Multiscale Simulations Give Insight into the Hydrogen In and Out

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Multiscale Simulations Give Insight into the Hydrogen In and Out Pathways of [NiFe]-Hydrogenases from Aquifex aeolicus and Desulfovibrio fructosovorans Francesco Oteri,† Marc Baaden,† Elisabeth Lojou,‡ and Sophie Sacquin-Mora*,† †

Laboratoire de Biochimie Théorique, CNRS UPR9080, Institut de Biologie Physico-Chimique, 13 rue Pierre et Marie Curie, 75005 Paris, France ‡ Bioénergétique et Ingénierie des Protéines, Institut de Microbiologie de la Méditerranée, CNRS, Aix Marseille University, 31 Chemin Joseph Aiguier, 13402 Marseille Cedex, France S Supporting Information *

ABSTRACT: [NiFe]-hydrogenases catalyze the cleavage of molecular hydrogen into protons and electrons and represent promising tools for H2-based technologies such as biofuel cells. However, many aspects of these enzymes remain to be understood, in particular how the catalytic center can be protected from irreversible inactivation by O2. In this work, we combined homology modeling, all-atom molecular dynamics, and coarse-grain Brownian dynamics simulations to investigate and compare the dynamic and mechanical properties of two [NiFe]-hydrogenases: the soluble O2-sensitive enzyme from Desulfovibrio f ructosovorans, and the O2tolerant membrane-bound hydrogenase from Aquifex aeolicus. We investigated the diffusion pathways of H2 from the enzyme surface to the central [NiFe] active site, and the possible proton pathways that are used to evacuate hydrogen after the oxidation reaction. Our results highlight common features of the two enzymes, such as a Val/Leu/Arg triad of key residues that controls ligand migration and substrate access in the vicinity of the active site, or the key role played by a Glu residue for proton transfer after hydrogen oxidation. We show specificities of each hydrogenase regarding the enzymes internal tunnel network or the proton transport pathways.

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INTRODUCTION

nature, [NiFe]-Hases are widespread in bacteria and archae and are usually involved in H2 oxidation. They have recently attracted much attention for their mechanism of action and potential uses,3,4 either as H2-oxidation catalysts in biofuel cells and other biocatalytic devices,5−7 or for H2 production in photoelectrochemical biofuel cells or by photosynthetic bioorganisms.8−10 However, most soluble hydrogenases are inhibited by oxygen and therefore, much effort is currently devoted to understand the bases of oxygen sensitivity. While it was originally thought that the shape and size of the intramolecular hydrophobic cavities leading to the [NiFe] active site were crucial for O2-insensitivity,11−13 the determination of the structure of several O2-tolerant membrane-bound Hases (MBHs) from Ralstonia eutropha,14 Hydrogenovibrio marinus,15 and Escherichia coli16 showed that the most prominent modification is the replacement of the [4Fe4S] cluster proximal to the [NiFe] site usually found in O2-sensitive Hases by a novel [4Fe3S] center coordinated by six cysteine residues instead of the canonical four (see Figure 1 in ref 17). Unlike the traditional [4Fe4S] cluster, this new [4Fe3S] cluster is able to perform two functionally meaningful single electron

The reversible oxidation of molecular hydrogen (H2) is a key process in the metabolism of many organisms. It is carried out by hydrogenases (Hases), which contain a protein bound metal complex in the active site connected to the primary electron donor or acceptor through an electronic relay of FeS clusters1,2 (see Figure 1). Among the most common hydrogenases in

Figure 1. [NiFe]-Hase from A. aeolicus with the electron, proton, and molecular hydrogen pathways shown. The large and small subunits are colored in red and blue, respectively. The [NiFe] active site, the Mg2+ ion and the FeS clusters are represented as van der Waals spheres. This figure and Figures 2, 5, 6 and 7 were prepared using Visual Molecular Dynamics.105 © XXXX American Chemical Society

Received: September 5, 2014 Revised: November 13, 2014

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dx.doi.org/10.1021/jp5089965 | J. Phys. Chem. B XXXX, XXX, XXX−XXX

The Journal of Physical Chemistry B

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transitions.18−20 As a consequence, all the electrons required to reduce O2 in H2O are readily available within the enzyme and can immediately be transferred to the active site when necessary.21,22 From this perspective, the MBH from Aquifex aeolicus (AaHase) is of particular interest for biotechnological applications, since it combines O2- and CO-tolerance with remarkable thermostability.10,23−25 However, no crystallographic or NMR structure is available yet for this specific enzyme, which would facilitate the investigation of the protein’s function. Therefore, we used homology modeling to construct a three-dimensional model of AaHase, that was validated in a previous work,26 and further used in long-time scale all atom molecular dynamics and coarse-grain Brownian dynamics simulations. A similar procedure was applied to the soluble, mesophilic, and O2-sensitive Hase from Desulfovibrio f ructosovorans (DfHase), for which several structures are available in the Protein Data Bank,27 and the results for both enzymes were compared. In a first paper, the simulations were combined with voltammetric experiments to study the electrostatic properties of these two proteins and relate them to their adsorption on charged electrodes.26 In this work, we focused our attention on the dynamic and mechanical properties of the enzymes and specifically investigated the network of hydrophobic tunnels that can serve as diffusion pathways from the enzyme surface to the central [NiFe] active site for molecular hydrogen, and the possible proton pathways that are used to evacuate hydrogen after the oxidation reaction. Previous simulations on [NiFe]-Hases focused on H2 and inhibitor (such as CO) diffusion in the hydrophobic cavities connecting the enzyme’s surface to it active site, and highlighted how two conserved residues, Val74L and Leu122L (DfHase numbering), form a bottleneck at the end of this channel that could influence H2 and/or O2 access to the active site (see Greco et al.28 for a recent review). Proton transfer pathway studies led to several suggestions with residues Glu25L and Arg476L playing a central role in the process.28 However, all these theoretical studies were made on O2-sensitive Hases, mostly from Desulfovibrio species. Therefore, one of our goals was to perform a joint investigation of both an O2-sensitive and an O2-tolerant Hase in order to improve our understanding of the oxygen-tolerance mechanism in this group of enzymes. A key result of our work is that, similarly to what was previously demonstrated for the globin family,29 both [NiFe]hydrogenases present a mechanical nucleus formed by a conserved Val/Leu/Arg triad that controls ligand migration in the vicinity of the active site. Our results highlight other common features of the two enzymes, such as the key role played by a Glu residue for proton transfer after hydrogen oxidation and its potential importance in the oxygen-tolerance mechanism of AaHase, and show specificities of AaHase compared to DfHase regarding the enzymes’ internal tunnel network or the proton transport pathways.

in Figure SI1). MODELER v9.1030,31 was then used to build the starting structure using the following templates: Desulfovibrio desulf uricans (1E3D),32 Desulfovibrio vulgaris Miyazaki (1WUI),33 Desulfovibrio gigas (1FRV),34 D. f ructosovorans (1YQW),35 H. marinus (3AYX),15 R. eutropha (3RGW),14 and Allochromatium vinosum (3MYR).36 The structures were superimposed using the Chimera software37,38 and used as input for the MODELER program. Regarding the small subunit, only the residues for the soluble domain (i.e., from Pro47S to Gly316S), were retained. The metallic centers were obtained from the oxygen tolerant hydrogenase of H. marinus15 and were treated as rigid blocks during the modeling procedure. The loops originating from gaps in the alignment were energyoptimized in order to obtain a refined, energetically favorable structure according to the dope-score of the Modeler v9.10 software. The secondary structure regularity and the degree of steric clashes in the model were evaluated using the MolProbity (http://molprobity.biochem.duke.edu) web server39 at two different stages: namely on the starting model and after equilibration. Metal Center Parametrization. In this paper we attempt to study the hydrogenase enzymes in the oxidation state prior to H2 processing. According to Niu and co-workers,40 the active site has been assumed to be in the Ni-SIa state (where the four cysteines are deprotonated, while Ni and Fe are both in the oxidation state +2, thus resulting in a total −2 charge) and the FeS clusters were treated as oxidized. Bonded and nonbonded parameters for the [4Fe4S] proximal clusters in DfHase were obtained from ref 41, while the medial clusters were parametrized according to ref 42. Charges for the metallic centers (i.e., the active sites of both Hases, the distal and medial clusters in DfHase, the three FeS clusters of AaHase) were obtained through the R.E.D. Server43 using the B3LYP hybrid functional44,45 and the 6-31G* basis set,46 corresponding to the RESP-X1 charge model in R.E.D. To reduce the complexity of the calculations, we only retained the metal atoms and the side chains of the coordinating residues. The Cβ has been treated as a methyl group and the neutrality has been imposed to these four atoms. The metallic centers were maintained rigid during the simulations through an elastic network (spring force constant 200 kJ mol−1 Å−2) between the metallic atoms and the carbons of the side chains of the coordinating residues. System Composition and Force Field Parametrization. The proteins were solvated in a cubic box of water and Na+ and Cl− ions were added afterward at a concentration of 0.150 M. The systems were represented using CHARM27 with CMAP corrections47 and the standard TIP3P water model as implemented in the GROMACS software48 was used. The chosen protonation state was the most probable one at pH 7 based on the default GROMACS guess. Consequently, all Asp and Glu residues were deprotonated, all Arg and Lys residues were protonated. All His were protonated on their Nε, with the exception of H613L, which was protonated on its Nδ, and H289S and H602L that were protonated on both their Nε and Nδ Simulation Setup. Both systems were simulated using GROMACS 4.5.3.49 The system’s energy was initially minimized for 2000 steps, and then equilibrated by simulating for 1 ns in the NVT ensemble and subsequently for 1 ns in the NPT ensemble, prior to starting production runs. The temperature of protein and solvent (water and ions) was separately regulated using the velocity rescaling50 method with a reference temperature of 300 K and a coupling constant of 1

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MATERIALS AND METHODS Classical Molecular Dynamics. Starting Structures. The wild type DfHase crystal structure (PDB-id 1FRF) served as the starting structure for the DfHase simulation, while comparative homology modeling was used to build the original structure for AaHase. The amino acid sequences of the two soluble AaHase domains were taken from the GenBank id AAC06862.1 (small subunit) and AAC06861.1 (large subunit) (an alignment of the AaHase and DfHase sequences is shown B



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ps for both groups. We used the Parinello−Rahman51,52 algorithm to maintain the pressure at 1 atm, the SETTLE53 algorithm to maintain the water rigidity and the LINCS procedure54,55 to constrain the covalent bonds involving hydrogen atoms. The two optimized and relaxed systems were simulated for 2 μs, with a 2.0 fs time step, in periodic boundary conditions. van der Waals interactions were switched off between 1.0 to 1.2 nm, updating the neighbor pair lists every 10 steps while the long-range electrostatic interactions were evaluated through the particle-mesh Ewald method56 with a 1.2 nm cutoff. Analysis. Unless otherwise stated, the trajectories were saved every 5 ps and analyzed with GROMACS 4.5.5 analysis tools. Since the RMSD reaches a stable plateau within 0.2 μs, the analysis has been carried out on the last 1.8 μs, considering the initial 0.2 μs as an equilibration period. We used the g_cluster algorithm from the Gromacs suite with a cutoff of 0.15 nm to obtain five representative structures for each Hase over the simulation production period. Finally, the online software Pocket-Finder (http://www.modelling.leeds.ac.uk/ pocketfinder/)57 was used for detecting cavities in the Hase structures that were produced. Coarse-Grain Brownian Dynamics Simulations. For both Hases, coarse-grained Brownian dynamics simulations using the ProPHet58,59 (Probing Protein Heterogeneity) program have been carried out on five structures produced by clustering the all-atom MD simulations. The simulations used a coarse-grained protein model, in which each amino acid is represented by one pseudoatom located at the Cα position, and either one or two (for larger residues) pseudoatoms replacing the side chain (with the exception of Gly).60 Interactions between the pseudoatoms are treated according to the standard elastic network model.61 The elastic network model is a simplification of the heterogeneity of internal protein forces, as all pseudoatoms lying closer than 9 Å are joined with quadratic springs having the same force constant of 0.6 kcal mol−1 Å−2. Springs are assumed to be relaxed in the starting conformation of the protein. Following earlier studies, which showed that ligands as large as a heme group actually had little influence on calculated force constants,58,62 we chose not to include the prosthetic groups (NiFe and FeS clusters) in the protein representation. The simulations use an implicit solvent representation via the diffusion and random displacement terms in the equation of motion,63 and hydrodynamic interactions are included through the diffusion tensor.64 Further details regarding the simulation procedure can be found in refs 58 and 59. The Brownian dynamics simulations have been performed with 200000 steps at an interval of 10 fs and at a temperature of 300 K. Effective force constants for displacing each particle i were calculated as ki =

taken to be the average of the force constants calculated according to eq 1 for each of the pseudoatoms i forming this residue. Within this framework, the mechanical properties of the protein are described at the residue level by its “rigidity profile”, that is, by the ordered sequence of the force constants (in kcal mol−1 Å−2) calculated for each residue.

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RESULTS AND DISCUSSION (a). Structural Fluctuations. The time evolution of the root-mean-square deviation (RMSD) values with respect to the starting conformations (i.e., the first frame of the trajectory) is shown in Figure SI2a. Both simulations reach stability after the first 0.2 μs that were discarded in the analysis stages. AaHase presents a higher average RMSD value (0.23 nm) than DfHase (0.16 nm), deriving from the fact that, since AaHase is a model, it undergoes slightly larger rearrangements compared to DfHase (which starts from a crystallographic structure) before reaching a stable conformation. The contribution for the two different subunits has been evaluated and is shown in Figures SI2, parts b and c. The small subunits display similar RMSDs (around 0.12 nm) for both enzymes. On the contrary, the large subunit RMSDs are quite different for the two proteins: the average RMSD value reaches 0.22 nm for AaHase, while in DfHAse it remains close to 0.15 nm. These larger fluctuations of the large subunit compared to the small one also appear in the root-mean-square fluctuation (RMSF) profiles of both enzymes (see Figure SI3). (b). Electrostatic Interactions. Electrostatic interactions were recorded for pairs of residues where the minimum distance between the atoms of the charged groups (i.e., COO− of Asp and Glu, NH3+ of Lys and the guanidinium group of Arg) is smaller than 0.5 nm. The total number of interactions as a function of time, as well as the individual contributions of the large subunit, the small one and the intersubunit interface, are reported in Figure SI4. The average number of salt bridges is higher in AaHase than DfHase (90 and 70 respectively). The biggest difference occurring in the large subunit where 65 couples have been detected in AaHase and 50 in DfHase (Figure SI4c). In the small subunit the difference is smaller: 22 interactions in AaHase versus 18 in DfHase (Figure SI4b). Finally, only a few interactions are detected at the interfaces without any remarkable difference (Figure SI4d). In line with the simulations, the available X-ray structures of the O2-tolerant proteins do present more charge−charge interactions (Table SI1) than the O2-sensitive enzymes. As usually found in thermostable proteins,65,66 AaHase presents more charged saltbridges on its surface in comparison with the mesophile DfHase. Few interactions involving residues of the same charge have been detected, conserved couples made of two negative charges are present during 70% of the trajectory, forming a network composed by Glu13L, Glu58S, and Glu118S in AaHase (Glu25L, Glu16S, and Glu75S in DfHase). It is very likely that these three residues are involved in the coupled electron−proton transport, as pointed out by mutational67 and computational68,69 studies carried out on DfHase, that focused on the role of Glu25L, whose substitution with an aspartic acid impairs the proton transport. Their role will be discussed later on in this paper. In the present simulations Glu13L presents two conformations (Figure 2). The most populated rotamer (found in 70% of the AaHase simulation and 100% of DfHase, and shown in orange in Figure 2) points its carboxylic group toward the proximal FeS clusters in a conformation close to the Xray structures. The

3kBT ⟨(di − ⟨di⟩)2 ⟩

(1)

where the brackets indicate the average taken over the whole simulation, kB is the Boltzmann constant, and di is the average distance of particle i from the other particles j in the protein, excluding the pseudoatoms, which belong to the same residue m to which also particle i belongs. The distances between the Cα pseudoatom of residue m and the Cα pseudoatoms of the adjacent residues m + 1 and m − 1 are not included in the average. The force constant associated with each residue m is C



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Pro192S). In DfHase, these peaks indicating rigid residues are conserved and observed for Cys17S, Thr18S, Glu22S, Arg26S, Glu75S, Cys147S, and Pro148S, with an additional peak for Thr47S which is located on the S/L interface. The L chain rigidity profile for both enzymes is dominated by residues surrounding the [NiFe] cluster, namely Cys62L, Val64L, Cys65L, Leu100L, Asp104L, Arg540L, Cys607L, and Cys610L in AaHase, and their equivalents in DfHase: Cys72L, Val74L, Cys75L, Gln110L, Asp114L, Arg476L, Cys543L, and Cys546L. The L chain of DfHase presents an additional peak compared with AaHase for residue Glu25L, which has been identified as a key point for proton transfer during the enzyme’s catalytic cycle.67 Note that, as we mentioned earlier, during the all-atom simulations, Glu25L forms a network with rigid residues Glu16S and Glu75S (see Figure 2) which are involved in a proton transfer pathway from the active site to the molecular surface.71,72 Overall, the most rigid residues of theses Hases are either located around the active sites (in particular the cysteines bound to the NiFe and proximal FeS clusters, which present remarkably small RMSF’s in the all-atom simulation, see Figure SI3), or at the S/L interface, a common feature of multidomain proteic systems.58,73−75 Next to the proximal cluster, DfHis228L and AaHis237L also present small rigidity peaks, and are thought to play a part in the O2-tolerance of the Hase from S. enterica.76 (d). Mechanical Fluctuations in Ni−Fe Hases during All-Atom MD Simulations. Following a procedure developed in an earlier work on globins (see ref 29), we compared the rigidity profiles obtained for the five structures produced by clustering all-atom MD simulations. Although these structures do not present important variations, with Cα RMSDs between two conformations that are always inferior to 3 Å, these small structural changes are nonetheless sufficient to induce noticeable variations of the mechanical properties of a limited number of residues. For both Hases, we made a pairwise comparison of the five rigidity profiles, and for each residue we kept the maximum value that could be observed for its force constant variation. The resulting max(⊗k) profiles are plotted in Figure 4. We then define as “mechanically sensitive” (MS) those residues presenting a max(⊗k) value above a given threshold of 20 kcal mol−1 Å−2 for AaHase and 15 kcal mol−1 Å−2 for DfHase. This procedure leads to the selection of around

Figure 2. Close up view of the active site of AaHase, with the large subunit in white, the small one in gray, and the two conformations of residue Glu13L shown in orange and purple.

network composed by these three negative residues is intrinsically unfavorable, but is stabilized by two Na+ ions. Although in the experimental structures this position is assigned to water molecules, the presence of the ions is more likely since they would neutralize the three negative charges. The second conformation (observed in 30% of the AaHase conformations and shown in purple in Figure 2), has the carboxylic group pointing toward the active site. Interestingly, this dual conformation of a Glu residue (Glu279) involved in proton transport has also been observed in MD simulations of [Fe− Fe]-Hase from Clostridium pasteurianum.70 (c). General Mechanical Properties of Ni−Fe Hases from A. aeolicus and D. fructosovorans. The important sequence identity between both Hases leads to considerable structural similarity, which in turn results in similar rigidity profiles for both enzymes (see Figure 3). In AaHase, the profile of the S chain shows rigidity peaks corresponding to residues located at the interface between the two subunits S and L (Thr60S, Glu64S, and Arg68S) and surrounding the proximal FeS cluster (Cys59S, Cys61S, Cys62S, Glu118S, Cys191S,

Figure 3. Force constant profiles of the main structural cluster for the two [NiFe]-Hases under study. AaHase: (a) small subunit, (b) large subunit. DfHase: (c) small subunit, (d) large subunit. All curves are in kcal mol−1 Å−2 (note that 1 kcal mol−1 Å−2 = 0.7 n m−1). D



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Figure 4. Maximum variation (in kcal mol−1 Å−2) of the force constant upon changing the Hases conformation. AaHase: (a) small subunit, (b) large subunit. DfHase: (c) small subunit, (d) large subunit. The red horizontal lines indicate the threshold values chosen for the selection of mechanically sensitive residues that are listed in Tables 1 and SI2.

In addition, Thr47S and Val120S of DfHase, which are listed as tunnel lining,68,78 present a rigidity peak and are mechanically sensitive, while Thr89S, and Val183S, their AaHase counterparts, have no such properties. Finally, a recent study on the Hase from S. enterica showed that residue Glu73L is important in the oxygen tolerance mechanism,76 this residue’s equivalent in DfHase, Gln69L, is listed as mechanically sensitive, while the AaHase equivalent (Gln59L) is not (see Table SI2). (e). Hydrophobic Tunnels. The active site of [NiFe]hydrogenases is buried in the large subunit near the intersubunit interface. However, previous crystallographic and simulation studies identified a tunnel network in DfHase and the [NiFe]-Hase from D. gigas, connecting the active site with the solvent and permitting the access of the substrate as well as inhibitors.68,82,87 To characterize these tunnels, we combined results obtained with the CAVER software88 to find the channels and analyses carried out with the MDPocket program89 to estimate their volume and the composition of the surface. Our calculations confirm that the environment around these cavities is essentially hydrophobic as demonstrated by the ratio of apolar to total solvent accessible surface area (59% in AaHase and 65% in DfHase). The inspection of the five most frequent tunnels for both enzymes (Figures 5 and 6) shows that the respective cavity networks are quite different. As seen in Figure 5, DfHase presents entry points located on multiple sides of the enzyme, which finally meet in the [NiFe] active site. Figure 5a uses the same perspective as in Figure 1 from Montet et al.,87 and we can see how the tunnel network located in the enzyme’s lower part shows similarities with the “VA”-shaped tunnels that were previously observed in experimental and theoretical investigations made on DfHase and on the [NiFe]-Hase from D. gigas.68,78,79,82,87 Furthermore, tunnels directed toward the enzyme’s upper part can be related to pathways 2 and 3 that have been identified by Wang et al.83 using different simulation techniques on DfHase. CAVER computes internal tunnels that reach the protein surface using the central [NiFe]-active site as a starting point from equilibrium MD simulations on the protein without any substrates, thus giving us information on the Hases intrinsic structural properties. On the other hand, Wang et al.83 performed equilibrium and non equilibrium (with an external constraint applied on the substrate molecule) MD simulations

10% of the residues, i.e. Thirty residues for each enzyme. After analyzing the cluster-representative structures with the PocketFinder program,57,77 it appears that our MS residues are almost always lining internal cavities within the Hases, and that roughly one-half of the MS residues are frontier residues, that is, aminoacids lining two or more internal cavities. Furthermore, 17 MS residue positions are common to both Hases (see Table 1). Table 1. List of the Positions Corresponding to Mechanically Sensitive Residues That Are Common to both Hases S chain AaHase

Ser63/Glu64

DfHase

Thr21/Glu22

L chain Ile12/Cys62/Gly63/Val64/Cys65/Leu100/ Asp104/Val107/Leu112/Pro236/Pro539/ Arg540/Thr563/Cys607/Ala609 Ile24/Cys72/Gly73/Val74/Cys75/Gln110/ Asp114/Val117/Leu122/Pro227/Pro475/ Arg476/Ser499/Cys543/Ala545

In a previous study on the globin family,29 we have shown how, for MS-frontier residues, the combinations of these two specific qualities, a fluctuating rigidity and a strategic location between two cavities, allows them to as gates between these cavities and play a key role for the control of ligand diffusion along the internal tunnel network. It seems that the same applies to MS-frontier residues in [NiFe]-Hases, as the key positions detected by our CG simulations have already been mentioned in numerous studies on this protein family. Three MS residues in particular, Val74L, Leu122L and Arg476L (DfHase numbering), are usually considered as key control points for H2 diffusion in the hydrophobic channels near the active site, and have been highlighted in a number of experimental11,12,14,78−81 and theoretical works68,69,82−86 performed mainly on DfHase, but also on [NiFe]-Hases from other organisms such as D. gigas,68 D. baculatum,85 or R. eutropha.11,14 Other important MS residues for both enzymes and that appear in previous studies on [NiFe]-Hases are Thr21S, Glu22S and Val117L in DfHase (respectively Ser63S, Glu64S and Val107L in AaHase), which are conserved tunnel lining residues in this family.68,78 Furthermore, the equivalent of Thr21S in the [NiFe]-Hase from D. gigas is involved in the proton transfer pathway.34 E



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Hases and therefore become useless, since small substrates could no longer enter them. These differences notwithstanding, in both proteins, the mouth of the hydrophobic tunnels is surrounded by the Df Val74L/Leu122L/Arg476L (respectively Aa Val64L/Leu112L/ Arg486L) triad (shown in orange in Figures. 5 and 6), which we previously highlighted as being formed by MS residues, and that are thought to form a “bottleneck” for gas diffusion within the protein.69,91 Put together, our data regarding the enzymes’ mechanical properties and the hydrophobic tunnels’ topology support the idea that, just like globins, [NiFe]-Hases possess a central mechanical nucleus built from frontier residues that control ligand diffusion within the protein. Compared to AaHase, DfHase presents two more MS-residues that might be of importance for the control of internal ligand migration. Thr47S and Val120S (shown in purple in Figure 5) both lie next to the tunnel network, Thr47S in particular is located at the junction between two major tunnels (see Figures 5b and c). It has long been thought that the tolerance to O2 and CO of Hases originated in a narrow bottleneck. Although several results have been obtained through mutations,11−13,68,79 this hypothesis has been superseded by the resolution of several oxygen resistant Hases.14−17,19−22,81 To check the influence of the tunnel size, the total volume of the tunnels (Figure SI5) as well as the distance V64L−L112L between the Cβ of L122 and Cγ of V64 have been measured (Figure SI6). The distribution of the sections is centered at 1 nm for AaHase and 0.9 nm for DfHase (in line with the average value of 0.8 nm found in ref 84), in agreement with previous data showing that this Val-Leu gate diameter is larger in the O2-tolerant MBH from R. eutropha than in the O2-sensitive hydrogenases from D. vulgaris, D. Fructosovorans, and A. vinosum.14,81 Furthermore, the volume of the cavity harboring the active site is smaller in DfHase than in AaHase, with an average volume of 2.0 nm3 in the former and 2.5 nm3 in the latter. Altogether, these data confirm that, at least for the natural enzymes, narrower hydrophobic tunnels do not necessarily lead to O2-tolerance. (b). Proton Transport Pathways. After hydrogen cleavage, two protons are generated. Coupling experiments with theory, roughly two different pathways have been proposed in soluble Hases from the Desulfovibrio family or the membrane-bound Hyn Hase from Thiocapsa roseopersicina (TrHase).28 Although this paper focuses on the general description of the conformational features of AaHase and DfHase, the simulations can contribute to the discussion as they provide−to the best of our knowledge−the first insight into hydrogenase conformational dynamics on the microsecond time scale. In Hases from the Desulfovibrio family, it is widely accepted that, following the heterolytic scission of the H2 molecule, the resulting proton is transferred to DfCys543L and then to DfGlu25L (see ref67), while the homologous residue in TrHase only plays a marginal role.92 Although no data are available for AaHase, AaGlu13L probably plays an important role, since, as stated earlier, its side-chain presents two conformations pointing either toward the proximal FeS cluster or the active site. Additionally, AaGlu13L is listed as a MS residue, thus further supporting the hypothesis of its functional relevance. Until now, computational studies on Hases from D. gigas,72 D. fructosovorans,71 or D. vulgaris Miyazaki93 converged on the central role of residues DfGlu16S, DfGlu46S, DfGlu75S, and DfGlu25L (respectively AaGlu58S, AaGlu88S, AaGlu118S, and AaGlu13L), while there is less agreement regarding the final

Figure 5. Three different views of DfHase showing the five more frequent tunnels colored in blue, with the mechanical nucleus (Val74L, Leu122L, and Arg476L) residues represented as orange van der Waals spheres. In addition, mechanically sensitive residues Thr47S and Val120S are represented as purple van der Waals spheres.

Figure 6. Three different view of AaHase showing the five more frequent tunnels colored in blue, with the mechanical nucleus (Val64L, Leu112L, and Arg540L) residues represented as orange van der Waals spheres.

on the enzyme with substrate molecules (H2 or O2) and were therefore able to obtain substrate diffusion rates within the enzyme. AaHase presents multiple substrate entry points, but these are all located on the same side of the enzyme’s surface (see Figure 6), with the branches merging in a single tunnel reaching the active site (Figure 6b). This variety in the tunnels’ topology might be related to the Hases’ biological environment: while any side of the soluble DfHase surface should be solvent accessible and can serve as an entry point for molecular hydrogen, in the case of the membrane-bound AaHase, the enzyme’s attachment to the membrane might result in the shielding of some parts of its surface, which a small substrate could no longer use as entry point to reach the [NiFe] active site. For example, the MBH from E. coli can form a complex with cytochrome b comprising two Hases and a cytochrome subunit.90 In such a structure, the hydrophobic tunnels that are specific to DfHase in Figure 5 (on the enzyme’s upper side in panels 5a and 5b) would lie on the interface between the two F



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Figure 7. Two putative proton transfer pathways for the Hases: (a, b) DfHase (c, d) DfHase.

partners.28 The work of Sumner and Voth93 on the Hase from D. vulgaris Miyazaki is of particular interest, since they used multistate empirical valence-bond reactive MD simulations coupled with metadynamics In contrast with previous computational studies, this methodology allowed to find unbiased proton transport pathways. Figures 7a and SI7a show an interaction network centered on DfGlu25L based on the MD simulation electrostatic interactions and hydrogen bond record and on the enzymes’ mechanical properties. The network is composed of DfTrp11S, DfGlu16S, DfThr18S, DfThr21S, DfGlu46S, DfGlu75S, and DfGlu25L. DfGlu46S is exposed to the solvent and could be the last protein residue holding the proton before its release into water, at least in D.fructosovorans. Although several residues of the previous list are conserved in AaHase, the interactions they are involved in are slightly different. The substitutions AaAsp88S/DfGlu46S and AaArg102 S /DfLeu60 S promote the formation of AaAsp88S−AaArg102S and AaAsp87S−AaArg102S salt-bridges, resulting in the disconnection of AaAsp88S from AaGlu13L (see Figures 7c and SI7c). Interestingly, DfGlu16S, DfGlu46S, DfGlu75S and DfGlu25L are all rigid residues (Figure 3, parts c and d), while in AaHase only Glu58S and Glu118S present rigidity peaks. Moreover, the two conserved MS residue positions AaSer63S, and AaGlu64S (corresponding to DfTrh21S and DfGlu22S) in AaHase are not linked to the proposed proton pathway like in DfHase (through the hydrogen bond

between Thr21S and Glu75S). This observation can be related to the different lengths of the pathways. In DfHase the first solvent-exposed residue is Glu46S, while in AaHase, Glu13L (i.e., the putative proton acceptor) lines a cavity thus making the transfer to the solvent easier. In addition, MS residues AaSer63S and AaGlu64S control an internal cavity without being connected to the proposed proton pathway. On the contrary, in DfHase a link between the proposed proton pathway and cavity controlling residues (through the hydrogen bond between Thr21S and Glu75S) suggests a communication pathway binding these two entities. For the membrane-bound Hyn Hase from T. roseorpersicina, Szori-Doroghàzi et al.92 propose a completely different pathway composed by TrArg487L, TrAsp103L, TrHis104L, TrGlu436L (corresponding to AaArg540 L , AaAsp104 L , AaHis105 L , AaArg435 L , and DfArg476 L , DfAsp114 L , DfHis115 L , DfArg388L) using homology modeling based on the X-ray structure of the periplasmic [Ni−Fe]-Hase from D. vulgaris Miyazaki and tested through mutagenesis. In particular, they find that TrHis104L is quite important for the H+ transport while the homologue of DfGlu25L /AaGlu13L only plays a secondary role. Interestingly, this alternative pathway presents similarities with the proton transports pathway 3 obtained by Sumner and Voth in a computational study on this same Hase from D. vulgaris Miyazaki.93 DfArg476L occupies a conserved MS position (Table 1) and could be a bridge between the G



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protein, in a first step via the migration of molecular H2 in hydrophobic tunnels, and, after oxidation, via proton transport pathways. The joint investigation of the protein mechanics and internal cavity network shows that both Hases present a conserved mechanical nucleus formed by a Val/Leu/Arg triad, that controls ligand migration in the vicinity of the active site. In DfHase this nucleus is completed by two additional mechanically sensitive residues, Thr47S and Val120S lining the hydrophobic tunnels. This triad, whose properties had previously been highlighted in numerous experimental and theoretical studies on various [NiFe]-Hases, presents similarities with the four residues forming the mechanical nucleus of globins that we identified in a previous work,29 and that are known to control ligand migration in the protein internal cavity network. Further work on other globular protein families, in particular redox enzymes presenting internal cavities and channels,12,101,102 will therefore be needed to determine wether this is a common feature for this class of proteins. Another key point is that the hydrophobic tunnels and cavities are actually larger in AaHase than in DfHase. While in O2-sensitive Hases a narrow bottleneck for gas diffusion could be a strategy to improve the O2tolerance,91,103 our results support the idea that, at least in MBHs, O2-tolerance does not arise from a restricted substrate access to the active site, but more likely from the structural rearrangement of the metal cofactors.21 Finally, the different topologies of the hydrophobic tunnel networks for both Hases might be related to their soluble or membrane-bound nature. Regarding the proton transport pathways, the importance of residues DfGlu25L, that had already been pointed out by mutational studies,67 has been confirmed and also shown for its AaHase homologue AaGlu13L. On the basis of the all-atom MD simulations, two possible proton shuttle mechanisms have been suggested. One starts from this Glu residue, which transfers the proton to its neighbors DfGlu16S or DfGlu46S (respectively AaGlu58S and AaGlu118S), while the other one begins on the opposite side of the active-site with an initial transfer to DfArg476L (AaArg540L). Interestingly, DfGlu25L is encaged in a highly rigid interaction with DfGlu16S, DfThr18S, and DfGlu75S that severely slows down its side-chain rotation rate. In order to recover a functional active site, an O2-tolerant Hase must send it back electrons but also protons. Hence the higher rotation rate observed the side-chain of Glu13L in AaHase might contribute to a faster donation of protons toward the oxidized active site and play an important part in the oxygen-tolerance mechanism. Further studies will be needed to better characterize these two proteins. First, experimental data or in silico experiments are needed to validate the suggested proton pathways as well as their relative weight in the context of the balance between hydrogen oxidation and reduction. Furthermore, we did not address the thermophilicity difference observed in the two proteins, the optimal functioning temperatures of the two proteins being 35 °C for DfHase and 85 °C for AaHase.24,104 Homology modeling did not reveal any significant differences allowing for such a large temperature gap. However, the simulations were carried out at room temperature, and therefore high temperature simulations could bring in new information on the subject. Finally, since AaHase is a promising candidate for the development of biofuel cells, further studies will address the impact of the enzyme’s interaction with electrodes on its function, and in particular how it can affect

active site and a proton pathway. It is in fact crucial for active site stability in DfHase,94 while in T. roseopersicina its homologue participates to H+ transport together with the homologue of DfHis115L and DfGlu431L. In the all-atom simulations, these three residues are involved in an interaction network made by DfAsp114 L , DfArg388L , DfArg428 L , DfAsp473L, DfArg476L, DfAsp541L and DfHis115L. Interestingly, a continuous pathway connecting the active site and the solvent passing through these residues can be identified in AaHase (Figures 7d and SI7d). Indeed, in AaHase the conserved electrostatic clusters are connected by the His105L (homologue of TrHis104L) bridging Glu489L and Arg486L. This pathway comprises two conserved MS residues: Asp104L and Arg540L (Table 1). On the contrary, in DfHase the two clusters are not connected but His115L is exposed and could be the putative proton release point (Figures 7b and SI7b). In this pathway there are four MS residues (conserved or not): Asp114L, His115L, Arg476L and Asp541L (Tables 1 and SI2). These simulation data, together with the experimental results on D. f ructosovorans67 and T. roseopersicina92 suggest two possible scenarios. First, different strategies might have been adopted to transport the protons in different classes of Hase. In line with this hypothesis, the position of the solvent exposed DfGlu46S can discriminate between [NiFe]-Hases from the Desulfovibrio family and H2-sensing hydrogenases. Figure 9 in ref 95 shows that in Desulfovibrio Hases this position is occupied by a Glu, while in H2-sensitive hydrogenases it is occupied by a Pro, or an Asp in O2-tolerant Hases (like AaAsp88S, see Figure SI5 from ref 14). Moreover, in T. roseorpersicina (where a different proton pathway has been reported) this position is occupied by a histidine. Because of its position close to the proximal FeS cluster and its role in the interaction network of DfGlu25L, this residue might explain the differences observed in TrHase with respect to DfHase, for example by impairing proton transport via a different pKa and redirecting it toward an alternative pathway. This position may also be responsible for controlling the H2 reduction/oxidation balance. In line with this hypothesis, O2-tolerant Hases can only oxidize molecular hydrogen,25 while in Desulfovibrio Hases the oxidation reaction is predominant, and in T. roseorpersicina the weight of the oxidation with respect to the reduction is nearly the same.92 Finally, we can note that this configuration with two proton transport pathways located on opposite sides of the active site has also been observed in a computational study on the [Fe−Fe]-Hase from Clostridium pasteurianum that combined atomistic and coarse-grained calculations,96 thus suggesting that this feature might be common to several Hase classes.

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CONCLUSION Hydrogenases play a central part in the development of green economy and several studies have been published both for energy5,6 and hydrogen8 production. Different techniques such as spectroscopy,18,97,98 site-directed mutagenesis,67,92 and in silico approaches68,69,82−84 have been used to clarify the complexity associated with this family. Among the hydrogenases, the [NiFe]-Hases of D. f ructosovorans and A. aeolicus have been widely studied.26,99,100 Unlike previous approaches, we used homology modeling coupled with long time scale all-atom molecular dynamics and coarse-grain Brownian dynamics simulation to assess the enzymes’ dynamic and mechanical properties. The results bring light on the in- and out- pathways of hydrogen in the H



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and oxygen sensitivity in hydrogenase. Nature Chem. Biol. 2010, 6 (1), 63−70. (13) Leroux, F.; Liebgott, P. P.; Cournac, L.; Richaud, P.; Kpebe, A.; Burlat, B.; Guigliarelli, B.; Bertrand, P.; Leger, C.; Rousset, M.; Dementin, S. Is engineering O-2-tolerant hydrogenases just a matter of reproducing the active sites of the naturally occurring O-2-resistant enzymes? Int. J. Hydrogen Energy 2010, 35 (19), 10770−10777. (14) Fritsch, J.; Scheerer, P.; Frielingsdorf, S.; Kroschinsky, S.; Friedrich, B.; Lenz, O.; Spahn, C. M. The crystal structure of an oxygen-tolerant hydrogenase uncovers a novel iron-sulphur centre. Nature 2011, 479 (7372), 249−252. (15) Shomura, Y.; Yoon, K. S.; Nishihara, H.; Higuchi, Y. Structural basis for a 4Fe-3S cluster in the oxygen-tolerant membrane-bound NiFe -hydrogenase. Nature 2011, 479 (7372), 253−U143. (16) Volbeda, A.; Amara, P.; Darnault, C.; Mouesca, J. M.; Parkin, A.; Roessler, M. M.; Armstrong, F. A.; Fontecilla-Camps, J. C. X-ray crystallographic and computational studies of the O2-tolerant [NiFe]hydrogenase 1 from Escherichia coli. Proc. Natl. Acad. Sci. U.S.A. 2012, 109 (14), 5305−5310. (17) Pandelia, M. E.; Lubitz, W.; Nitschke, W. Evolution and diversification of Group 1 [NiFe] hydrogenases. Is there a phylogenetic marker for O(2)-tolerance? Biochim. Biophys. Acta 2012, 1817 (9), 1565−1575. (18) Pandelia, M. E.; Nitschke, W.; Infossi, P.; Giudici-Orticoni, M. T.; Bill, E.; Lubitz, W. Characterization of a unique FeS cluster in the electron transfer chain of the oxygen tolerant NiFe hydrogenase from Aquifex aeolicus. Proc. Natl. Acad. Sci. U.S.A. 2011, 108 (15), 6097− 6102. (19) Goris, T.; Wait, A. F.; Saggu, M.; Fritsch, J.; Heidary, N.; Stein, M.; Zebger, I.; Lendzian, F.; Armstrong, F. A.; Friedrich, B.; Lenz, O. A unique iron-sulfur cluster is crucial for oxygen tolerance of a [NiFe]hydrogenase. Nat. Chem. Biol. 2011, 7 (5), 310−318. (20) Mouesca, J. M.; Fontecilla-Camps, J. C.; Amara, P. The structural plasticity of the proximal [4Fe3S] cluster is responsible for the O2 tolerance of membrane-bound [NiFe] hydrogenases. Angew. Chem., Int. Ed. Engl. 2013, 52 (7), 2002−2006. (21) Fritsch, J.; Loscher, S.; Sanganas, O.; Siebert, E.; Zebger, I.; Stein, M.; Ludwig, M.; De Lacey, A. L.; Dau, H.; Friedrich, B.; Lenz, O.; Haumann, M. [NiFe] and [FeS] cofactors in the membrane-bound hydrogenase of Ralstonia eutropha investigated by X-ray absorption spectroscopy: insights into O(2)-tolerant H(2) cleavage. Biochemistry 2011, 50 (26), 5858−5869. (22) Evans, R. M.; Parkin, A.; Roessler, M. M.; Murphy, B. J.; Adamson, H.; Lukey, M. J.; Sargent, F.; Volbeda, A.; Fontecilla-Camps, J. C.; Armstrong, F. A. Principles of sustained enzymatic hydrogen oxidation in the presence of oxygen–the crucial influence of high potential Fe-S clusters in the electron relay of [NiFe]-hydrogenases. J. Am. Chem. Soc. 2013, 135 (7), 2694−2707. (23) Guiral, M.; Tron, P.; Aubert, C.; Gloter, A.; Iobbi-Nivol, C.; Giudici-Orticoni, M. T. A membrane-bound multienzyme, hydrogenoxidizing, and sulfur-reducing complex from the hyperthermophilic bacterium Aquifex aeolicus. J. Biol. Chem. 2005, 280 (51), 42004− 42015. (24) Luo, X.; Brugna, M.; Tron-Infossi, P.; Giudici-Orticoni, M. T.; Lojou, E. Immobilization of the hyperthermophilic hydrogenase from Aquifex aeolicus bacterium onto gold and carbon nanotube electrodes for efficient H2 oxidation. J. Biol. Inorg. Chem. 2009, 14 (8), 1275− 1288. (25) Pandelia, M. E.; Fourmond, V.; Tron-Infossi, P.; Lojou, E.; Bertrand, P.; Leger, C.; Giudici-Orticoni, M. T.; Lubitz, W. Membrane-bound hydrogenase I from the hyperthermophilic bacterium Aquifex aeolicus: enzyme activation, redox intermediates and oxygen tolerance. J. Am. Chem. Soc. 2010, 132 (20), 6991−7004. (26) Oteri, F.; Ciaccafava, A.; de Poulpiquet, A.; Baaden, M.; Lojou, E.; Sacquin-Mora, S. The weak, fluctuating, dipole moment of membrane-bound hydrogenase from Aquifex aeolicus accounts for its adaptability to charged electrodes. Phys. Chem. Chem. Phys. 2014, 16 (23), 11318−11322.

hydrogen migration within the protein before and after redox events.

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ASSOCIATED CONTENT

S Supporting Information *

Sequence alignment for the two Hases, structural data (RMSD, RMSF, number of electrostatic interactions, cavity volumes, distance distributions) from the MD simulations, and schematic representations of the proton pathways in both Hases. This material is available free of charge via the Internet at http:// pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*(S.S.-M.) E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank the ANR Bioénergies for financial support (Grant ANR-10-BIOE-003), this work was further supported by the “Initiative d’Excellence” program from the French State (Grant “DYNAMO”, ANR-11-LABX-0011).

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REFERENCES

(1) Vignais, P. M.; Billoud, B. Occurrence, classification, and biological function of hydrogenases: an overview. Chem. Rev. 2007, 107 (10), 4206−4272. (2) Lubitz, W.; Ogata, H.; Rudiger, O.; Reijerse, E. Hydrogenases. Chem. Rev. 2014, 114 (8), 4081−4148. (3) Friedrich, B.; Fritsch, J.; Lenz, O. Oxygen-tolerant hydrogenases in hydrogen-based technologies. Curr. Opin. Biotechnol. 2011, 22 (3), 358−364. (4) Shafaat, H. S.; Rudiger, O.; Ogata, H.; Lubitz, W. [NiFe] hydrogenases: a common active site for hydrogen metabolism under diverse conditions. Biochim. Biophys. Acta 2013, 1827 (8−9), 986− 1002. (5) Ciaccafava, A.; De Poulpiquet, A.; Techer, V.; Giudici-Orticoni, M. T.; Tingry, S.; Innocent, C.; Lojou, E. An innovative powerful and mediatorless H2/O2 biofuel cell based on an outstanding bioanode. Electrochem. Commun. 2012, 23, 25−28. (6) Xu, L.; Armstrong, F. A. Optimizing the power of enzyme-based membrane-less hydrogen fuel cells for hydrogen-rich H2−air mixtures. Energy Environ. Sci. 2013, 6 (7), 2166. (7) de Poulpiquet, A.; Ranava, D.; Monsalve, K.; Giudici-Orticoni, M.-T.; Lojou, E. Biohydrogen for a New Generation of H2/O2 Biofuel Cells: A Sustainable Energy Perspective. ChemElectroChem. 2014, 1 (11), 1724−1750. (8) Kim, D. H.; Kim, M. S. Hydrogenases for biological hydrogen production. Bioresour. Technol. 2011, 102 (18), 8423−8431. (9) King, P. W. Designing interfaces of hydrogenase-nanomaterial hybrids for efficient solar conversion. Biochim. Biophys. Acta 2013, 1827 (8−9), 949−957. (10) de Poulpiquet, A.; Ciaccafava, A.; Gadiou, R.; Gounel, S.; Giudici-Orticoni, M. T.; Mano, N.; Lojou, E. Design of a H-2/O-2 biofuel cell based on thermostable enzymes. Electrochem. Commun. 2014, 42, 72−74. (11) Buhrke, T.; Lenz, O.; Krauss, N.; Friedrich, B. Oxygen tolerance of the H2-sensing [NiFe] hydrogenase from Ralstonia eutropha H16 is based on limited access of oxygen to the active site. J. Biol. Chem. 2005, 280 (25), 23791−23796. (12) Liebgott, P. P.; Leroux, F.; Burlat, B.; Dementin, S.; Baffert, C.; Lautier, T.; Fourmond, V.; Ceccaldi, P.; Cavazza, C.; Meynial-Salles, I.; Soucaille, P.; Fontecilla-Camps, J. C.; Guigliarelli, B.; Bertrand, P.; Rousset, M.; Leger, C. Relating diffusion along the substrate tunnel I



Article

(27) Berman, H. M.; Battistuz, T.; Bhat, T. N.; Bluhm, W. F.; Bourne, P. E.; Burkhardt, K.; Feng, Z.; Gilliland, G. L.; Iype, L.; Jain, S.; Fagan, P.; Marvin, J.; Padilla, D.; Ravichandran, V.; Schneider, B.; Thanki, N.; Weissig, H.; Westbrook, J. D.; Zardecki, C. The Protein Data Bank. Acta Crystallogr., Sect. D: Biol. Crystallogr. 2002, 58 (Pt 6 No 1), 899−907. (28) Greco, C.; Fourmond, V.; Baffert, C.; Wang, P. H.; Dementin, S.; Bertrand, P.; Bruschi, M.; Blumberger, J.; De Gioia, L.; Leger, C. Combining experimental and theoretical methods to learn about the reactivity of gas-processing metalloenzymes. Energy Environ. Sci. 2014, 7, 3543−3573. (29) Bocahut, A.; Bernad, S.; Sebban, P.; Sacquin-Mora, S. Frontier residues lining globin internal cavities present specific mechanical properties. J. Am. Chem. Soc. 2011, 133 (22), 8753−8761. (30) Fiser, A.; Do, R. K.; Sali, A. Modeling of loops in protein structures. Protein Sci. 2000, 9 (9), 1753−1773. (31) Fiser, A.; Sali, A. Modeller: generation and refinement of homology-based protein structure models. Methods Enzymol. 2003, 374, 461−491. (32) Matias, P. M.; Soares, C. M.; Saraiva, L. M.; Coelho, R.; Morais, J.; Le Gall, J.; Carrondo, M. A. [NiFe] hydrogenase from Desulfovibrio desulfuricans ATCC 27774: gene sequencing, three-dimensional structure determination and refinement at 1.8 A and modelling studies of its interaction with the tetrahaem cytochrome c3. J. Biol. Inorg. Chem. 2001, 6 (1), 63−81. (33) Ogata, H.; Hirota, S.; Nakahara, A.; Komori, H.; Shibata, N.; Kato, T.; Kano, K.; Higuchi, Y. Activation process of [NiFe] hydrogenase elucidated by high-resolution X-ray analyses: conversion of the ready to the unready state. Structure 2005, 13 (11), 1635−1642. (34) Volbeda, A.; Charon, M. H.; Piras, C.; Hatchikian, E. C.; Frey, M.; Fontecilla-Camps, J. C. Crystal structure of the nickel-iron hydrogenase from Desulfovibrio gigas. Nature 1995, 373 (6515), 580− 587. (35) Volbeda, A.; Martin, L.; Cavazza, C.; Matho, M.; Faber, B. W.; Roseboom, W.; Albracht, S. P. J.; Garcin, E.; Rousset, M.; FontecillaCamps, J. C. Structural differences between the ready and unready oxidized states of NiFe hydrogenases. J. Biol. Inorg. Chem. 2005, 10 (3), 239−249. (36) Ogata, H.; Kellers, P.; Lubitz, W. The crystal structure of the [NiFe] hydrogenase from the photosynthetic bacterium Allochromatium vinosum: characterization of the oxidized enzyme (Ni-A state). J. Mol. Biol. 2010, 402 (2), 428−444. (37) Pettersen, E. F.; Goddard, T. D.; Huang, C. C.; Couch, G. S.; Greenblatt, D. M.; Meng, E. C.; Ferrin, T. E. UCSF Chimera–a visualization system for exploratory research and analysis. J. Comput. Chem. 2004, 25 (13), 1605−1612. (38) Couch, G. S.; Hendrix, D. K.; Ferrin, T. E. Nucleic acid visualization with UCSF Chimera. Nucleic Acids Res. 2006, 34 (4), e29. (39) Davis, I. W.; Leaver-Fay, A.; Chen, V. B.; Block, J. N.; Kapral, G. J.; Wang, X.; Murray, L. W.; Arendall, W. B., 3rd; Snoeyink, J.; Richardson, J. S.; Richardson, D. C. MolProbity: all-atom contacts and structure validation for proteins and nucleic acids. Nucleic Acids Res. 2007, 35 (Web Server issue), W375−W383. (40) Niu, S.; Thomson, L. M.; Hall, M. B. Theoretical Characterization of the Reaction Intermediates in a Model of the Nickel−Iron Hydrogenase of Desulfovibrio gigas. J. Am. Chem. Soc. 1999, 121, 4000−4007. (41) Chang, C. H.; Kim, K. Density Functional Theory Calculation of Bonding and Charge Parameters for Molecular Dynamics Studies on [FeFe] Hydrogenases. J. Chem. Theory Comput. 2009, 5 (4), 1137− 1145. (42) Meuwly, M.; Karplus, M. Theoretical investigations of Ferredoxin I: the possible role of internal water molecules on the coupled electron proton transfer reaction. Faraday Discuss 2003, 124, 297−313 discussion 343−252, 453−295.. (43) Dupradeau, F. Y.; Pigache, A.; Zaffran, T.; Savineau, C.; Lelong, R.; Grivel, N.; Lelong, D.; Rosanski, W.; Cieplak, P. The R.E.D. tools: advances in RESP and ESP charge derivation and force field library building. Phys. Chem. Chem. Phys. 2010, 12 (28), 7821−7839.

(44) Becke, A. D. Density-functional exchange-energy approximation with correct asymptotic behavior. Phys. Rev. A 1988, 38 (6), 3098− 3100. (45) Lee, C. T.; Yang, W. T.; Parr, R. G. Development of the ColleSalvetti correlation-energy formula into a functional of the electrondensity. Phys. Rev. B 1988, 37 (2), 785−789. (46) Rassolov, V. A.; Ratner, M. A.; Pople, J. A.; Redfern, P. C.; Curtiss, L. A. 6-31G*basis set for third-row atoms. J. Comput. Chem. 2001, 22 (9), 976−984. (47) MacKerell, A. D., Jr.; Feig, M.; Brooks, C. L., 3rd Improved treatment of the protein backbone in empirical force fields. J. Am. Chem. Soc. 2004, 126 (3), 698−699. (48) Bjelkmar, P. r.; Larsson, P.; Cuendet, M. A.; Hess, B.; Lindahl, E. Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models. J. Chem. Theory Comput. 2010, 6 (2), 459−466. (49) Hess, B.; Kutzner, F.; Van der Spoel, D.; Lindahl, E. GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 435− 447. (50) Bussi, G.; Parrinello, M. Accurate sampling using Langevin dynamics. Phys. Rev. E 2007, 75 (5 Pt 2), 056707. (51) Nosé, S.; Klein, M. L. Constant pressure molecular dynamics for molecular systems. Mol. Phys. 1983, 50 (5), 1055−1076. (52) Parrinello, M.; Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 1981, 52 (12), 7182−7190. (53) Miyamoto, S.; Kollman, P. A. Settle - an analytical version of the shake and rattle algorithm for rigid water models. J. Comput. Chem. 1992, 13 (8), 952−962. (54) Hess, B.; Bekker, H.; Berendsen, H. J. C.; Fraaije, J. LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem. 1997, 18 (12), 1463−1472. (55) Hess, B. P-LINCS: A Parallel Linear Constraint Solver for Molecular Simulation. J. Chem. Theory Comput. 2007, 4 (1), 116−122. (56) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A smooth particle mesh ewald method. J. Chem. Phys. 1995, 103 (19), 8577−8593. (57) Hendlich, M.; Rippmann, F.; Barnickel, G. LIGSITE: Automatic and efficient detection of potential small molecule-binding sites in proteins. J. Mol. Graphics Model. 1997, 15 (6), 359−+. (58) Sacquin-Mora, S.; Lavery, R. Investigating the local flexibility of functional residues in hemoproteins. Biophys. J. 2006, 90 (8), 2706− 2717. (59) Lavery, R.; Sacquin-Mora, S. Protein mechanics: a route from structure to function. J. Biosci. 2007, 32 (5), 891−898. (60) Zacharias, M. Protein-protein docking with a reduced protein model accounting for side-chain flexibility. Protein Sci. 2003, 12 (6), 1271−1282. (61) Tozzini, V. Coarse-grained models for proteins. Curr. Opin. Struct. Biol. 2005, 15 (2), 144−150. (62) Sacquin-Mora, S.; Laforet, E.; Lavery, R. Locating the active sites of enzymes using mechanical properties. Proteins 2007, 67 (2), 350− 359. (63) Ermak, D. L.; McCammon, J. A. Brownian dynamics with hydrodynamic interactions. J. Chem. Phys. 1978, 69, 1352−1360. (64) Pastor, R. W.; Venable, R.; Karplus, M. Brownian dynamics simulation of a lipid chain in a membrane bilayer. J. Chem. Phys. 1988, 89, 1112−1127. (65) Karshikoff, A.; Ladenstein, R. Ion pairs and the thermotolerance of proteins from hyperthermophiles: a ″traffic rule″ for hot roads. Trends Biochem. Sci. 2001, 26 (9), 550−556. (66) Sterpone, F.; Melchionna, S. Thermophilic proteins: insight and perspective from in silico experiments. Chem. Soc. Rev. 2012, 41 (5), 1665−1676. (67) Dementin, S.; Burlat, B.; De Lacey, A. L.; Pardo, A.; Adryanczyk-Perrier, G.; Guigliarelli, B.; Fernandez, V. M.; Rousset, M. A glutamate is the essential proton transfer gate during the catalytic J



Article

cycle of the [NiFe] hydrogenase. J. Biol. Chem. 2004, 279 (11), 10508−10513. (68) Teixeira, V. H.; Baptista, A. M.; Soares, C. M. Pathways of H2 toward the active site of [NiFe]-hydrogenase. Biophys. J. 2006, 91 (6), 2035−2045. (69) Topin, J.; Rousset, M.; Antonczak, S.; Golebiowski, J. Kinetics and thermodynamics of gas diffusion in a NiFe hydrogenase. Proteins 2012, 80 (3), 677−682. (70) Long, H.; King, P. W.; Chang, C. H. Proton transport in Clostridium pasteurianum [FeFe] hydrogenase I: a computational study. J. Phys. Chem. B 2014, 118 (4), 890−900. (71) Fdez Galvan, I.; Volbeda, A.; Fontecilla-Camps, J. C.; Field, M. J. A QM/MM study of proton transport pathways in a [NiFe] hydrogenase. Proteins 2008, 73 (1), 195−203. (72) Teixeira, V. H.; Soares, C. M.; Baptista, A. M. Proton pathways in a [NiFe]-hydrogenase: A theoretical study. Proteins 2008, 70 (3), 1010−1022. (73) Navizet, I.; Cailliez, F.; Lavery, R. Probing protein mechanics: residue-level properties and their use in defining domains. Biophys. J. 2004, 87 (3), 1426−1435. (74) Stadler, A. M.; Garvey, C. J.; Bocahut, A.; Sacquin-Mora, S.; Digel, I.; Schneider, G. J.; Natali, F.; Artmann, G. M.; Zaccai, G. Thermal fluctuations of haemoglobin from different species: adaptation to temperature via conformational dynamics. J. R. Soc. Interface 2012, 9 (76), 2845−2855. (75) Sacquin-Mora, S. Motions and mechanics: investigating conformational transitions in multi-domain proteins with coarsegrain simulations. Mol. Simul. 2014, 40 (1−3), 229−236. (76) Bowman, L.; Flanagan, L.; Fyfe, P. K.; Parkin, A.; Hunter, W. N.; Sargent, F. How the structure of the large subunit controls function in an oxygen-tolerant [NiFe]-hydrogenase. Biochem. J. 2014, 458 (3), 449−458. (77) Laurie, A. T.; Jackson, R. M. Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites. Bioinformatics 2005, 21 (9), 1908−1916. (78) Fontecilla-Camps, J. C.; Volbeda, A.; Cavazza, C.; Nicolet, Y. Structure/function relationships of [NiFe]- and [FeFe]-hydrogenases. Chem. Rev. 2007, 107 (10), 4273−4303. (79) Leroux, F.; Dementin, S.; Burlat, B.; Cournac, L.; Volbeda, A.; Champ, S.; Martin, L.; Guigliarelli, B.; Bertrand, P.; Fontecilla-Camps, J.; Rousset, M.; Leger, C. Experimental approaches to kinetics of gas diffusion in hydrogenase. Proc. Natl. Acad. Sci. U.S.A. 2008, 105 (32), 11188−11193. (80) Liebgott, P. P.; de Lacey, A. L.; Burlat, B.; Cournac, L.; Richaud, P.; Brugna, M.; Fernandez, V. M.; Guigliarelli, B.; Rousset, M.; Leger, C.; Dementin, S. Original design of an oxygen-tolerant [NiFe] hydrogenase: major effect of a valine-to-cysteine mutation near the active site. J. Am. Chem. Soc. 2011, 133 (4), 986−997. (81) Fritsch, J.; Lenz, O.; Friedrich, B. Structure, function and biosynthesis of O(2)-tolerant hydrogenases. Nat. Rev. Microbiol. 2013, 11 (2), 106−114. (82) Wang, P. H.; Best, R. B.; Blumberger, J. A microscopic model for gas diffusion dynamics in a [NiFe]-hydrogenase. Phys. Chem. Chem. Phys. 2011, 13 (17), 7708−7719. (83) Wang, P. H.; Best, R. B.; Blumberger, J. Multiscale simulation reveals multiple pathways for H2 and O2 transport in a [NiFe]hydrogenase. J. Am. Chem. Soc. 2011, 133 (10), 3548−3556. (84) Wang, P. H.; Blumberger, J. Mechanistic insight into the blocking of CO diffusion in [NiFe]-hydrogenase mutants through multiscale simulation. Proc. Natl. Acad. Sci. U.S.A. 2012, 109 (17), 6399−6404. (85) Baltazar, C. S.; Teixeira, V. H.; Soares, C. M. Structural features of [NiFeSe] and [NiFe] hydrogenases determining their different properties: a computational approach. J. Biol. Inorg. Chem. 2012, 17 (4), 543−555. (86) Topin, J.; Diharce, J.; Fiorucci, S.; Antonczak, S.; Golebiowski, J. O2 migration rates in [NiFe] hydrogenases. A joint approach combining free-energy calculations and kinetic modeling. J. Phys. Chem. B 2014, 118 (3), 676−681.

(87) Montet, Y.; Amara, P.; Volbeda, A.; Vernede, X.; Hatchikian, E. C.; Field, M. J.; Frey, M.; Fontecilla-Camps, J. C. Gas access to the active site of Ni-Fe hydrogenases probed by X-ray crystallography and molecular dynamics. Nat. Struct. Biol. 1997, 4 (7), 523−526. (88) Chovancova, E.; Pavelka, A.; Benes, P.; Strnad, O.; Brezovsky, J.; Kozlikova, B.; Gora, A.; Sustr, V.; Klvana, M.; Medek, P.; Biedermannova, L.; Sochor, J.; Damborsky, J. CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures. PLoS Comput. Biol. 2012, 8 (10), e1002708. (89) Schmidtke, P.; Bidon-Chanal, A.; Luque, F. J.; Barril, X. MDpocket: open-source cavity detection and characterization on molecular dynamics trajectories. Bioinformatics 2011, 27 (23), 3276− 3285. (90) Volbeda, A.; Darnault, C.; Parkin, A.; Sargent, F.; Armstrong, F. A.; Fontecilla-Camps, J. C. Crystal structure of the O(2)-tolerant membrane-bound hydrogenase 1 from Escherichia coli in complex with its cognate cytochrome b. Structure 2013, 21 (1), 184−190. (91) Lubitz, W.; Ogata, H.; Rudiger, O.; Reijerse, E. Hydrogenases. Chem. Rev. 2014, 114 (8), 4081−4148. (92) Szori-Doroghazi, E.; Maroti, G.; Szori, M.; Nyilasi, A.; Rakhely, G.; Kovacs, K. L. Analyses of the Large Subunit Histidine-Rich Motif Expose an Alternative Proton Transfer Pathway in NiFe Hydrogenases. PLoS One 2012, 7 (4). (93) Sumner, I.; Voth, G. A. Proton transport pathways in [NiFe]hydrogenase. J. Phys. Chem. B 2012, 116 (9), 2917−2926. (94) DeLacey, A. L.; Fernandez, V. M.; Rousset, M.; Cavazza, C.; Hatchikian, E. C. Spectroscopic and kinetic characterization of active site mutants of Desulfovibrio fructosovoransNi-Fe hydrogenase. J. Biol. Inorg. Chem. 2003, 8 (1−2), 129−134. (95) Buhrke, T.; Loscher, S.; Lenz, O.; Schlodder, E.; Zebger, I.; Andersen, L. K.; Hildebrandt, P.; Meyer-Klaucke, W.; Dau, H.; Friedrich, B.; Haumann, M. Reduction of unusual iron-sulfur clusters in the H2-sensing regulatory Ni-Fe hydrogenase from Ralstonia eutropha H16. J. Biol. Chem. 2005, 280 (20), 19488−19495. (96) McCullagh, M.; Voth, G. A. Unraveling the role of the protein environment for [FeFe]-hydrogenase: a new application of coarsegraining. J. Phys. Chem. B 2013, 117 (15), 4062−4071. (97) Pandelia, M. E.; Ogata, H.; Currell, L. J.; Flores, M.; Lubitz, W. Probing intermediates in the activation cycle of NiFe hydrogenase by infrared spectroscopy: the Ni-SIr state and its light sensitivity. J. Biol. Inorg. Chem. 2009, 14 (8), 1227−1241. (98) Pandelia, M. E.; Bykov, D.; Izsak, R.; Infossi, P.; GiudiciOrticoni, M. T.; Bill, E.; Neese, F.; Lubitz, W. Electronic structure of the unique 4Fe-3S cluster in O-2-tolerant hydrogenases characterized by Fe-57 Mossbauer and EPR spectroscopy. Proc. Natl. Acad. Sci. U.S.A. 2013, 110 (2), 483−488. (99) Lojou, E.; Luo, X.; Brugna, M.; Candoni, N.; Dementin, S.; Giudici-Orticoni, M. T. Biocatalysts for fuel cells: efficient hydrogenase orientation for H2 oxidation at electrodes modified with carbon nanotubes. J. Biol. Inorg. Chem. 2008, 13 (7), 1157−1167. (100) Lojou, E. Hydrogenases as catalysts for fuel cells: Strategies for efficient immobilization at electrode interfaces. Electrochim. Acta 2011, 56 (28), 10385−10397. (101) Fontecilla-Camps, J. C.; Amara, P.; Cavazza, C.; Nicolet, Y.; Volbeda, A. Structure-function relationships of anaerobic gasprocessing metalloenzymes. Nature 2009, 460 (7257), 814−822. (102) Baron, R.; Riley, C.; Chenprakhon, P.; Thotsaporn, K.; Winter, R. T.; Alfieri, A.; Forneris, F.; van Berkel, W. J. H.; Chaiyen, P.; Fraaije, M. W.; Mattevi, A.; McCammon, J. A. Multiple pathways guide oxygen diffusion into flavoenzyme active sites. Proc. Natl. Acad. Sci. U.S.A. 2009, 106 (26), 10603−10608. (103) Dementin, S.; Leroux, F.; Cournac, L.; de Lacey, A. L.; Volbeda, A.; Leger, C.; Burlat, B.; Martinez, N.; Champ, S.; Martin, L.; Sanganas, O.; Haumann, M.; Fernandez, V. M.; Guigliarelli, B.; Fontecilla-Camps, J. C.; Rousset, M. Introduction of methionines in the gas channel makes [NiFe] hydrogenase aero-tolerant. J. Am. Chem. Soc. 2009, 131 (29), 10156−10164. (104) Brugna-Guiral, M.; Tron, P.; Nitschke, W.; Stetter, K. O.; Burlat, B.; Guigliarelli, B.; Bruschi, M.; Giudici-Orticoni, M. T. NiFe K



Article

hydrogenases from the hyperthermophilic bacterium Aquifex aeolicus: properties, function, and phylogenetics. Extremophiles 2003, 7 (2), 145−157. (105) Humphrey, W.; Dalke, A.; Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 1996, 14 (1), 33−38 27−38..

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