Effect of Asp122 Mutation on the Hydride Transfer in E. coli DHFR

Article Cite This: J. Phys. Chem. B XXXX, XXX, XXX−XXX

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Effect of Asp122 Mutation on the Hydride Transfer in E. coli DHFR Demonstrates the Goldilocks of Enzyme Flexibility Anil R. Mhashal,† Yaron Pshetitsky,† Reuven Eitan,† Christopher M. Cheatum,‡ Amnon Kohen,‡ and Dan Thomas Major*,† †

Department of Chemistry and the Lise Meitner-Minerva Center of Computational Quantum Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel ‡ Department of Chemistry, University of Iowa, Iowa City, Iowa 52242, United States J. Phys. Chem. B Downloaded from pubs.acs.org by MOUNT ROYAL UNIV on 08/10/18. For personal use only.

S Supporting Information *

ABSTRACT: Dihydrofolate reductase (DHFR) catalyzes the reduction of dihydrofolate (DHF) to tetrahydrofolate (THF) in the presence of NADPH. The key hydride transfer step in the reaction is facilitated by a combination of enzyme active site preorganization and correlated protein motions in the Michaelis−Menten (E:NADPH:DHF) complex. The present theoretical study employs mutagenesis to examine the relation between structural and functional properties of the enzyme. We mutate Asp122 in Escherichia coli DHFR, which is a conserved amino acid in the DHFR family. The consequent effect of the mutation on enzyme catalysis is examined from an energetic, structural and short-time dynamic perspective. Our investigations suggest that the structural and short-time dynamic perturbations caused by Asp122X mutations (X = Asn, Ser, Ala) are along the reaction coordinate and lower the rate of hydride transfer. Importantly, analysis of the correlated and principle component motions in the enzyme suggest that the mutation alters the coupled motions that are present in the wildtype enzyme. In the case of D122N and D122S, the mutations inhibit coupled motion, whereas in the case of D122A, the mutation enhances coupled motion, although all mutations result in similar rate reduction. These results emphasize a Goldilocks principle of enzyme flexibility, that is, enzymes should neither be too rigid nor too flexible.

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INTRODUCTION Enzymes are highly flexible biological macromolecules that catalyze chemical reactions of the cell. The catalytic power of enzymes may be ascribed to preorganization of the charge distribution in active sites.1,2 However, protein flexibility is also a crucial ingredient of enzyme functionality. Indeed, rigidified enzymes are considerably less active than their wild-type (WT) analogues,3,4 due to effects on substrate binding, product release, as well as the chemical step. A well-studied enzyme in this regard is dihydrofolate reductase (DHFR) and in particular the E. coli strain (ecDHFR).5−11 ecDHFR is a flexible, small, monomeric protein with no metals or SS bonds. The enzyme catalyzes a simple chemical transformation (C−H → C): the reduction of 7,8-dihydrofolate (H2folate) to 5,6,7,8tetrahydrofolate (H4folate) with the stereospecific transfer of a hydride from the pro-R C4 position of the nicotinamide ring of nicotinamide adenine dinucleotide phosphate hydride (NADPH) to the si face of the C6 of the pterin ring (Scheme 1). H4folate is an important cofactor in many biochemical processes including biosynthesis of nucleotides, and thus, DHFR is a target for various antibiotic and chemotherapeutic drugs. DHFR has served as a platform for many experimental5−7,12−16 and theoretical studies,4,8,17−31 and its protein dynamics−function relations have been a matter of ongoing debate.3,4,27−29,32−35 © XXXX American Chemical Society

In DHFR, a network of promoting motions has been suggested to accompany catalysis.11,36−39,45,46 This network is manifested as conformational changes along the reaction coordinate, which stretches throughout the enzyme, from the surface to the active site. Structurally, ecDHFR has been characterized as having several functional loops, namely, M20 (residues 9−23), C−D (residues 64−71), βF−βG (residues 116−132), and G−H (residues 142−149) loops. Numerous studies in the past have emphasized the role of these loops in the catalytic cycle. It has been suggested that the motions of these loops play a role in promoting catalysis,32 and mutations within the M20,40 βF−βG,41 or G−H42 loops have been reported to modulate the catalysis allosterically. Extensive studies by Brooks and co-workers,43 and our own recent investigation have also shown a significant correlation between the substrate acidity (N5 pKa) and the M20 conformation.44 We reported that closure of the M20 loop reduces the acidity of the N5-proton, thereby stabilizing the H3F+ state in preparation for hydride transfer. Early theoretical investigations identified correlated and anticorrelated motions in the ternary complex, which were supported by NMR measurements.45−47 Received: June 11, 2018 Revised: July 24, 2018 Published: July 24, 2018 A

DOI: 10.1021/acs.jpcb.8b05556 J. Phys. Chem. B XXXX, XXX, XXX−XXX

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The Journal of Physical Chemistry B Scheme 1. DHFR Catalyzed Hydride Transfera

a

The green arrow marks the transfer of the hydride (HR) from its donor to the acceptor. R: adenine dinucleotide 2′-phosphate. R′: paminobenzoyl-glutamate.

Subsequently, several studies have focused on the dynamic coupling between the M20, βF−βG, and G−H loops, as the interactions between the loops surrounding the active site are likely coupled to enzyme function.37,48,49 Mutagenesis has been employed as a tool to study the potential role of longrange structural and dynamic perturbations along the reaction coordinate. Methionine 42 and Glycine 121 are classic examples of such distant mutations that affect the reaction rates in ecDHFR via long-range perturbations.6,36 For instance, the M42W mutant was found to impact the probability of sampling protein motions conducive to the catalyzed chemical reaction.12,37,50 Glycine 121 (G121), which is located in the βF−βG loop, is an extensively discussed mutation that also impacts the reaction in ecDHFR.6,12,14,36−38,51,52 The substitution of this conserved amino acid has been reported to decrease the steady-state rate constant (kcat) 20-fold, despite being located far from the active site.53 Simulations have shown that the G121 mutation interferes with contacts between the βF−βG and M20 loops, hence, perturbing the cofactor and substrate orientation and consequently affecting the preorganization of the transition state.11,37,54 The double mutants of M42 and G121 showed even more adverse effects on the reaction, exhibiting nonadditive contributions.37 For other loops, Bhabha et al. have shown that the double mutation of N23 (M20 loop) and S148 (G-H loop) results in rigidification of the M20 loop, resulting in lowering of the reaction rates.3 Despite the extensive work done on ecDHFR mutants, atomic level details are still lacking regarding the coupling between distal loops and the active site and their relevance in modulating the enzyme chemistry. In the current work, we focus on conserved amino acid Asp122 (D122) located in the βF−βG loop (Figure 1). This mutation has been studied experimentally by Miller et al. and this work emphasized the importance of D122 in the βF−βG loop.41 The substitution of D122 to Asn, Ser, or Ala resulted in significant lowering of the rate of hydride transfer. Interestingly, all three mutants resulted in similar rate reductions, in spite of the different nature of the three mutants. D122 residue has been proposed to participate in a network of correlated protein motions along the reaction coordinate. In particular, the hydrogen bond interaction between D122 (Oδ) in the βF−βG loop and Glu17 (HN) in the M20 loop is likely important for stabilizing the closed conformation of the enzyme. Theoretical modeling of these mutants also reported an increase in free energy barriers for the hydride transfer reaction in the D122 mutants, although an extensive analysis of the results was not performed.55 Herein, to complement earlier work we probe the effect of mutating

Figure 1. Cartoon representation of ecDHFR showing the position of Asp122, as well as selected loops.

D122 on enzyme chemistry and in particular on the structure and dynamics of the protein. We adopt a quantum mechanics− molecular mechanics (QM/MM) strategy, in conjunction with free energy simulations. Based on the current simulations we point to a finely balanced network of coupled motions, which can be upset by both becoming too rigid or too flexible.

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METHODS The X-ray crystal structure of WT ecDHFR (PDB ID code 4RGC)56 with folate and the oxidized cofactor NADP+ were used to construct the initial configurations for the present study. The setup and molecular dynamics (MD) heating and equilibration simulations of all systems were carried out employing procedures similar to those employed for the WT and mutant DHFR in previous studies.8,9,57 Briefly, the protonation states of all polar amino acid residue side chains were adjusted to pH 7, and the protonation states of the His residues (either neutral tautomeric forms or positively charged form) were determined based on the hydrogen bonding patterns of the local environment. The N5 position of the pterin ring of the dihydrofolate was protonated.10,17,58 The HBUILD facility in the program CHARMM was used to add hydrogen atoms.59,60 A total of 29 sodium ions and 15 chlorine ions were added to the iso-charged WT to neutralize the overall negative charge. This ionic concentration mimics experimental conditions57 and effectively screens the charges in the system. The mutant enzymes D122X (X = S, A, and N) were constructed in silico from the WT structure, using the PYMOL program (https://www.pymol.org/). Special care was taken to maintain the hydrogen bonds between the βF−βG and M20 loop for residues other than the mutated one. The potential B


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The Journal of Physical Chemistry B

steps. A typical simulation starts with a short equilibration (2 ps), followed by collection of the probability densities of configurations (ρ) along the reaction coordinates. Whenever the biasing potential was updated, the subsequent simulation commenced with a short 2 ps equilibration, and the accompanying equilibration data was discarded. The positions and velocities of the last recorded configuration in a specific window were used to start its successor, to maintain continuity of propagation. The cumulative simulation time per window was 500 ps, resulting in 7.5 ns sampling for each PMF profile. The statistics for the reaction coordinates were sorted into bins of width 0.01 Å (antisymmetric stretch coordinate). PMF profiles were computed using the weighted histogram analysis method (WHAM).78 The statistical error was estimated using the bootstrapping algorithm (1000 steps) combined with WHAM.78 The resulting error analysis of the free energy profiles obtained is provided in the Supporting Information (Figure S1). Nuclear quantum effects (NQE) were incorporated via pathintegral (PI) simulations,79−81 as described previously. The transferring hydride atom, as well as the donor and acceptor atoms were quantized, and we employed 32 beads per quantized atom. A total of 10200 classical configurations (each for the ground state (GS) and transition states (TS) for WT and mutant enzymes) were extracted from the classical PMF simulations, and for each classical configuration, we performed 100 Monte Carlo steps to sample the PI polymer rings. Addition of NQE to the classical PMF yielded the quantum PMF, ΔG‡Q. We computed all possible hydrogen bonds within the enzyme to understand the effects of mutation on underlying hydrogen bonded networks. The calculations were done with geometrical selection criteria of H−A distance 2.4 Å82 and ∠D−H−A 150°. Further, the normalized frequencies (over number of frames) of these bonds were computed and plotted for respective donor−acceptor pairs. We obtained correlated motions in DHFR by computing the atomic displacement covariance matrix. All the frames in each trajectory were reoriented to remove net translations and rotations during the course of the simulations. Covariance matrices for the Cα atoms were calculated from a 10 ns trajectory of sampling windows in the GS and TS. The covariance (Cij) between two atoms i and j is given by

energy surface in the current study is described by a hybrid QM/MM Hamiltonian,61,62 where the QM region is treated by a modified AM1 semiempirical Hamiltonian,63 denoted AM1SRP (specific reaction parameters).64 This Hamiltonian has been designed to reproduce high-level calculations for an assortment of electronic and thermodynamic properties for reactions involving various nicotinamide and pterin derivatives.8 Additionally, the Hamiltonian is augmented by a ribose puckering correction surface, wherein the potential energy corrections and gradients are calculated on a grid.65 We term this modified method QM(mAM1-SRP)/MM. The QM region includes significant fragments of DHF and NADPH, which are proximal to the reaction center (69 QM atoms), whereas the MM region contains the remaining ligand atoms, the entire protein, water molecules and salt. The water molecules were represented by the three-point charge TIP3P model.66 The generalized hybrid orbital method (2 GHO atoms) was employed to treat the covalent QM/MM boundaries.67 The QM/MM interactions were treated by electrostatic embedding. A detailed QM/MM partitioning scheme, and a thorough description of the development of the AM1-SRP Hamiltonian is provided elsewhere.8 In modeling the MM region, we used the all-atom CHARMM36 force field.68−70 Periodic boundary conditions were employed to solvate the Michaelis complex using a pre-equilibrated cubic water box (∼65 Å × ∼65 Å × ∼65 Å), while long-range electrostatic interactions were realized with the Ewald summation technique (64 × 64 × 64 FFT grid, κ = 0.340 Å−1).71 All systems were fully minimized, heated up gradually to 298 K for 25 ps, and equilibrated for 2 ns at that temperature. The initial 1 ns equilibration was carried out with several nuclear Overhauser effect (NOE) restraints on key hydrogen bond interactions between the ligands and the surrounding residues, as well as within the protein. The restraints were then removed, and an additional 1 ns equilibration was performed to relax the WT and mutant enzymes. All equilibrations were conducted with the isothermal−isobaric (NPT) ensemble at 1 atm pressure and the target temperature was controlled by the extended constant pressure/temperature (CPT) method72,73 and the Hoover thermostat.74 The leapfrog integration scheme75 was used to propagate the equations of motions, and the SHAKE algorithm76 was applied to constrain all MM bonds involving hydrogen atoms, allowing a time step of 1 fs. The umbrella sampling (US) technique77 was used to determine the classical-mechanical potential of mean force (PMF), ΔG‡C, for the hydride transfer reaction at 25 °C. In the current study, several reaction coordinates were employed. The chemical reaction coordinate was defined as the antisymmetric reactive stretch coordinate, ζasym. Specifically, ζasym is defined as the difference between the lengths of the breaking C4N−H and forming H−C6 bonds. The ribose puckering coordinates were defined as described previously (results shown in Supporting Information).65 The reaction coordinates were discretized and divided into 15 evenly spaced regions, or “windows”, covering the relevant chemical and conformational space. Each window was subject to an appropriate harmonic restraint, which keeps the reaction coordinate in the desired region. The chemical reaction coordinate was supplemented by an umbrella potential (roughly the negative of the PMF). To efficiently update the biasing potential as necessary, each window was sampled in multiple successive series with a predetermined number of MD

Cij = ⟨(xi − ⟨xi⟩). (xj − ⟨xj⟩)⟩

(1)

where xi is the position of atom i. The normalized covariance (cij) is obtained by cij = Cij/ (CiiCjj)

(2)

We performed Principal Component Analysis (PCA) to filter out the fast-local fluctuations from the functionally relevant collective motions of the simulation trajectory using Bio3D.83 This program calculates principal components (orthogonal eigenvectors) that describe the axes of maximal variance from the distribution of superimposed structures. Further projection of the total distribution onto the selected eigenvector (subspace of largest principal component) results in a lower dimensionality representation of the structural data set, allowing us to extract the functionally relevant motions from the trajectory. We extracted the principal motions in the WT and mutant enzymes from 10 ns QM/MM MD trajectories (these are reported in the Supporting InformaC


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The Journal of Physical Chemistry B tion). The backbone Cα atom were used for superposition of the DHFR structures from the trajectory. The obtained collective motions were identified and are discussed in the Results section. All structural and dynamic analyzes of WT and mutant enzymes of GS and TS were averaged over 10 ns.

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RESULTS AND DISCUSSION Effect of Mutation on Hydride Transfer Rate. The free energy simulations for the WT and mutant enzyme forms were

Figure 2. Potential of mean force profiles for WT ecDHFR and a series of D122 mutants. Inset: active site in ecDHFR. Figure 3. Root mean square fluctuations between the (A) GS and (B) TS for WT ecDHFR and mutant systems. Colors black, red, green, and blue represent WT, D122N, D122S, and D122A systems, respectively.

Table 1. Experimental Single-Turnover Rates and Corresponding Experimental and Computed Activation Free Energy Barriers for the Hydride Transfer Reaction in ecDHFR and D122X Mutants

experimental valuesa enzyme

kH (s−1)

ΔG‡ (kcal/mol)

wild type D122N D122S D122A

220 ± 10 9.4 ± 0.7 5.9 ± 0.3 4.0 ± 0.1

14.3 16.1 16.4 16.6

± ± ± ±

0.03 0.01 0.01 0.01

classical potential of mean force

quantum corrected potential of mean force

ΔG‡C (kcal/mol)

ΔG‡Q (kcal/mol)

16.2 17.6 17.6 17.5

± ± ± ±

0.2 0.4 0.3 0.3

14.0 15.5 15.5 15.4

± ± ± ±

free energy barriers for the mutants relative to the WT enzyme, which is a slight underestimation of the experimentally observed effect (Figure 2 and Table 1). Previous studies have shown that mutations at positions 121 and 122 of ecDHFR impair the ability of the enzyme to form the closed conformation, which instead favors the occluded conformation.19,41,48,52,53,85−89 The current simulations commenced with the catalytically competent closed state, and part of the underestimation of the free energy barrier could be because we do not include a possible occluded to closed transformation. However, the current simulations do capture the majority of the mutant effect, and we ascribe the observed barrier increase to perturbation of the protein−protein and protein−ligands interactions caused by the D122 mutations (vide infra). D122 is located in the βF−βG loop and is a conserved amino acid among the DHFR family.11 It has also been reported to participate in a network of coupled protein motions along the reaction coordinate and, as such, might help stabilize the TS.11,37,87,90 In particular, the functionally important closed conformation of the M20 loop is stabilized by hydrogen bonding interactions between D122 (Oδ) in the βF−βG loop and Glu17 (HN) in the M20 loop.91 In order to rule out the possible role of electrostatics of D122 in catalysis, we constructed a free energy profile with the MM partial charges of the D122 side-chain annihilated, but with a NOE restraint on the H-bond between D122 and Glu17. The free energy barrier in this case is slightly lower than for the WT (Figure S2), suggesting that electrostatics of this residue is not at play, as nullifying an electrostatic effect would be expected to increase the barrier. Therefore, we propose that the D122 mutations possibly influence ligand and enzyme

0.2 0.4 0.3 0.3

a

Experimental rates are from ref 41, and corresponding activation free energies were calculated using Eyring’s equation.

obtained using the multiscale approach described in the Methods section. The PMF profiles for the hydride transfer from NADPH to H3folate+ in WT DHFR and the D122X (X = N, S, A) mutants are plotted in Figure 2. In Table 1 the free energy barriers, including NQE, are compared with the experimental single turnover rates reported by Miller and Benkovic,41 that we translated into phenomenological free energy barriers by applying Eyring’s equation. The agreement between experimental and computed absolute values and trend is good.55 The computed WT free energy barrier is 14.0 kcal/ mol compared to 14.2 kcal/mol from experiment. The good agreement is due to the accuracy of the employed hybrid QM(AM1-SRP)/MM Hamiltonian.16 In previous work we showed that this Hamiltonian reproduces the experimental rates both for WT and several series of mutants of DHFR,8,39,57 and this Hamiltonian has successfully been adopted by others as well.27,28,84 Turning to the effect of the distal D122X mutants, we note a ∼1.5 kcal/mol increase in D


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Figure 4. Hydrogen bond occurrence map between M20 and βF−βG loop residues. The abscissa and ordinate represent hydrogen bond donor and acceptor residues, respectively, in the ground and transition state. Figures A and B depict hydrogen bond occurrences where M20 residues act as donors and acceptors, respectively. Numbers in the picture depict normalized occurrences.

C−D loop (residues 64−71, 25 Å from active site) for all the systems, in agreement with earlier experiments and theoretical investigations.29,44,46,92−94 For example, Boehr et al. reported flexibility in the C−D loop resulting from G121 V mutation, suggesting that the βF−βG and C−D loop motions are correlated.38 To assess the overall loop flexibility, we computed the average residue RMSF for WT and D122X (X = N, S, A) for segments M20 and FG loops and helix 40−50, and obtained values of 0.58, 0.71, 0.57, and 0.77 Å (GS) and 0.60, 0.66, 0.65, and 0.78 Å (TS), respectively. However, we note that these thermal fluctuations do not necessarily represent functionally important conformational motions that are proposed to be dynamically coupled.37,48 Below, we provide a detailed atomic-level analysis of the underlying reasons for the changing loop dynamics. Effect of Mutation on Interloop Interactions. Several studies have addressed the network of hydrogen bonds between the βF−βG and M20 loop that maintains the reactive

structure and dynamics and, thereby, reduce hydride transfer rates (Figure 2).41 In the following we will address the various factors that might govern this structure and dynamics. Effect of Mutation on Protein Structure and Flexibility. Previous studies speculated that mutations of D122 or G121 bring about loss of interloop contacts, resulting in greater flexibility and an inability of the M20 loop to reach the closed conformation required for catalysis.41,54 To investigate this, we present root-mean-square fluctuations of Cα as a function of amino acid residues for GS and TS for WT and mutant ecDHFR (Figure 3). The RMSF values here indicate significant changes in the thermal fluctuations in the mutant enzymes for the βF−βG loop residues. This change in mobility in the βF−βG loop (containing the mutated residue 122) is carried over to the neighboring M20 loop, which closes the active site. The perturbation caused is likely due to the loss of direct hydrogen bond contact between these two loops. Moreover, we also note significant change in flexibility in the E


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Figure 5. Distribution of backbone dihedral angles for WT and mutant enzymes in the GS (top) and TS (bottom). Residues I14, G15, M16, G121, and D122 are colored black, red, green, blue, and magenta, respectively. (A)−(D) represent WT, D122N, D122S, and D122A systems, respectively.

closed state conformation of the enzyme.41,42,91 Especially the H-bond between D122 of the βF−βG loop and the backbone amide of Glu17 of the M20 loop is central to this network. Here, we examined the interloop interactions by computing the hydrogen bond interactions between the M20 and βF−βG loops. We measured all possible hydrogen bonds between these loops and plotted their normalized frequencies for the GS and TS in Figure 4 and tabulated in Table S1. A residue pair frequency value of 1.0 indicates stronger interaction, while lower occurrences indicate weaker interactions. The mutation of D122 perturbs the local interactions and as a result we note loss of interloop interactions. We observe occurrence frequencies 0.76 and 0.73 for the E17NH-D122OD pair in ground and transition states, respectively, suggesting strong interaction. Depending upon the mutation, we observe a gradual decrease in the hydrogen bonded interactions between these loops (e.g., for D122S, 0.30 and 0.69 for GS and TS, respectively, while the interaction is lost in D122A and

D122N). In addition to the side chain hydrogen bond, D122 also offers a backbone hydrogen bond to G15 in the M20 loop, which disappears in the D122A and D122N mutants. The hydrogen bond between T123NH−G15O is also weakened in mutant enzymes. In the WT enzyme, I14 and T123 also form a strong hydrogen bond, which is weakened in the mutant enzymes. Moreover, due to the flexibility in these loops, we find an unusual salt bridge formation between R12 and D127, which is weak in the case for WT enzyme, but stronger in D122 (N/S) mutants. This occurrence for these interactions are 0.83 and 0.93 for D122N and D122S mutant, respectively, in ground state and 0.83 for D122A mutant in transition state, suggesting that this loop might have adopted a different conformation. In conclusion, we see a change in the overall interloop interactions that can potentially interrupt the network of coupled promoting motions that serve to aid catalysis. Hammes-Schiffer et al. have demonstrated that a network of residues I14, G15, F31, M42, Y100, G121, and F


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affect the donor−acceptor distance (DAD) and the angle between donor-hydride-acceptor (∠D−H−A). We computed and plotted the DAD and ∠D−H−A distribution in Figure S3. From this figure, we notice that the DAD distribution shifts slightly toward greater values for the D122N/A mutants, as well as wider ∠D−H−A angle distributions in the ground state, suggesting a more loosely organized active site in the mutants (Figure S3). The other M20 residues, such as E17, A19, and M20 display nearly identical φ/ψ angle patterns for WT and mutant enzymes (Figure S4). The observed dihedral angles obtained for E17 and M20 are consistent with some of the studies reported earlier and do not change significantly due to the D122 mutations (Figure S4).44,48 These results suggest that the mutations significantly perturb the conformational sampling of the βF−βG and M20 loop residues, and this may lead to different protein dynamics. We also plot the NADPH diphosphate dihedral angles for WT and mutant enzymes (Figure S5). Here we observe that the diphosphate angle distributions are very similar for WT and D122N in ground state but perturbed for D122(S/A). This is due to the loss of a water-bridged hydrogen bond with a polar reside at position 122 and the NADPH ribose moiety. Effect of Mutations near Active Site. Miller and Benkovic have discussed the significance of functional loops in ecDHFR.41 The structural information regarding these loops was provided by Sawaya and Kraut,91 who emphasized the principle conformations of the M20 loop during the catalytic cycle. The water dynamics near the active site are reported to play a crucial role during catalysis by screening the charges and assisting ligand binding.56,91,95−97 The role of water in the protonation of N5 has also been reported.56,58,98 Recent studies have shown the presence of a water triad near the substrate molecule that provides stability to the substrate molecule.44,98 Here, based on the current QM/MM MD simulation trajectories, we highlight the water distribution in the vicinity of the substrate−cofactor complex and the M20 loop. We compute the radial distribution function (RDF) between the O4 atom of the DHF pterin ring and the water oxygens in the ground and transition states (Figure 6). For the WT enzyme we observe a nonexchangeable water molecule in the O4 vicinity, followed by two smaller and less structured peaks (at ∼4.6 and ∼7.5 Å), similar to what we observed in our earlier work.44 The RDFs obtained for the mutant enzymes in the GS are very similar to WT, while at the TS the second peak is less distinct, similar to our observation for I14 mutants with disordered M20 loop.44 We ascribe this to the loose M20 and βF−βG loop interactions perturbing the M20 loop dynamics and the hydration near the active site. We also investigated the hydrogen bonds between protein and substrate-cofactor in the GS and TS and these showed little difference between WT and mutant enzymes (Table S2). On the other hand, the D122 mutation had a significant impact on the nicotin−ribonucleoside ribose puckering (Figure S6) and substrate−cofactor dynamics (Figure S7), as D122 interacts with the ribose moiety via a water molecule. However, no simple correlation between ribose puckering or substrate−cofactor dynamics and relative reaction rate was found. Effects of Mutation on Protein Motions. To better understand the overall effect of the 122 mutations on the coupling between the βF−βG and the G−H and M20 loops, we assessed the correlated motions in WT and mutant DHFR enzymes. This was done by constructing the covariance

Figure 6. Radial distribution function between pterin O4 and water oxygen atoms for (A) ground and (B) transition state. Color code: black, red, green, and blue represent WT, D122N, D122S, and D122A, respectively.

D122 works in concerted fashion.11 As a result of mutation, the ps−ns dynamic motions are perturbed and this effect propagates to additional residues. We further investigate the effects of these lost interactions on surrounding residues in sections below. Effects of Mutation on Substate Distribution. We further investigated the local peptide backbone perturbation caused by the D122X mutations. We recorded and plotted the backbone φ/ψ angles distribution for the mutant and neighboring residues in the GS and TS, as they can report on the conformational flexibility in the loops (Figure 5). The most striking effect of the mutations is wider distributions for the φ/ψ angles for D122, G121, and some of the M20 loop residues, especially active site I14 for mutant enzymes. The WT enzyme shows D122 backbone φ and ψ centered around ∼−15° and −110°, respectively (Figure 5a,b). The D122A mutant exhibits significant perturbation in the φ/ψ angles, as the contacts between the loops are lost, while the D122N mutant adopts a slightly different set of φ/ψ angles with values of 10/−120°. The neighboring amino acid in the same loop, G121, also shows perturbation in the φ/ψ angles for all mutants. D122(N/A) mutants show pronounced differences in the dihedral angle set stabilizing slightly different conformation of the loops (Figure 5a, b). This perturbation entails both shift in the center of the angle distributions, as well as the width of the distributions. Apart from the βF−βG loop, the M20 loop residues are also found to be affected. For example, the dihedrals of I14 and G15, which form H-bond with the βF−βG loop, are highly distorted for the mutant enzymes. Residue I14 plays an important role in positioning of the nicotinamide ring and therefore, I14 perturbations are likely to G


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Figure 7. Covariance matrix for the fluctuation of the Cα atoms in WT (A) and mutant systems (B−D) D122N, D122S, and D122A, respectively, in the ground state (top triangles) and transition state (bottom triangles). Color scale from blue to red represents perfectly anticorrelated (−1) motions to fully correlated (+1) motions. Anticorrelated regions between ABD and βF−βG/M20/G−H are highlighted in the boxes in (C).

excessive flexibility along the reaction coordinate can also be related to reduced catalytic rates. This then supports the notion that enzymes should neither to be too rigid nor too flexible. We ascribe the change in correlated motions to the changes in the underlying protein−protein and protein− substrate−cofactor hydrogen bond pattern and the subtle structural rearrangements caused due to the mutations. Rod et al. studied the effects of distal mutations (G121 and M42) on protein dynamics, and they speculated that the mutations have long-range effects that causes perturbation of the protein correlated motions.48 The current work confirms these findings for the D122 mutants as well. The correlated motions between the NADPH and several loops are shown in Figures 7 and S8. The correlation patterns between the cofactor and the loops change in the mutant enzymes relative to that in the WT, suggesting that mutation of the distal D122, influences the motions of the cofactor. This may be due to direct interaction between D122 and the cofactor ribose moiety or indirectly via other loops. We also studied the principle motions in the protein using PCA, which is a measure that explores the relationship between different conformations sampled during the trajectory. Here we report the principle collective motions in ecDHFR, which fits well with the reported experimental and theoretically

matrices for the fluctuations of residue pairs (described in Methods section). The covariance values +1 and −1 correspond to perfectly correlated and anticorrelated motions, respectively. The coupling between the βF−βG loop and the M20 and G−H loops is evident from inspection of Figure 7 (dark red regions), as we observe strong correlation for both WT and mutant enzymes as these elements move in concert. We also note distinct anticorrelation between the βF−βG/ M20 loop and adenosine binding domain (ABD). These signature patterns observed for WT enzyme are consistent with earlier reported studies.46,48,99 In particular, our results are in good agreement with the correlated motions that are captured by long time-scale coarse-grained simulations.99 The correlated motions are similar in the GS and TS with distinct anticorrelated motions between G−H loop and C−D and αE−βE loops (residues 85−91). Turning to the mutants, Figure 7 shows that there is a change in the overall correlation patterns for the mutant enzymes, suggesting that the dynamic coupling in the enzyme is affected due to the mutations. The characteristic anticorrelated motions between the βF−βG/ M20 loops and ABD are less pronounced in the mutants D122N/S and could be related to the reduced enzyme kinetics. On the other hand, in the D122A mutant, we observe an intensified correlation pattern, which might suggest that H


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The Journal of Physical Chemistry B hypothesized mechanism (Movie S1).18,40,45,47,91,100,101 It is presumed that mobile protein loops assist in the tight binding of the reactive complex at the transition state.18,40,100 Here, we identify a characteristic collective anticorrelated motion of two domains in ecDHFR that may explain the tightening of reactive complex at the transition state. In Movie S1, we show that in WT ecDHFR, the adenosine binding domain, comprising residues 40−90 (consisting of two helices, two strands and loops), and a second domain, consisting of the loops M20, βF−βG, and G-H, move in an anticorrelated fashion. The functional significance of these motions is seemingly to move the NADPH cofactor closer to the folate moiety, as the chemical step occurs. Most importantly, these motions are discernible from the covariance data shown in Figure 7. Hence, the positive correlation within the domains and negative correlation between the domains suggests a network of interactions that assist the sliding motion of NADPH toward the substrate. In the D122 mutants, the overall dynamics of the protein are perturbed relative to the WT motion (Movie S1). From the PCA analysis, we note significant differences in the enzyme dynamics, especially in the M20, βF−βG, and G−H loops. In the D122N and D122S mutants, much of the anticorrelated motions, which are conducive to chemical reaction, are lost. Interestingly, in the D122A mutant these anticorrelated motions are intensified, suggesting that in this mutant, loss of contacts between the M20 and βG−βH and M20 loops results in increased anticorrelated motion. This is also reflected in the covariance data in Figure 7, which shows that the correlated and anticorrelated motions in the loops with respect to the ligands are also found to be perturbed in the mutants (Movie S1). In the current simulations we observe that a single mutation of D122 in the βG−βH loop of ecDHFR impairs the overall dynamics of the protein and cofactor. The mutation seemingly leads to a chain of small changes that propagate throughout the protein and impacts the overall network of hydrogen bonds. In the case of D122N and D122S, the mutation leads to alternative hydrogen bonds, which seem to result in an overall tempering effect of the correlated and anticorrelated functional motions throughout the protein. In the case of the D122A mutant, we observe excessive flexibility along the reaction coordinate due to the loss of a key hydrogen bond. Hence, it seems like the different D122 mutations upset a finely tuned network of coupled motions in different ways, but the end result is the same: a slight slowing down of the chemical step of the enzyme.

suggest that these cumulative perturbations caused by the remote mutation affect the global dynamics of the protein and thereby modulate the kinetics of the chemical step. In the case of D122N and D122S, the mutations inhibit coupled functional motion, whereas, in the case of D122A, the mutation enhances coupled functional motion, although all mutations result in similar rate reduction. These results emphasize a Goldilocks principle of enzyme flexibility, that is, enzymes should neither be too rigid nor too flexible.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcb.8b05556. Associated content includes, tables representing hydrogen bond occurrences, and ensemble averaged distances, bootstrapped free energy profiles, free energy profiles for the charge annihilated system, distribution of DAD, loop residues substate analysis, cofactor geometrical analysis, ribose puckering free energy profiles, substrate thermal fluctuations, substrate-cofactor covariance map, description of ribose puckering simulations (PDF). Supporting Movie S1 (MPG).

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Anil R. Mhashal: 0000-0002-8232-8135 Christopher M. Cheatum: 0000-0003-3881-3667 Amnon Kohen: 0000-0001-8793-8939 Dan Thomas Major: 0000-0002-9231-0676 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by Israel Science Foundation Grant 2146/15 and United States−Israel Binational Science Foundation Grant 2012340.

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REFERENCES

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CONCLUSIONS In this study, we investigated the structure−dynamics− function relationship in the enzyme ecDHFR. We compared the WT and three mutant forms (D122X, X = N, S, A) of the enzyme. The mutation is positioned in the βF−βG loop, which is located remotely from the active site. We employed hybrid QM/MM free energy simulations and found that the mutation in the βF−βG loop causes a consistent slight increase in the activation free energy barrier for the mutant enzymes, in good agreement with published experimental pre-steady-state kinetics. Based on extensive trajectory analyses, we conclude that the reduced catalytic rates in the mutant enzymes are the result of cumulative perturbation effects induced by the structural and dynamical differences in the WT and mutant enzymes. Covariance and principle component analyses I


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