Direct observation of ultrafast large-scale dynamics of an enzyme under turnover conditions

Aviram, Haim Yuval; Pirchi, Menahem; Mazal, Hisham; Barak, Yoav; Riven, Inbal; Haran, Gilad

doi:10.1073/pnas.1720448115

Cited by 104 publications

(168 citation statements)

References 38 publications

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“…The stabilization may also result in lower interconversion rate between open and closed states in stable mutants. This is in agreement with recent single-molecule FRET study in Adk where mutations that reduced the rate of interconversion also reduced the k cat (41).…”

Section: Discussionsupporting

confidence: 93%

Substrate inhibition imposes fitness penalty at high protein stability

Adkar

Bhattacharyya

Gilson

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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Proteins are only moderately stable. It has long been debated whether this narrow range of stabilities is solely a result of neutral drift toward lower stability or purifying selection against excess stability—for which no experimental evidence was found so far—is also at work. Here, we show that mutations outside the active site in the essential Escherichia coli enzyme adenylate kinase (Adk) result in a stability-dependent increase in substrate inhibition by AMP, thereby impairing overall enzyme activity at high stability. Such inhibition caused substantial fitness defects not only in the presence of excess substrate but also under physiological conditions. In the latter case, substrate inhibition caused differential accumulation of AMP in the stationary phase for the inhibition-prone mutants. Furthermore, we show that changes in flux through Adk could accurately describe the variation in fitness effects. Taken together, these data suggest that selection against substrate inhibition and hence excess stability may be an important factor determining stability observed for modern-day Adk.

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Section: Discussionsupporting

confidence: 93%

Substrate inhibition imposes fitness penalty at high protein stability

Adkar

Bhattacharyya

Gilson

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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“…Aside from accelerating certain biochemical reactions, enzymes also inhibit undesired, off-pathway reactions involving highly reactive intermediate species (2). The collective dynamics of enzyme and substrate are often tightly coupled to the catalytic cycle (3)(4)(5)(6). For example, substrate binding can shift the enzyme's conformational distribution to structurally and electrostatically re-organize the active site.…”

Section: Introductionmentioning

confidence: 99%

Mix-and-inject XFEL crystallography reveals gated conformational dynamics during enzyme catalysis

Dasgupta

Budday

Oliveira

et al. 2019

Preprint

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Post-translational modification of cysteine residues can regulate protein function and is essential for catalysis by cysteine-dependent enzymes. Covalent modifications neutralize charge on the reactive cysteine thiolate anion and thus alter the active site electrostatic environment. Although a vast number of enzymes rely on cysteine modification for function, precisely how altered structural and electrostatic states of cysteine affect protein dynamics remains poorly understood.Here we use X-ray crystallography, computer simulations, and enzyme kinetics to characterize how covalent modification of the active site cysteine residue in isocyanide hydratase (ICH) affects the protein conformational ensemble. ICH exhibits a concerted helical displacement upon cysteine modification that is gated by changes in hydrogen bond strength between the cysteine thiolate and the backbone amide of the highly strained residue Ile152. The mobile helix samples alternative conformations in crystals exposed to synchrotron X-ray radiation due to the X-rayinduced formation of a cysteine-sulfenic acid at the catalytic nucleophile (Cys101-SOH). This oxidized cysteine residue resembles the proposed thioimidate intermediate in ICH catalysis. Neither cysteine modification nor helical disorder were observed in X-ray free electron laser (XFEL) diffraction data. Computer simulations confirm cysteine modification-gated helical motion and show how structural changes allosterically propagate through the ICH dimer. Mutations at a Gly residue (Gly150) that modulate helical mobility reduce the ICH catalytic rate and alter its presteady state kinetic behavior, establishing that helical mobility is important for ICH catalytic efficiency. Our results suggest that cysteine modification may be a common and likely underreported means for regulating protein conformational dynamics. Figure 2: Cys101 oxidation leads to a weakening of the Ile152-Cys101 H-bond. Electrostatic Poisson-Boltzmann surfaces (red negative, blue positive charge) calculated from the Cys101-Ile152 (A) and Cys-SOH-Ile152 (B) environments. Cysteine photooxidation neutralizes the negative charge of the sulfur atom, weakening the N-H … S hydrogen bond. (C-E) Schematic showing covalent modification of Cys101 weakens the hydrogen bond (red dotted/dashed line) to Ile152 and allows relaxation of backbone strain (curved arrow). (F) The catalytic thioimidate covalent intermediate resembles photooxidized Cys101-SOH. Both modifications neutralize negative charge on Cys Sγ.

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“…In contrast to D152, however, this shift leads to a proportional reduction of the enzymatic activity, suggesting that the effect of V164R is more directly linked to the minoration of the dynamics of the open:close cycle. [33]. They propose that numerous cycles of conformational rearrangements, occurring on time scales 100-200 times faster than the turnover rate, are required to find the optimal orientation of substrates.…”

Section: Discussionmentioning

confidence: 99%

“…Whilst our results agree with Kovermann et al [32] who found that an arrested closed conformation reduced catalytic activity, we can't fully conclude that there is a causal relationship. Aviram et al [33] have shown that there is a relationship between the domain opening and closing times that can measurably modulate enzymatic activity, however, this doesn't extend to the open and closed equilibrium.…”

Section: Computational Arginine Scan Identifies Distinct Mutations Anmentioning

confidence: 99%

Unsupervised Graph-Based Learning Predicts Mutations That Alter Protein Dynamics

Peach

Saman

Yaliraki

et al. 2019

Preprint

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Proteins exhibit complex dynamics across a vast range of time and length scales, from the atomistic to the conformational. Adenylate kinase (ADK) showcases the biological relevance of such inherently coupled dynamics across scales: single mutations can affect large-scale protein motions and enzymatic activity. Here we present a combined computational and experimental study of multiscale structure and dynamics in proteins, using ADK as our system of choice. We show how a computationally efficient method for unsupervised graph partitioning can be applied to atomistic graphs derived from protein structures to reveal intrinsic, biochemically relevant substructures at all scales, without re-parameterisation or a priori coarse-graining. We subsequently perform full alanine and arginine in silico mutagenesis scans of the protein, and score all mutations according to the disruption they induce on the large-scale organisation. We use our calculations to guide Förster Resonance Energy Transfer (FRET) experiments on ADK, and show that mutating residue D152 to alanine or residue V164 to arginine induce a large dynamical shift of the protein structure towards a closed state, in accordance with our predictions. Our computations also predict a graded effect of different mutations at the D152 site as a result of increased coherence between the core and binding domains, an effect confirmed quantitatively through a high correlation (R 2 = 0.93) with the FRET ratio between closed and open populations measured on six mutants.

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Direct observation of ultrafast large-scale dynamics of an enzyme under turnover conditions

Cited by 104 publications

References 38 publications

Substrate inhibition imposes fitness penalty at high protein stability

Substrate inhibition imposes fitness penalty at high protein stability

Mix-and-inject XFEL crystallography reveals gated conformational dynamics during enzyme catalysis

Unsupervised Graph-Based Learning Predicts Mutations That Alter Protein Dynamics

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