Active sites without restraints: high-resolution analysis of metal cofactors

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ScienceDirect Active sites without restraints: high-resolution analysis of metal cofactors Eva-Maria Burger1, Susana LA Andrade1,2 and Oliver Einsle1,2 For most three-dimensional structures of biological macromolecules, the factual accuracy of atom positions by far exceeds the resolution of the experimental data, although the refinement problem presented by a protein structure is substantially underdetermined. This is achieved through using restraints that precisely define protein geometries and thus reduce the degrees of freedom of the refinement problem. If such information is not available or when unusual geometries or particular ligand states complicate structural analysis, possible pitfalls arise that not only concern the precise definition of spatial arrangements, but also the identification of atom types and bond distances. Prominent examples include CO dehydrogenase, hydrogenase, acetylene hydratase and nitrogenase, all of which employ unique active sites that turned out not to be what they seemed upon first inspection. Addresses 1 Institut fu¨r Biochemie, Albert-Ludwigs-Universita¨t Freiburg, Albertstrasse 21, 79104 Freiburg, Germany 2 BIOSS Centre for Biological Signalling Studies, Scha¨nzlestrasse 1, 79104 Freiburg, Germany Corresponding author: Einsle, Oliver ([email protected])

Current Opinion in Structural Biology 2015, 35:32–40 This review comes from a themed issue on Catalysis and regulation Edited by Judith P Klinman and Amy C Rozenzweig

http://dx.doi.org/10.1016/j.sbi.2015.07.016 0959-440/# 2015 Elsevier Ltd. All rights reserved.

Introduction Modern-day structural biology is indispensable for gaining mechanistic insights into complex biochemical systems [1,2]. Advances in its disciplines frequently make it feasible to characterize the architecture of a novel macromolecule even before addressing the questions of activity, dynamics and interaction that define its physiological functionality. The power of structural analysis lies in its astounding precision that eventually allows deriving exact orientations, distances and angles for the calibration of all subsequent analyses. Crystallography commonly describes the precision of a structure determination through the concept of resolution. In microscopy, resolution is defined as the Current Opinion in Structural Biology 2015, 35:32–40

minimal distance at which two objects (spots, atoms, etc.) can be recognized as being separate (Figure 1a). Although the formal definition in diffraction analysis is somewhat more technical — resolution is the minimal Bragg spacing according to which diffraction maxima can be recorded to sufficient completeness [3] — the two concepts yield a similar outcome. Today the most highly resolved EM images have reached a quality that allows for building and refinement of atomic models [4], very similar to the process established for X-ray diffraction data [5]. The boundaries of both techniques overlap increasingly, holding the promise of many exciting revelations to be made by their combined power in the future. However, diffraction measurements on macromolecular objects (far less on small molecules or salts) provide limited information content: the experimental result is a distribution of electrons in space, as X-rays and electrons are similar in wavelength and interact with the electron shells of atoms rather than with the nuclei. The final structural model, however, consists of atomic coordinates (the positions of the unseen nuclei), representing merely an interpretation of the actual data. To improve on this subjective interpretation, Hendrickson and colleagues introduced the positional and thermal refinement of the models against the experimental data [6]. This requires at least four parameters per atom (three real-space coordinates x, y and z and an isotropic temperature factor B). At moderate resolutions the data/parameter ratio is unfavorable, and this is compensated by using geometric and topological constraints and restraints that limit the degrees of freedom for the refinement problem [6]. As libraries of restraints derive from structural data at high precision, the resulting atomic structure is in fact more accurate than the resolution of the diffraction data set would seem to allow (Figure 1b). However, the generation of restraints requires the precise knowledge of molecular geometries and topologies, and structural biology is arguably most interesting where such knowledge is missing, because the observed structures are unprecedented.

Geometries of metal sites — EXAFS in one or three dimensions X-rays are ionizing radiation, and while the routine collection of diffraction data at cryogenic temperatures immobilizes radical molecules, lone solvated electrons will retain their mobility even at 100 K. Even when not causing immediate damage to the macromolecule itself, the electrons tend to end up at sites with positive redox potentials, leading to the problem of photoreduction. Radiation damage is particularly detrimental to the study www.sciencedirect.com

High-resolution metal sites Burger, Andrade and Einsle 33

Figure 1

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Resolution limits in macromolecular structures. (a) Resolution can be defined as the separate detection of electron density maxima in a map. Calculated electron density profiles for two atoms at 2.2 A˚ distance show that with decreasing resolution the peak height is reduced while the with is increased. (b) Quality of electron density maps. At a true atomic resolution of 1.0 A˚ atoms generate individual electron density peaks that yield precise structural information. Already at 2.0 A˚ resolution — and far more at 3.0 A˚ — the precision of the map is insufficient to allow for building an atomic model, so that restraint and constraint libraries are used to define the exact appearance of individual amino acids.

of metal sites in biomolecules if the center in question undergoes redox transitions between various functionally relevant states, or suffers partial or complete depletion of one or several metals. Structures then possibly do not represent the functional or catalytic state that was — often tediously — generated or adjusted during preparation of the protein or the crystal, but rather a more reduced or decomposed form of the system, or a mixture of various states that represents an average across the crystal. Spectroscopy is essential for defining such states in the first place, and it can help to assess the situation in the crystal at the beginning and at the end of a diffraction experiment. The arsenal of spectroscopic methods is richly equipped for metal-containing proteins in particular, and the obvious complementation for X-ray diffraction analyses is X-ray spectroscopy (XAS). Absorption of X-rays occurs at specific energies, when the incoming photon triggers characteristic electronic transitions in atoms of a given element. In XAS, the K-edge corresponds to transitions from the 1s orbital, an effect that is also exploited for structure solution by analyzing the anomalous dispersion occurring at these energies [7]. For the study of metal sites, a preferred method is metal L-edge spectroscopy that detects allowed transitions from a 2p orbital to an unfilled 3d orbital within the transition metal [8]. Such transitions are electric-dipole allowed, giving them a higher energy resolution and a higher intensity than K-edge features. At energies slightly above the edge, a fine structure emerges with properties of a dampened oscillation, the extended X-ray absorption fine structure (EXAFS). While intraatomic transitions determine she www.sciencedirect.com

shape of the rising edge, the EXAFS region is dominated by interactions of the ejected electron with its surroundings, leading to a high distance resolution, but lacking three-dimensional information due to the isotropy of the emitted wave [9]. EXAFS spectroscopy thus complements X-ray diffraction of metal clusters, as the latter can reveal the nature and geometry of the ligand environment, but EXAFS is potentially more precise in determining exact bond distances and provides additional information about the oxidation state of a metal. Losing an electron by oxidation juxtaposes an unaltered nuclear charge with fewer remaining electrons, so that the energy required for ejecting a core electron increases. The analysis of the shape and position of an edge, frequently in comparison with model compounds, can reveal the oxidation state of a metal, as exemplified recently for the FeMo cofactor of nitrogenase, the enzyme that catalyzes biological nitrogen fixation, where the single molybdenum ion was found to be a Mo(III) state that is unique in biology [10]. As XAS is typically measured on powder samples, the spectra represent an average of all atoms of the respective element in random orientation, and individual analyses are thus complicated in multinuclear metalloenzymes. An abundance of metals is not uncommon, as heme groups [11] or iron–sulfur clusters [12] can form extended cofactor chains for efficient long-range electron transfer. For such instances, a solution to the problem of individual redox state assignment was proposed in the form of a spatially refined anomalous dispersion (SpReAD) analysis [13]. A series of diffraction data sets is collected to high Current Opinion in Structural Biology 2015, 35:32–40

34 Catalysis and regulation

anomalous completeness at a range of energies spanning the absorption edge of an element. As the strength of the anomalous effect is proportional to the absorption of Xrays by a given element, the information about the shape of an absorption edge is encoded in the intensity differences of the Bijvoet pairs. Diffraction data adds the additional benefit of spatial resolution, so that the anomalous signal can be refined for each scatterer individually. This was demonstrated for a [2Fe:2S] cluster in the ferredoxin Fdx4 from Aquifex aeolicus where antiferromagnetic coupling leads to localized charges (Fe(II)/Fe(III)) in the reduced state [13], but the method promises broad applicability for metal-containing proteins, revealing tendencies for oxidation states even in complex multinuclear metal clusters.

Atom identification from electron density maps The result of a diffraction experiment is a distribution function of electrons in space, where the identity of an element is reflected in the magnitude of an electron density maximum. In the resolution regime of structural biology, this identification is not always unambiguous, but sufficient to distinguish sulfur from lighter atoms. It might even differentiate among C, N and O in welldefined regions of a structure at resolutions significantly better than 2 A˚. Ambiguities regarding the identity of heavier atoms is rare, as their presence is known beforehand, possibly from spectroscopy. I. Carbon Monoxide Dehydrogenase — For transition metals that show absorption edges (K or L) in the energy range accessible at protein beam lines on synchrotron light sources, the calculation of anomalous difference electron density maps has become routine for verifying the identity of a species. Among the first instances where this strategy was applied was Mo,Cu CO dehydrogenase, a molybdoenzyme of the xanthine dehydrogenase family with a unique Mo–S-Cu active site (Figure 2a) that was originally described to contain selenium (as S-selanylcystein, Cys-S-Se) instead of copper [14]. The copper ion is in the reduced Cu(I) state (3d10 configuration), making it undetectable in EPR and UV/vis spectroscopies. The sole hint at its presence was found in the EPR spectrum of the Mo(V) state of the enzyme, a minor species beside the diamagnetic Mo(IV) and Mo(VI), where the I = 3/2 nuclear spin of Cu led to a splitting of the Mo(V) signal into four distinct lines. A substantial improvement of resolution from 2.2 A˚ to 1.1 A˚A using a humidity control device [15] and optimized purification protocols then identified the second metal through diffraction data collection around the absorption edges of candidate transition metals [16]. This method is unambiguous when using anomalous double difference electron density maps (DDano), where coefficients are calculated by subtracting two anomalous difference data sets collected before and after an element-specific absorption edge. Current Opinion in Structural Biology 2015, 35:32–40

While an indication for the presence of copper could also come from X-ray fluorescence, diffraction adds the benefit of a precise spatial localization of the scattering atom. The analogous approach was used on multiple occasions thereafter, for example for the Ni sites in CODH/Acetyl-CoA synthase [17–19] or a further instance of an unexpected Cu(I) site in cytochrome c sulfite reductase MccA [20]. II. Nitrogenase — In biological nitrogen fixation the enzyme nitrogenase reduces the chemically inert dinitrogen molecule, N2, to bioavailable ammonium, NH4+ [21]. The N2 triple bond is the most stable bond to be broken in any enzymatic reaction, and accordingly the active site of nitrogenase is a highly evolved, multinuclear metal cluster, the FeMo cofactor. The stoichiometry of this cluster is [Mo:7Fe:9S:C]:homocitrate, making it the largest iron–sulfur cluster known to date [22]. The central cavity of FeMo cofactor contains a light atom that was overlooked in initial analyses (Figure 2b), but subsequently identified to be either C, N or O [23]. In spite of a resolution of 1.16 A˚, it was not possible at the time to unambiguously assign the correct atomic identity, and the question arose how a difference of a single electron distinguishing N from C or O could be resolved. Even at 1.16 A˚ resolution the refinement of occupancies versus B-factors was inconclusive, and only 9 years later a combination of spectroscopic and crystallographic analyses answered the question. A key achievement was the further improvement of diffraction quality for crystals of MoFe protein, yielding a data set with a limiting resolution of 1.0 A˚ [24]. In this data set, small variances in the diffraction behavior of C-atoms, N-atoms and Oatoms were sought and found through evaluation of electron density in spheres of increasing radius around an atom position. Here, the average density will decrease with growing sphere radius, leading to a characteristic profile. Multiple observations for each atom type within the nitrogenase structure allowed for a sound statistical analysis of the diffraction behavior. The seemingly modest improvement of resolution from 1.16 A˚ to 1.0 A˚ implied an increase in the number of diffraction data points by a factor of 1.5, and in the resulting analysis the higher resolution data showed substantially reduced errors bars (Figure 2c). The plot then provided a reference for average electron density values measured in the central cavity of FeMo cofactor. Interestingly, at the lower resolution of 1.16 A˚ the measured curve more closely matched the profile for nitrogen, while at 1.0 A˚ resolution the data precisely coincided with a central carbon atom [24]. A more extensive analysis then revealed that this was still due to distortions of electron density and that carbon indeed was the central atom in FeMo cofactor. The result was independently corroborated by ESEEM and X-ray emission spectroscopies [24,25], and shortly thereafter, S-Adenosylmethionine was confirmed to be source of the interstitial carbide [26]. www.sciencedirect.com

High-resolution metal sites Burger, Andrade and Einsle 35

Figure 2

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Identification of atoms by X-ray diffraction. (a) The active site of Mo,Cu-CODH contains a linearly coordinated Cu(I) ion that was initially mistaken for Se. (b) In the first structure for FeMo cofactor of nitrogenase the cluster was described with an empty central cavity that was later found to contain a light atom (Figure 4). (c) The identity of the central atom was verified also by X-ray diffraction at 1.0 A˚ resolution, where the electron density profiles of all C (black), N (blue) and O (red) atoms calculated in spheres of increasing radii were statistically analyzed and compared to the electron density observed in the central cavity (green), yielding a perfect match with carbon. (d) Structure of Ni-Fe hydrogenase from D. vulgaris Miyazaki at 0.89 A˚ resolution [29]. Cartoon representation of the heterodimeric enzyme. The a-subunit (green) contains the active site NiFe cluster, while the b-subunit (grey) holds an electron transfer chain consisting of three iron–sulfur clusters. (e) Stereo representation of the active site in the Ni-R state, with a hydride anion bridging the Fe2+ and Ni2+ ions and an observed protonation at the Sg atom of residue C546. The depicted electron density maps are a 2Fo–Fc map contoured at the 2s level (blue) and a Fo–Fc difference density map with hydrogen positions omitted contoured at the 5s level (green).

Photons versus neutrons to see protons If the detection of single-electron differences among carbon, nitrogen and oxygen proved difficult in nitrogenase, the problem is even more pronounced in the metalloenzymes that convert the simplest substrate possible, combining protons and electrons to form hydrogen gas [27]. In hydrogenase catalysis, the single electrons — bound or not to a proton — were considered invisible for protein crystallographic analyses. It was thus suggested early on that here the method of choice was neutron diffraction, where a particle (neutron) beam emitted from a cyclotron is scattered by atomic nuclei rather than electrons, leading to a substantial contribution of protons in diffraction. However, in spite of recent developments including spallation neutron sources, cryogenic sample www.sciencedirect.com

handling and dedicated detector systems [28], the methodology remains under development and both the sensitivity of most hydrogenases towards O2 and the requirement for large single crystals (V = 0.1–1 mm3) have so far prevented the experiment. In a most recent analysis, Ogata and co-workers have nevertheless provided essential evidence for the mechanism of Ni-Fe hydrogenases (Figure 2d), with X-ray diffraction data for a central reaction intermediate that was previously identified spectroscopically. At 0.89 A˚ resolution the structure showed the so-called ‘Ni-R’ state within the catalytic cycle [29], most suitable for at least two reasons: first, Ni-R is the most highly reduced state during catalysis and is consequently least prone to Current Opinion in Structural Biology 2015, 35:32–40

36 Catalysis and regulation

photoreduction during data collection, a common problem in metalloprotein crystallography. Second, Ni-R arguably represents the most interesting state for crystallographic analysis, as it contains a hydride anion bridging the Ni2+ and Fe2+ ions of the active site, with the additional proton released through heterolytic cleavage of the H2 molecule bound at one of the cysteine ligands to nickel, C546. The obtained atomic resolution structure allowed for modeling 93% of all hydrogen atoms of the enzyme, including both the bridging hydride and a protonation of the Sg atom of residue C546, albeit at an unusually steep angle (Figure 2e). Following an analysis originally employed for the 1.0 A˚ structure of nitrogenase [24], the density maximum for the 2-electron species hydride was indeed discernible from other protons. The structure confirmed the picture obtained from spectroscopy, and the authors remarked that X-ray diffraction at this resolution actually alleviates the need for neutron scattering analyses.

Fourier series termination artifacts A final potential pitfall in structural analysis arises from the fact that an electron density map is the result of a Fourier transform, integrating the entirety of measured structure factors. These are the diffracted waves that are recorded as maxima of constructive interference on a crystal lattice, and the impressive power of the method lies in the fact that already a limited subset of all structure factors can yield an interpretable map. Incompleteness of data manifests in a limited resolution, but it can also reveal the underlying periodic nature of the structure factor function. In such cases, the resulting electron density maps show intermittent, repeated maxima and minima. In strong cases these resemble the waves from a stone cast into a pond, and are thus frequently referred to as ‘ripples’. While usually more of an aesthetic problem, Fourier ripples can lead to unexpected effects in particular cases. I. Acetylene hydratase — Pelobacter acetylenicus is a free-living Deltaproteobacterium with the ability to ferment acetylene, an industrial byproduct for which, to date, no natural source is known [30]. The activity was traced back to the tungsten/[Fe:S]-containing enzyme acetylene hydratase (AH), a member of the complex iron–sulfur molybdoenzyme (CISM) family of Mo-proteins and W-proteins [31,32]. The crystal structure of AH revealed the typical four-domain CISM family fold and a W(IV) ion coordinated by two molybdopterin-guanin dinucleotide cofactors (Figure 3a) [33,34]. The distorted octahedral coordination environment of the active site tungsten ion is composed of four sulfur ligands (from the dithiolene moieties of the cofactors and an additional cysteine residue) and an additional oxygen species (Figure 3b). The reaction of AH is the hydration of acetylene (C2H2) to form acetaldehyde (H3CCHO), an untypical non-redox reaction that mirrors classical Reppe chemistry [35] or the Kucherov hydration of acetylene where Hg(II) is used as a catalyst Current Opinion in Structural Biology 2015, 35:32–40

(Figure 3c) [36]. In a mechanistic proposal, acetylene does not bind directly to the metal ion. Rather, W(IV) acts to activate the bound oxygen species that then adds to the triple bond of the alkyne substrate. The details of this mechanism depend on the nature of the oxygen species: a tungsten-coordinated hydroxo ligand would favor a nucleophilic attack on one of the substrate carbons, leading to a vinyl anion intermediate that is then protonated by nearby asparate D13 (Figure 3d). In contrast, a bound water, supported D13, would act as a Lewis acid and add to the triple bond electrophilically (Figure 3e). In both mechanisms, the immediate product is vinyl alcohol that spontaneously tautomerizes to yield acetaldehyde. At 1.26 A˚ resolution, the structure of AH was expected to be sufficiently precise to distinguish between a hydroxo ligand with an expected distance of 1.9–2.1 A˚ from W(IV) and a coordinated water at 2.0–2.3 A˚. However, the distance obtained from the refined structural model of AH was a seemingly ambiguous 2.04 A˚. With 70 electrons, W(IV) is the heaviest atom known to occur naturally in a biological macromolecule, and sevenfold more electronrich than its reactive ligand in AH (Figure 3f). In Wdependent and — to a lesser extent — also in Modependent enzymes this particular constellation leads to the unusual situation that the magnitude of Fourier ripples created as periodic series termination artifacts around the metal ion can approach the electron density maximum of the ligand, leading to significant distortions of the observed electron density features. Such effects are again strictly resolution-dependent, and they can be straightforwardly simulated by integration of the respective atomic scattering factors [23]. For simplicity, electron density can be inspected as a onedimensional profile along the W–O bond, with W at the origin. As expected, the tungsten peak dwarfs the electron density maximum generated by oxygen (Figure 3f), but when the resolution (i.e. the integration limit) of the analysis is reduced an additional effect becomes apparent. At 0.75 A˚ resolution the sum of both electron density peaks yields an observable distribution with maxima precisely at the positions of the two atoms (Figure 3g). However, already at 1.25 A˚, the strong W peak generates periodic ripples with a magnitude that is non-negligible when compared to that of the oxygen peak. The resulting electron density maximum is observed at 2.04 A˚ distance from W (dotted blue line), but the oxygen atom generating it is located at a distance of 2.19 A˚ (dotted red line). In the analysis of the AH structure this meant that the real bond distance to the oxygen ligand was longer than the observed one, making the ligand most likely a water and supporting the electrophilic addition mechanism [34]. Furthermore, while in each panel of Figure 3f the W–O coordination distance remains constant at 2.19 A˚, the series termination artifacts generated by W lead to substantial www.sciencedirect.com

High-resolution metal sites Burger, Andrade and Einsle 37

Figure 3

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Structure and reactivity of acetylene hydratase. (a) Cartoon representation of the enzyme. (b) Stereo image of the active site with a bis-MGDcoordinated tungsten ion and a coordinated O species close to a [4Fe:4S] cluster. (c) Reaction scheme. Acetylene is hydrated to vinyl alcohol that spontaneously tautomerizes to acetaldehyde. (d) A coordinated OH would add nucleophilically to acetylene via a vinyl anion intermediate. (e) In contrast, bound H2O would be activated by nearby D13 to act as an electrophile. (f) In a calculated electron density profile for a W central atom with an O at 2.19 A˚ distance, the peak for the metal dwarfs that of the light ligand. (g) At decreasing resolution, the peaks of W and O are broadened, and series termination artifacts around the W maximum increase in magnitude. The red dotted line indicates the actual position of the ligand, the black dotted line is the position of the observed maximum.

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38 Catalysis and regulation

and increasing shifts of the observed electron density maximum. At 1.25 A˚ resolution the maximum appears at 2.04 A˚ distance, but is shifted to 2.46 A˚ at a resolution of 1.75 A˚ and to 3.07 A˚ at 2.25 A˚ resolution. For a novel metalloprotein structure, 2.25 A˚ would be considered a decent resolution, but the above example underlines with how much caution metal-ligand distances near heavy atoms must be considered.

third-row transitions metals Mn, Fe, Co, Nu, Cu and Zn are less prone to the effect, and yet the iron centers of the enzyme nitrogenase provide the arguably most striking example for Fourier series termination artifacts to date. The FeMo cofactor of nitrogenase was described above, in the context of the identification of its unique central atom as carbide. Its chemical nature remained enigmatic for nearly a decade, but even its actual presence was only discovered 10 years after the first three-dimensional structure of nitrogenase was presented in 1992. The original analysis, at resolutions up to 2.2 A˚, depicted FeMo cofactor as an iron–sulfur cluster of unprecedented

II. Nitrogenase — Distortions of electron density predominantly occur around the heaviest metal ions found in biological systems, W and Mo. The more abundant Figure 4

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Fourier series termination artifacts in nitrogenase FeMo cofactor. (a) A calculated, one-dimensional electron density profile for an iron atom in the origin shows the effect of decreasing resolution: peak broadening and lower intensity. (b) Magnified view of the boxed red area in (a). Series termination errors manifest in periodic artifacts, commonly of low amplitude. At 2.0 A˚ distance from the central atom (red line), the resolutiondependence of the artifactual density is shown in the inset. (c) The particular geometry of FeMo cofactor places six of the seven Fe atoms on a sphere with radius 2.0 A˚ around the central position, and all nine sulfurs on a second sphere of 3.5 A˚ radius. Accordingly, the density artifacts in the cavity are multiplied by the number of surrounding atoms. (d) The resolution-dependent electron density profile for the cofactor cavity is the sum of four components: the apical Fe1, the Mo ion, 9 S on the outer sphere and 6 Fe on the inner sphere. This creates an artifactual density minimum in a resolution range from 1.5 to 2.2 A˚. Current Opinion in Structural Biology 2015, 35:32–40

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High-resolution metal sites Burger, Andrade and Einsle 39

complexity, and one of its most striking characteristics was an extensive, central cavity formed by six coordinatively unsaturated iron ions (Fe2–Fe7) [37]. In spite of this seemingly reactive arrangement, the MoFe protein of nitrogenase isolated in this way represented a stable resting state and showed no propensity for binding any ligand whatsoever (Figure 2b). The enigma was lifted only years later, when the empty central cavity of FeMo cofactor turned out to be more than met the eye. Using the formalism introduced above, electron density profiles can be calculated for individual atoms and in dependence on the limiting resolution of the Fourier summation (Figure 4a,b). Among all bioinorganic metal clusters known to date the geometry of the [Mo:7Fe:9S:C] FeMo cofactor is unique, and its distinguished position is the central cavity. Here, all six of the inner iron atoms are equidistant at 2.0 A˚, and the same is true for all nine sulfur atoms that lie on the surface of a sphere with a radius of 3.5 A˚ (Figure 4c). As in the case of acetylene hydratase, the proximity of other scattering atoms will invariably give rise to periodic series termination features, but with the possible exception of Mo at the apex of the cluster these would not be expected to be significant. However, in the central cavity ripples of identical magnitude are not only generated by one iron atom, but six, and not only by one sulfur atom, but by nine. The analysis revealed that while ripple effects were moderate at higher resolutions, a strong minimum of electron density was generated in the central cavity in a resolution range of 1.55–2.2 A˚ (Figure 4d). The magnitude of this artifact was sufficient to conceal the presence of a central light atom in a 2Fo–Fc electron density map, leading to the initial interpretation of an empty cavity in FeMo cofactor [37]. The reevaluation of the structure with a central carbide substantially facilitated theoretical interpretations as it completed the ligand sphere of the six central iron atoms in a chemically reasonable way, paving the way for an experimental analysis of the magnetic properties of the cluster by single-crystal EPR spectroscopy [38] and the discovery that the molybdenum in resting nitrogenase was in the unique Mo(III) state [10]. It also showed that the central cavity was not a likely candidate for a substrate-binding site, as subsequently confirmed in a complex with CO that replaces a bridging sulfur, but leaves the central atom in place [39].

Conclusion Metal-containing and cofactor-containing proteins are mostly characterized by non-canonical chemical entities that are not described in restraints libraries, but are of high functional relevance. Structure determination at high — true atomic — resolution thus is desirable, but cannot always be achieved. In such instances, additional data from other techniques can be invaluable, although even then the diffraction method and features of the Fourier transform can lead to unexpected effects that must be considered. www.sciencedirect.com

This is particularly the case for light ligands in the proximity of heavy atoms, but unusual geometries and high symmetry can have analogous effects.

Acknowledgments This work was supported by Deutsche Forschungsgemeinschaft (Priority Programme 1319: Anaerobic Transformations of Hydrocarbons) and the European Research Council (ERC grant no. 310656).

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40 Catalysis and regulation

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24. Spatzal T, Aksoyog˘lu M, Zhang LM, Andrade SLA, Schleicher E,  Weber S, Rees DC, Einsle O: Evidence for interstitial carbon in nitrogenase FeMo cofactor. Science 2011, 334:940. Identification of the central ligand was only successful 9 years later, when a combination of atomic-resolution X-ray diffraction and ESEEM spectroscopy provided evidence for a central carbon atom. 25. Lancaster KM, Roemelt M, Ettenhuber P, Hu YL, Ribbe MW,  Neese F, Bergmann U, DeBeer S: X-ray emission spectroscopy evidences a central carbon in the nitrogenase iron– molybdenum cofactor. Science 2011, 334:974-977. Additional evidence for the nature of the central ligand was provided by Xray emission spectroscopy (Fe-Kb). Comparison with simulations for C, N and O clearly hinted towards carbon.

Current Opinion in Structural Biology 2015, 35:32–40

37. Kim JS, Rees DC: Structural models for the metal centers in the nitrogenase molybdenum–iron protein. Science 1992, 257:1677-1682. 38. Spatzal T, Einsle O, Andrade SL: Analysis of the magnetic  properties of nitrogenase FeMo cofactor by single-crystal EPR spectroscopy. Angew Chem 2013, 52:10116-10119. Using single-crystal EPR spectroscopy, the orientation of the magnetic tensor representing the S = 3/2 spin system of FeMo cofactor could be aligned to the structure of the moiety, providing direct infromation on a symmetry break between the cluster structure and its magnetic moment. 39. Spatzal T, Perez KA, Einsle O, Howard JB, Rees DC: Ligand  binding to the FeMo-cofactor: structures of CO-bound and reactivated nitrogenase. Science 2014, 345:1620-1623. This is the first structural description of a small-molecule ligand binding to nitrogenase FeMo cofactor, with possible major implications for understanding the mechanism of the enzyme. The inhibitor CO was added under turnover conditions and was found to replace a bridging sulfide within the cluster, reversibly generating a metal carbonyl compound.

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