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* Department of Bioengineering and
Graduate Group in Biophysics, University of California at Berkeley, Berkeley, California 94720
Correspondence: Address reprint requests to Teresa Head-Gordon, E-mail: tlhead-gordon{at}lbl.gov.
| ABSTRACT |
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| INTRODUCTION |
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Experimental limitations for studying molecular events in the dynamics of protein water hydration arise from several factors. The highly dilute protein concentrations (required to avoid aggregation) used means that the hydration water dynamics are dominated by bulk water relaxation or diffusion timescales. In other cases the number of hydration waters or other specifics of their hydration sites cannot be directly measured or lack sufficient time resolution. Furthermore, unlike bulk water, or "crystal" waters that reside in specific locations in the protein interior, study of water dynamics near the protein is limited by the highly averaged information obtained over an inhomogeneous protein surface in various protein conformational states. We note that
5060% of a folded protein's surface is hydrophobic (Janin, 1999
). Thus, it is difficult to distinguish the contribution, for example, arising from a hydrophobic, hydrophilic, or aromatic site or between regions more or less exposed to the solvent. Russo et al. (2003)
have controlled for this protein surface inhomogeneity by characterizing the dynamics of the first interacting water near a homogeneous hydrophobic oligopeptide that adopts a ß-sheet conformation.
In this work we propose a complementary experimental quasielastic neutron scattering (QENS) and molecular dynamics simulation study of a greatly simplified protein model system that addresses some of these limitations. We consider the hydration water dynamics near N-acetyl-leucine-methylamide (NALMA), a hydrophobic amino acid side chain attached to a blocked polypeptide backbone, as a function of concentration between 0.5 and 2.0M. In previous work we have primarily focused on the structural organization of these peptide solutions and their connection to protein folding (Hura et al., 1999
; Sorenson et al., 1999
). Throughout the full concentration range of 0.52.0 M studied by x-ray scattering experiments and molecular dynamics simulations, we find that water stabilizes monodispersed and small clusters of amino acids, as opposed to more complete segregation of the hydrophobic monomers into a sequestered hydrophobic core (Hura et al., 1999
; Sorenson et al., 1999
), which defines the role of water in the later stages of folding. In this work we have performed QENS experiments on both the deuterated and nondeuterated leucine to isolate the hydration water dynamics from the solute motions. Furthermore, two sets of experiments were carried out using different incident neutron wavelengths to give two different time resolutions to separate rotational and translational motion of the hydration dynamics.
The NALMA-water system and the high quality QENS data provide a unique study for characterizing the dynamics of different hydration layers for a homogeneous solution of a hydrophobic side chain attached to its hydrophilic backbone. By analyzing the diffusion timescales at the highest concentration of 2.0 M, where our structural work indicates that NALMA solutes only have enough water to share one water hydration layer, and comparing it to more dilute concentrations of 0.5 M, where each solute has (in principle) enough water for
23 hydration layers of its own, permits us to cleanly separate inner sphere and outer sphere hydration dynamics, around a purely hydrophobic amino acid hydration site.
We report several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics that are tracked by the self-diffusion measured with QENS. The translational water dynamics of these biological solutions under ambient conditions are analyzed in a first approximation with a jump diffusion model and their rotation dynamics by diffusion on a sphere (Sears, 1996
). At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by long residential time and slow diffusion coefficients, similar to supercooled water at -10°C. The analysis of the more dilute concentration solutions has been performed taking into account the result of the 2.0-M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0-M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential times are converged to bulk-water values.
The clean separation of rotational and translational timescales allows us to define an experimental "elastic incoherent structure factor" (EISF) from the rotational motion, which can be interpreted as a measure of the fraction of hydrogens whose rotational dynamics is faster or slower than our experimental resolution of 1.05.5 ps (Bellissentfunel et al., 1992; Zanotti et al., 1997
). The EISF shows significant evolution between 0.5 and 2.0 M; the EISF for the 0.5 M solution measures 37% immobile hydrogen, whereas 17% of the protons are not observed for the 2.0 M concentration. The EISF results are supported by MD simulations, in which the highest concentration has fewer waters with longer rotational relaxation times than that observed for the lowest concentration. The MD results also measure specific first layer water residence times and rotational dynamics near hydrophobic and hydrophilic sites. We see spatially heterogeneous dynamics in that water near the hydrophilic backbone is
34 times slower than waters that reside near the hydrophobic side chain.
This study of the NALMA water solution, and future work that will analyze dynamics near homogeneous hydrophilic and aromatic amino acid monomers, provides an important dissection of hydration dynamics near inhomogeneous protein surfaces. We discuss the implications of the dynamics measured on our model system and its possible connection to supercooled liquids (Angell, 1995
; Ediger et al., 1996
; Green et al., 1994
), protein function (Barron et al., 1997
; Bellissent-Funel, 2000
; Bizzarri and Cannistraro, 2002
; Bu et al., 2000
; Denisov et al., 1999
; Tournier et al., 2003
), and protein-protein interfaces (Bizzarri and Cannistraro, 2002
).
| EXPERIMENTAL PROCEDURES |
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The quasielastic neutron scattering experiment was performed at the National Institute of Standards and Technology Center for Neutron Research, using the disk chopper time-of-flight spectrometer (DCS). To separate the translational and rotational components in the spectra, two sets of experiments were carried out using different incident neutron wavelengths of 7.5 Å and 5.5 Å to give two different time resolutions. The DCS spectrometer operating at the high-resolution range of
= 7.5 Å with an incident energy of Einc = 1.45 meV, gives a wave vector range of 0.146 Å-1 < Q < 1.574 Å-1 and an energy resolution of 35 µeV at full width half-maximum (FWHM). At the lower resolution,
= 5.5 Å and Einc = 2.7 meV, with the wave vector range covering 0.199 Å-1 < Q < 2.147 Å-1 with a FWHM of 81 µeV.
The sample containers were two concentric cylinders with radius differing by 0.1 mm for the Leu(D): H2O sample. All the spectra were measured at room temperature, and the data collection lasted for
610 h depending on the resolution and sample. The spectra were corrected for the sample holder contribution. Detector efficiencies, energy resolution, and normalization are measured with standard vanadium. The resulting data were analyzed with DAVE programs (http://www.ncnr.nist.gov/dave/). The data have been corrected for the buffer contribution, and we neglect the contribution from the structure factor in the analysis of the spectra.
Experimental analysis
The experimental quantity measured during a quasielastic neutron experiment is the differential cross section, defined as the number of neutrons with a transfer energy dE, scattered into a solid angle d
(Bee, 1988
). The incoherent differential cross section can be experimentally determined as:
![]() | (1) |
is the total incoherent cross section, ki and ks are the wave vector of the incident and scattered neutron, Q is the momentum transfer,
is the frequency, and Sinc(Q,
) is the incoherent dynamic structure factor. The fit to the experimental data generated at all resolutions used a combination of Lorentzian functions convoluted with the instrumental resolution. The success of the proposed experimental analysis procedure for the hydration dynamics lies in performing two identical experiments corresponding to two different resolutions. The high-resolution spectra better characterizes motion arising from translational water diffusion. In the other set of lower-resolution experiments, both translational and rotational contributions are significant. However, because the width of the sharp Lorentzian due to translation is previously determined with accuracy as a function of Q, it is introduced in the Lorentzian fit, favoring the evaluation of the other (rotational) parameters. The compatibility of the low-resolution fit with the high-resolution spectra is then cross-checked, and found to be consistent in our work. Based on those fits we were able to further interpret the data using the following analytical models traditionally applied to liquids (Bee, 2003
Sinc(Q,
) can be expressed as a convolution of three terms:
![]() | (2) |
The translational incoherent dynamic structure factor can be described as:
![]() | (3) |
trans is the halfwidth at half-maximum of a Lorentzian function (Bee, 1988
0 for one site in a given network before jumping to another site (Egelstaff, 1992
![]() | (4) |
and Dtrans is the translational diffusion coefficient between two sites.
The simplest model of internal rotational motion of a molecule corresponds to a random motion of protons on the surface of a sphere (Sears, 1966
). The rotational incoherent dynamic structure factor is:
![]() | (5) |
rot = 2Drot, which corresponds to a rotational characteristic time of
Rotation = 1/6Drot.
The first term in Eq. 5 corresponds to the form factor of the restricted volume explored by the hydrogen atoms, known as the "elastic incoherent structure factor." Experimentally, the EISF is defined as Ielast(Q)/[Ielast(Q)+Iquasielast(Q)], where Ielast(Q) and Iquasielast(Q) are the integrated elastic and quasielastic scattering, respectively. This can be seen if we convolute Eq. 3 with Eq. 5 for l = 1 so that Eq. 2 becomes
![]() | (6) |
Theoretical procedure
Analysis of the QENS experiments for aqueous NALMA solutions were aided by molecular dynamics simulations. Various representative solute configurations: dispersed, small molecular aggregates, and fully clustered as described in Hura et al. (1999)
. Solute configurations at all concentrations were prepared as maximally dispersed as described in Hura et al. (1999)
and Sorenson et al. (1999)
. These configurations were equilibrated for 75 ps before any statistics were collected.
The AMBER force field due to Cornell et al. (1995)
and the SPCE water models (Berendsen et al., 1987
) were used for modeling the NALMA solute and water, respectively. The simulations were carried out at 298 K in the NVT-ensemble using velocity Verlet integration, velocity rescaling, with a time step of 1.5 fs. Each simulation was equilibrated for 0.1 ns and statistics were gathered over the remaining 0.65 ns, sampled every 100 fs. Ewald sums were used for calculation of the long-range Coulomb forces.
was set to 6.4/L where L is the length of the simulation box and a total of 2 x 292 k-vectors were used (|kmax|2 = 26). Rigid-body dynamics for the water solvent were integrated using RATTLE (Anderson, 1983
).
For the analysis of the water dynamics in the NALMA aqueous solutions, we performed simulations of a dispersed solute configuration consistent with our structural analysis (Hura et al., 1999
; Sorenson et al., 1999
). We used the Einstein relation to derive the translational self-diffusion coefficients from the mean square displacement of water oxygens, and the rotational dynamics using the orientational autocorrelation function:
![]() | (7) |
(t) measures the angle between the dipole vector of the water molecule at times t and 0. To analyze the EISF results, we also evaluated an average residence time of water molecules that maintained a distance of 4.0 Å or less from the branching carbon center of the hydrophobic side chain, and within 4.0 Å of one of the backbone carboxyl oxygens of the NALMA molecule. We also calculate the rotational dynamics of that subset of water molecules maintaining twice that residence time using Eq. 6. | RESULTS |
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trans(Q) with Q2 (Fig. 4) at all solute concentrations. The resulting diffusion coefficient, Dtrans, and residential time
0 obtained for each concentration are reported in Table 1. It is evident that by increasing the NALMA concentration, the
trans(Q) exhibits an increasingly pronounced plateau at high Q-values, which translates to a longer residential time, whereas at the smallest Q-values the marginal slope reflects a smaller diffusion coefficient value. At the higher NALMA concentrations the dynamics are substantially suppressed, approaching values more typical of a supercooled water diffusion coefficient and corresponding long residential time. The corresponding molecular dynamics simulation quantities of Dtrans for water are in qualitative agreement with experimental trend over the entire concentration range studied (Table 1), although the MD evaluated diffusion constants are systematically slower than that derived from analytical fits to the experimental data.
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25 waters around the NALMA is completely described by the analysis of the 2.0-M data, it may be possible to characterize the dynamical behavior of the outer hydration sphere separately using the 1-M data. The analysis is comprised of subtracting the data with the 2.0-M translational linewidths as known values, leaving the remaining data to be fit by two free Lorentzian functions. In Fig. 5 a we show the new
trans inferred from this analysis in comparison with the 0.5-M and 1-M halfwidth obtained with the standard analysis. The new translational dynamics for 1.0 M is quite similar to the 0.5-M hydration water dynamics, with a translational diffusion coefficient of the same order of magnitude but with a longer residential time. In Fig. 5 b we show the reanalyzed 0.5-M data by taking into account the results of the 2.0-M data, exactly in the manner in which we reanalyzed the 1.0-M data. Together the 0.5-M and 1.0-M data results show that the translational dynamics of the outer sphere hydration layer(s) of water are in themselves perturbed from bulk-like water dynamics.
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rot is clearly independent of Q and shows small error. The
rot is 0.1 meV for these highest concentrations, which corresponds to a rotational relaxation time of
2.2 ps, longer than that of bulk water and consistent with the suppressed translational dynamics seen for the high-concentration solutions. However, the linewidth of the broader Lorentzian for the 1.0-M and 0.5-M data gives a larger error in the fit to the intensity data, which therefore will be better analyzed with the low-resolution data.
Low-resolution experiment
The data from the low-resolution runs were analyzed by including the narrow translational Lorentzian functions based on the high-resolution experiment as known values. The remaining motion is due to rotation, and we plot the resulting
rot as a function of concentration in Fig. 6. The characteristic
rot of the hydration water at 2.0 M and 2.3 M measured at low resolution shows the proper lack of Q-dependence with an average value equal to 0.1 meV, a value that is consistent with the high-resolution analysis (Table 1). In this particular case, the best fit has been obtained by including a third Lorentzian function, the l = 2 term in Eq. 5; only when the data are of high quality can we resolve terms where l > 1.
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rot appears to increase for Q2 > 2.0, suggesting that a small translational component is present in the low-resolution data. In this case we introduce a third Lorentzian function, corresponding to the 2.0-M translational water dynamics, as a model of the first hydration shell at more dilute NALMA concentrations. Once the translational dynamics of the first hydration layer is subtracted, the remaining signal gives a broad linewidth that is independent of Q, with a mean value of 0.22 MeV for both the 1.0-M and 0.5-M data, which corresponds to a characteristic rotational relaxation time of 1 ps (Table 1). The intensity modeled in this way correctly gives translation and rotation functions that follow j0(Qa) and j1(Qa) behavior, respectively, whereas the intensity of the third Lorentzian is independent of Q with small amplitude. Again we see that molecular dynamics estimates of rotational dynamics qualitatively support the experimental values obtained over the full concentration range (Table 1).
Fig. 7 presents the hydration water EISF variation as a function of NALMA concentration. It is possible to estimate from the experimental EISF the fraction of hydration atoms that is rotationally "immobile", i.e. hydrogen motions that are faster or slower than the experimental resolution (Bellissentfunel et al., 1992; Zanotti et al., 1997
). In this experiment, the EISF is the elastic term of the rotational motion in Eq. 5, for which we only observe rotational motions on timescales between 1 and 5.5 ps. For the total intensity we do not take into account intensity arising from the translational motion analyzed from the 2.0-M contribution to the 1-M and 0.5-M spectra. The EISF shows a significant evolution between the 0.5-M and the 2.0-M concentrations. The EISF shows a significant evolution between the 0.5 M and the 2.0 M concentrations. At 0.5 M the percentage of immobile hydrogen is 37%, while 17% is observed to be outside the experimental resolution at 2.0 M.
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3.54.0 ps near the hydrophobic side chain, whereas it is
10.010.5 ps near the hydrophilic site (Table 2). For 0.5 M there were
270 water molecules per solute with the average residence time or longer over the length of the 2.15-ns simulation, whereas for 2.0 M there are only
55 water molecules per solute with the average residence time (Table 2).
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5 ps) near the hydrophilic site, and a faster rotational timescale (
2 ps) near the hydrophobic site (Table 2). The 0.5 M P2(t) data were fit with two exponentials, but fixing one exponential to that determined from the 2 M data at each of the two sites. The second exponential for the 0.5 M data for both sites corresponds to 1.0 ps (Table 2). A stretched exponential model, exp(-t/
)ß, also provided a good fit to the autocorrelation function of the 2-M data as well as the 0.5-M data, with a ß-exponent value between 0.4 and 0.6. This complementary analysis confirms that over the full range of NALMA concentration there is a distribution of rotational timescales.
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NALMA (leucine) dynamics
We first analyze the leucine dynamics by fitting the data with one Lorentzian function. The translational linewidth at halfwidth half-maximum,
(Q), is represented in Fig. 9 a for all concentrations; its dependence on Q follows to a reasonable approximation the hydrodynamic regime behavior, yielding a diffusion coefficient value that ranges between 3.1 and 3.6 x 10-6 cm2/s, and therefore roughly constant over the full concentration range (Table 1). In the observed dynamical range of the experiment only the random walk is observed, and to isolate the side-chain movement from the Brownian diffusion another instrumental resolution would be needed. From the diffusion coefficient, measured at the lowest concentration, a value of 6 Å has been extracted for the hydrodynamic radius. Molecular dynamics simulations show quantitative agreement in the evaluated NALMA translational diffusion constants at the lowest concentration but deviates from the experimental 2.0-M data. (Table 1).
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0.8 Å-1, consistent with the x-ray diffraction data. Because our analysis of the integrated intensity shows that the peak cannot be isolated from an elastic component, it suggests that a collective dynamical component is present. In the same figure, we plot
(Q) x Q2 versus Q, in which we observe a deviation from the expected independence of Q, and showing a corresponding weak minimum in
(Q) x Q2 at the same wave vector as the maximum in the integrated intensity. Thus the NALMA dynamics are consistent with "de Gennes narrowing" (de Gennes, 1959
Given the presence of the coherent dynamics contribution to the leucine dynamics spectra, and the simulated self-diffusion coefficient of 1.0 x 10-6 cm2/s, a different analysis strategy has been used. The analysis has been performed by fitting the data with three Lorentzian functions, without subtracting the aqueous D2O background. We impose the
trans(Q) consistent with the molecular dynamics simulation, and we leave the remaining Lorentzians free to fit the remaining buffer contribution and possibly the coherent contribution, presented in Fig. 9 c. The detected buffer dynamics contribution is in excellent accord with our previous hydration water dynamics results for the 2-M deuterated NALMA (Fig. 4), whereas the second free Lorentzian is very broad and presents two minimums at
0.8 Å-1 and
1.1 Å-1. The HWHM of the second Lorentzian is very broad and too noisy; it is only an alternative analysis, and is the most that we can extrapolate from this data.
An important corollary that emerges from the integrated QENS intensity, which exploits scattering contrast to isolate the NALMA correlations, is further support that the structural organization of the leucines in solution is identical over the full concentration range from 0.5 to 2.0 M, something that was not fully resolvable by diffraction at the lower concentrations. This implies that at 0.5 M and 1.0 M, the NALMA organizes into water-penetrated clusters, and therefore their first hydration layer dynamics can be analyzed in terms of the dynamics of the 2.0-M data.
| CONCLUSION |
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-10°C). The second component arises from outer layer(s) water dynamics, which exhibits bulk water rotational motion times, and faster translational dynamics than the first hydration layer, but which does not fully recover to room temperature "bulk-like" translational diffusion values. We also find evidence of collective motion of the NALMA solutes that is consistent with de Gennes narrowing, with a self-diffusion constant that is almost an order of magnitude slower than accompanying hydration dynamics. An additional goal of this work is to precisely study water dynamics as a function of its location in a situation better defined and less complex than a protein. We note that a folded protein's surface is roughly equally distributed between hydrophobic and hydrophilic domains, whose length scales are on the order of a few water diameters, and which justify our study of hydration dynamics of the simple NALMA system with both hydrophilic and hydrophobic regions. The systematic study of the NALMA water hydration dynamics provides an important dissection of hydration dynamics near inhomogeneous protein surfaces, with implications for supercooled liquids, protein folding and function, and protein-protein interfaces. Given these caveats of our simplified model protein, we provide comment and contrast to hydration dynamics observed near real proteins surfaces.
Until a critical hydration level is reached, proteins do not function (Rupley and Careri, 1991
). This critical level of hydration is analogous to a similar lack of protein function observed for temperatures below a dynamical temperature range of 180220 K that also is connected to the dynamics of protein surface water (Doster and Settles, 1998
; Rupley and Careri, 1991
). Restoration of some enzymatic activity is observed in partially hydrated protein powders, sometimes corresponding to less than a single hydration layer on the protein surface, which indicates that the dynamical and structural properties of the surface water is intimately connected to protein stability and function (Bellissent-Funel, 2000
; Bizzarri and Cannistraro, 2002
; Careri and Peyrard, 2001
; Dellerue and Bellissent-Funel, 2000
; Denisov and Halle, 1996
; Denisov et al., 1999
; Halle and Denisov, 1995
; Mattos, 2002
; Otting, 1997
; Tarek and Tobias 1999
, 2000
, 2002
; Zanotti et al., 1999
). The molecular mechanism of the solvent motion that is required to instigate the protein structural relaxation above a critical hydration level or transition temperature has yet to be determined.
We focus our QENS and MD results of hydration dynamics near a model protein surface on the issue of how enzymatic activity might be restored once a critical hydration level is reached, and provide a hypothesis for the molecular mechanism of the solvent motion that is required to trigger protein structural relaxation when above the hydration transition. Below the critical hydration level, as measured by 2.0 M water dynamics, we find that the water translational and rotational dynamics are slow. Some hydration waters are tightly bound to the surface, especially near hydrophilic regions, and their slow dynamics suggest a large barrier to rearrangement with other waters, which would primarily be lateral across the peptide or protein surface. At sufficiently high levels of hydration, as measured by the 0.5 M dynamics, we find that the inner sphere water translational and rotational dynamics are still slow (equivalent to 2.0 M), but that the barrier to exchange with other waters is apparently lower, with diffusion timescales between inner and outer sphere regions approaching more bulk-like values. Therefore we might view the catalyzing effect of "sufficient" water on side-chain rearrangement on the protein surface (that is necessary for protein folding or function) as arising from a second hydration layer that lowers the barriers for water solvent rearrangement, i.e., restoration of the plasticity of the water network itself.
There is greater uncertainty in the literature about how much the dynamics of outer hydration layers are perturbed by the protein interface, with some studies supporting the view that the outer layer dynamics have recovered bulk-like water dynamics, whereas other analysis suggest perturbations well into the second or third layer. Recent work has supported the provocative suggestion that outer layer dynamics are up to 50 times slower than inner protein layer dynamics, and might support "slip streams" for ligand or metabolite diffusion to relevant protein active sites. Our results find faster water diffusion in outer hydration layers relative to the first hydration level, but still suppressed with respect to bulk-like values, whereas rotational motions in outer layers are fully recovered to bulk water values. Due to the high density of molecules within the cell, there can on average only be two to three hydration layers between proteins (Mentre, 2001
). We do see spatially heterogeneous dynamics at all hydration levels we have examined that might have functional importance in the crowded cell or at a protein-protein interface. Perhaps analysis of hydrophilic and hydrophobic patterns on protein surfaces should be analyzed for "slip streams" into active sites (our results suggesting that one follow hydrophobic tributaries), or for protein-protein molecular recognition events involving arrested water motions to aid docking.
| ACKNOWLEDGEMENTS |
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We gratefully acknowledge the support of the National Institutes of Health (GM65239-01). This work utilized facilities supported in part by the National Science Foundation (under agreement number DMR-0086210). We acknowledge the support of the National Institute of Standards and Technology, U. S. Department of Commerce, in providing the neutron research facilities used in this work.
Submitted on August 19, 2003; accepted for publication November 20, 2003.
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