Study of Protein Dynamics under Nanoconfinement by Spin-Label

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Study of Protein Dynamics under Nanoconfinement by Spin-Label ESR: A Case of T4 Lysozyme Protein Kuo-Jung Chang, Yun-Hsuan Kuo, and Yun-Wei Chiang J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.7b00014 • Publication Date (Web): 14 Apr 2017 Downloaded from http://pubs.acs.org on April 23, 2017

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The Journal of Physical Chemistry

Study of Protein Dynamics Under Nanoconfinement by Spin-label ESR: A Case of T4 Lysozyme Protein

Kuo-Jung Chang†, Yun-Hsuan Kuo†, and Yun-Wei Chiang* Department of Chemistry, National Tsing Hua University, Hsinchu, 30013, Taiwan

†

These authors contributed equally to this work.

*Correspondence email: [email protected]

1 ACS Paragon Plus Environment


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Abstract ESR spectra of spin-labeled proteins are sensitive to dynamics, but discrimination between the various dynamics is often difficult. Here, we report an improvement in ESR spectral sensitivity to local backbone dynamics of a protein by a methodology that performs ESR measurement when the protein is confined in nanochannels of mesoporous material. An extensive set of ESR data, which includes spectra of a nitroxide-based side chain from buried and solvent-exposed sites of T4 lysozyme (T4L) protein, were obtained over a range of temperature 200−300 K, to explore the dynamics of T4L under nanoconfinement. Spectra were simulated by performing theoretical fits to the data using the microscopic ordering with macroscopic disordering model. Two principle dynamic modes, which differ in mobility and ordering, are required to account for the spectra at temperatures > 240 K. We show that the mobile one correlates only with local backbone dynamics of buried sites, while the other reflects the difference in local hydration dynamics between the labeling sites in T4L. The assignment of the mobile component is supported by the X-ray crystallography data of T4L. Collectively, this study has demonstrated the validity of such a methodology for improving ESR sensitivity to buried sites in a protein.


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Introduction Mesoporous silica materials are characterized by large surface area, narrow pore size distribution, high structural stability, as well as their tunable pore diameter in a nanometer range.1,2 The materials have in recent years been extensively developed and applied to biomedical applications, such as drug release and delivery, as well as immobilization of enzyme to enhance the reuse and recovery of protein activity.3–5 These recent studies have also demonstrated that proteins could retain their structures and enzymatic activities after being encapsulated into the mesoporous materials.6–9 Besides, some studies showed that water molecules, when confined in the nanochannels of mesoporous material, remain in a noncrystalline state at subfreezing temperatures. This finding has opened up new avenues for studying water dynamics within the no man’s land (150−235 K) where bulk water is crystalline.10–13 Despite the variety of applications, a comprehensive investigation and characterization of the dynamics present in a nanoconfined protein remains to be explored. To gain more knowledge about the immobilization/encapsulation process, it is crucial to reveal details of how protein structure and dynamics are affected by the microenvironment inside the nanochannels. Mesoporous materials have in recent years also been utilized to improve spin-label ESR technique for protein dynamics.14–16 A variety of mesoporous materials were used together with ESR as a novel biophysical approach for probing dynamics on linear polypeptides. Previous studies showed that the nanochannels in mesoporous material provide well confined environment to immobilize the tumbling motions of the encapsulated molecules; the studied molecules include nitroxide-based radicals and several spin-labeled polypeptides with different lengths varying from 10 to 30 residues.14,15,17 It was demonstrated that under nanoconfinement both the tumbling motion and side chain internal motion are largely excluded from the time scale of ESR spectroscopy. As a result, difference in the local backbone fluctuation (LBF) of a β-hairpin versus α-helical polypeptides is clearly reported and revealed in the ESR lineshape. When studied at subfreezing temperatures, nanoconfinement is effective in suppressing the formation of ice crystals and preventing the aggregation of spin-labeled molecules.11,12 Taken together, advantages of studying biomolecules under nanoconfinement by ESR include: i) reduced sensitivity of ESR spectral lineshape to the global tumbling motions of a biomolecule, ii) improved spectral sensitivity to LBF along a segment of secondary structure, and iii) ESR measurement at higher temperatures (e.g. 300 K) without the use of viscosity reagents.



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However, these advantages were derived based on the studies of simple polypeptides, in which tertiary contacts are absent, protein folds are simple, and local solvent accessibilities are similar among spin-labeled sites. The combined methodology of ESR and nanochannels has not been applied to any complex protein molecule containing not only secondary but also tertiary structures and tertiary contacts. Here we report a comprehensive study to identify the dynamic modes coexisting in the ESR spectra of spin-labeled T4 lysozyme (T4L) protein when confined in nanochannels of silica mesoporous materials. A variety of single-cysteine variants of T4L mutants, which cover solvent-exposed and buried sites over different secondary and tertiary segments of T4L, are prepared for the spin-label ESR study under nanoconfinement. General principles of studying protein dynamics using the combined methodology of ESR and nanochannels are therefore reported. We should note that this study provides a series of experiments (SI data), as also previously reported,18 to demonstrate that most of T4L proteins loaded on the mesoporous material are adsorbed inside the nanochannels of the material and the adsorbed T4L retains its structure in the nanochannel. Thus, we herein regard the adsorbed/encapsulated T4L as nanoconfined T4L.

Materials and Methods T4 lysozyme (T4L) protein expression and purification. The pseudo-wild type T4L construct containing the substitutions C54T and C97A was subcloned into NdeI/HindIII site of pET28a vector (New England Biolabs, Inc.), and then used to prepare single-cysteine constructs: F4C, E22C, A41C, L46C, L99C, T109C, T115C, A129C, V131C, L133C, I150C, and F153C. All point mutations were generated using the Quick-change site-directed mutagenesis kit (Stratagene) and verified by DNA sequencing. The recombinant pET28a vector was transformed into the E. coli BL21(DE3) expression strain (Novagen). Recombinant proteins fused with six histidines at the N-terminal of T4L were expressed and purified by affinity Ni column, as previously described.19 Briefly, bacterial culture was grown at 37 ℃ in LB medium containing kanamycin (50 µg/mL) until OD600 reached 0.8−1.0. T4L overexpression was induced upon addition of 1 mM of IPTG (isopropyl-β-Dthiogalactopyranoside) at 30 ℃ for 1-2 h. The cells were then harvested by centrifugation and the supernatant was discarded. The cell pellet was collected and resuspended in ice-cold lysis 4 ACS Paragon Plus Environment

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buffer (25 mM Tris-HCl, 25 mM Mops, pH 7.6, 40 mM imidazole and 1 mM PMSF). The resuspended pellet was sonicated on ice for 5 min, followed by centrifugation at 13,000× g for 50 min. Supernatant was filtrated through 0.22 µm filter and then loaded onto an affinity Ni column using HisTrap HP (GE Healthcare) at a flow rate about 0.5−1 mL/min. The column was washed with 3 column volumes of wash buffer (200 mM NaH2PO4, pH 7.6, 40 mM imidazole, 0.5 M NaCl). T4L fraction was eluted with elution buffer (200 mM NaH2PO4, pH 7.6, 0.5 M imidazole, 0.5 M NaCl). Imidazole was removed using PD-10 desalting column (GE Healthcare) equilibrated with buffer (50 mM MOPS, 25 mM NaCl, pH 6.8). Purified protein was confirmed by SDS-PAGE with coomassie blue staining, and protein concentration was estimated via absorption spectroscopy at 280 nm. Spin labeling of T4L mutants was performed in buffer containing 50 mM MOPS and 25 mM NaCl at pH 6.8. Proteins were labeled with a 10-fold excess of (1-oxy-2,2,5,5tetramethyl-3-pyrroline-3-methyl)

methanethiosulfonate

spin

label

(MTSL)

(Alexis

Biochemicals, San Diego, CA) per cysteine residue in the dark. The reaction was allowed to proceed at 4 ℃ for at least 6 h for solvent-accessible sites and at room temperature overnight for buried sites. Excess MTSL reagent was removed using PD-10 desalting column equilibrated with the same buffer. MALDI-TOF experiments were conducted to confirm the identity of proteins carrying spin labels. Information of local environment derived from crystal data. The crystal structure data (PDB: 3LZM) of T4 lysozyme was used to calculate solvent accessible surface area (SASA) using get_area function of the PyMol software. The crystal data were collected at 100 K. Based on the structural model, the site of interest was mutated to cysteine residue before calculating the SASA of the site. Solvent radius of 1.4 Å was used in the calculation. Relative solvent accessibility (RSA) is obtained by normalizing the SASA values of respective sites with the SASA value of site 109, the most solvent-exposed one among the studied sites of T4L. B-factors of protein crystal structures reflect the fluctuation of atoms about their average positions and provide important information about protein dynamics. It was previously demonstrated that the B-factors derived from crystal data of T4L are consistent with the Bfactors of backbone atoms predicted from a MD simulation.20 Studies of other proteins also supported that B-factors of protein crystals are well correlated with protein dynamics in solution.21–23 It is, therefore, reasonable to assume that B-factors of the T4L crystal reflect LBF of T4L in solution. Thus, summation of B-factor values on backbone (i.e., one nitrogen, one



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oxygen, and two carbon atoms on the main chain of the target residue) of T4L was used to represent local backbone dynamics of the studied site. Details of the values are given in Table S1. Encapsulation of T4L into nanochannels of mesoporous material. Mesoporous silica material with a cross-linked hexagonal pore structure, pore volume of 0.91 cm3/g, average pore size of 7.1 nm, and pore size distribution of ±10% (known as MSU-H) was purchased from Aldrich. Herein MSU-H is abbreviated as MSU. Prior to the protein encapsulation, MSU materials were placed in a vacuum oven at 100 ℃ overnight to remove moisture. For continuous wave (cw) ESR measurements, 6 µL protein solution was mixed with 12 mg of MSU, then the sample was directly loaded into a quartz ESR tube (5 mm o.d.) sealed with Parafilm. The protein solution volume of 6 µL was determined to best retain protein in a hydrated state in the nanochannels of 12-mg MSU material (Fig. S1). Concentration of T4L prior to the encapsulation is 50 g/L (i.e., 300 µg of T4L in the 6 µL solution, which is equivalent to 2.9 mM, approximately). Experiments (Fig. S2) similar to Hartmann et al.18 were performed to verify that T4L proteins remain monomeric, have negligible interactions with inner surface of the MSU materials, and are homogeneously dispersed in the nanochannels. In all of the reported nanochannel studies, no cryoprotectant was used. Circular dichroism (CD), IR spectroscopy, and double electron-electron resonance measurements (DEER). CD spectroscopy measurement for nanoconfined proteins/peptides was previously reported.17 The CD spectrum of nanoconfined T4L (Fig. S3) exhibits typical characteristic peaks at 208 and 225 nm, consistent with the CD spectrum of a wild type T4L in bulk solution.19 To further verify whether T4L retains its conformation under nanoconfinement, this study performed IR spectroscopy and distance measurements of a doubly labeled T4L under nanoconfinement by DEER spectroscopy (Fig. S3). For the IR measurement, 6 µL protein solution was mixed with 12 mg of MSU. Attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectra were recorded on Bruker Tensor 27 infrared spectrometer equipped with Pike Miracle ATR accessory. All spectra were collected by averaging 200 scans with a resolution of 2 cm-1 at room temperature. Analysis of the secondary structure of protein was based on the characteristic amide I and II bands. Therefore, all data were cut off to wavenumber between 1400 cm-1 and 2000 cm-1. The IR result supports that T4L retains its conformation in MSU (Fig. S3B). For the DEER measurements, both MSU and bulk vitrified solution conditions were measured. As shown in


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Figure S3, the results of the two distance measurements are consistent with the crystal structure of T4L and the previous study using pulsed ESR techniques.24 Taken together the CD, IR, and DEER results, it indicates that the structure of the studied T4L remains largely unchanged under nanoconfinement. ESR measurements. A Bruker ELEXSYS E580 cw/pulsed spectrometer, equipped with a Bruker pulse ELDOR unit E580-400, a split-ring resonator (ER4118X-MS3), and a helium gas flow system (4118CF and 4112HV), was used. The cw-ESR experiment was performed at an operating frequency of 9.4 GHz and 1.5 mW incident microwave power. DEER experiments were carried out using the four-pulse constant-time DEER sequence: π/2(ωA)− τ1− π(ωA)− (τ1+t)− π(ωB)− (τ2−t)− π(ωA)− τ2− echo.25 The detection pulses (ωA) were set to 32 and 16 ns for π and π/2 pulses, respectively and pump frequency (ωB) was set to approximately 70 MHz lower than the detection pulse frequency. The pulse amplitudes were chosen to optimize the refocused echo. The π/2-pulse was employed with +x/-x phase cycle to eliminate receiver offsets. The duration of the pumping pulse was about 32 ns, and its frequency (ωB) was coupled into the microwave bridge by a commercially available setup from Bruker. All pulses were amplified via a pulsed traveling wave tube amplifier (E580-1030). The field was adjusted such that the pump pulse is applied to the maximum of the nitroxide spectrum, where it selects the central mI = 0 transition of Azz together with the mI = ±1 transitions. Accumulation time for each set of data was about 10 h at temperature 80 K. A common cooling approach was used. The sample tube was plunge-cooled in liquid nitrogen, and then transferred into the ESR probehead, which was pre-cooled to 80 K using the helium flow system. The determination of interspin distance distribution of the DEER spectroscopy was performed in the time-domain analysis by Tikhonov regularization based on the L-curve method,26,27 followed by a data refinement process using the maximum entropy method (MEM)27 to obtain non-negative probability density P(r). For simplicity of the presentation, the above approach combining both the Tikhonov regularization and the MEM is herein called TIKR method. ESR spectral simulation. This study performed theoretical analyses of the experimental cw-ESR spectra using a nonlinear least squares (NLLS) fitting program based upon the stochastic Liouville equation (SLE).28,29 The NLLS program is implemented by nonlinear least-squares fitting with Levenberg-Marquardt algorithm.29 In the SLE-based lineshape theory, spin degrees of freedom in a system are treated in a quantum-mechanical fashion while the orientational dynamics of the spin probe is determined by a classical



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stochastic process. Such rigorous SLE-based interpretation for cw-ESR spectral analysis has been demonstrated useful for analyzing the spectra of complex macromolecules, e.g., proteins and membranes, to extract the dynamic parameters of spin probes from the experimental spectra.17,30–34 The microscopically ordered but macroscopically disordered (MOMD) model was included in the SLE-based lineshape analysis of the spectra.35 In this model the nitroxide side chain is constrained by a local ordering potential while the globular core of the protein is assumed to be immobilized on the ESR time scale and is statistically distributed with respect to the magnetic field. Thus, the simulated spectrum represents the integration of the spectra of all possible orientations over the distribution of local director with respect to magnetic field. As demonstrated previously,14,17 the tumbling motion of spin-labeled protein, which is extremely slow in nanochannels or at low temperatures, is largely excluded out of the ESR time scale. The MOMD model is, therefore, an appropriate model to simulate the spectra of the spin-labeled proteins in the present study. Principal values for A-tensor are (6.2, 4.3, 37.1) Gauss. The determined principal values for g-tensor are (2.0084, 2.0062, 2.0024). Rotational diffusion rate (R) that describes the motion of nitroxide spin probe is assumed to be axially symmetric (i.e., R⊥=Rx=Ry, R||=Rz) in the present study. It is common to show only values of R⊥ as R|| is often found insensitive against spectral lineshape in many of protein dynamics studies.32–34 In our simulations, the ratio of R⊥/R|| was fixed at unity. The correlation time

R

was obtained by 1/6R⊥. The ordering

potential of the anisotropic motion of the nitroxide is described by the order parameter S0, which is calculated from the ordering coefficients varied in the NLLS fitting. Linewidth parameter (Δ(0)) was used to account for the inhomogeneous Gaussian broadening. Multicomponent spectral fitting was allowed in the NLLS program. Populations of spectral components were determined by the program of the nonlinear least squares fits and were an output of the fitting. Average errors estimated from the simulations are 9% for R⊥, 0.04 for S0, and 3% for component populations. The parameter uncertainties were calculated from the covariance matrices returned from the SLE-based nonlinear least squared fitting.

Results


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This study has prepared twelve single-cysteine variants of T4L protein (Fig. 1A) for spinlabeling ESR study. The twelve studied sites can be classified into two groups: buried (in red color) and solvent exposed (in blue color) sites. The criteria for classification of the sites are displayed in Figure 1B. Sites, which are characterized by lower values in both the B factor of the backbone atoms and the relative solvent accessibility (RSA), are considered buried; otherwise, they are solvent exposed sites. The information of the B factor and RSA are directly derived from the reported crystal data (PDB: 3LZM), as detailed in Methods. All of the collected ESR spectra of the T4L mutants are given in Figures S4 and S5. Figure 1C shows

Figure 1. (A) Cartoon model of T4L structure (PDB code: 3LZM). Twelve singlecysteine variants of T4L studied are classified into two groups: solvent-exposed (blue) and buried (red) sites. The criteria for the classification are given in (B). (B) A plot of B factor versus RSA for the sites studied. RSA is obtained by normalizing the SASA values to site 109, the most solvent-exposed one among the sites studied. (C) ESR spectra (300 K) of the five representative sites, including solvent-exposed, buried, and loop sites. Spectral lineshape changes distinctly with the different local environment. A good quality of the theoretical fits (red) to experimental spectra (blue) is obtained. The best-fit parameters are given in Tables S2 and S3.



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ESR experimental spectra (blue solid lines) and simulation fits (red broken lines) of five representative sites, which include spin-labeled sites within a loop region, the buried group, and the solvent-exposed group. Due to the nanoconfinement the experimental spectra exhibit typical slow-motional lineshapes even at room temperature 300 K. However, there are still some small but significant differences in the lineshape between the solvent exposed and buried sites, which warrant further theoretical analysis. To extract dynamic parameters from the experimental ESR spectra, theoretical fits (see Figs. 1C and S4) to the temperature-dependent (200−300 K) spectra of the nanoconfined T4L mutants were performed using the nonlinear least squares (NLLS) fitting program based on stochastic Liouville equation (SLE; see Methods). Figure 2A shows the rotational diffusion

Figure 2. The best fit dynamic parameters obtained from the SLE-based theoretical fits to experimental spectra. (A) Rotational diffusion rates (R⊥) of the Mb (red) and Im (blue) and population of the Im component ([Im], shown in green) as a function of temperature. (B) One representative example of the T4L study illustrating the best fit to the experimental spectrum can be achieved with two spectral components (i.e., the Im and Mb) which are highly dissimilar to each other.


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rate (R⊥) as a function of temperature (200−300 K) for the five representative sites. Two spectral components were required to achieve a good quality of fits when temperature is greater than (approximately) 240 K. The two components are denoted by mobile (Mb) and immobile (Im), the first of which is characterized by (relatively) greater values of R⊥ than the later. Population of the Im (shown in green color in Fig. 2A) remains abundant (> 75%, approximately) throughout the temperature range studied. The rotational diffusion rate (R⊥) of the Im is relatively more sensitive to temperature than that of the Mb. The large differences in the parameters of the two dynamic modes render the distinct difference in the spectral lineshape between the two spectral components (Fig. 2B). The dissimilarity of the components not only reduces the possibility of overfitting but also provide support for the existence of the components. The best-fit parameters are given in Tables S2 and S3.

Figure 3. (A) Logarithmic plot of rotational correlation time ( R) as a function of inverse temperature (1/T). The data are fit to an Arrhenius-type equation (solid lines) to obtain the activation energy (EA) for each of the spin-labeled sites. EA values are noted in the plots. (B) Correlation plot of the EA and RSA, which reveals a positive correlation between the two measures.



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The temperature-dependence of R⊥ can be used to yield a plot of log(τR) versus 1/T, in which τR represents the rotational correlation time that can be directly calculated from the obtained rotational diffusion rates (see Methods). In the plot of log(τR) versus 1/T for the Im (Fig. 3A), the data can be fitted well (solid lines in Fig. 3A) to an Arrhenius-type equation. The analysis suggests that the dependence of τR on temperature follows the Arrhenius-type law, τR = τ0 exp(EA/kBT), where kB is the Boltzmann constant and EA is the activation energy for the molecular relaxation process. In other words, the analysis yields an activation energy (EA) for each of the studied sites, which provides a quantitative description for the extent of the confinement on the R1 side chain dynamics, and is therefore considered as a measure of the local dynamics of R1. The greater EA value, the greater the constraint on the side chain motions. A positive correlation between EA and RSA is suggested from the plot (Fig. 3B), whereas little is correlated between EA and the B factor data (plot not shown). Strikingly, our study reveals that the solvent exposed sites (e.g., 22R1, 109R1, and 131R1 in Fig. 3A) generally experience a greater magnitude of local constraints to the R1 dynamics than the buried sites (e.g., 99R1 and 133R1). This appears to be relevant to the nanoconfined dynamics of hydration on the outer surface of T4L, as discussed in a later section. To relate the results of the theoretical analyses (e.g., R⊥ and molecular ordering S0, as shown in Tables S2 and S3) to protein dynamics (e.g., LBF, which can be inferred from the B factor of crystal data, and local environment, which is correlated with RSA), we focus on the results obtained at 300 K (fits and parameters shown in Fig. S5 and Table S3). Plots of R⊥ for the Mb or Im as a function of B factor of the backbone atoms and RSA are displayed in Figures 4A and 4B, respectively. For either the Im or Mb, R⊥ shows little correlation with RSA (Fig. 4A). For the correlation plot of R⊥ and B factor (Fig. 4B), R⊥ of the Im shows little correlation, but R⊥ of the Mb exhibits a positive correlation with B factor. Specifically, the result of the Mb shows that the greater B factor of the backbone atoms (i.e., the greater in the mean square isotropic displacement of the atoms), the greater rotational diffusion rate R⊥. It indicates that the Mb component reflects largely the difference in LBF of the studied sites. As for the assignment of the Im, its significance is revealed in the plot of ordering parameter (S0), as shown in Figure 4C. It indicates that S0 for the buried versus solvent-exposed sites change oppositely with increasing RSA; specifically, the former decreases but the later increases with increasing RSA. It has been reported that hydration layers at the outer versus inner surfaces of protein behave differently with various changes in protein environment such as 12 ACS Paragon Plus Environment

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Figure 4. (A) Correlation plots of RSA and respective R⊥ values of the Im and Mb components. (B) Correlation plots of B factor and respective R⊥ values of the Im and Mb. Residues having a B-factor greater than 80 Å2 are classified to the solvent-exposed group, as demonstrated in Figure 1. For spin-labeled sites within the buried site group, R⊥ of the Mb shows correlation (as displayed by the guiding arrow) with B factor, which corresponds to the LBF. (C) Correlation plots of RSA and respective S0 values of the Im and Mb components. As described in Figure 1, residues having a RSA value greater than 50% belong to the solvent-exposed group. The guiding arrows emphasize that the correlations of S0 and RSA are opposite for the buried versus solvent exposed sites. temperature.36,37 At the solvent exposed sites, hydration dynamics is largely slowed down and restricted by the nanoconfinement, explaining the increase in S0 with increasing RSA. This behavior of S0 with RSA is specific to the effect of the nanoconfinement, opposite to what is expected for a bulk solution study. At buried sites, local hydration is little affected by the nanoconfinement. Thus, the deeper the solvent molecules are buried in the structure, the greater constraint they experience, explaining the increase in S0 with decreasing RSA. The lower the RSA value of a buried site, the greater constraint on the local dynamics. These observations are made from the data of the Im component and are well consistent with the temperaturedependent study (Fig. 3) that the solvent exposed sites generally experience greater constraint on the dynamics of R1 side chain than do the buried sites.

Discussion



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Assignment of coexisting dynamic modes in the spectra. The present study has reported a comprehensive investigation of protein dynamics under nanoconfinement by ESR at X-band frequency. We show that T4L, when encapsulated into the nanochannels of the MSU material, retains its conformational structure and the global tumbling motion of the protein appears frozen in the ESR time scale even at room temperatures. As a result, the slow tumbling of the nanoconfined T4L proteins contributes insignificantly to the ESR lineshapes, making the backbone dynamics (i.e., the LBF) and the local environment of the R1 side chain better pronounced in the spectral lineshape. The ESR spectra of the nanoconfined T4L are generally featured with slow-motional-like lineshapes, which exhibit anisotropy and multiple narrow (better resolved) peaks. The spectra can therefore be easily separated into two distinct components by the spectral peaks, characterized by large differences in both rotational diffusion rate and molecular ordering as demonstrated from the theoretical analysis. The Mb component is shown to be correlated with LBF of buried sites (Fig. 4B). The Im component, which is dominant in population throughout the temperature range studied, is shown to reflect the extent of how the reorientation of the spin label side chain is restricted by the local environment. Generally, the constraints on the side chain dynamics by the local environment include the interaction with nearby residues and the slow hydration dynamics due to the nanoconfinement. This study suggests that the effect from the hydration dynamics is a dominant factor in the spectra of nanoconfined T4L, as the greater the solvent-exposed, the greater the constraint to the side chain motions (Fig. 3). The observed change for the Im (Fig. 3) is consistent with the expectation for the presence of nanoconfined surface hydration. The finding is also in a good agreement with the previous study that the R1 side chain is sufficiently sensitive to the dynamics of surface hydration on a nanoconfined polypeptide at subfreezing temperatures.17,37 As for the finding of the correlation between the Mb and LBF, it is in line with the previous result that the relatively mobile component in the ESR spectra of nanoconfined polypeptides (such as 26-aa-long α-helix, β-hairpin, or linear polyproline peptides) correlates highly with the characteristics of LBF of the peptides.14,15,17 Given that the Mb component is generally found to reflect the differences in the LBF of the nanoconfined proteins/peptides, it suggests that the Mb is not attributed to the presence of weakly immobilized protein/peptides in nanochannels. We should, however, emphasize that the correlation between the Mb and LBF can only be observed for buried sites in T4L in the present study. The interaction between protein and the inner surface of the MSU material is shown to be relatively trivial as demonstrated in our control experiments (Fig. S2). The two spectral


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components (alternatively, dynamic modes), Mb, and Im, are therefore assigned to the LBF of buried sites and the local hydration dynamics in T4L, respectively. Challenges in the study of protein dynamics by ESR. Below, we briefly summarize the status of the protein dynamics study by ESR and how our approach can benefit the field. Site-directed spin-labeling ESR is a general method for investigating structural dynamics and local ordering in proteins.38 A general strategy of the method is to introduce a nitroxide-based side chain (e.g. R1 side chain) at selected sites in a protein using cysteine-substitution mutagenesis so as to probe local environments. By analyzing a wealth of information in the ESR spectral lineshape, one can derive dynamic valuables (e.g. rotational diffusion rates and molecular ordering) that characterize the local environment of the side chain. It has been previously demonstrated that the mobility information can be obtained from either theoretical analysis using the sophisticated SLE-based methods or semi-empirical analysis of the nitroxide spectrum.39,40 The side-chain mobilities, reflected in the ESR spectral lineshapes, provide a fingerprint of the protein dynamics. Specifically, the lineshape-derived mobility information has proven to be a convenient measure of LBF, particularly when the inter-helical interactions of particular R1 rotamers with neighboring side chains are insignificant and the local solvent accessibility differs little between spin-labeled sites. Studies that fulfill the conditions are polypeptide chains, which exhibit only one or two secondary structures of a simple fold.38,40,41 When the labeling sites are everywhere (including positions in buried, solvent exposed, loop, and tertiary contact regions, e.g., the case of the present study) in a protein, the connection between the mobility information of a nitroxide side chain and the LBF is compromised. When this is a case, changes in the ESR lineshape are attributed to not only the LBF but also the differences in local solvent accessibility, tertiary contacts between nearby residues, and global tumbling motions. It is commonly observed that the Hubbell plot (i.e., a correlation plot of the linewidth mobility and the second moment of ESR spectra) provides a discrimination between residues belonging to a loop, helix surface, tertiary interactions, and buried regions, but it provides little information about the LBF of a protein.19,40,42 To overcome the difficulty, it is necessary to employ multifrequency ESR spectroscopy together with even more sophisticated SLE-based theoretical models (e.g., the slowly relaxing local structure model) to discriminate between different dynamic modes reported in the multifrequency ESR spectra. A convenient approach for applying the methodology to protein dynamics is still under development.



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An improvement by the combined method of ESR and nanochannels. The present study has provided a complement to the existing cw-ESR method for studying protein dynamics. Below, we show how easily the mobility information of a side chain buried within T4L is compromised by the conformational complexity of T4L and how such a situation can be alleviated by studying protein dynamics under nanoconfinement. Figures 5A and 5B show correlation plots of the semiquantitative measure of nitroxide mobility (i.e., the inverse of the width of the ESR central resonance line, ∆H0-1) versus B factor of the buried sites for the spectra obtained in solution and under nanoconfinement, respectively. Although sites 129 and 133 are within the same short helix and that both of them are buried in T4L and characterized by high B-factor values (> 60 Å2), they are largely different in the value of ∆H0-1 for the solution result; the measure of the nitroxide mobility shows weak correlation with B factor (Fig. 5A). It shows that in the presence of tertiary contacts, the nitroxide R1 side chain often makes weak interactions with other groups in the protein and the interaction is often within the ESR time scale. As a result, the ESR data obtained from bulk solution is not necessarily correlated with LBF. For the result of nanoconfined T4L (Fig. 5B), the mobility shows an improved correlation with B factor; the mobility extracted from the Mb of the nanoconfined T4L spectra is better

Figure 5. (A) Correlation plot of the measure of nitroxide mobility (∆H0-1) and the B factor of the spectra from the bulk solution study. All of the sites shown belong to the buried site group. (B) The same correlation plot, as defined in (A), for the spectra from the nanoconfined T4L study. The mobility (∆H0-1) is derived from the Mb component of the spectra. A positive correlation between the mobility and B factor is observed. The Pearson’s correlation coefficient increases from 0.42 (the bulk solution study) to 0.57 (the nanochannel study). (C) Illustration for extracting central linewidth (∆H0) from a typical spectrum in a bulk solution study. The spectrum shown is 133R1 in a bulk solution (with 30% glycerol as a viscosity reagent) at 300 K. (D) Illustration for extracting central linewidth (∆H0) from a typical spectrum in the nanochannel study. The spectrum shown is 133R1 under nanoconfinement at 300 K. All of the nanoconfined spectra are characterized by the distinct splitting in the lower part of the central peak. This feature makes it convenient to obtain the linewidth of the Mb from experimental data.


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consistent in trend with the B-factors of X-ray crystallography data. This improvement, which is made possible by the use of nanoconfinement, allows one to perform the SLE-based theoretical analysis of the spectra (cf. the result for the Mb component of buried sites in Fig. 4B) to further resolve the local backbone dynamics of buried sites. Figures 5C and 5D illustrate how the semiquantitative measure of nitroxide mobility can be obtained from an experimental spectrum. Information of LBF for buried sites in T4L can be conveniently obtained using the combined method of ESR and nanochannels even at room temperatures. Due to that proteins are trapped in the nanochannels, it is reasonable to see the spectra are dominated by the Im component throughout the temperature range studied. We consider being able to study at room temperatures is an advantage of our combined approach as the classical use of spin-label ESR requires one to study protein dynamics at lower temperatures to remove the unwanted global tumbling motions from the spectrum. The study approach combining ESR and nanochannels provides a great complement to the classical use of the solution spin-label ESR. As the nanochannel of mesoporous material is useful to protect proteins against denaturing conditions (such as unfavorable solution pH and ionic strength conditions), it has been used to modulate catalytic activity of an enzyme. Several studies have reported an enhancement in enzyme activity upon the encapsulation/adsorption into mesoporous materials.1,43 Despite of the success, it remains to be explored how the dynamics of the adsorbed protein, which is relevant to protein activity, is affected by the confinement and how the resulting change in dynamics leads to the change in enzymatic activity. Our study not only improves the ability of spin-label ESR in probing local dynamics of buried sites at room temperatures, but also provides a useful tool for exploring site-specific dynamics of a protein when confined/adsorbed inside nanochannels of mesoporous material. However, precaution is necessary when using this method for protein dynamics because the adsorption might alter activity and structure of the incorporated proteins and the problem is complex owing to the large number of rather weak interactions that determine the native protein folds and activity. Previously T4L, when adsorbed at solid surface such as quartz44 or silica nanoparticles45, was found to become partially unfolded and lose its enzymatic activity, but the present study indicates that T4L retains its conformation when adsorbed inside nanochannels. Therefore, it is important to perform a careful inspection of the protein properties, when proteins are loaded onto surface of nanoparticles or into nanochannels, using the demonstration methods of the present study.



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Conclusion The large set of spin-labeled T4L mutants has provided enough sequence-specific environmental variables for one to deduce key features of the protein dynamics under nanoconfinement. When a protein is confined in nanochannels, its corresponding spectra are characterized by typical slow-motional lineshape, which is sensitive to dynamics within the slow-motional regime, and an improved spectral resolution, when compared to a spectrum from a bulk solution, even at room temperatures. As a result, prior to a sophisticated theoretical analysis, information concerning LBF of buried sites within a protein can be conveniently distinguished from other dynamic components and, therefore, assessed using the semiempirical measure of nitroxide mobility. This study has reported the results of the semiempirical and the SLE-based theoretical analyses of the T4L spectra for buried sites. The two results are consistent with each other, but the result of the SLE-based analysis provides more quantitative details concerning the local backbone and hydration dynamics. The molecular ordering S0 of the Im component is shown to identify the local hydration dynamics of specific sites in the protein fold. The dynamics of the Mb component is shown to correlate with the LBF of buried sites in T4L. We show that information of LBF in buried sites at room temperatures can be obtained by analyzing ESR spectra of a nanoconfined protein. Collectively, this study has demonstrated the feasibility of the combined methodology of ESR and nanochannels for investigating protein dynamics.

Associated Content Supporting Information. Figures S1 – S5 and Tables S1 – S2. This material is available free of charge via the Internet at http://pubs.acs.org. Author Information.

Corresponding author: [email protected]

Acknowledgements


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This work was supported by grants from the Ministry of Science and Technology of Taiwan (105-2628-M-007-005 and 104-2627-M-007-004). All of the CW/pulse ESR measurements were conducted in the Research Instrument Center of Taiwan located at NTHU. References (1) (2) (3) (4) (5)

(6) (7) (8) (9)

(10) (11) (12) (13) (14) (15)

Carlsson, N.; Gustafsson, H.; Thörn, C.; Olsson, L.; Holmberg, K.; Åkerman, B. Enzymes Immobilized in Mesoporous Silica: A Physical-Chemical Perspective. Advances in Colloid and Interface Science, 2014, 205, 339–360. Ravindra, R.; Shuang, Z.; Gies, H.; Winter, R. Protein Encapsulation in Mesoporous Silicate: The Effects of Confinement on Protein Stability, Hydration, and Volumetric Properties. J Am Chem Soc 2004, 126, 12224–12225. Vallet-Regi, M.; Balas, F.; Arcos, D. Mesoporous Materials for Drug Delivery. Angew Chem Int Ed 2007, 46, 7548–7558. Hartmann, M. Ordered Mesoporous Materials for Bioadsorption and Biocatalysis. Chem. Mater. 2005, 17, 4577–4593. Chen, Y.-P.; Chen, C.-T.; Hung, Y.; Chou, C.-M.; Liu, T.-P.; Liang, M.-R.; Chen, C.T.; Mou, C.-Y. A New Strategy for Intracellular Delivery of Enzyme Using Mesoporous Silica Nanoparticles: Superoxide Dismutase. J Am Chem Soc 2013, 135, 1516–1523. Urabe, Y.; Shiomi, T.; Itoh, T.; Kawai, A.; Tsunoda, T.; Mizukami, F.; Sakaguchi, K. Encapsulation of Hemoglobin in Mesoporous Silica (FSM) - Enhanced Thermal Stability and Resistance to Denaturants. Chembiochem 2007, 8, 668–674. Ikemoto, H.; Tubasum, S.; Pullerits, T.; Ulstrup, J.; Chi, Q. Nanoscale Confinement and Fluorescence Effects of Bacterial Light Harvesting Complex LH2 in Mesoporous Silicas. J Phys Chem C 2013, 117, 2868–2878. Bolivar, J. M.; Eisl, I.; Nidetzky, B. Advanced Characterization of Immobilized Enzymes as Heterogeneous Biocatalysts. Catal. Today 2016, 259, 66–80. Tu, J.; Boyle, A. L.; Friedrich, H.; Bomans, P. H. H.; Bussmann, J.; Sommerdijk, N. A. J. M.; Jiskoot, W.; Kros, A. Mesoporous Silica Nanoparticles with Large Pores for the Encapsulation and Release of Proteins. ACS Appl. Mater. Interfaces 2016, 8, 32211–32219. Xu, L. M.; Mallamace, F.; Yan, Z. Y.; Starr, F. W.; Buldyrev, S. V; Stanley, H. E. Appearance of a Fractional Stokes-Einstein Relation in Water and a Structural Interpretation of Its Onset. Nat Phys 2009, 5, 565–569. Huang, Y. W.; Lai, Y. C.; Tsai, C. J.; Chiang, Y. W. Mesopores Provide an Amorphous State Suitable for Studying Biomolecular Structures at Cryogenic Temperatures. Proc. Natl. Acad. Sci. U.S.A. 2011, 108, 14145–14150. Lai, Y.-C.; Chen, Y.-F.; Chiang, Y.-W. ESR Study of Interfacial Hydration Layers of Polypeptides in Water-Filled Nanochannels and in Vitrified Bulk Solvents. PLoS One 2013, 8. Tsukahara, T.; Hibara, A.; Ikeda, Y.; Kitamori, T. NMR Study of Water Molecules Confined in Extended Nanospaces. Angew Chem Int Ed 2007, 46, 1180–1183. Sung, T.-C.; Chiang, Y.-W. Identification of Complex Dynamic Modes on Prion Protein Peptides Using Multifrequency ESR with Mesoporous Materials. Phys Chem Chem Phys 2010, 12, 13117–13125. Huang, Y. W.; Chiang, Y. W. Spin-Label ESR with Nanochannels to Improve the Study of Backbone Dynamics and Structural Conformations of Polypeptides. Phys 19 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(16)

(17) (18) (19) (20) (21) (22) (23) (24) (25) (26) (27) (28) (29) (30) (31) (32)

Chem Chem Phys 2011, 13, 17521–17531. Yang, C.; Lo, W.-L.; Kuo, Y.-H.; Sang, J. C.; Lee, C.-Y.; Chiang, Y.-W.; Chen, R. P.Y. Revealing Structural Changes of Prion Protein during Conversion from α-Helical Monomer to β-Oligomers by Means of ESR and Nanochannel Encapsulation. ACS Chem Biol 2015, 10, 493–501. Tsai, C.-J.; Chiang, Y.-W. Effects of Anisotropic Nanoconfinement on Rotational Dynamics of Biomolecules: An Electron Spin Resonance Study. J Phys Chem C 2012, 116, 19798–19806. Vinu, A.; Murugesan, V.; Hartmann, M. Adsorption of Lysozyme over Mesoporous Molecular Sieves MCM-41 and SBA-15: Influence of pH and Aluminum Incorporation. 2004. Mchaourab, H. S.; Lietzow, M. A.; Hideg, K.; Hubbell, W. L. Motion of Spin-Labeled Side Chains in T4 Lysozyme, Correlation with Protein Structure and Dynamics. Biochemistry 1996, 35, 7692–7704. Arnold, G. E.; Ornstein, R. L. An Evaluation of Implicit and Explicit Solvent Model Systems for the Molecular Dynamics Simulation of Bacteriophage T4 Lysozyme. Proteins Struct. Funct. Genet. 1994, 18, 19–33. Schneider, B.; Gelly, J. C.; de Brevern, A. G.; Černý, J. Local Dynamics of Proteins and DNA Evaluated from Crystallographic B Factors. Acta Crystallogr. D. Biol. Crystallogr. 2014, 70, 2413–2419. Li, D.-W.; Brüschweiler, R. All-Atom Contact Model for Understanding Protein Dynamics from Crystallographic B-Factors. Biophys J 2009, 96, 3074–3081. Haliloglu, T.; Bahar, I. Structure-Based Analysis of Protein Dynamics: Comparison of Theoretical Results for Hen Lysozyme with X-Ray Diffraction and NMR Relaxation Data. Proteins 1999, 37, 654–667. Borbat, P. P.; Mchaourab, H. S.; Freed, J. H. Protein Structure Determination Using Long-Distance Constraints from Double-Quantum Coherence ESR: Study of T4 Lysozyme. J Am Chem Soc 2002, 124, 5304–5314. Pannier, M.; Veit, S.; Godt, A.; Jeschke, G.; Spiess, H. W. Dead-Time Free Measurement of Dipole-Dipole Interactions between Electron Spins. J Magn Reson 2000, 142, 331–340. Chiang, Y. W.; Borbat, P. P.; Freed, J. H. The Determination of Pair Distance Distributions by Pulsed ESR Using Tikhonov Regularization. J. Magn. Reson. 2005, 172, 279–295. Chiang, Y.-W.; Borbat, P.; Freed, J. H. Maximum Entropy: A Complement to Tikhonov Regularization for Determination of Pair Distance Distributions by Pulsed ESR. J. Magn. Reson. 2005, 177, 184–196. Schneider, D. J.; Freed, J. H. Spin Relaxation and Motional Dynamics. Adv. Chem. Phys. 1989, 73, 387–527. Budil, D. E.; Lee, S.; Saxena, S.; Freed, J. H. Nonlinear-Least-Squares Analysis of Slow-Motion EPR Spectra in One and Two Dimensions Using a Modified LevenbergMarquardt Algorithm. J Magn Reson A 1996, 120, 155–189. Lai, A. L.; Freed, J. H. HIV gp41 Fusion Peptide Increases Membrane Ordering in a Cholesterol-Dependent Fashion. Biophys J 2014, 106, 172–181. Ge, M.; Freed, J. H. Two Conserved Residues Are Important for Inducing Highly Ordered Membrane Domains by the Transmembrane Domain of Influenza Hemagglutinin. Biophys J 2011, 100, 90–97. Chiang, Y.-W.; Otoshima, Y.; Watanabe, Y.; Inanami, O.; Shimoyama, Y. Dynamics and Local Ordering of Spin-Labeled Prion Protein: An ESR Simulation Study of a Highly PH-Sensitive Site. J Biomol Struct Dyn 2008, 26, 355–365. 20 ACS Paragon Plus Environment

Page 20 of 22

Page 21 of 22

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(33) (34) (35) (36) (37) (38)

(39) (40) (41) (42) (43) (44) (45)

Zhang, Z.; Fleissner, M. R.; Tipikin, D. S.; Liang, Z.; Moscicki, J. K.; Earl, K. A.; Hubbell, W. L.; Freed, J. H. Multifrequency Electron Spin Resonance Study of the Dynamics of Spin Labeled T4 Lysozyme. J Phys Chem B 2010, 114, 5503–5521. Liang, Z. C.; Lou, Y.; Freed, J. H.; Columbus, L.; Hubbell, W. L. A Multifrequency Electron Spin Resonance Study of T4 Lysozyme Dynamics Using the Slowly Relaxing Local Structure Model. J Phys Chem B 2004, 108, 17649–17659. Meirovitch, E.; Nayeem, A.; Freed, J. H. Analysis of Protein Lipid Interactions Based on Model Simulations of Electron-Spin Resonance-Spectra. J Phys Chem 1984, 88, 3454–3465. Kaieda, S.; Halle, B. Internal Water and Microsecond Dynamics in Myoglobin. J Phys Chem B 2013, 117, 14676–14687. Kuo, Y.-H.; Tseng, Y.-R.; Chiang, Y.-W. Concurrent Observation of Bulk and Protein Hydration Water by Spin-Label ESR under Nanoconfinement. Langmuir 2013, 29, 13865–13872. Altenbach, C.; López, C. J.; Hideg, K.; Hubbell, W. L. Exploring Structure, Dynamics, and Topology of Nitroxide Spin-Labeled Proteins Using Continuous-Wave Electron Paramagnetic Resonance Spectroscopy. In Methods in Enzymology; 2015; Vol. 564, pp. 59–100. Hubbell, W. L.; Mchaourab, H. S.; Altenbach, C.; Lietzow, M. A. Watching Proteins Move Using Site-Directed Spin Labeling. Structure 1996, 4, 779–783. Columbus, L.; Hubbell, W. L. A New Spin on Protein Dynamics. Trends Biochem. Sci. 2002, 27, 288–295. Columbus, L.; Hubbell, W. L. Mapping Backbone Dynamics in Solution with SiteDirected Spin Labeling: GCN4-58 bZip Free and Bound to DNA. Biochemistry 2004, 43, 7273–7287. Chan, C.-H.; Tsai, C.-J.; Chiang, Y.-W. Side-Chain Packing Interactions Stabilize an Intermediate of BAX Protein against Chemical and Thermal Denaturation. J. Phys. Chem. B 2015, 119, 54–64. Lynch, M. M.; Liu, J.; Nigra, M.; Coppens, M.-O. Chaperonin-Inspired pH Protection by Mesoporous Silica SBA-15 on Myoglobin and Lysozyme. Langmuir 2016, 32, 9604–9610. Kerstin Jacobsen, W. L. H. O. P. E. T. R.; Jacobsen, K.; Hubbell, W. L.; Ernst, O. P.; Risse, T. Details of the Partial Unfolding of T4 Lysozyme on Quartz Using SiteDirected Spin Labeling. Angew Chem Int Ed 2006, 45, 3874–3877. Pan, Y.; Neupane, S.; Farmakes, J.; Bridges, M.; Froberg, J.; Rao, J.; Qian, S. Y.; Liu, G.; Choi, Y.; Yang, Z. Probing the Structural Basis and Adsorption Mechanism of an Enzyme on Nano-Sized Protein Carriers. Nanoscale 2017, 9, 3512–3523.



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Study of Protein Dynamics under Nanoconfinement by Spin-Label

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