(βα)8-barrel enzyme indole-3-glycerol phosphate synthase

that in both cases, namely the application of activating mutations and temperature increase, the net rise of the catalytic turnover number is afforded...
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Relationship of catalysis and active site loop dynamics in the (##)-barrel enzyme indole-3-glycerol phosphate synthase 8

Sandra Schlee, Thomas Klein, Magdalena Schumacher, Julian Nazet, Rainer Merkl, Heinz-Juergen Steinhoff, and Reinhard Sterner Biochemistry, Just Accepted Manuscript • DOI: 10.1021/acs.biochem.8b00167 • Publication Date (Web): 02 Mar 2018 Downloaded from http://pubs.acs.org on March 3, 2018

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Biochemistry

Relationship of catalysis and active site loop dynamics in the (β βα)8-barrel enzyme indole-3-glycerol phosphate synthase Sandra Schlee,§ Thomas Klein,§ Magdalena Schumacher,⊥ Julian Nazet,§ Rainer Merkl,

§

Heinz-Jürgen Steinhoff, ,⊥ and Reinhard Sterner*,§

§

Institute

of

Biophysics

and

Physical

Biochemistry,

University

of

Regensburg,

Universitätsstrasse 31, D-93053 Regensburg, Germany;



Department of Physics, University of Osnabrück, Barbarastr. 7, D-49076 Osnabrück,

Germany.

*Corresponding author: Reinhard Sterner Phone: +49-941-943 3015; FAX: +49-941-943 2813; Email: [email protected]

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ABSTRACT

It is important to understand how the catalytic activity of enzymes is related to their conformational flexibility. We have studied this activity-flexibility correlation using the example of indole-glycerol-phosphate synthase from Sulfolobus solfataricus (ssIGPS), which catalyzes the fifth step in the biosynthesis of tryptophan. ssIGPS is a thermostable representative of enzymes with the frequently encountered and catalytically versatile (βα)8barrel fold. Four variants of ssIGPS with increased catalytic turnover numbers were analyzed by transient kinetics at 25°C, and wild-type ssIGPS was likewise analyzed both at 25°C and at 60°C. Global fitting with a minimal three-step model provided the individual rate constants for substrate binding, chemical transformation, and product release. The results showed that in both cases, namely the application of activating mutations and temperature increase, the net rise of the catalytic turnover number is afforded by acceleration of the product release rate relative to the chemical transformation steps. Measurements of the solvent viscosity effect at 25°C versus 60°C confirmed this change of the rate-determining step with temperature, which is in accordance with a kink in the Arrhenius diagram of ssIGPS at about 40°C. When plotting rotational diffusion rates of electron paramagnetic spin labels attached to the active site loop β1α1 in form of an Arrhenius diagram, kinks are observed at the same temperature. These findings, together with molecular dynamics simulations, demonstrate that a different degree of loop mobility correlates with different rate-limiting steps in the catalytic mechanism of ssIGPS.

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Biochemistry

INTRODUCTION Enzymes accelerate chemical reactions by many orders of magnitude1 and the question what makes them such outstanding catalysts has intrigued biochemists for many decades. Although an enormous array of crystal structures with bound substrate (analogues) reveal the identity and positions of functional groups arranged in the active sites, this information is insufficient to understand catalysis. This problem is, for example, reflected in the limited success of computational enzyme design: In spite of some encouraging progress in this field, catalytic efficiencies of artificial enzymes are generally many orders of magnitude lower than those of natural enzymes.2-4 It has been postulated that one of the keys for enzyme catalysis, which is not sufficiently accounted for in enzyme design algorithms, lies in the flexibility and intrinsic dynamics of the polypeptide chain.5-9 Indeed, it is well known that many enzymes change conformation significantly as an intrinsic part of their catalytic cycles.10-12 For example, nuclear magnetic resonance (NMR) relaxation experiments have shown that enzyme motions can be critical for optimizing the active site13-16, enable effective substrate or product binding/release17 or facilitate trapping of reactive intermediates. Characterizing the time and distance scales of molecular motions is thus important for comprehension of enzymatic catalysis and for efficient enzyme design18 as well as for benchmarking and fine-tuning molecular dynamics simulations. The (β/α)8- or TIM-barrel is the most common single-domain enzyme fold in nature, with about 10% of structurally characterized proteins containing at least one domain with this fold.19 (β/α)8-barrel enzymes occur in five of the six primary classes as defined by the enzyme commission (EC)20 and they catalyze a wide range of unrelated reactions.21 The core of the (β/α)8-barrel structure is composed of eight β-strands forming a curved central 3 ACS Paragon Plus Environment

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parallel β-barrel, which is surrounded by eight α-helices. The β-strands and α-helices are linked by βα-loops, which often accommodate residues that are important for substrate binding and catalysis. The remainder of the fold, including the αβ-loops, is important for conformational stability.21-23 This structural separation of a catalytic face from a stability face make (βα)8-barrel enzymes ideal scaffolds for protein design3, 24, 25 and for evaluating the role of loop dynamics in enzyme function.26, 27 Prototypic triosephosphate isomerase (TIM) provided the first clear evidence that loop dynamics play important roles in enzyme catalysis of (β/α)8-barrel enzymes. TIM catalyzes the reversible isomerization of dihydroxyacetone phosphate to D-glyceraldehyde 3phosphate, while suppressing the elimination of orthophosphate.28 Structural studies have highlighted the importance of two flexible loops (loop β6α6 and loop β7α7), which move between open and closed conformations.29, 30 The most important effect of loop closure in TIM is to extrude water from the active site. This causes a decrease in the effective dielectric constant, such that the pKa-value of the carboxylate side chain of the catalytic glutamate base

is

increased

dramatically.31-34

Accordingly,

temperature-dependent

NMR

measurements in the presence of substrate or substrate analogues revealed that loop motions are partially rate-limiting for the chemical steps of this reaction in both directions.3537

Here we study another (βα)8-barrel enzyme, namely indole-3-glycerol phosphate synthase from the hyperthermophile Sulfolobus solfataricus (ssIGPS) (Figure 1A). IGPS catalyzes the ring closure of 1-(o-carboxyphenylamino)-1-deoxyribulose-5-phosphate (CdRP) into indole-3glycerol phosphate (IGP) (Figure 1B) in the fifth step of the tryptophan biosynthetic pathway.

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Biochemistry

FIGURE 1: Structure of the ssIGPS enzyme and catalyzed reaction. (A) Ribbon diagram of ssIGPS with substrate CdRP (blue) (PDB entry 1LBL) and product IGP (cyan) (PDB entry 1A53). The β1α1-loop is colored in yellow; the variant D61C was generated for spin labeling to monitor dynamics of the β1α1loop. Residues essential for catalysis (E51, K53 and K110) are colored orange. Residues substituted in variants with increased catalytic activity (G212E, L236Q, M237T and F246S) are highlighted in red. (B) The enzyme catalyzes a ring closure reaction of the substrate CdRP to the product IGP. The chemical reaction consists of a sequence of condensation, decarboxylation, and dehydration. Chemical reduction of CdRP by borohydride produces the substrate analogue rCdRP.

The enzymatic mechanism of ssIGPS is based on acid/base catalysis, where Lys110 in βstrand 3 acts a general acid to protonate the C2´ carbonyl of CdRP, mediating ring closure and decarboxylation. During the subsequent dehydration step, Glu51 and Lys53 in the β1α1loop act as the general base and acid, respectively.38, 39 Crystal structures of ssIGPS illustrate 5 ACS Paragon Plus Environment

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that two adjacent but distinct hydrophobic pockets are involved in binding of substrate CdRP and product IGP38 (Figure 1A). Moreover, the analysis of three different crystal forms of ssIGPS has revealed large deviations in the Cα positions between Pro57 and Glu63, suggesting the population of at least two distinct low-energy conformations for loop β1α1 (comprising residues Lys53-Asp65).40 Also, it was proposed that the ring closure and dehydration steps in the chemical transformation are catalyzed by distinct active-site surfaces39, which implies that following decarboxylation the reaction intermediate must undergo a rearrangement in the active site. Motions of ssIGPS, including those of the β1α1loop, may facilitate this process. We have previously monitored conformational transitions of this loop by fluorophore-labeling at position Asp61.41 Dyes attached to this position reported on a substrate-induced conformational switch and conformational changes during chemical transformation on the same timescale as enzyme catalysis. We have also shown that product release or a conformational change of the enzyme during product release is the rate-determining step at 25°C.41 Using solvent viscosity and kinetic isotope effects, Boehr and co-workers demonstrated that at 60°C, a proton transfer event in the chemical transformation becomes rate-determining.42 This indicates that a fine balance between enzyme dynamics and rates of chemical steps has evolved to control enzymatic turnover in ssIGPS. Within the current work, we have analyzed four variants of ssIGPS with increased turnover numbers and the wild-type enzyme by steady-state and pre-steady state kinetics, molecular dynamics simulation, and electron paramagnetic resonance (EPR) spectroscopy to show that different rate-determining steps of ssIGPS catalysis are correlated with different dynamics of its β1α1-loop.

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Biochemistry

MATERIALS AND METHODS Synthesis of CdRP. CdRP was synthesized chemically according to a modified protocol43 by incubating anthranilic acid with ribose 5-phosphate for 20 h in the dark. The resulting yellow solution was mixed with a tenfold excess of water and stirred for 1 h. Unreacted anthranilic acid was removed by extraction with ethyl acetate; ethyl acetate traces in the aqueous phase were removed using nitrogen flow. The resulting CdRP preparation was applied to a POROS HQ-20 column (Thermo Scientific) and CdRP was eluted by a linear gradient of 0.052.0 M Tris-acetate, pH 8.0, using an ÄKTA prime FPLC system (GE Healthcare). Fractions containing CdRP were pooled and stored at -80°C.

Site-directed Mutagenesis, Overexpression, and Purification of ssIGPS. The gene encoding ssIGPS, sstrpC, was cloned into the pET21a(+) plasmid (Stratagene) using the restriction sites for NheI and XhoI. Consequently, the recombinant ssIGPS protein carries a C-terminal hexahistidine tag. Site-directed mutagenesis to generate ssIGPS variants G212E, L236Q, M237T, F246S, and D61C were performed using overlap extension PCR44 with the plasmid pET21a(+)-sstrpC as a template and appropriate primers. All sequences were confirmed through DNA sequencing (SEQLAB). Overexpression and purification of wild-type and variant

ssIGPS enzymes was performed similarly as described.41 Enzyme concentrations were determined by measuring the absorbance at 280 nm, using a molar extinction coefficient of 17210 M-1cm-1 as calculated from the amino acid sequence.45

Site-directed Spin Labeling. The ssIGPS variantD61C was applied to a Ni-NTA affinity column (His Trap FF crude, GE Healthcare) and washed with 100 mM KP, pH 7.5, 0.5 mM DTT to reduce the cysteine side chain. The reducing agent was removed by washing with 100 mM KP, pH 7.5, 300 mM KCl (wash buffer). To attach the probes, a 10-fold molar excess of the spin labels (1-oxyl-2,2,5,5,-tetramethylpyrroline-3-methyl)-methanethiosulfonate (MTSSL) 7 ACS Paragon Plus Environment

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(Cayman Chemical Company) or N-(1-oxyl-2,2,5,5-tetramethyl-3-pyrrolidinyl)maleimide (MP) (Santa Cruz Biotechnology) dissolved in dimethyl sulfoxide was applied to the Ni-NTA affinity column in one column volume of wash buffer and incubated for 12 h at 4°C. The affinity column was washed to remove free label, and spin labeled protein was eluted using a linear imidazole gradient (50 mM – 1 M). Spin labeled proteins were dialyzed against 50 mM KP, pH 7.5, and stored at -80°C. Spin label efficiency was about 50 % for MTSSL and in the range of 65 – 100 % for MP spin labels. Catalytic activity of spin-labeled proteins equaled activity of the unlabeled protein within experimental error.

Steady-State Enzyme Kinetics. Steady-state enzyme assays for ssIGPS followed previously established procedures.41,

46

In short, ssIGPS activity was measured via fluorescence by

monitoring the formation of IGP from CdRP. IGP was excited at 280 nm and emission measured at 350 nm. In order to determine the turnover number (kcat) and the Michaelis constant (KM), initial rate data were fitted to the Michaelis-Menten equation (Eq. 1) using non-linear regression with the program SigmaPlot (Systat Software):

v  k cat /ET S/K M + S

(1)

v is the initial reaction velocity, ET is the total amount of enzyme in the assay, and [S] is the substrate concentration. Effects of temperature and solvent viscosity were determined by varying the buffer conditions of the standard assay. Arrhenius plots (ln kcat versus 1/T) were generated using the observed rate constants from temperature dependence kinetics assays. The temperature dependence of the pKa-value of the buffer (50 mM HEPES, 4 mM EDTA, ∆pKa/∆°C = -0.014) was taken into account, when adjusting pH 7.5 of the buffer at different temperatures.

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Biochemistry

Solvent viscosity effects (SVE) were determined using enzyme assays in 50 mM HEPES, pH 7.5, 4 mM EDTA, with glycerol (0 - 35 % (w/v)) as the viscogen. The relative viscosities (ηi/η0) of buffers containing different concentrations of glycerol (0, 5, 10, 20, and 35 % (w/v)) at 25°C and 60°C were taken from literature.47 SVEs were obtained from the slope of a plot of relative viscosity versus rate0/rateviscogen.

Transient Kinetics and Global Fitting Analysis. Stopped-flow studies were performed in 50 mM HEPES, pH 7.5, 4 mM EDTA at the indicated temperature (25°C or 60°C) using the SX20 instrument (Applied Photophysics). Tryptophan/IGP fluorescence was excited at 280 nm (LED light source), and the increase in fluorescence emission was recorded over time using a 335 nm cutoff filter. Single turnover concentration series were measured by mixing 1.0 µM of CdRP with [0, 1.0, 2.5, 5.0, 10, 15] µM of the respective ssIGPS variant at 25°C or with [0, 1.0, 2.5, 5.0, 7.5] µM wild-type ssIGPS at 60°C in a 1:1 volume ratio (concentrations denote final concentrations in the observation cell). Multiple turnover concentration series were measured by mixing [0, 25, 50, 100, 250, 500] nM of the respective ssIGPS variant with 3 µM CdRP (wild-type) or with 14 µM CdRP (variants L236Q, M237T, F246S) at 25°C or 60°C. CdRP concentration was adapted according to KMCdRP-values of variants to ensure substrate saturation throughout the experiments. At least five individual traces were recorded at each condition and averaged. Pre-steady-state data from single turnover and multiple turnover experiments were fit to a three-state kinetic model by an iterative, global fitting process using DynaFit (BioKin).48 All rate constants (k1, k-1, k2, k-2, k3, and k-3) and the associated differential response coefficients (rES, rEP, and rP) were optimized in the fit.

Molecular Dynamics Simulations. Molecular Dynamics (MD) simulations were calculated by means of GROMACS49 (version 5.1.2) and the AMBER0350 force field. Structures were placed 9 ACS Paragon Plus Environment

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in a rectangular water box; the simulation cell was at least 5 Å larger than the solute along each axis. The system was neutralized by adding NaCl ions. To prepare the production run, the solvated system was at first energy minimized by a maximum of 5000 steps of steepest descent MD minimization followed by a two-part equilibration phase (each lasted 50 ps). These were an NVT simulation followed by an NPT simulation.51 Finally, the production run (NVT conditions, time step 1 fs) was started at 298 K and ran for 860 ns, generating a snapshot every 0.2 ns. During the simulation, the temperature was kept constant at 298 K by using a Berendsen thermostat. For each simulation, the root mean square fluctuation (RMSF) value was deduced from the snapshots for each Cα-atom, which represents the deviation from the mean position. The RMSF values were averaged and mapped onto the corresponding residues of the 3D structures.

Continuous Wave (cw) EPR Spectroscopy. Previous to EPR measurements ssIGPS was washed with 50 mM HEPPS, pH 7.5, 4 mM EDTA, and 20 μl of the sample were filled into EPR glass capillaries (0.9 mm inner diameter) with a final concentration of 100 μM protein and 300 μM of CdRP, IGP, or rCdRP. Temperature dependent cw EPR spectra of ssIGPS samples were recorded with homemade X-band EPR spectrometers equipped with a dielectric resonator, MD-5 (Bruker), using a microwave power of 0.5 mW or 0.9 mW. The magnetic field was measured with a RMN-2 B-field meter (Drusch) or an ER 032 M field controller (Bruker). B-field modulation was set to 0.15 mT and temperature was controlled by a liquid flow cryostat (10% ethylene glycole, 90% water) in the range of 5°C - 60°C. One to five averages per sample were recorded.

Spectra Simulations. Data were analyzed using the fitting program ‘MultiComponent’ (written by Christian Altenbach (University of California, Los Angeles) in LabVIEW (National Instruments)

and

available

freely

from

the

following

site: 10

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Biochemistry

http://www.chemistry.ucla.edu/directory/hubbell-wayne-l"). The fitting program is based on the numerical solution of the stochastic Liouville equation.52, 53 The Levenberg-Marquardt algorithm as well as the Lelder-Mead algorithm were applied. During fitting the g-tensor and the hyperfine tensor components, Axx and Ayy, were held fixed (MTSSL: gxx = 2.0084, gyy = 2.0061, gzz = 2.0022, Axx = 0.52 mT, Ayy = 0.45 mT; MP spin label: gxx = 2.0079, gyy = 2.0054, gzz = 2.003, Axx = 0.75 mT, Ayy = 0.75 mT), whereas Azz, line width W, and the rotational diffusion tensor R, were variable. For non-interacting solvent-exposed MTSSL side chains it has been shown that spectra are adequately fit by a model of axial symmetric reorientation motion, characterized by two rotational diffusion rates, R∥ and R⊥, and the angle between the symmetry axis and the nitroxide p-orbital, βD = 36°.54 For the present samples best fits could be achieved with a slightly increased diffusion tilt angle βD of 40° for both spin labels (see

Figure S2), without application of any ordering potential. The values of the activation energy were determined from the temperature dependence of the averaged rates, = (R∥∙R⊥2)1/3, the apparent re-orientational correlation time is given by τ = (6)-1.

RESULTS AND DISCUSSION Kinetic Mechanism of Activated ssIGPS Variants. In a directed evolution approach, Kirschner and co-workers have used in vivo complementation of a tryptophan-auxotrophic Escherichia

coli ∆sstrpC strain to isolate variants of ssIGPS with increased enzymatic activity at 37°C 55. We chose four single-site variants from this study, G212E, L236Q, M237T, and F246S (Figure

1A), for a detailed kinetic characterization. These variants supported the fastest growth rates in the complementation studies. According to their position in the crystal structure, three of the substitutions are likely to interfere with phosphate binding. The amide proton of G212 in loop β7α7 forms a hydrogen bond with one of the phosphate oxygens, whereas the 11 ACS Paragon Plus Environment

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negatively charged side chain of G212E should repel the bound phosphate. Moreover, substitutions L236Q and M237T are likely to destabilize helix α8´, which interacts via its positive dipole with another phosphate oxygen. M237 has previously been identified as component of a hydrogen bond network involving R64 and D65 on the β1α1-loop.56, 57 The F246S substitution at the C-terminus presumably promotes fraying at the C-terminal end, thereby increasing the flexibility of the rigid structure of ssIGPS. The recombinantly produced ssIGPS variant proteins were purified to homogeneity and corresponding steady-state kinetic constants of the IGPS reaction were determined at 25°C by a fluorimetric assay. The steady-state parameters are listed in Table 1.

Table 1. Steady-state kinetic parameters for wild-type ssIGPS and activated variants at 25°C. Variant kcat (s-1) KM (µM) kcat/KM (M-1 s-1) wt 0.11 ± 0.02a 0.085 ± 0.015 1.18 x 106 G212E 0.16 ± 0.025 21.7 ± 5.1 > 0.01 x 106 L236Q 0.20 ± 0.009 3.4 ± 0.3 0.06 x 106 M237T 0.23 ± 0.016 2.9 ± 0.4 0.08 x 106 F246S 0.32 ± 0.014 1.3 ± 0.1 0.24 x 106 a Error in regression.

In accordance with published data55 substitutions primarily affected KM values, which increased from 15-fold (F246S) up to 255-fold (G212E). A 2- to 3-fold increase in the turnover number of the variants (kcat) resulted in significantly decreased catalytic efficiencies (kcat/KM), confirming that variants must have been selected for increased values of kcat rather than for improved catalytic efficiency. To elucidate the mechanistic basis of accelerated catalytic turnover in the ssIGPS variants, rate constants of individual steps in the catalytic reaction were determined in pre-steadystate measurements. Kinetics of the ssIGPS variants were recorded under single and multiple 12 ACS Paragon Plus Environment

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Biochemistry

turnover conditions in a stopped-flow instrument by monitoring the fluorescence change upon conversion of the substrate CdRP to the product IGP. Single turnover kinetics were measured after a constant concentration of CdRP had been mixed with a molar excess of ssIGPS. Representative transients feature biphasic progressions for all ssIGPS variants with the exception of G212E (Figure 2A). Due to its extremely low substrate affinity, this variant was excluded from further studies.

FIGURE 2: Single turnover and multiple turnover kinetics of wild-type ssIGPS and activated variants at 25°C. (A) Under single turnover conditions kinetic traces monitoring Trp/IGP fluorescence (excitation: 280 nm, emission cutoff: 335 nm) were recorded in a stopped-flow apparatus after mixing 1.0 µM CdRP with an excess of enzyme (15 µM). (B) Under multiple turnover conditions kinetic traces were recorded after mixing 0.5 µM enzyme with an excess of CdRP (3 µM for wild-type ssIGPS and 14 µM for L236Q, M237T and F246S). Concentrations are final concentrations in the observation cell.

As allocated for wild-type ssIGPS41 the first phase with negative signal amplitude represents formation of the enzyme-substrate complex, which is associated with a change in intrinsic tryptophan fluorescence. The second phase in the single turnover curves with large positive signal amplitude relates to formation of the fluorescent product IGP. Multiple turnover experiments were performed by mixing different concentrations of ssIGPS with a molar 13 ACS Paragon Plus Environment

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excess of CdRP. Representative traces document differences in curve shapes between wildtype ssIGPS and the activated variants (Figure 2B). Whereas the trace corresponding to wildtype ssIGPS featured a distinct burst followed by a steady-state phase, the activated variants do not show a product burst. Datasets recorded in stopped-flow experiments under single and multiple turnover conditions were analyzed in global fitting approaches according to a simple three-step kinetic model (Scheme 1). Scheme 1 k1

IGPS + CdRP

IGPS:CdRP k-1

k2

IGPS:IGP

k3

IGPS + IGP

k-3

This mechanism implies that upon binding of CdRP the intrinsic fluorescence of the enzyme changes, chemistry occurs, and IGP is released while the enzyme returns back to the resting fluorescent state. The mechanism depicts a simplification of the actual kinetic mechanism, as the three chemical steps, condensation, decarboxylation, and dehydration, were merged to one irreversible chemical transformation step. In addition, an induced-fit-type binding mechanism was established for wild-type ssIGPS, where a conformational change of the β1α1-loop is associated with binding of the substrate CdRP.41 However, conformational changes were not rate-limiting and could only be uncovered in pre-steady-state measurements with extrinsic fluorophores attached to the β1α1-loop. Therefore, analysis of turnover data with the simplified mechanism shown in Scheme 1 should yield net rate constants for substrate binding/release (k1/k-1), the chemical transformation step (k2) and product release/binding (k-3/k3).

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Biochemistry

The agreement of data and fit is shown for the F246S variant in Figure S1. A global analysis with the integrated form of the equation yielded values for rate constants of individual steps in the mechanism, which are summarized in Table 2. Table 2. Kinetic rate constants derived from the global fitting analysis of single- and multiple-turnover transients to the three-step mechanism shown in scheme 1. Variant T (°C) k1 (µM-1s-1) k-1 (s-1) k2 (s-1) k3 (s-1) k-3 (µM-1s-1) wt 25 1.7 ± 0.03 < 0.5 1.3 ± 0.01 0.3 ± 0.01 6.0 ± 0.17 L236Q 25 0.2 ± 0.01 0.03 0.6 ± 0.01 3.4 ± 0.95 6.0 ± 1.40 M237T 25 0.2 ± 0.01 < 0.2 0.7 ± 0.02 1.2 ± 0.12 5.9 ± 0.25 F246S 25 0.3 ± 0.01 < 0.2 0.9 ± 0.03 3.1 ± 0.31 6.0 ± 0.46 < 0.2 wt 60 9.8 ± 0.2 9.6 ± 0.08 11.6 ± 0.15 43 ± 1.2

Rate constants for substrate binding (k1), the chemical transformation step (k2), and product release/binding (k-3/k3) could be identified in the global fitting analysis; for the substrate dissociation rate constant (k-1) an upper limit could be determined. In comparison to wildtype ssIGPS the rates of substrate binding (k1) are diminished by a factor 6 - 9, which is in accordance with the reduced CdRP affinity. The rates of product release (k3) for the activated variants are accelerated by a factor 4 - 11, whereas the rates of the chemical transformation (k2) are reduced about 2-fold. As a consequence, in contrast to wild-type ssIGPS, product release is not the rate-determining step in the kinetic mechanism of the ssIGPS variants, in accordance with the absence of a burst phase in multiple turnover experiments. Instead, the chemical transformation step has become rate-determining in the variants. Temperature-dependent Changes of Steady-State Enzyme Activity. In further experiments, the temperature dependence of the catalytic turnover for wild-type ssIGPS was studied from 15 - 55°C. The corresponding Arrhenius diagram (ln kcat vs. 1/T) is curved (Figure 3). A linear approximation of the profile at low and high temperatures results in a “kink” at 38 ± 2°C.

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FIGURE 3: Temperature dependence of the turnover number of wild-type ssIGPS. The natural logarithm of kcat for the turnover of CdRP was plotted as function of reciprocal temperature in an Arrhenius diagram. The lines represent linear approximations of the last four data points at low temperatures and the first three data points at high temperatures. The deduced activation energies are listed in Table 3.

The two slopes give activation energies of 118 kJ mol-1 at temperatures below and of 46 kJ mol-1 at temperatures above the transition point (Table 3). Table 3. Activation energy derived from linear approximation of Arrhenius plots. Arrhenius ∆E5-30°C ∆E40-60°C plot of (kJ/mol) (kJ/mol) kcat 118 ± 15 46.4 ± 4.5 a R(R1) apo 16.0 ± 0.5 35.1 ± 1.3 CdRP 18.3 ± 1.1 25.9 ± 0.7 IGP 14.6 ± 0.6 23.5 ± 0.6 rCdRP 14.0 ± 0.9 33.2 ± 1.6

R(MP)

apo CdRP IGP rCdRP a Error in regression

∆E5-40°C (kJ/mol) 19.2 ± 0.3 19.2 ± 0.3 18.8 ± 0.6 18.9 ± 0.4

∆E40-60°C (kJ/mol) 23.5 ± 0.4 25.0 ± 0.6 25.4 ± 0.6 24.5 ± 0.3

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Curved Arrhenius plots can be trivially caused by protein unfolding at higher temperatures. However, as judged from CD spectroscopy, ssIGPS is folded up to 90°C, making it unlikely that enzyme denaturation is the reason for the observed plot. Also, sub-saturating substrate concentrations due to a large increase in Km at elevated temperature could result in curved Arrhenius plots.58 However, KM values at the lower (25°C, Km = 85 nM) and upper ends (60°C, Km = 105 nM) of the analyzed temperature range were quite similar (Table 4), verifying that the enzyme is always saturated with CdRP in the studied temperature range.

Table 4. Steady-state kinetic parameters and SVE for wild-type ssIGPS at 25°C and 60°C. Temp (°C) kcat (s-1) KM (nM) kcat/KM (M-1 s-1) SVE a 6 25 0.11 ± 0.02 85 ± 15 1.18 x 10 1.2 ± 0.17 7 60 2.1 ± 0.04 105 ± 23 2.0 x 10 0.23 ± 0.02 a Error in regression.

Another potential source of a curved Arrhenius plot is a change in the rate-limiting step at different temperatures.59,

60

We have shown previously that net product release is rate-

limiting for wild-type ssIGPS at 25°C; thus we considered that one of the chemical steps might become rate-limiting at temperatures higher than 38°C. To verify this assumption, we measured kinetics of wild-type ssIGPS under single and multiple turnover conditions at 60°C (Figure 4) analogous to the stopped-flow measurements at 25°C. It is notable that, in contrast to multiple-turnover kinetics at 25°C, stopped-flow transients at 60°C do not show a product burst, but resemble traces observed for the activated variants at 25°C. Datasets for wild-type ssIGPS recorded at 60°C in stopped-flow experiments were again analyzed in a global fitting approach according to the three-step kinetic model (Scheme 1). The agreement of data and fit is illustrated in Figure 4, the obtained values for the rate constants are listed in Table 2.

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Figure 4: Single turnover and multiple turnover kinetics of wild-type ssIGPS at 60°C. (A) Under single turnover conditions kinetic traces monitoring Trp/IGP fluorescence (excitation: 280 nm, emission cutoff: 335 nm) were recorded in a stopped-flow apparatus after mixing 1.0 µM CdRP with various enzyme concentrations (final concentrations from bottom to top: 1.0 µM, 2.5 µM, 5.0 µM and 7.5 µM). (B) Under multiple turnover conditions, kinetic traces were monitored after mixing 5.0 µM CdRP with various enzyme concentrations (final concentration from bottom to top: 25 nM, 100 nM, 250 nM, 500 nM). (A) and (B): The three-step reaction mechanism shown in Scheme 1 was fitted to the stopped-flow transients globally. The obtained rate constants are summarized in Table 2. Black lines represent data, grey lines the best fit.

Reactions occur when the kinetic thermal energy of colliding reactant molecules suffices to cross the energy barrier of the reaction.61 Therefore, as expected, the values of all rate constants in the reaction were increased at 60°C. However, the relative increase of the product release rate was larger than the relative acceleration of the chemical transformation step with rising temperature, so that chemical turnover became rate-limiting for the reaction of wild-type ssIGPS at 60°C. Solvent Viscosity Effects (SVEs) to Characterize Rate-Determining Steps at Different Temperatures. Pre-steady state kinetic measurements indicated that the identity of the rate-determining step changes as a function of temperature. At temperatures below 38°C product release seems to be rate-determining, whereas at higher temperatures product 18 ACS Paragon Plus Environment

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release appears to be relatively fast compared to the chemical steps. The effect of solvent viscosity upon kcat of wild-type ssIGPS was determined to verify the kinetic mechanisms obtained at different temperatures. In principle, diffusion limited events such as substrate binding or product dissociation are expected to be sensitive to solvent viscosity while unimolecular chemical transformation steps should impart no viscosity dependence.62-64 Solvent viscosity effects, as defined by the slope of a plot of relative rate versus relative viscosity, were determined for ssIGPS at 25 and 60°C using glycerol as viscosogen (Figure 5).

FIGURE 5: Effect of solvent viscosity on the turnover numbers for wild-type ssIGPS. The kcat values (ki) in 50 mM HEPES pH 7.5, 4 mM EDTA with saturating CdRP substrate concentration (7 µM) and increasing glycerol concentrations (5%, 10%, 20%, 35% w/v) at 25°C (closed circles, ) and 60°C (open circles, ) were compared to the rate without added glycerol (k0). SVEs, as defined by the slopes of the curves, were determined by linear regression and are reported in Table 4.

In accordance with previous measurements of the solvent viscosity effect42, the SVE reached the theoretical maximum of 1 at 25°C, but there was no significant SVE (∼ 0.1 ) at 60°C (Table 4). This data is consistent with results from pre-steady state measurements, which predict that at 25°C diffusion-controlled product dissociation is rate determining, whereas at 60°C chemical steps, which are not affected by solvent viscosity, determine kcat. The large SVE at 19 ACS Paragon Plus Environment

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25°C is observed irrespective of the applied substrate and enzyme concentrations, confirming that it is indeed product dissociation and not substrate binding that is influenced by solvent viscosity. Since dynamics of protein conformational changes might also be viscosity dependent65,

66

, the viscosity approach is not capable of distinguishing what

physical event comprises the product release step. The slow net rate of product release, associated with a large SVE at 25°C, may be limited by the release of IGP, a conformational change or a combination of both. Molecular Dynamics (MD) Simulations. To identify regions that undergo conformational changes in the course of the catalytic reaction, we performed molecular dynamics simulations of the wild-type ssIGPS at 25°C in the apo form and in the presence of the substrate CdRP. We have used the RMSFs of each amino acid in 800 ns MD simulations as a measure of the overall flexibility of the system. MD simulations probe timescales in the nano- to microsecond range. The mobility of different regions of ssIGPS is highlighted in Figure 6.

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FIGURE 6: Conformational changes of ssIGPS deduced from MD simulations. (A) Cartoon representation of the apo form. (B) Cartoon representation of the CdRP bound form; the ligand is shown as a stick model. The color represents the root mean square fluctuations (RMSF) of the corresponding Cα atoms as indicated by the scheme at the right. (C) Plot of the residue-specific RMSF values for the CdRP bound form given as z-score, which is the difference to the mean RMSF value expressed in standard deviations. Four regions with substantial conformational flexibility are indicated.

In general, the apo-form appears to be more rigid than the CdRP bound form; the mean RMSF-values were 0.70 and 0.79, respectively. The liganded form develops four regions with substantial flexibility, the N-terminal extension (Leu17-Phe22), loop β1α1 (Pro57-Asp61), loop β6α6 (Glu185-Leu187), and loop β7α7 (Gly212-Ser214). This is in accordance with results from a statistical coupling analysis (SCA)-MD approach at a temperature of 112°C, 21 ACS Paragon Plus Environment

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where the mentioned three loops were also identified as major moving regions in free ssIGPS, the ssIGPS:CdRP and the ssIGPS:IGP complex.67 In addition, another SCA approach had previously identified co-varying residues in the β1α1- and the β2α2-loops.68 Moreover, as revealed by NMR relaxation dispersion measurements, dynamics of the β1α1-loop, and concomitantly catalytic activity, are governed by competing interactions on the N- and Cterminal sides of the loop.56, 57 To correlate β1α1-loop movements with rate constants in the catalytic reaction of ssIGPS, we attached EPR spin labels at position D61. Analysis of Loop Dynamics by EPR Spectroscopy. Site directed spin labeling in combination with EPR spectroscopy has emerged as an efficient tool to elucidate conformational dynamics of biomolecules under physiological conditions.69 The EPR spectral shape of a spin labeled protein reflects the overall dynamics of the spin label side chain in the nanosecond scale, which consists of contributions from the spin label internal dynamics, the dynamics of the protein backbone and the rotational diffusion of the protein.70,

71

For ssIGPS with a

molecular weight of 29 kDa a rotational correlation time in water of 10 ns can be estimated72, which is more than one order of magnitude larger than the re-orientational correlation times observed here (see below). Thus, the contribution of the ssIGPS rotational diffusion to the nitroxide motion can be neglected and its dynamics is mainly determined by internal spin label side chain and backbone motions. In order to further discriminate between these contributions we have introduced two different spin labels, MTSSL and MP, at position 61 in the β1α1-loop of the ssIGPS variant D61C (Figure 7).

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FIGURE 7: Reaction of MTSSL and MP spin label with cysteine residues to generate nitroxide side chains R1 and MP, respectively.

The MTSSL side chain, in the following abbreviated R1, is very flexible because its linker to the protein backbone comprises five rotatable bonds, the two most dynamic ones connecting Sδ with the nitroxide ring.70 The MP spin label was used in addition, which is more rigidly bound to the ssIGPS backbone. Thus, the dynamic contributions from the backbone would contribute in larger proportion to the overall motion of the nitroxide in MP relative to R1. Cw EPR spectra of the spin-labeled D61C variant were recorded at different temperatures in the presence of the substrate CdRP, the reduced substrate analogue rCdRP, the product IGP, and in the apo state. The temperature-dependent spectra for the apo state are shown in Figure 8A for R1 and in Figure 8B for MP. 23 ACS Paragon Plus Environment

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FIGURE 8: Cw EPR spectra of spin-labeled ssIGPS variant D61C in the apo state at different temperatures. Cw EPR spectra of (A) R1-labeled or (B) MP-labeled ssIGPS were recorded in the range from 5°C to 60°C in steps of 5°C.

The EPR spectra reveal single component behavior with narrow line width indicating high mobility of the R1 and MP side chains typical for loop positions. To quantify their reorientational diffusion, the spectra were analyzed using a simulation approach based on the EPR line-shape theory for nitroxides.52,

53, 70, 71, 73

Detailed information about simulation

parameters (g- and A-tensors) can be found in Material and Methods, representative overlays of simulated curves and cw EPR data are included in Figure S2. In the temperature range from 5°C to 60°C the effective re-orientational correlation times, τ = (6)-1, for R1 and MP span the range from 1.0 ns to 0.2 ns and 2.0 ns to 0.5 ns, respectively. The logarithm of the determined rotational diffusion rates of the spin labels was plotted as function of the inverse temperature. The R1-labeled enzymes are associated with curved Arrhenius plots (Figure 9A), irrespective of the bound ligand, and have distinct kinks at 37 ± 4°C.

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FIGURE 9: Temperature dependence of rotational diffusion rates of spin-labeled ssIGPS. The logarithm of the rotational diffusion rates of R1- (A) or MP-labeled enzyme (B) was plotted as function of reciprocal temperature in form of Arrhenius diagrams. The lines represent linear approximations of the data points in the low (R1: 5 - 30°C, MP: 5 - 40°C) and high (40 - 60°C) temperature range (apo state (black), in presence of CdRP (red), in presence of IGP (blue), in presence of rCdRP (green)). The deduced activation energies are listed in Table 3.

The kink temperatures coincide with the kinks of the Arrhenius plots corresponding to the catalytic turnover numbers kcat (Figure 3). The activation energies calculated from linear approximation in the low temperature range (5 - 30°C) amount to about 16 kJ/mol and are not affected by the bound ligand. Activation energies above the kink point range from 23 kJ/mol (IGP bound) to 35 kJ/mol (apo form) (Table 3). The Arrhenius plots resulting from rotational diffusion rates of MP-labeled ssIGPS are shown in Figure 9B. Again, all the plots are curved, kink points are observed around T = 39 ± 2°C. The activation energies calculated from the Arrhenius plots amount to about 19 kJ/mol in the low temperature range and about 25 kJ/mol in the high temperature range irrespective of the bound ligand (Table 3). It is informative to compare the above activation energies with other relevant experimental 25 ACS Paragon Plus Environment

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values reported in the literature. For example, for the R1 side chain motion at position 72 of T4 lysozyme in 30% sucrose an apparent activation energy of 26 kJ/mol has been reported, a value similar to the activation energy for viscous flow of this solvent.54 Values between 20 and 26 kJ/mol have also been found for maleimide spin labeled hemoglobin in 65% to 74% sucrose.74 In water, the energy barrier for re-orientational motion of solvent-exposed side chains is smaller and again close to the value found for viscous flow: an activation energy for the spin label re-orientational motion in hemoglobin of 18 kJ/mol74 was found, the experimentally determined activation energy for torsional oscillations about the C-C bonds in lysine side chains in water has been reported to be 17 kJ/mol.75 Thus, the activation energy of the re-orientational motion of the nitroxide side chains is significantly governed by the properties of the environment. Therefore, the difference in activation energies for temperature above and below 40°C indicates a change of the spin label environment in ssIGPS and/or an alteration of the impact of the backbone dynamics on spin label side chain dynamics. Taken together, Arrhenius plots based on rotational diffusion rates of both spin label side chains display biphasic curves irrespective of the bound ligand. This points to a conformational change of the ssIGPS enzyme at the kink temperature, which transfers the nitroxide side chain into a different environment or alters backbone dynamics. We observe similar dynamic behaviour independent of linker length and flexibility of the spin label, indicating that the protein backbone, namely the β1α1-loop, undergoes a conformational transition at about 40°C.

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CONCLUSIONS Understanding the functional implications of protein dynamics for catalytic activity is a central issue in enzyme research. In particular, motions of loops have been shown to be important in controlling access to the active site in a large variety of enzymes, including dihydrofolate reductase12, 76 and protein kinases62, 77. Due to their frequent occurrence and their catalytic versatility, (βα)8-barrels occupy a central position among enzymes and the importance of loop motion in prototypic TIM has been well described.30, 78, 79 Here, we have studied the relationship between motions of an active site loop of the (βα)8-barrel enzyme ssIGPS and its catalytic activity. The enzyme is structurally well characterized38, 40, 80, 81 and its high thermostability allows for measurements over a broad temperature range. Moreover, the relationship between intrinsic dynamics and enzymatic activity has been reported in some detail.42, 56, 57 Initially we found that the activation of ssIGPS through certain amino acid substitutions or temperature increase, involves a change in the rate-limiting step from product release to a chemical transformation step. Subsequent EPR measurements demonstrated that the different rate-determining steps at different temperatures coincide with different dynamics of the β1α1-loop on the nanosecond timescale. In addition, it has recently been shown that disrupting interactions of the β1α1-loop on N- and C-terminal sides of the loop quenched loop dynamics on the picosecond to millisecond timescale and decreased catalytic activity.56, 57 The phosphate moiety of CdRP connects two neighboring loops (β7α7 and β8α8) via hydrogen bonds to backbone amide groups and also forms a salt-bridge with Lys53 in the β1α1 loop.80 It is therefore plausible to assume that rate acceleration in ssIGPS is achieved by sequestering the substrate in a structured protein cage, which provides for optimal stabilizing interactions with the transition state(s). This mechanism has been described 27 ACS Paragon Plus Environment

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among others for the reaction catalyzed by the orotidine 5´-monophosphate decarboxylase.82 A major problem faced by these protein catalysts is to ensure that the loop dynamics, which function to create highly ordered structures from disordered proteins, are sufficiently rapid to support turnover. Future work may address the question whether the present mutations affect the intrinsic activation barrier to loop closure. Finally, our findings point to a route for improved computational enzyme design algorithms that consider multiple transition states and active site loop dynamics. Current in silico protocols already allow for multi-state design83, 84 and MD simulations can help to distinguish active and inactive designs.85 These optimized protocols, together with increasing computational power, hold great promise for improved enzyme design.

ASSOCIATED CONTENT Supporting Information Single turnover and multiple turnover kinetics of ssIGPS variant F246S (Figure S1), representative overlays of experimental and simulated EPR spectra of spin labeled ssIGPSD61C (Figure S2).

AUTHOR INFORMATION S.S. and T.K. prepared and labeled the proteins and performed kinetic measurements and analysis, M.S. conducted EPR studies, J.N. undertook MD simulations. R.M., H.-J. S., and R.S. supervised the work. S.S. wrote the manuscript. R.M., H.-J.S., and R.S edited the manuscript.

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ACKNOWLEDGEMENTS We thank Jeanette Ueckert for excellent technical assistance and Esther Mönkemöller for preliminary kinetic measurements. We thank two anonymous reviewers for their thoughtful comments. This work was supported by a grant of the Deutsche Forschungsgemeinschaft to R.S. (STE 891/11-1).

LIST OF ABBREVIATIONS CdRP, 1-(o-carboxyphenylamino)-1-deoxyribulose-5-phosphate rCdRP, reduced CdRP IGP, indole-3-glycerol phosphate IGPS, IGP synthase ssIGPS, IGPS from Sulfolobus solfataricus MP, N-(1-oxyl-2,2,5,5-tetramethyl-3-pyrrolidinyl)maleimide MTSSL, (1-oxyl-2,2,5,5,-tetramethylpyrroline-3-methyl)-methanethiosulfonate

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REFERENCES [1] Wolfenden, R., and Snider, M. J. (2001) The depth of chemical time and the power of enzymes as catalysts, Acc. Chem. Res. 34, 938-945. [2] Jiang, L., Althoff, E. A., Clemente, F. R., Doyle, L., Röthlisberger, D., Zanghellini, A., Gallaher, J. L., Betker, J. L., Tanaka, F., Barbas, C. F., 3rd, Hilvert, D., Houk, K. N., Stoddard, B. L., and Baker, D. (2008) De novo computational design of retro-aldol enzymes, Science 319, 1387-1391. [3] Röthlisberger, D., Khersonsky, O., Wollacott, A. M., Jiang, L., DeChancie, J., Betker, J., Gallaher, J. L., Althoff, E. A., Zanghellini, A., Dym, O., Albeck, S., Houk, K. N., Tawfik, D. S., and Baker, D. (2008) Kemp elimination catalysts by computational enzyme design, Nature 453, 190-195. [4] Siegel, J. B., Zanghellini, A., Lovick, H. M., Kiss, G., Lambert, A. R., St Clair, J. L., Gallaher, J. L., Hilvert, D., Gelb, M. H., Stoddard, B. L., Houk, K. N., Michael, F. E., and Baker, D. (2010) Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction, Science 329, 309-313. [5] Callender, R., and Dyer, R. B. (2015) The dynamical nature of enzymatic catalysis, Acc. Chem. Res. 48, 407-413. [6] Hammes, G. G., Benkovic, S. J., and Hammes-Schiffer, S. (2011) Flexibility, diversity, and cooperativity: pillars of enzyme catalysis, Biochemistry 50, 10422-10430. [7] Hammes-Schiffer, S., and Benkovic, S. J. (2006) Relating protein motion to catalysis, Ann. Rev. Biochem. 75, 519-541. [8] Henzler-Wildman, K., and Kern, D. (2007) Dynamic personalities of proteins, Nature 450, 964-972. [9] Nagel, Z. D., and Klinman, J. P. (2009) A 21st century revisionist's view at a turning point in enzymology, Nat. Chem. Biol. 5, 543-550. [10] Gutteridge, A., and Thornton, J. (2004) Conformational change in substrate binding, catalysis and product release: an open and shut case?, FEBS Lett. 567, 67-73. [11] Ma, B., and Nussinov, R. (2010) Enzyme dynamics point to stepwise conformational selection in catalysis, Curr. Opin. Chem. Biol. 14, 652-659. [12] Venkitakrishnan, R. P., Zaborowski, E., McElheny, D., Benkovic, S. J., Dyson, H. J., and Wright, P. E. (2004) Conformational changes in the active site loops of dihydrofolate reductase during the catalytic cycle, Biochemistry 43, 16046-16055. [13] Boehr, D. D., McElheny, D., Dyson, H. J., and Wright, P. E. (2006) The dynamic energy landscape of dihydrofolate reductase catalysis, Science 313, 1638-1642. [14] Eisenmesser, E. Z., Millet, O., Labeikovsky, W., Korzhnev, D. M., Wolf-Watz, M., Bosco, D. A., Skalicky, J. J., Kay, L. E., and Kern, D. (2005) Intrinsic dynamics of an enzyme underlies catalysis, Nature 438, 117-121. [15] Henzler-Wildman, K. A., Thai, V., Lei, M., Ott, M., Wolf-Watz, M., Fenn, T., Pozharski, E., Wilson, M. A., Petsko, G. A., Karplus, M., Hubner, C. G., and Kern, D. (2007) Intrinsic motions along an enzymatic reaction trajectory, Nature 450, 838-844. [16] Loria, J. P., Berlow, R. B., and Watt, E. D. (2008) Characterization of enzyme motions by solution NMR relaxation dispersion, Acc. Chem. Res. 41, 214-221. [17] Bhabha, G., Lee, J., Ekiert, D. C., Gam, J., Wilson, I. A., Dyson, H. J., Benkovic, S. J., and Wright, P. E. (2011) A dynamic knockout reveals that conformational fluctuations influence the chemical step of enzyme catalysis, Science 332, 234-238. [18] Bhabha, G., Biel, J. T., and Fraser, J. S. (2015) Keep on moving: discovering and perturbing the conformational dynamics of enzymes, Acc. Chem. Res. 48, 423-430. [19] Henn-Sax, M., Höcker, B., Wilmanns, M., and Sterner, R. (2001) Divergent evolution of (betaalpha)8-barrel enzymes, Biol. Chem. 382, 1315-1320. [20] Nagano, N., Hutchinson, E. G., and Thornton, J. M. (1999) Barrel structures in proteins: automatic identification and classification including a sequence analysis of TIM barrels, Protein Sci. 8, 2072-2084. 30 ACS Paragon Plus Environment

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Relationship of catalysis and active site loop dynamics in the (β β α)8-barrel enzyme indole-3glycerol phosphate synthase Sandra Schlee, Thomas Klein, Magdalena Schumacher, Julian Nazet, Rainer Merkl, HeinzJürgen Steinhoff, and Reinhard Sterner TOC Graphic

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