High-Resolution NMR Reveals Secondary Structure and Folding of Amino Acid Transporter from Outer Chloroplast Membrane

James D. Zook; Trivikram R. Molugu; Neil E. Jacobsen; Guangxin Lin; Jürgen Soll; Brian R. Cherry; Michael F. Brown; Petra Fromme

doi:10.1371/journal.pone.0078116

Abstract

Solving high-resolution structures for membrane proteins continues to be a daunting challenge in the structural biology community. In this study we report our high-resolution NMR results for a transmembrane protein, outer envelope protein of molar mass 16 kDa (OEP16), an amino acid transporter from the outer membrane of chloroplasts. Three-dimensional, high-resolution NMR experiments on the ¹³C, ¹⁵N, ²H-triply-labeled protein were used to assign protein backbone resonances and to obtain secondary structure information. The results yield over 95% assignment of N, H_N, CO, C_α, and C_β chemical shifts, which is essential for obtaining a high resolution structure from NMR data. Chemical shift analysis from the assignment data reveals experimental evidence for the first time on the location of the secondary structure elements on a per residue basis. In addition T_1Z and T₂ relaxation experiments were performed in order to better understand the protein dynamics. Arginine titration experiments yield an insight into the amino acid residues responsible for protein transporter function. The results provide the necessary basis for high-resolution structural determination of this important plant membrane protein.

Citation: Zook JD, Molugu TR, Jacobsen NE, Lin G, Soll J, Cherry BR, et al. (2013) High-Resolution NMR Reveals Secondary Structure and Folding of Amino Acid Transporter from Outer Chloroplast Membrane. PLoS ONE 8(10): e78116. https://doi.org/10.1371/journal.pone.0078116

Editor: Oleg Y. Dmitriev, University of Saskatchewan, Canada

Received: October 26, 2012; Accepted: September 16, 2013; Published: October 29, 2013

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Funding: This work was supported by the U.S. National Institutes of Health (GM095583 to P.F. and EY012049 and EY018891 to M.F.B). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: Although one of the authors is currently employed by the commercial company “SABIC,” all contributions to this work including data collection and evaluation was performed while under the employment of the University of Arizona, Tucson. The authors include this information for purposes of transparency. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

Introduction

Integral membrane proteins are a rapidly growing field of interest in structural biology and biochemistry. They are responsible for a plethora of cell functions, ranging from energy generation by enzymes involved in respiration and photosynthesis such as ATP synthase [1], to cell signaling as shown by the large number of integral membrane receptors [2]. However, structure determination of these proteins remains a formidable challenge. While most of the 300 structures of membrane proteins solved so far are determined by X-ray diffraction, crystallization is difficult and is a major bottleneck for solving membrane structures [3], [4]. Improvements in magnetic resonance technology provide new methods as a powerful tool for in-depth analysis of the structure and function of membrane proteins. Although nuclear magnetic resonance (NMR) spectroscopy shows great promise in the field of structure determination, it remains a challenge for membrane proteins for several reasons. One such hurdle involves obtaining high yields of isotope-enriched proteins that are structurally stable in detergent micelles at concentrations high enough to produce adequate signal to noise. A further challenge is specific to proteins that are largely α-helical (as seen by many transmembrane proteins), which display spectra that have a narrow chemical shift dispersion in the ¹H dimension. This narrow ¹H dispersion, combined with the increased number of residues present in larger membrane proteins, yields a problem with regard to peak overlap in high-resolution NMR spectra. Yet another obstacle to consider is the necessity of solubilizing the protein in detergent micelles, which are used to maintain protein structural integrity. This increase in size of the complex results in slower rotational averaging, and therefore decreased transverse relaxation times [5].

One integral membrane protein that has shown promise as a target for NMR study is the outer envelope protein with a molecular mass of 16 kDa (OEP16) from the chloroplast membrane [6]. OEP16 is a transmembrane (TM) protein that shares some sequence homologies (52%) to a putative protein from the mitochondrial membrane translocase of the inner membrane (TIM) that may be part of the protein translocase complex (UniProtKB Accession number: ABF95523.1). Notably, OEP16 is located within the outer membrane of chloroplasts, and forms a channel for selective diffusion of amino acids into the intermembrane space. This pore-forming protein is remarkably selective, and may supply the chloroplast organelle with the amino acids for use in protein expression [7]. The first structural information for OEP16 was based on hydropathy plots from the amino acid sequence and circular dichroism (CD) experiments in phosphatidylcholine liposomes [7]. These studies hypothesized that OEP16 may consist of three TM helices with the N-terminus of the protein forming a β-sheet [7], [8]. A later model suggested a four TM-helix bundle [9], which contrasts with the textbook view that nearly all outer membrane channels form β-barrels. Yet improved CD spectral data support the four-helix bundle hypothesis [6]. Dimers have been considered from cross-linking studies [7]; electron micrographs have led to the suggestion of trimer formation [10]; and moreover hexameric and higher oligomeric forms have been hypothesized from gel filtration data [6].

This paper reports the results of NMR experiments for OEP16 in sodium dodecyl sulfate (SDS) detergent micelles. High yields of recombinantly expressed ¹⁵N-enriched OEP16 in minimal media have been previously reported [6]. These results give a starting point for expression and purification of the uniformly ¹⁵N, ¹³C, ²H-labeled protein needed for 3D NMR experiments. We show the first experimental evidence for how the protein traverses the membrane, and how the individual amino acid residues contribute to the secondary structure of the protein. We establish that OEP16 consists of four TM helices and identify the residues for helix formation. Relaxation measurements report on intramolecular dynamics [11], [12], and help to estimate the isotropic global correlation time that provides insight into the multimeric state of the protein, which is under debate in the literature. Chemical shift perturbation is used to elucidate the residues that are responsible for the selectivity and diffusion of amino acid molecules through OEP16. Results of this study reveal nearly complete assignment of the N, H, CO, C_α, and C_β chemical shifts, which is essential for a NMR high-resolution structure. In addition, a functional study performed via arginine titration provides data that reveals specific ligand binding to OEP16.

Materials and Methods

Protein Expression and Purification

For the NMR experiments, U-¹³C,¹⁵N-labeled and 80% perdeuterated recombinant OEP16 was expressed by using a slightly modified procedure compared to Ni et al. [6]. A 5-mL preculture was prepared in Lysogeny Broth (LB) media that was allowed to incubate at 310 K overnight, shaking at 200 rpm. The preculture was added directly to a 1-L culture of M9 media, with ¹⁵N-ammonium chloride as the sole ¹⁵N-nitrogen source and ¹³C-glucose as the sole ¹³C-carbon source. Perdeuteration was achieved by growing the cells in 80% ²H₂O solution. For experiments only requiring ¹⁵N-labeled protein, cell growth was performed in a similar manner without perdeuteration, employing ¹⁵N-ammonium chloride as the sole nitrogen source, and non-enriched D-glucose as the carbon source.

Protein expression was induced at OD₆₀₀ = 0.8 using 1 mM isopropyl-β-D-1-thiogalactopyranoside (IPTG) [6], and allowing it to incubate for an additional 5 h. Purification and reconstitution of OEP16 in SDS micelles was carried out using previously developed methods [6]. Protein was prepared for the NMR experiments by diluting the concentrated samples in a 10% ²H₂O buffer (100 mM NaCl, 20 mM NaH₂PO₄ pH 6.5, 1 mM β-mercaptoethanol (BME), 1 mM ethylenediaminetetraacetic acid (EDTA), 10% (v/v) glycerol, 0.4% (w/v) SDS, and 0.02% (w/v) NaN₃). Samples were then re-concentrated via ultrafiltration using a 30 kDa molar mass cut-off (MWCO) filter centricon. U-¹⁵N labeled OEP16 in β-D-dodecylmaltopyranoside (β-DDM) was prepared in a similar manner, replacing SDS as the detergent used to form OEP16 micelles.

Protein Backbone Assignments

NMR data were collected at 310 K (with the exception of one ¹H-¹⁵N HSQC spectrum collected at 298 K) using an INOVA 600 Varian NMR spectrometer equipped with a triple-resonance cryoprobe. Sample condition screening and chemical shift assignments were carried out by collecting a series of 2D and 3D NMR experiments. The ¹⁵N-HSQC, HNCA, HN(CO)CA, HNCACB, CBCA(CO)NH, HNCO, HN(CA)CO, TOCSY-¹⁵N-HSQC, and NOESY-¹⁵N-HSQC experiments were performed by standard pulse sequences [13]–[20]. The NOESY and TOCSY mixing times were 80 ms and 50 ms respectively. Additional NMR data for OEP16 in β-DDM micelles were acquired at 318 K with a Varian NMR System (VNMRS) operating at 800 MHz using a ¹H{¹³C/¹⁵N} 5 mm XYZ PFG triple-resonance room temperature probe. Data were processed with NMRPipe [21], while SPARKY [22] was used for resonance assignments performed by sequentially walking through the backbone, using C_β and C_α chemical shift statistics from the Biological Magnetic Resonance Data Bank (BMRB) for identification of amino acid residues [23]. Assigned chemical shifts were analyzed for secondary structure via torsion angles using TALOS+ [24], [25].

Relaxation Measurements

The ¹⁵N longitudinal Zeeman (T_1Z) and transverse (T₂) relaxation data were acquired on the singly labeled (¹⁵N) protein sample for relaxation analysis using standard experiments [26]. Relaxation delay times ranging from 10 ms to 2000 ms were used for T_1Z data, while delay times between 10 ms and 190 ms were used for obtaining the T₂ data. Data were processed using NMRPipe [21]. Initial relaxation analysis for calculating T_1Z and T₂ values was performed using SPARKY [22]. The average overall correlation time (τ_m) of the protein was estimated from the relaxation data in the limit of highly restricted internal motions [27]–[29].

Amino Acid Titration

For observing the amino acid residues of OEP16 involved with substrate binding, 500 mM arginine in a 10% ²H₂O buffer (100 mM NaCl, 50 mM NaH₂PO₄ pH 7.4, 1 mM BME, 1 mM EDTA, 10% (v/v) glycerol, 0.4% (w/v) SDS, and 0.02% (w/v) NaN₃) was titrated directly into the NMR tube containing 1.2 mM OEP16 and 100 mM NaCl, 20 mM NaH₂PO₄, pH 7.4, 1 mM BME, 1 mM EDTA, 10% (v/v) glycerol, 0.4% (w/v) SDS, and 0.02% NaN₃. Arginine concentrations of 0 mM, 10 mM, 20 mM, and 40 mM, were used for the titration studies of the singly-labeled ¹⁵N protein sample. The ¹H and ¹⁵N shifts chemical shifts were obtained using a 2D ¹⁵N-HSQC experiment.

Results

Backbone Residue Assignments

Very good yields of purified OEP16 in SDS micelles were obtained for the singly U-¹⁵N-labeled and U-¹³C, ¹⁵N, ²H-labeled samples. The 80% perdeuterated ¹³C, ¹⁵N sample preparations on average involved a 600-µL solution that contained 1 mM OEP16. Typical singly-labeled ¹⁵N sample preparations entailed a 1-mL solution at a protein concentration of 1.5 mM. The relatively high protein concentrations provided very good signal-to-noise ratios for all NMR experiments described in the study as indicated in Figure 1A. We were able to assign 95% of the carbon, nitrogen, and proton backbone resonances with the experiments described. Fairly well-resolved spectra were seen in all experiments conducted at 600 MHz. Figure 1B shows a segment of a strip plot using HNCO and HN(CA)CO chemical shifts to sequentially assign the backbone of OEP16. Only residue M1 and the C_β shift for Y144 could not be confidently assigned. A representative 2D ¹⁵N-¹H HSQC spectra is shown in Figure 2A, which includes non-backbone amide resonances due to arginine, asparagine, glutamine, tryptophan, and, lysine side chains. The assigned resonances are shown in the expansion of the 2D ¹⁵N-HSQC spectrum in Figure 2B and a complete list of assigned resonances can be accessed via the Biological Magnetic Resonance Bank (BMRB), accession number 19267.

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Figure 1. Three-dimensional NMR spectroscopy of U-¹⁵N,¹³C-labled OEP16 in SDS micelles provides sequential backbone assignments.

(A) The HNCO experiment result in well-resolved peaks that aided in the assignment of over 95% of the ¹⁵N and ¹³C resonances. (B) Section of a strip plot from the HN(CA)CO and HNCO spectra. Spectra were recorded for OEP16 at 600 MHz in 0.4% SDS micelles, containing 20 mM NaH₂PO₄ buffer pH 6.5 and 100 mM NaCl at 310 K.

https://doi.org/10.1371/journal.pone.0078116.g001

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Figure 2. Two-dimensional ¹H-¹⁵N HSQC spectra of OEP16 in SDS detergent micelles show well-dispersed peak patterns indicative of secondary structure.

(A) ¹H-¹⁵N-HSQC spectrum obtained at 600 MHz for OEP16 in SDS detergent micelles at 310 K. Sample conditions are identical to Figure 1. Horizontal lines connect the amino side chain resonances. (B) Expansion of the central crowded region of ¹H-¹⁵N HSQC spectrum of OEP16, showing the polypeptide backbone resonance peak assignments corresponding to the amino acid sequence. Assignable resonance peak patterns are observed despite the narrow ¹H chemical shift dispersion.

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Among the amino acid assignments, seven residues (F6, S7, G8, S44, L67, G74, and A75) as shown in Figure S1 were found to have two peaks in the 2D ¹⁵N HSQC spectrum, but maintained the same CO, C_α, C_β, and H_α chemical shifts, which may suggest two isoforms. This interesting finding is further addressed in the discussion. The combined HN(CA)CO, HNCO, HNCA, HN(CO)CA, HNCACB, and CBCA(CO)NH data provided the necessary information to assign nearly 95% of the protein using strip plot methods to sequentially walk through the backbone. Short range NOEs between the H_α and the amide protons provided by the NOESY-HSQC experiment clarified resonance assignments that were ambiguous in the ¹³C NMR spectra. A complete list of the assigned resonances is provided in Table S1.

Helix Prediction

Predictions of secondary structure estimated with the program TALOS+ revealed that OEP16 consists of α-helices and loops as seen in Figure 3A. In combination with hydropathy analysis [9] the data suggest the presence of four transmembrane helices with two small extrinsic helical regions. Additionally, TALOS+ evidence suggests that each transmembrane helix displays a break or a possible kink at the N-terminal side of the helix. TALOS+ can also estimate the squared order parameters (S²) for each residue using the random coil index (RCI) as described [30]. The value of S² characterizes intramolecular motion in the molecular reference frame [11], [31], [32], which can provide insight into the flexible loop regions of the protein seen in Figure 3B [5]. Flexible regions of the protein are apparent at either end of the polypeptide chain, as well as a large region between residues F49 and S66. The data are used to generate a possible model for OEP16. This model includes areas of the TM helices where there are bends or breaks, as well as two small helices on the surface of the membrane protein.

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Figure 3. Analysis of backbone chemical shifts of OEP16 in SDS detergent micelles using TALOS+ program.

(A) Predictions of the α-helical structure of OEP16 and (B) estimated ¹H-¹⁵N bond orientational order parameters (1-S²) as a function of residue position in protein amino acid sequence. The suggested TM regions are indicated by the red bars above the plot, with yellow arrows indicating the breaks or kinks in the helix. Additionally, the green bars represent the solvent-exposed helices.

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High-resolution structural restraints are necessary to confirm the presence of a well-folded protein in detergent micelles. However, SDS is not traditionally considered a detergent used for folding proteins. Therefore, a 2D ¹⁵N-HSQC spectrum was obtained for ¹⁵N-labeled OEP16 purified in β-D-dodecyl maltopyranoside (β-DDM), a detergent more widely used for structural studies of membrane proteins, at 318 K using an 800 MHz spectrometer. Figure S2 shows the superimposed ¹H-¹⁵N-HSQC spectra recorded for OPE16 in SDS micelles versus β-DDM micelles. The overlay of spectra shows a similar resonance peak pattern which strongly suggests that OEP16 is similarly folded in both SDS and β-DDM micelles. Broader peak widths are observed in the β-DDM spectra despite being acquired at a greater field strength for two reasons: the first is that the 600 MHz spectra were acquired to higher resolution (1024 t₁ points compared to the 256 t₁ points for the 800 MHz spectra); additionally the micelle size of β-DDM is nearly four times larger than SDS micelles, which contributes to a significantly longer rotational correlation time (estimated to be ∼26 ns in β-DDM as compared to the calculated 12.5±0.5 ns in SDS as calculated by relaxation analysis), and thus broader resonance peaks despite the greater field strength. Therefore a ¹H-¹⁵N HSQC spectrum of OEP16 in SDS acquired at a lower temperature of 298 K is used in the overlay shown in Figure S2. Nonetheless it is possible to identify several of the resolved peaks and assign them based on the assignments from the SDS measurements shown in Figure S2. This provides further evidence of a similar fold of OEP16 in both SDS as well as β-DDM detergent micelles.

Relaxation Measurements

The¹⁵N spin-lattice (T_1Z) and spin-spin (T₂) relaxation time values were measured for assigned resonances in the 2D ¹⁵N-HSQC spectra, and are expressed in terms of the corresponding relaxation rates R_1Z = 1/T_1Z and R₂ = 1/T₂. The ¹⁵N R_1Z and R₂ values are plotted against residue number in Figure 4A and 4B respectively. They demonstrate a pattern of rising and falling R₂/R_1Z values that are related to the protein backbone and local dynamics of the residues within the protein. Variations of the R₂/R_1Z profile shown in Figure 4C support the predicted secondary structure. Higher flexibility is seen in the loop regions and N- and C-terminal ends of the protein. Assuming the relaxation is due to ¹H and ¹⁵N dipolar interactions together with ¹⁵N chemical shift anisotropy (CSA) modulated by local fluctuations and overall protein tumbling motion, the relaxation rates are given by the following expressions [27], [32], [33]:(1)(2)

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Figure 4. Variations in ¹⁵N relaxation rates R_1Z and R₂ and the ratios R₂/R_1Z support the predicted secondary structure of OEP16 and backbone assignments.

(A) ¹⁵N spin-lattice R_1Z relaxation rates, (B) ¹⁵N transverse R₂ relaxation rates, and (C) R₂/R_1Z ratios. The suggested TM helical regions are indicated by the red bars above the plot with helical breaks in yellow and solvent-exposed helices in green. Relaxation rates for U-¹⁵N-labeled OEP16 in SDS micelles were obtained at 600 MHz at 310 K with sample conditions identical to Figure 1. Higher R₂/R_1Z values are located in the central part of the TM helices possibly indicating relatively rigid regions of the protein.

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Here , , µ₀ is the permeability of free space, h = 2πħ is Planck’s constant, γ_H and γ_N are the magnetogyric ratios of the ¹H and ¹⁵N nuclei respectively, r_NH is the ¹⁵N–¹H bond length, ω_H and ω_N are the Larmor frequencies of the ¹H and ¹⁵N spins, and Δσ is the chemical shift anisotropy of the ¹⁵N spin. Typically peptide bonds demonstrate an axially symmetric chemical shift tensor, and have an average CSA of –160 ppm [28]. Consequently a uniform value of Δσ = –160 ppm was used in this study.

In Eqs. 1 and 2 the spectral densities J(ω) are given by [5], [11], [31], [32], [34]:(3)where S² is the generalized ¹H-¹⁵N bond orientational order parameter, and τ_m is the isotropic rotational correlation time of the protein molecule. If τ_f is the correlation time for internal fast motions, then the effective correlation time can be defined as:

(4)Assuming that internal motions are restricted in their amplitude and fast enough that their contributions can be neglected in the relaxation processes, then J(ω) takes the simple canonical form [11], [31] :(5)

The expression for R₂/R_1Z is given by:(6)

Note that the R₂/R_1Z ratio is independent of S². Hence one can estimate the local effective correlation time, and thereby anisotropic diffusion tensor, by fitting the experimental R₂/R_1Z data to theoretical expressions given by above equations, assuming the ¹⁵N-H bond vector orientation distribution is known. However, for a spherical protein, due to lack of a unique principal projection axis, a single correlation time (τ_m = 1/6D_iso) can be defined as the mean value of the effective correlation times independent of N-H bond vector orientation [28], [29]. For determining τ_m, the contributions from residues that are highly mobile and residues responsible for chemical exchange have to be eliminated, so that only residues rigidly bound to protein are used.

Accordingly, we calculated the local effective correlation times by fitting the experimental R₂/R_1Z values for each residue to Eq. 6. In our calculations, because we do not have the N-H orientation data, as a first approximation we estimated the isotropic overall correlation time by assuming OEP16 to be a nearly spherical protein. In this process, we did not consider the highly mobile residues (first 10 residues from N-terminal end and last two residues from C-terminal end). To eliminate the residues responsible for chemical exchange, we chose the residues with R₂ values higher than one standard deviation from the average R₂ value. In fact none of the residues show such high R₂ values. Here we considered all other residues to estimate τ_m. The loop region (residue numbers 55–65) is relatively flexible but inclusion of those residues did not show much impact in the average correlation time calculations.

The assumption of a single isotropic rotational correlation time is a simplification for most macromolecules. However, the anisotropic effects are small for slightly non-spherical proteins. Here, the calculated τ_m value is used as a qualitative signature of the presence of a monomeric OEP16 molecule. It is not intended to explain the anisotropic diffusion parameters, for which a 3D structure either from X-ray crystallography or NMR spectroscopy would be necessary. That is beyond the scope of the present study, and is not needed to substantiate our major findings. The estimated τ_m value is typically taken as the initial value for the model-free analysis. The assumption is that if a dimer or multimer state exists, it would be reflected in the average overall tumbling time corresponding to slowing down of the motions. Previously, such an estimation of effective correlation times was established in the case of a 18 kDa protein [28], and those correlation times were used to estimate the order parameters. Furthermore, we expect the variations observed in R₂/R_1Z ratio are predominantly the signatures of dynamics of the α-helices, rather than the internal motions or exchange. Notably the plots of R₂ and R₂/R_1Z as a function of residue number reflect a similar trend as the TALOS+ predicted secondary structure of OEP16. We observe higher R₂ values and hence R₂/R_1Z values in the middle of helices than the edges and loops. Such a trend in relaxation rates reflects the secondary structure on the one hand, and supports the backbone assignments on the other.

The average overall global correlation time of 12.5±0.5 ns can then be used to estimate a hydrodynamic radius of 2.4 nm by applying Stoke’s Law [5]:(7)

In this expression η is the viscosity of the solvent, estimated to be 0.931 cP for a 10% glycerol-water solution at 310 K [35], r_H is the hydrodynamic radius of the protein-micelle complex, k_B is the Boltzmann constant, and T is temperature. Additionally, the molar mass of the complex can be estimated from r_H [5] if the protein density is assumed to be ρ = 1.37 g/cm³ (and therefore a protein-micelle density of ρ = 1.18 g/cm³) and the hydration layer is estimated to be 1.6 Å (corresponding to one-half a hydration shell):(8)

Here N_A is Avogadro’s number, and is the specific volume of the protein. For OEP16 a molar mass (M_r) of 31.8 kDa is calculated. This value corresponds to an OEP16 monomer plus 65 SDS molecules forming the micelle. An estimated correlation time of an OEP16 dimer with a sufficient SDS micelle would correspond to between 18–19 ns which is significantly larger than what was measured. Although the assumptions necessary for the molar mass calculation prevent an exact number, the conclusion of a monomeric protein can be made with confidence.

Arginine Titration Results

A number of significant chemical shift perturbations were observed throughout the protein upon titration with increasing amounts of arginine as depicted in Figure 5. Specific binding yields a rectangular hyperbola with a saturating end point similar to what is shown for E64 and E92 (the two most prominent shift perturbations) in the inset of Figure 5. The y-axis reports the scaled chemical shift perturbation across both ¹⁵N and ¹H dimensions (scaled according to Ref. [36]). The chemical shift perturbation via the introduction of arginine displays specific, weak binding of the amino acid to the OEP16 monomer. The residues show significant chemical shift perturbations which are nonlinear compared to the other residues, such as D128 and A139, which suggests that any binding that occurs at these sites is strictly nonspecific.

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Figure 5. Arginine titration studies reveal the ligand binding regions of OEP16.

Chemical shift perturbations for the most significantly affected residues of wild-type OEP16 are plotted as function of arginine concentration (shown in inset). A 500-mM arginine solution in a 10% ²H₂O buffer containing 100 mM NaCl, 50 mM NaH₂PO₄ pH 7.4, 1 mM BME, 1 mM EDTA, 10% (v/v) glycerol, 0.4% (w/v) SDS, and 0.02% (w/v) NaN₃ was titrated into the NMR tube for final concentration values of 0 mM, 10 mM, 20 mM, and 40 mM of arginine. The hyperbolic shape of the binding curves suggests the specific binding of arginine to OEP16. Nonspecific binding residues D128 and A139 show a distinctively linear relationship upon arginine titration. Blue indicates the spectrum in the absence of arginine and progresses to green, then orange, and ultimately red as increasing amounts of arginine are added.

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OEP16 Topology

Taken together, the TALOS+ calculations and relaxation data provide information on how the protein crosses the membrane when the hydrophobicity analysis [9] also considered. The first TM helix begins at residue F25 and spans the membrane to S44; the second TM helix starts at residue E64 and traverses the membrane ending at residue Y89; the peptide crosses the membrane a third time at residue N102 and ends at residue N119; and finally the fourth TM region begins at residue V127 and ends at residue T146, as illustrated in Figure S3. Figure S3 demonstrates that the independent calculations and measurements align well with each other along with the hydropathy data generated from the protein’s primary structure. The α-helix prediction by TALOS+ also suggests that there is a small break within each of the four TM helical regions, at N27, K72, A103, and I130. Order parameters and relaxation data suggest that these residues are flexible relative to the surrounding residues in the sequence.

Discussion

In this work we have addressed three important properties of the membrane protein OEP16: the formation of transmembrane helices of OEP16 protein, its likely monomeric state in SDS detergent micelles, and the ligand binding properties of this protein using results obtained from various high-resolution NMR experiments. The three-dimensional NMR data for the OEP16 protein have been used to obtain 95% of the amino acid backbone chemical shift assignments. These chemical shift data have been analyzed using the TALOS+ program to detect the secondary structure elements, and to estimate ¹H-¹⁵N bond orientational order parameters. The evaluated secondary structure reveals that OEP16 contains four α-helices connected by flexible loop regions. The overall α-helix content calculated in this method (∼55%) fits well with previously measured circular dichroism [6] and hydropathy plot data (∼50%) [9].

Notably, the information unveiled in these studies provides the first experimental evidence that OEP16 consists of four TM helices, and identifies the residues involved with helix formation. The presence of four α-helical based on our results coincides with the four-helix model inferred from residue hydropathy analysis [9]. Moreover, the amount of helix content calculated by TALOS+ is in agreement with the CD data provided in previous studies [6], [9]. By comparing TALOS+ predicted α-helices regions and ¹H-¹⁵N bond orientational order parameters with the ¹⁵N relaxation data, one can locate the TM helices as shown in Figures 3 and 4. The breaks in the TM α-helices provide additional structural information. The location of each of these breaks is interesting as well: they all begin at the N-terminal part of the helix as it traverses the membrane. This means that when the N-terminus of the protein is oriented “down” in the membrane, the breaks for H1 and H3 are closer to the bottom, while the breaks for H2 and H4 helices are located at the top. 6 All of the experimental results and conclusions are pictorially summarized in Figure 6. It is possible that these flexible regions function either for specificity of substrate diffusion, or play a role in opening and closing the channel as a way for the amino acids to diffuse into the chloroplast. Interestingly, the seven identified residues with two peaks in the ¹⁵N-HSQC may suggest that OEP16 may exist as two different conformations in slow exchange on the NMR time scale. This may provide a mechanistic insight to OEP16 when a high-resolution structure is obtained. As an example it is possible that one isoform is in a conformation that inhibits amino acid diffusion across the outer chloroplast membrane versus the other conformation.

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Figure 6. illustration of secondary fold based on evidence in this study.

Side view of the protein is shown to demonstrate how the helices traverse the membrane, and indicates amino acids involved with ligand transport. Included in red are the locations where there are possible breaks or kinks in the helices.

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The chemical shift perturbation study agrees with mutation studies, which show that H1 and H2 are required for protein function. Chemical shift data describes regions of the protein where α-helices are present, and relaxation results point to the flexible loop regions of the protein. Due to the selectivity of OEP16 for amino acids, the arginine titration experiment identifies residues within OEP16 where the ligand directly interacts. This study provides insight into the mechanism of OEP16 function, although more indepth studies are required to provide further detailed information. An additional aspect addressed in this study is the possibility of forming oligomeric states of OEP16. The multimeric state of OEP16 has been a topic of discussion in the past literature, with dimer formation imposed from cross-linking cysteine residues, [7] whereas trimers are suggested from electron micrograph data [10]. Moreover, previous gel filtration results have suggested a larger multimeric state [6]. Nonetheless the average rotational correlation time of ∼12.5 ns calculated by the relaxation data clearly suggests the presence of an OEP16 monomer in SDS micelles. Although these calculations assume OEP16 as a rigid globular protein, for the overall tumbling motion of simple rigid proteins of the size of 16 kDa, these time scales can be well established. Hence one can conclude that OEP16 predominantly forms monomers in SDS micelles.

The data presented in this study represents the penultimate step in understanding the functional and structural characteristics of OEP16. The information obtained will be crucial for a three-dimensional structure. Future experiments will involve amino acid specific labeling in order to take advantage of the structural information provided by long range NOEs. Orienting OEP16 in a weakly aligning media such as polyacrylamide will also provide structural refinement via residual dipolar couplings.

Supporting Information

Figure S1.

Two-dimensional ¹H-¹⁵N HSQC spectra indicate the possibility of conformational exchange of OEP16 solubilized in SDS detergent micelles. The spectrum was acquired at 600 MHz and sample conditions are identical to Figure 1. Seven residues have two peaks each in the 2D ¹⁵N-HSQC spectrum and are shown in the boxes: (A) F6, (B) S7, (C) G8, (D) S44, (E) L67, (F) G74, and (G) A77 all have two peaks, but have identical ¹³C_α, ¹³C_β, ¹³CO, and ¹H_α chemical shifts; (H) control showing single peaks. The different chemically shifted resonances may indicate two different conformations of the protein in slow exchange on the NMR time scale.

https://doi.org/10.1371/journal.pone.0078116.s001

(TIF)

Figure S2.

A comparison of ¹H-¹⁵N HSQC spectra of OEP16 in SDS micelles and β-DDM micelles. Similarities in protein secondary structure and folding are clearly evident. The spectrum of OEP16 in SDS micelles (red) obtained at 600 MHz at 298 K is superimposed onto the spectrum of the protein in β-DDM (blue) obtained at 800 MHz. at 318 K. Inset is a ¹H-¹⁵N HSQC spectrum of OEP16 in SDS at 310 K (black) superimposed on a spectrum of OEP16 in SDS at 298K (red), both obtained at 600 MHz. Several resolved resonances are assigned. Sample conditions are identical to Figure 1. The similar peak positions of the backbone amides suggest that OEP16 folds similarly in the nonionic detergent β-DDM and the anionic detergent SDS. Linewidths are significantly broader at 298K compared to 310K, and are very similar to the linewidths of OEP16 in β-DDM despite the temperature at which the spectra were acquired.

https://doi.org/10.1371/journal.pone.0078116.s002

(TIF)

Figure S3.

Transmembrane regions of OEP16 are predicted using different methods and are shown together for comparison. Results of relaxation measurements (red), TALOS+-predicted secondary structure (green), and S² values (purple) are indicated. Orange represents the comparisons to predictions of previously published hydropathy plot analysis [7]. Beginning and ending residues differ slightly yet the data are in agreement for the general location of the TM helices.

https://doi.org/10.1371/journal.pone.0078116.s003

(TIF)

Table S1.

Assigned chemical shifts for each residue in OEP16. Assignments were made using a combination of HNCO, HN(CA)CO, HNCA, HN(CO)CA, HNCACB, CBCA(CO)NH, ¹⁵N-TOCSY-HSQC, and ¹⁵N-NOESY-HSQC experiments.

https://doi.org/10.1371/journal.pone.0078116.s004

(DOC)

Author Contributions

Conceived and designed the experiments: JDZ TRM NEJ GL JS BRC MFB PF. Performed the experiments: JDZ TRM NEJ GL JS BRC MFB PF. Analyzed the data: JDZ TRM NEJ GL JS BRC MFB PF. Contributed reagents/materials/analysis tools: JDZ TRM NEJ GL JS BRC MFB PF. Wrote the paper: JDZ TRM NEJ GL JS BRC MFB PF.

References

1. Boyer PD (1997) The ATP synthase - a splendid molecular machine. Annu Rev Biochem 66: 717–749.
- View Article
- Google Scholar
2. Cuatrecasas P (1974) Membrane receptors. Annu Rev Biochem 43: 169–214.
- View Article
- Google Scholar
3. Kobilka B, Schertler GFX (2008) New G-protein-coupled receptor crystal structures: insights and limitations. Trends Pharmacol Sci 29: 79–83.
- View Article
- Google Scholar
4. Fromme P, Spence JCH (2011) Femtosecond nanocrystallography using X-ray lasers for membrane protein structure determination. Curr Opin Struct Biol 21: 509–516.
- View Article
- Google Scholar
5. Cavanagh J, Fairbrother WJ, Palmer AG, Rance M, Skelton MJ (2007) Protein NMR spectroscopy: principles and practice. Boston: Academic Press. 885 p. p.
6. Ni D, Zook J, Klewer DA, Nieman RA, Soll J, et al. (2011) Isolation, folding and structural investigations of the amino acid transporter OEP16. Protein Expresssion Purif 80: 157–168.
- View Article
- Google Scholar
7. Pohlmeyer K, Soll J, Steinkamp T, Hinnah S, Wagner R (1997) Isolation and characterization of an amino acid-selective channel protein present in the chloroplastic outer envelope membrane. P Natl Acad Sci 94: 9504–9509.
- View Article
- Google Scholar
8. Steinkamp T, Hill H, Hinnah SC, Wagner R, Rohl T, et al. (2000) Identification of the pore-forming region of the outer chloroplast envelope protein OEP16. J Biol Chem 275: 11758–11764.
- View Article
- Google Scholar
9. Linke D, Frank J, Pope MS, Soll J, Ilkavets I, et al. (2004) Folding kinetics and structure of OEP16. Biophys J 86: 1479–1487.
- View Article
- Google Scholar
10. Linke D, Frank J, Holzwarth JF, Soll J, Boettcher C, et al. (2000) In vitro reconstitution and biophysical characterization of OEP16, an outer envelope pore protein of pea chloroplasts. Biochemistry 39: 11050–11056.
- View Article
- Google Scholar
11. Brown MF (1982) Theory of spin-lattice relaxation in lipid bilayers and biological-membranes: ²H and ¹⁴N quadrupolar relaxation. J Chem Phys 77: 1576–1599.
- View Article
- Google Scholar
12. Nevzorov AA, Trouard TP, Brown MF (1998) Lipid bilayer dynamics from simultaneous analysis of orientation and frequency dependence of deuterium spin-lattice and quadrupolar order relaxation. Phys Rev E 58: 2259–2281.
- View Article
- Google Scholar
13. Marion D, Kay LE, Sparks SW, Torchia DA, Bax A (1989) Three-dimensional heteronuclear NMR of ¹⁵N-labeled proteins. J Am Chem Soc 111: 1515–1517.
- View Article
- Google Scholar
14. Marion D, Driscoll PC, Kay LE, Wingfield PT, Bax A, et al. (1989) Overcoming the overlap problem in the assignment of ¹H NMR spectra of larger proteins by use of three-dimensional heteronuclear ¹H-¹⁵N Hartmann-Hahn-multiple quantum coherence and nuclear Overhauser-multiple quantum coherence spectroscopy: Application to interleukin 1b. Biochemistry 28: 6150–6156.
- View Article
- Google Scholar
15. Bax A, Ikura M, Kay LE, Torchia DA, Tschudin R (1990) Comparison of different modes of two-dimensional reverse-correlation NMR for the study of proteins. Journal of Magnetic Resonance 86: 304–318.
- View Article
- Google Scholar
16. Kay LE, Ikura M, Tschudin R, Bax A (1990) Three-dimensional triple-resonance NMR-spectroscopy of isotopically enriched proteins. Journal of Magnetic Resonance 89: 496–514.
- View Article
- Google Scholar
17. Grzesiek S, Bax A (1992) Improved 3D triple-resonance NMR techniques applied to a 31 kDa protein. Journal of Magnetic Resonance 96: 432–440.
- View Article
- Google Scholar
18. Grzesiek S, Bax A (1992) Correlating backbone amide and side chain resonances in larger proteins by multiple relayed triple resonance NMR. Journal of the American Chemical Society 114: 6291–6293.
- View Article
- Google Scholar
19. Clubb RT, Thanabal V, Wagner G (1992) A constant-time three-dimensional triple-resonance pulse scheme to correlate intraresidue ¹H^N, ¹⁵N, and ¹³C′ chemical shifts in 15^N-13^C-labelled proteins. Journal of Magnetic Resonance 97: 213–217.
- View Article
- Google Scholar
20. Wittekind M, Mueller L (1993) HNCACB, a high-sensitivity 3D NMR experiment to correlate amide-proton and nitrogen resonances with the alpha- and beta-carbon resonances in proteins. Journal of Magnetic Resonance 101: 201–205.
- View Article
- Google Scholar
21. Delaglio F, Grzesiek S, Vuister GW, Zhu G, Pfeifer J, et al. (1995) NMRPipe: A multidimensional spectral processing system based on UNIX pipes. J Biomol NMR 6: 277–293.
- View Article
- Google Scholar
22. Goddard TD, Kneller DG (2008) SPARKY 3. University of California, San Francisco.
23. Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, et al. (2008) BioMagResBank (BMRB) as a partner in the worldwide protein data bank (wwPDB): new policies affecting biomolecular NMR depositions. Nucleic Acids Res 36: D402–D408.
- View Article
- Google Scholar
24. Cornilescu G, Delaglio F, Bax A (1999) Protein backbone angle restraints from searching a database for chemical shift and sequence homology. J Biomol NMR 13: 289–302.
- View Article
- Google Scholar
25. Shen Y, Delaglio F, Cornilescu G, Bax A (2009) TALOS plus: A hybrid method for predicting protein backbone torsion angles from NMR chemical shifts. J Biomol NMR 44: 213–223.
- View Article
- Google Scholar
26. Farrow NA, Muhandiram R, Singer AU, Pascal SM, Kay CM, et al. (1994) Backbone dynamics of a free and a phosphopeptide-complexed Src homology-2 domain studied by ¹⁵N NMR relaxation. Biochemistry 33: 5984–6003.
- View Article
- Google Scholar
27. Abragam A (1961) Principles of nuclear magnetism. Oxford: Clarendon Press.
28. Kay LE, Torchia DA, Bax A (1989) Backbone dynamics of proteins as studied by ¹⁵N inverse detected heteronuclear NMR-spectroscopy: application to staphylococcal nuclease. Biochemistry28: 8972–8979.
- View Article
- Google Scholar
29. Lee LK, Rance M, Chazin WJ, Palmer AG (1997) Rotational diffusion anisotropy of proteins from simultaneous analysis of ¹⁵N and ¹³C^a nuclear spin relaxation. J Biomol NMR 9: 287–298.
- View Article
- Google Scholar
30. Berjanskii MV, Wishart DS (2005) A simple method to predict protein flexibility using secondary chemical shifts. J Am Chem Soc 127: 14970–14971.
- View Article
- Google Scholar
31. Lipari G, Szabo A (1982) Model-free approach to the interpretation of nuclear magnetic resonance relaxation in macromolecules. 1. Theory and range of validity. J Am Chem Soc 104: 4546–4559.
- View Article
- Google Scholar
32. Brown MF, Chan SI (1996) Bilayer membranes: Deuterium & Carbon-13 NMR. In: Harris RK, Grant DM, editors. Encyclopedia of Nuclear Magnetic Resonance. New York: John Wiley & Sons, Ltd.
33. Nevzorov AA, Brown MF (1997) Dynamics of lipid bilayers from comparative analysis of ²H and ¹³C nuclear magnetic resonance relaxation data as a function of frequency and temperature. J Chem Phys 107: 10288–10310.
- View Article
- Google Scholar
34. Meirovitch E, Shapiro YE, Polimeno A, Freed JH (2010) Structural dynamics of bio-macromolecules by NMR: The slowly relaxing local structure approach. Prog Nucl Magn Reson Spectrosc 56: 360–4058.
- View Article
- Google Scholar
35. Cheng NS (2008) Formula for the viscosity of a glycerol-water mixture. Ind Eng Chem Res 47: 3285–3288.
- View Article
- Google Scholar
36. Grzesiek S, Stahl SJ, Wingfield PT, Bax A (1996) The CD4 determinant for downregulation by HIV-1 Nef directly binds to Nef. Mapping of the Nef binding surface by NMR. Biochemistry 35: 10256–10261.
- View Article
- Google Scholar

[ref1] 1. Boyer PD (1997) The ATP synthase - a splendid molecular machine. Annu Rev Biochem 66: 717–749.
View Article
Google Scholar

[2] View Article

[3] Google Scholar

[ref2] 2. Cuatrecasas P (1974) Membrane receptors. Annu Rev Biochem 43: 169–214.
View Article
Google Scholar

[5] View Article

[6] Google Scholar

[ref3] 3. Kobilka B, Schertler GFX (2008) New G-protein-coupled receptor crystal structures: insights and limitations. Trends Pharmacol Sci 29: 79–83.
View Article
Google Scholar

[8] View Article

[9] Google Scholar

[ref4] 4. Fromme P, Spence JCH (2011) Femtosecond nanocrystallography using X-ray lasers for membrane protein structure determination. Curr Opin Struct Biol 21: 509–516.
View Article
Google Scholar

[11] View Article

[12] Google Scholar

[ref5] 5. Cavanagh J, Fairbrother WJ, Palmer AG, Rance M, Skelton MJ (2007) Protein NMR spectroscopy: principles and practice. Boston: Academic Press. 885 p. p.

[ref6] 6. Ni D, Zook J, Klewer DA, Nieman RA, Soll J, et al. (2011) Isolation, folding and structural investigations of the amino acid transporter OEP16. Protein Expresssion Purif 80: 157–168.
View Article
Google Scholar

[15] View Article

[16] Google Scholar

[ref7] 7. Pohlmeyer K, Soll J, Steinkamp T, Hinnah S, Wagner R (1997) Isolation and characterization of an amino acid-selective channel protein present in the chloroplastic outer envelope membrane. P Natl Acad Sci 94: 9504–9509.
View Article
Google Scholar

[18] View Article

[19] Google Scholar

[ref8] 8. Steinkamp T, Hill H, Hinnah SC, Wagner R, Rohl T, et al. (2000) Identification of the pore-forming region of the outer chloroplast envelope protein OEP16. J Biol Chem 275: 11758–11764.
View Article
Google Scholar

[21] View Article

[22] Google Scholar

[ref9] 9. Linke D, Frank J, Pope MS, Soll J, Ilkavets I, et al. (2004) Folding kinetics and structure of OEP16. Biophys J 86: 1479–1487.
View Article
Google Scholar

[24] View Article

[25] Google Scholar

[ref10] 10. Linke D, Frank J, Holzwarth JF, Soll J, Boettcher C, et al. (2000) In vitro reconstitution and biophysical characterization of OEP16, an outer envelope pore protein of pea chloroplasts. Biochemistry 39: 11050–11056.
View Article
Google Scholar

[27] View Article

[28] Google Scholar

[ref11] 11. Brown MF (1982) Theory of spin-lattice relaxation in lipid bilayers and biological-membranes: ²H and ¹⁴N quadrupolar relaxation. J Chem Phys 77: 1576–1599.
View Article
Google Scholar

[30] View Article

[31] Google Scholar

[ref12] 12. Nevzorov AA, Trouard TP, Brown MF (1998) Lipid bilayer dynamics from simultaneous analysis of orientation and frequency dependence of deuterium spin-lattice and quadrupolar order relaxation. Phys Rev E 58: 2259–2281.
View Article
Google Scholar

[33] View Article

[34] Google Scholar

[ref13] 13. Marion D, Kay LE, Sparks SW, Torchia DA, Bax A (1989) Three-dimensional heteronuclear NMR of ¹⁵N-labeled proteins. J Am Chem Soc 111: 1515–1517.
View Article
Google Scholar

[36] View Article

[37] Google Scholar

[ref14] 14. Marion D, Driscoll PC, Kay LE, Wingfield PT, Bax A, et al. (1989) Overcoming the overlap problem in the assignment of ¹H NMR spectra of larger proteins by use of three-dimensional heteronuclear ¹H-¹⁵N Hartmann-Hahn-multiple quantum coherence and nuclear Overhauser-multiple quantum coherence spectroscopy: Application to interleukin 1b. Biochemistry 28: 6150–6156.
View Article
Google Scholar

[39] View Article

[40] Google Scholar

[ref15] 15. Bax A, Ikura M, Kay LE, Torchia DA, Tschudin R (1990) Comparison of different modes of two-dimensional reverse-correlation NMR for the study of proteins. Journal of Magnetic Resonance 86: 304–318.
View Article
Google Scholar

[42] View Article

[43] Google Scholar

[ref16] 16. Kay LE, Ikura M, Tschudin R, Bax A (1990) Three-dimensional triple-resonance NMR-spectroscopy of isotopically enriched proteins. Journal of Magnetic Resonance 89: 496–514.
View Article
Google Scholar

[45] View Article

[46] Google Scholar

[ref17] 17. Grzesiek S, Bax A (1992) Improved 3D triple-resonance NMR techniques applied to a 31 kDa protein. Journal of Magnetic Resonance 96: 432–440.
View Article
Google Scholar

[48] View Article

[49] Google Scholar

[ref18] 18. Grzesiek S, Bax A (1992) Correlating backbone amide and side chain resonances in larger proteins by multiple relayed triple resonance NMR. Journal of the American Chemical Society 114: 6291–6293.
View Article
Google Scholar

[51] View Article

[52] Google Scholar

[ref19] 19. Clubb RT, Thanabal V, Wagner G (1992) A constant-time three-dimensional triple-resonance pulse scheme to correlate intraresidue ¹H^N, ¹⁵N, and ¹³C′ chemical shifts in 15^N-13^C-labelled proteins. Journal of Magnetic Resonance 97: 213–217.
View Article
Google Scholar

[54] View Article

[55] Google Scholar

[ref20] 20. Wittekind M, Mueller L (1993) HNCACB, a high-sensitivity 3D NMR experiment to correlate amide-proton and nitrogen resonances with the alpha- and beta-carbon resonances in proteins. Journal of Magnetic Resonance 101: 201–205.
View Article
Google Scholar

[57] View Article

[58] Google Scholar

[ref21] 21. Delaglio F, Grzesiek S, Vuister GW, Zhu G, Pfeifer J, et al. (1995) NMRPipe: A multidimensional spectral processing system based on UNIX pipes. J Biomol NMR 6: 277–293.
View Article
Google Scholar

[60] View Article

[61] Google Scholar

[ref22] 22. Goddard TD, Kneller DG (2008) SPARKY 3. University of California, San Francisco.

[ref23] 23. Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, et al. (2008) BioMagResBank (BMRB) as a partner in the worldwide protein data bank (wwPDB): new policies affecting biomolecular NMR depositions. Nucleic Acids Res 36: D402–D408.
View Article
Google Scholar

[64] View Article

[65] Google Scholar

[ref24] 24. Cornilescu G, Delaglio F, Bax A (1999) Protein backbone angle restraints from searching a database for chemical shift and sequence homology. J Biomol NMR 13: 289–302.
View Article
Google Scholar

[67] View Article

[68] Google Scholar

[ref25] 25. Shen Y, Delaglio F, Cornilescu G, Bax A (2009) TALOS plus: A hybrid method for predicting protein backbone torsion angles from NMR chemical shifts. J Biomol NMR 44: 213–223.
View Article
Google Scholar

[70] View Article

[71] Google Scholar

[ref26] 26. Farrow NA, Muhandiram R, Singer AU, Pascal SM, Kay CM, et al. (1994) Backbone dynamics of a free and a phosphopeptide-complexed Src homology-2 domain studied by ¹⁵N NMR relaxation. Biochemistry 33: 5984–6003.
View Article
Google Scholar

[73] View Article

[74] Google Scholar

[ref27] 27. Abragam A (1961) Principles of nuclear magnetism. Oxford: Clarendon Press.

[ref28] 28. Kay LE, Torchia DA, Bax A (1989) Backbone dynamics of proteins as studied by ¹⁵N inverse detected heteronuclear NMR-spectroscopy: application to staphylococcal nuclease. Biochemistry28: 8972–8979.
View Article
Google Scholar

[77] View Article

[78] Google Scholar

[ref29] 29. Lee LK, Rance M, Chazin WJ, Palmer AG (1997) Rotational diffusion anisotropy of proteins from simultaneous analysis of ¹⁵N and ¹³C^a nuclear spin relaxation. J Biomol NMR 9: 287–298.
View Article
Google Scholar

[80] View Article

[81] Google Scholar

[ref30] 30. Berjanskii MV, Wishart DS (2005) A simple method to predict protein flexibility using secondary chemical shifts. J Am Chem Soc 127: 14970–14971.
View Article
Google Scholar

[83] View Article

[84] Google Scholar

[ref31] 31. Lipari G, Szabo A (1982) Model-free approach to the interpretation of nuclear magnetic resonance relaxation in macromolecules. 1. Theory and range of validity. J Am Chem Soc 104: 4546–4559.
View Article
Google Scholar

[86] View Article

[87] Google Scholar

[ref32] 32. Brown MF, Chan SI (1996) Bilayer membranes: Deuterium & Carbon-13 NMR. In: Harris RK, Grant DM, editors. Encyclopedia of Nuclear Magnetic Resonance. New York: John Wiley & Sons, Ltd.

[ref33] 33. Nevzorov AA, Brown MF (1997) Dynamics of lipid bilayers from comparative analysis of ²H and ¹³C nuclear magnetic resonance relaxation data as a function of frequency and temperature. J Chem Phys 107: 10288–10310.
View Article
Google Scholar

[90] View Article

[91] Google Scholar

[ref34] 34. Meirovitch E, Shapiro YE, Polimeno A, Freed JH (2010) Structural dynamics of bio-macromolecules by NMR: The slowly relaxing local structure approach. Prog Nucl Magn Reson Spectrosc 56: 360–4058.
View Article
Google Scholar

[93] View Article

[94] Google Scholar

[ref35] 35. Cheng NS (2008) Formula for the viscosity of a glycerol-water mixture. Ind Eng Chem Res 47: 3285–3288.
View Article
Google Scholar

[96] View Article

[97] Google Scholar

[ref36] 36. Grzesiek S, Stahl SJ, Wingfield PT, Bax A (1996) The CD4 determinant for downregulation by HIV-1 Nef directly binds to Nef. Mapping of the Nef binding surface by NMR. Biochemistry 35: 10256–10261.
View Article
Google Scholar

[99] View Article

[100] Google Scholar