects in non-heme iron enzyme catalysis: insights from multiscale models. from second-sphere residues. The long-range electrostatic effects on reaction barriers are small for many systems. In the systems where large electrostatic effects have been reported, these lead to higher barriers. There is thus no evidence of any significant long-range electrostatic effects contributing to the catalytic efficiency of non-heme iron enzymes. However, the correct evaluation of electrostatic contributions is challenging, and the correlation between calculated residue contributions and the effects of mutation experiments is not very strong. The largest benefits of QM/MM models are thus the improved active-site geometries, rather than the calculation of accurate energies. Reported differences in mechanistic predictions between QM and QM/MM models can be explained by differences in hydrogen bonding patterns in and around the active site. Correctly constructed cluster models can give results with similar accuracy as those from multiscale models, but the latter reduces the risk of drawing the wrong mechanistic conclusions based on incorrect geometries and are preferable for all types of modeling, even when using very large QM parts. Journal of Biological Inorganic

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Computational modeling of redox enzymes

Siegbahn

2022

FEBS Letters

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A computational methodology is briefly described, which appears to be able to accurately describe the mechanisms of redox active enzymes. The method is built on hybrid density functional theory where the inclusion of a fraction of exact exchange is critical. Two examples of where the methodology has been applied are described. The first example is the mechanism for water oxidation in photosystem II, and the second one is the mechanism for N2 activation by nitrogenase. The mechanism for PSII has obtained very strong support from subsequent experiments. For nitrogenase, the calculations suggest that there should be an activation process prior to catalysis, which is still strongly debated.

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The quantum chemical cluster approach for modeling enzyme reactions

Cited by 262 publications

References 83 publications

Effect of Geometry Optimizations on QM-Cluster and QM/MM Studies of Reaction Energies in Proteins

Effect of Geometry Optimizations on QM-Cluster and QM/MM Studies of Reaction Energies in Proteins

Protein effects in non-heme iron enzyme catalysis: insights from multiscale models

Computational modeling of redox enzymes

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