Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation

Yang, Zhongyue; Mehmood, Rimsha; Wang, Mengyi; Qi, Helena W.; Steeves, Adam H.; Kulik, Heather J.

doi:10.1039/c8re00213d

Cited by 45 publications

(56 citation statements)

References 151 publications

(216 reference statements)

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“…Average and maximum values of CC magnitudes are not strongly sensitive to residue type, but they are, as expected, higher for charged and polar residue interactions than for those involving nonpolar residues (ESI Table S15). For the special case of the six Cys residues involved in stabilizing disulfide bonds in mini-CD4, we observe even lower average CC magnitudes than those for nonpolar residues, consistent with earlier observations [124][125] that sidechains that form strong bonds exhibit reduced crosscorrelations (ESI Tables S15-S16).…”

Section: B Linear Coupling Of Residue Charge Distributionssupporting

confidence: 89%

“…by summing the Mulliken partial charges, q i , of all backbone and sidechain atoms within each amino acid residue, as in prior work 35,76,[124][125] . Taking this sum over the entire residue minimizes sensitivity to partial charge scheme, yielding comparable results on test systems with alternative real space [141][142][143] partitioning schemes (ESI Table S7).…”

Section: A Residue Charge Distributionsmentioning

confidence: 99%

“…500 atoms treated at the QM level with range-separated hybrid DFT and showed that catalysis-facilitating charge transfer at the active site was influenced by fluctuations in charge distributions of residues distant from the active site. [124][125] Proteins are not just flexible but undergo concerted changes in shape, meaning that the motions of residues (e.g., changes in positions of Cα atoms or dihedral angles) are coupled.…”

Section: Introductionmentioning

confidence: 99%

“…The same techniques that have provided valuable insight into concerted geometric motions in proteins, i.e., the linear cross-correlation and mutual information, may help to describe the length-scale and nature of electronic coupling in proteins. Although some analysis of electronic properties has been leveraged to understand dynamic events in materials [129][130][131] , interpret QM/MM simulations 76,121,125 , or to guide QM method selection 132 , it has not been applied to the charge coupling obtained from ab initio molecular dynamics (AIMD) of entire proteins.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying the Long-Range Coupling of Electronic Properties in Proteins with Ab Initio Molecular Dynamics

Yang¹,

Hajlasz²,

Steeves³

et al. 2020

Preprint

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A delicate interplay of covalent and noncovalent interactions gives proteins their unique ability to flexibly play numerous roles in cellular processes. This interplay is inherently quantum mechanical and highly dynamic in nature. To directly interrogate the evolving nature of the electronic structure of proteins, we carry out 100-ps-scale <i>ab initio</i> molecular dynamics simulations of three representative small proteins with range-separated hybrid density functional theory. We quantify the nature and length-scale of the coupling of residue-specific charge probability distributions in these proteins. While some nonpolar residues exhibit expectedly narrow charge distributions, most polar and charged residues exhibit broad, multimodal distributions. Even for nonpolar residues, we observe sequence-specific deviations corresponding to charge accumulation or depletion that would be challenging to capture in a fixed charge force field. We quantify the effect of residue–residue interactions on charge distributions first with linear cross-correlations. We then show how additional insight can be gained from evaluating the mutual information of charge distributions. We show that a significant number of residues couple most strongly with residues that are distant in both sequence and space over a range of secondary structures including a-helical, b-sheet, disulfide bridging, and lasso motifs. The mutual information analysis is necessary to capture coupling between some polar and charged residues. These analyses are expected to be broadly useful in understanding the mechanisms of long-range charge transfer in proteins and for determining what interactions require a quantum mechanical description for predictive simulation of enzyme mechanism and protein function.

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Section: B Linear Coupling Of Residue Charge Distributionssupporting

confidence: 89%

Section: A Residue Charge Distributionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quantifying the Long-Range Coupling of Electronic Properties in Proteins with Ab Initio Molecular Dynamics

Yang¹,

Hajlasz²,

Steeves³

et al. 2020

Preprint

Self Cite

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show abstract

“…On the other hand, the model that is constructed according to the guideline, δρ(I)/δv(J)<0.01, the core part is described with the correct surrounding effects such as hydrogen bonds and the hyperconjugation effects. In fact, almost all models that are employed by most QM/MM researchers seem to satisfy this criterion [5,6,7,8,9,10,11,12,13,14,15,16,17,50,51]. As shown Figure 15c, the criterion, δρ(I)/δv(J)<0.001, leads to a greater number of interaction islands, which interconnect among units, and so, in other words, it requires a large QM region.…”

Section: Resultsmentioning

confidence: 99%

Linear Response Functions of Densities and Spin Densities for Systematic Modeling of the QM/MM Approach for Mono- and Poly-Nuclear Transition Metal Systems

et al. 2019

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We applied our analysis, based on a linear response function of density and spin density, to two typical transition metal complex systems-the reaction centers of P450, and oxygen evolving center in Photosystem II, both of which contain open-shell transition metal ions. We discuss the relationship between LRF of electron density and spin density and the types of units and interactions of the systems. The computational results are discussed in relation to quantum mechanics (QM) cluster and quantum mechanics/molecular mechanics (QM/MM) modeling that are employed to compute the reaction centers of enzymes.

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Quantifying the Long‐Range Coupling of Electronic Properties in Proteins with ab initio Molecular Dynamics**

et al. 2021

Self Cite

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The delicate interplay of covalent and non-covalent interactions in proteins is inherently quantum mechanical and highly dynamic in nature. To directly interrogate the evolving nature of the electronic structure of proteins, we carry out 100-ps-scale ab initio molecular dynamics simulations of three representative small proteins with range-separated hybrid density functional theory. We quantify the nature and length-scale of the coupling of residue-specific charge probability distributions in these proteins. While some nonpolar residues exhibit expectedly narrow charge distributions, most polar and charged residues exhibit broad, multimodal distributions. Even for nonpolar residues, we observe sequence-specific deviations correspond-ing to charge accumulation or depletion that would be challenging to capture in a fixed charge force field. We quantify the effect of residue-residue interactions on charge distributions first with linear cross-correlations. We then show how additional insight can be gained from evaluating the mutual information of charge distributions. We show that a significant number of residues couple most strongly with residues that are distant in both sequence and space over a range of secondary structures including α-helical, β-sheet, disulfide bridging, and lasso motifs. The mutual information analysis is necessary to capture coupling between some polar and charged residues that would be otherwise missed.

show abstract

Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation

Abstract: Large scale quantum mechanical simulation systematically reveals length scales over which electronically driven interactions occur at enzyme active sites.

Cited by 45 publications

References 151 publications

Quantifying the Long-Range Coupling of Electronic Properties in Proteins with Ab Initio Molecular Dynamics

Quantifying the Long-Range Coupling of Electronic Properties in Proteins with Ab Initio Molecular Dynamics

Linear Response Functions of Densities and Spin Densities for Systematic Modeling of the QM/MM Approach for Mono- and Poly-Nuclear Transition Metal Systems

Quantifying the Long‐Range Coupling of Electronic Properties in Proteins with ab initio Molecular Dynamics**

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