Tyrosine as a Non-perturbing Site-Specific Vibrational Reporter for

Jun 7, 2017 - Sean C. Edington , Andrea Gonzalez , Thomas R. Middendorf , D. Brent Halling , Richard W. Aldrich , Carlos R. Baiz. Proceedings of the ...
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Tyrosine as a Non-Perturbing Site-Specific Vibrational Reporter for Protein Dynamics Farzaneh Chalyavi, David G. Hogle, and Matthew J. Tucker J. Phys. Chem. B, Just Accepted Manuscript • Publication Date (Web): 07 Jun 2017 Downloaded from http://pubs.acs.org on June 8, 2017

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Tyrosine as a Non-perturbing Site-specific Vibrational Reporter for Protein Dynamics Farzaneh Chalyavi, David G. Hogle, and Matthew J. Tucker* Department of Chemistry, University of Nevada, Reno, 1664 N. Virginia Street, Reno, NV 89557 (USA) ABSTRACT: The ability to detect changes in the local environment of proteins is pivotal to determining their dynamic nature during many biological processes. For this purpose, the utility of the tyrosine ring breathing vibration as a sensitive infrared reporter for measuring the local electric field in protein is investigated. Variations in the bandwidth of this vibrational transition in a variety of solvents indicate differences in microenvironment affect the inhomogeneous broadening and thus the frequency distribution. The ring mode is influenced by direct and indirect interactions associated with the charge distribution of the surrounding solvent molecules. Molecular dynamics simulations were implemented to obtain a correlation between the electric field induced by the solvent on the mode and the observed vibrational bandwidth. Moreover, Trp-cage was synthesized as a model peptide system to access the efficacy of the correlation to predict the electric field strength within the hydrophobic core of the native and denatured states of the protein. The 2D IR spectra of tyrosine in dimethyl sulfoxide (DMSO) and water (D2O) show a two-fold difference in the time constant of the vibrational dynamics alluding to the dephasing mechanisms of the vibration and supporting the model put forth about the solvachromatic nature of the transition.

28,29

Introduction Proteins and peptides rely on the roles of key sidechain interactions to provide stability in structure and overall func1–4 tion, such as the formation of strong hydrophobic cores or 5–7 Dynamic active a means of regulation as in ion channels. biomolecules exploit conformational changes and molecular interactions to perform their requisite biological functions. Both static and dynamic behavior is governed by subtle intramolecular interaction between side chain moieties. Understanding these processes via quantification of changes in local electric field within a protein requires a spectroscopic probe located within the region of the peptide where the action takes place. Generally, spectroscopic reporters/probes 8 allow detection of local conformations, different solvation 9 10 states, electrostatic interactions, and peptide or protein 1,11 dynamics. Examples of probes suitable for this task include the amide I and carboxylic acids for infrared spectros12,13 copy as well as arginine guanidyl modes, the aromatic amino acids for fluorescence spectroscopy and absorption 14 15 spectroscopy, and sulfur radicals for EPR spectroscopy. Vibrational spectroscopy is especially useful for studying changes in conformations and local environment dynamics of biological molecules by providing detailed information about sidechain and backbone conformations and their sur1,3,16,17 rounding environments. Both two dimensional infrared spectroscopy (2D IR) and IR spectroscopy have been employed in the determination of protein secondary structures via vibrational frequencies and overall line shapes of the am-1 16,18–21 ide I band (1600-1700 cm ). The ability of 2D-IR photon echo spectroscopy to obtain and 22,23 characterize ultrafast structural dynamics has been uti23 lized to uncover fast chemical exchange, energy transfer 24 23,25–28 within molecules, inter and intra-mode coupling, and

interactions of solvents and solute. In particular, 2D IR has captured molecular movies of the wiggling and jiggling 30 of HIV inhibitors in a binding pocket, protein conformation 31,32 changes due to mutations, 3D structures of a transmem27 brane helix dimer, and water flow within Influenza AM2 17 transmembrane channel, and even non-equilibrium dynam33 ics of peptides. 2D IR measurements of Ubiquitin and Ribonuclease A have utilized the amide I region to observe loss of β-sheet content and an increase in random coil structure after thermal un34 folding. Structural identification via the amide I transition 34 has also uncovered the presence of an α-helix in Myoglobin 34 and anti-parallel β-sheet in Concanavalin A. In another study, the ratio of β-sheet and random coil structures during the amyloid formation of human islet amyloid polypeptide 35 has also been detected. Although useful, one limitation of the broad amide I transition is that it does not capture local environmental or site–specific dynamics in the region where most peptide/protein activity transpires. Furthermore, while isotope labeling can shift the vibrational frequency of a single resonance to isolate specific backbone amide I transitions, the absorbance often is obscured by side chain absorp19 tions that spectrally overlap. For this reason, non-natural amino acid side chain probes, such as cyano-, azido-, isonitrile, selenocyanate and thiocyanate, have been developed to track the dynamics observed in 25,36–39 the sidechain region. The utility of these non-native probes have been extended to investigate dynamics both in 40,41 vivo and in vitro, specifically for capturing changes in local electric fields and degree of hydration at distinct loca1– tions in soluble proteins and membrane binding proteins. 4,9,42 Extrinsic probes have uncovered dynamics in active sites 1– of enzymes, binding to myoglobin, and amyloid formation. 4,10,35,40,42–45

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Although the utility of extrinsic probes have been established, an approach involving an intrinsic amino acid sidechain probe would avoid any unnecessary perturbations to the system, which would be of significant value in larger proteins. Tyrosine (Tyr) is a native amino acid, containing a phenyl sidechain, and it is found in many peptides and proteins. The tyrosine ring has been shown to have several ring breathing modes which can be detected in the infrared spec46 trum. One of these ring breathing modes, shown in Figure 1, has been identified as a potentially promising vibrational 47 reporter. Tyrosine is ubiquitous in protein systems and many times plays a pivotal role in several biological functions 48,49 The aromatic side chain of tyrosine is often and activities. involved in the gating mechanisms of membrane proteins as 48,50 well as the catalyst in enzymatic activity, and performs a major role in proton and electron transfer for different bio51,52 Using 2D IR spectroscopy, Ge logical reaction pathways. and coworkers measured spectral diffusion of several phenolic ring modes suggesting that the observed changes were related to hydrogen bonding interactions of the phenolic 47 hydroxyl group in bulk water. However, a model that correlates the Tyr ring mode with the local environment and/or electric field has yet to be realized. 53

Using Onsager field theory, past studies have established a relationship between the vibrational frequency and the calculated electric field only taking into account interactions due to the charge-dipole approximation. While showing a linear correlation between the frequency and field distribution, this model did not account for direct electrostatic interactions, such as H-bonding, limiting its success describing protic solvents. Using Molecular dynamic (MD) simulations 10,54 as well as linear stark spectroscopy, Boxer et al. established a new method for calculating the influence of the electric field on a vibration resulting from its local environment via its infrared spectrum, shown by the following formula:  ̂  =  , . ∆  

where ̅ ! is the observed vibrational frequency, ̅" is a reference frequency calibrated to zero electric field, ∆  is the magnitude of the probe’s difference dipole, which is defined by measuring the vibrational Stark effects and the  ̂  is sensitivity of vibrational shifts to electric field. . the electric field experienced by the vibration projected onto 10 the difference dipole vector, ∆ . Pazos and coworkers extended the method to determine electric field effects on the ester transitions by correlating the vibrational frequen4 cies within both protic and aprotic solvents. Others have shown such correlations between the electric field and the 10,55,56 frequency for other oscillators. Herein, we attempt to determine the sensitivity of the tyrosine ring breathing mode to capture changes in environment due to differences in electric field around the ring. A similar analysis as described above was performed to provide a correlation between a spectral feature of the infrared absorption of the tyrosine ring and the local electric field. The utility of the tyrosine ring mode as an electric field reporter for protein dynamics is established through changes in the vibrational bandwidth. This spectral bandwidth is known to capture the inhomogeneous broadening of vibrations. The observed differences in bandwidth were further examined via

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2D IR spectroscopy to assess the molecular interactions responsible for the spectral diffusion within two dynamically distinct local environments. To test the efficacy of our measured correlation to predicted electric field from the vibrational bandwidth, a model tyrosine containing miniprotein, Trp-cage, was synthesized and the changes in the electric field were monitored within the hydrophobic core of Trpcage in its native and denatured states.

Experimental Methods Materials. N-Acetyl L-Tyr amide (N-capped and C-capped) was obtained from Chem Impex International, Inc. Fmocamino acids was purchased from Advanced Chem Tech (CreoSalus). Guanidine Hydrochloride was purchased from the Fisher Scientific. Deuterium oxide was purchased from the Cambridge Isotope Laboratories, Inc. All organic solvents were purchased from the Fisher Scientific (HPLC grade) and were utilized without further purification. Sample Preparation. To determine the concentration of the samples, the absorption spectra were measured using a commercial dual-beam UV-Vis spectrophotometer (PerkinElmer Lambda 25). The desired pH, ranging from 7-12, of the tyrosine solutions was achieved by monitoring via a pH meter (Orion/Thermo Scientific). Trp-cage was synthesized by standard Fmoc solid-phase protocol on the aapptec Focus XC peptide synthesizer. The peptide was purified by reversephase HPLC with Vydac C18 column and characterized by Bruker MALDI-TOF mass spectrometry. FTIR Spectroscopy. All IR spectra were collected on a ThermoNicolet 6700 FTIR spectrometer, equipped with a liquid nitrogen cooled mercury cadmium telluride detector, -1 at 1 cm using a homemade two-compartment CaF2 sample cell with a 56µm Teflon spacer. The cell is divided into two compartments to collect IR measurements of the reference and the sample under similar experimental conditions. An automated translation stage moves the sample cell between the reference and the sample side collecting a single beam 57 spectrum for each side. For all the studies, tyrosine was utilized with the N-terminus acetylated and C-terminus amidated. The concentration was maintained at 20 mM for all samples corresponding to an OD ~0.04-0.05. 2D IR methods. Heterodyned spectral interferometry was utilized for obtaining the spectra. Fourier-transform limited 80 fs pulses with a central wavelength of 6591 nm were employed in the 2D IR experiments. Three ∼1 µJ laser pulses with wave vectors k1, k2, and k3 were incident to the sample generating a signal in the direction ks = −k1 + k2 + k3 with the ordering 123 (rephasing) and 213 (nonrephasing). To obtain absorptive spectra, the rephasing and nonrephasing 2D frequency spectra were properly phased and combined. To observe any changes in the spectral characteristics, the waiting time, T, between the second and third pulse was varied from 0 to 2 ps. After appropriate Fourier transforms along the coherence, τ, and detection, t, axes, the 2D IR spectra were 58 plotted as ωτ vs ωt. A ~40 mM solution of tyrosine in D2O with OD~0.09 and a ~90 mM solution of tyrosine in DMSO with OD~0.19 OD were utilized for the 2D IR experiment. Each sample was placed in a Harrick sample cell with CaF2 windows with a 56 µm spacer.

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Computational Methods. Gaussian09 density function theory (DFT) calculations of tyrosine with an acetylated Nterminus and an amidated C-terminus were performed using B3LYP/6-31+G** level of theory with implicit solvation model of water via the conducting polarizable continuum model (CPCM). Frequencies were obtained following structural optimization. Gaussian09 calculations were also performed with the same level of theory using a single explicit DMSO molecule or water molecule at various distances from the tyrosine ring to determine the overall effect on the vibrational frequency. MD simulations were performed using Nanoscale Molecular Dynamics (NAMD) 2.9 and force field parameters from CHARMM36 all-hydrogen topology and the CGenFF topology. 59 The tyrosine molecule was first immersed in a 30Å solvent box with periodic boundary conditions. Following an initial 2 ps equilibration run at 298 K and 1 atm in the NPT ensemble, a production run of 10 ns at 298 K in the NVT ensemble was then computed. The trajectory was saved every 500 fs, which resulting in a total of 20,000 frames. MD simulations were performed for the following solvent: water, methanol, dimethyl sulfoxide (DMSO), trifluoroethanol (TFE), diethyl ether (Et2O), acetonitrile (ACN), and chloroform (CHCl3). The subsequent electric field calculations were performed utilizing methods discussed further in the supporting information.

Results and Discussion Linear IR Spectroscopy. The infrared spectrum of the ring mode of the side chain of tyrosine in water exhibits one peak -1 in the spectral region between 1500 and 1700 cm (Figure 1). To confirm the identity of the transitions and determine the transition dipole strength, a Gaussian09 DFT frequency calculation using B3LYP/6-31+G** level of theory with an implicit solvation model of water was computed. Within the

Figure 1. Infrared spectrum of ~20 mM Tyrosine in D2O solution showing corresponding ring breathing mode (inspectral region mentioned above, two vibrational modes -1 were found with corrected frequencies of 1499 and 1574 cm . The single vibrational transition, corresponding to a breathing mode of the phenyl ring of tyrosine (pictured in Figure 1), -1 is observed at 1517 cm . Despite the presence of two rings modes in the frequency calculation, the IR intensity of one mode was much larger (by a factor of 10 times larger) than

1500 cm-1

1517 cm-1

Figure 2. Plot of normalized ratio of peak position for the tyrosine ring mode as a function of pH. the other and corresponded more closely with the frequency observed experimentally. The full width at half maximum -1 (FWHM) was determined to be ~5.5 cm by fitting the observed signal in vibrational spectrum to a single Gaussian. The experimental dipole was calculated from the following 60 equation; |% % |& = 9.18 * 10, -

./ /

01,

where μ is the transition dipole strength, ε(ω) is the extinction coefficient for each frequency, and ω is the corresponding frequency. The value was determined to be 0.213±0.034 D. This measured transition dipole strength was in good agreement with the DFT calculated value, 0.215 D. The concentration dependent FTIR experiment (quantified by -1 -1 abs@280 nm; ε280nm~1490 M ·cm ) of the tyrosine ring mode in water was performed to determine the peak extinction -1 -1 -1 coefficient, 365 ± 14 M ·cm , at 1517 cm . The magnitude of the extinction coefficient is well within the range of commonly used vibrational probes utilized for protein dynamics, 1 such as cyano- and amide transitions. Although the transition dipole magnitude suggests the potential of this infrared probe, the effectiveness of any probe depends on its ability to differentiate and detect local environments. For example, the cyano- labelled amino acids have been effectively utilized to determine site-specific information during binding, folding, peptide-membrane interactions, protein-ligand interactions, and the dehydration status 8,11,61 of an antimicrobial peptides. Although these probes have been shown to be minimally perturbing, it would be a significant advance to have an intrinsic vibrational transition within the biomolecule that avoids adverse effects on the struc31,36 ture and function. Tyrosine is found ubiquitously in protein systems, allowing the ring mode to potentially fill the gap as an intrinsic and non-perturbing side chain probe. The ring mode offers similar advantages to the cyano- labels including: the transition is located in the spectral region isolated from other vibrational transitions found in biomolecules, and the vibrational band is sensitive to its local environment as will be demonstrated below. The ring mode is also spectrally distinct unlike the carbonyl stretches found within the cluttered amide I region. Finally, the vibrational mode encompasses the entire ring providing a larger ‘antenna’ to interact and detect the surrounding environment.

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pH Dependence of Tyrosine. The tyrosine ring mode is sensitive to pH changes resulting in significant variations in the peak position of the vibrational spectrum. Increasing the pH of the solution from 7 to 12 red shifts the transition ~17 -1 -1 cm from 1517 cm . This spectral shift is caused by the deprotonation of the OH on the ring (pKa ~ 10) which alters the ring mode due to resonance effects. In Figure 2, the contribution of each band is measured as a function of pH. Based on normalized peak intensity ratio, tyrosine acts as an internal pH meter. The deprotonation of the OH corresponding to the observed changes in the infrared has been shown to occur during many biological process such as the enzymatic 62 activity of cytochrome C oxidase, proton transfer of green 63,64 65 fluorescent protein, and fibrillation of bovine insulin. It should also be noted that there were no significant changes in the bandwidth or peak position of the transition when temperature is increased from 16-82°C in water. (see the Supporting Information) Solvachromatic effect of Tyrosine ring mode. To assess the sensitivity of the ring mode to its surroundings, the infrared spectrum was measured in two solvents with dielectric constants varying by 40, water (εr ~ 80.1) and DMSO (εr ~ 46.7). The solvation in bulk water is representative of the environment of exposed residues in a water soluble peptides, while DMSO is comparable to the hydrophobic environment 66 found within a membrane environment. No spectral shift in frequency is observed but there is a significant change in bandwidth (Figure 3). The FWHM of this vibrational transition in DMSO was determined to be ~1.5 times larger than the corresponding bandwidth in water.

DMSO D2O

Figure 3. Infrared spectra of Tyrosine in DMSO (blue) and D2O (Red). This change in bandwidth is somewhat unexpected based upon the behavior of other vibrational probes. Usually, a larger inhomogeneous distribution of states is observed within water due to the direct hydrogen bonding to the probes themselves and the indirect electric field distribution both resulting in a larger number of observed vibrational states 8 with various frequencies. To examine the nature of the broadening mechanisms within DMSO, DFT calculations were performed on the tyrosine molecule in the presence of a DMSO and water molecules. The DMSO was positioned at a distance of 2.4 Å, 5.2 Å and 8.3 Å between the O of DMSO and the center of the tyrosine ring and the vibrational frequencies were calculated (Figure 4). A difference in vibra-1 tional frequency of ~8-10 cm was calculated between the different molecular configurations with varying distances. These computations suggest that the observed changes in bandwidth are likely due to a direct charge-charge interac-

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tion between the lone pairs of the oxygen on the DMSO and 67–69 the electron rich tyrosine ring. The repulsive lone pair – pi interactions create a larger inhomogeneous distribution of frequencies. Yet, tyrosine is also fully capable of forming weakly polar interactions/hydrophobic interactions with other compounds,70 which influence the overall inhomogeneous distribution. A similar calculation was performed for water showing no -1 significant change (45 cm and the overall configuration was energetically unfavorable, suggesting that the interaction of water with the ring is to a much less extent. Although a large change in bandwidth in the observed spectrum would be expected for water molecules within 2.3 Å, the observed bandwidth is quite small suggesting that water does not have

a)

b)

Figure 4. Optimized configurations of tyrosine in the presence of DMSO with a distance of a) 8.3 Å and b) 2.4 Å from the center of the tyrosine ring. such close proximity likely due to the hydrophobicity of the ring. Several solvents were employed to characterize the subtle interplay between the weak hydrophobic interactions and the direct repulsive interactions between the lone pairs and the ring. These results are summarized in Table 1. Unlike 71,72 the other vibrational probes, such as cyano- moieties, dielectric constant of the solvent was uncorrelated to the observed changes in the bandwidth (i.e.the frequency distribution). As suggested from Table 1, DMSO and diethyl ether exhibit the largest partial negative charge on the oxygen atom containing lone pairs resulting in the largest bandwidth due to their interaction with the electron rich ring. The hydrophobicity of the two ethyl groups of diethyl ether influences the overall interaction with the ring system resulting in a slightly increased in bandwidth compared to DMSO. Due to the highly electronegativity of the fluorine atoms on TFE, the lone pairs on the oxygen are less partial charge, causing the bandwidth to decrease significantly compared to the other organic solvents. As mentioned above, water is a hydrophilic and cannot solubilize the ring well, thereby exhibiting the smallest bandwidth. The other organic solvents have characteristics between these extreme cases. It should be noted for all solvents that no significant changes in maximum peak position were observed. Computational/Theoretical Studies. Initially, we attempted to determine a relationship between the changes in bandwidth and the dielectric constant, such as the common53 ly used Onsager model. However, since no correlation was found between the vibrational bandwidth and the dielectric constant, further calculations were performed to determine the role of the local electric field on the changes in band10 width. Thus, following the work of Boxer and coworkers, we

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utilized MD simulations to directly quantify the electric field experienced by the tyrosine ring mode (see details in the Supporting Information). Briefly, the electric field was directly calculated by averaging the necessary coulombic interactions. The resulting force determined from the interactions between each atom on the ring and the solvent molecules was projected on the dipole moment to calculate the electric field The electric field contribution of each atom was added together to find the total electric field acting on the vibrational mode in each solvent.

Figure 5. Correlation between the infrared spectral width of the ring mode transition of tyrosine and the solvent electric fields determined from molecular dynamics simulations. For calculating the charge-charge interactions, the atoms selected to represent the net charge of the ring were approximated as the 6-carbons of the aromatic ring. Using this methodology, the electric field was determined for the solvents shown in Table 1. A clear trend was observed regarding the electric field and bandwidth (frequency distribution) of the experiment. A correlation in the spectral bandwidth with the electric field was determined (Figure 5). The slope of the resulting line is related to the Stark Effect as 4,10 Boxer and coworkers found for other vibrational probes. have shown these types of trends correspond to the effects 10 resulting from application of an external field to a sample. Diethyl ether shows the lowest electric field value (most negative) of -9.11 MV/cm. Thus, since it exhibits the largest partial negative charge distribution and it is the most hydro-1 phobic solvent, the largest bandwidth (10.2 cm ) is observed for this solvent. On the other hand, the highest (most positive) electric field strength, 32.80 MV/cm, among all the solvents of was manifested by water. Combined with a large positive field, water is also the least hydrophobic solvent leading to the narrowest bandwidth in the experimental data. As shown in Figure 5/Table 1, dimethyl sulfoxide also exhibits a negative electric field of -4.75 MV/cm displayed the next largest bandwidth. Methanol has the least positive field value of 8.54 MV/cm. Acetonitrile and chloroform are both found middle of the trend with the similar electric field and bandwidths suggesting interactions with the ring are much less other organic solvents. Trifluoroethanol and water are in the high positive range of the electric field with the values of 26.45 MV/cm and 32.80 MV/cm, respectively. Despite the large field strength, the observed bandwidth is the least for these two solvents. Although it might be expected that the

large field strength may result in a larger distribution of frequencies, the large positive field does not cause a large effect on the ring mode, likely due to stabilization of the electron rich phenyl ring.

Table 1. Solvatochromic effect on tyrosine ring breathing vibrational transition Solvent

Dielectric Constant

Electric Field (MV/cm)

Bandwidth -1 (cm )

Peak Position -1 (cm )

Et2O

4.34

-9.11

10.2

1518.5

DMSO

46.7

-4.75

8.3

1516.7

MeOH

32.7

8.54

6.5

1518.9

ACN

37.5

15.72

6.7

1517.2

CHCl3

4.81

17.46

6.3

1518.9

TFE

27.68

26.45

5.6

1518.3

D2O

80.1

32.80

5.4

1516.5

Models to Account for Solvatochromic Contributions to the Bandwidth: To further explain the observed trend, the Kamlet–Taft solvatochromic parameters (β), the electron 73 donating ability, was investigated for the different solvents.. A clear linear trend was identified for the experimental bandwidth as a function of the electron donating capability of each solvent (Figure S7). As suggested by the above G09 calculations, the lone pairs of each solvent can influence the variation in the vibrational frequency caused by the repulsive interactions with the ring. This observed trend in the beta parameter also seems to correspond to changes in the bandwidth as a function of electric field strength discussed above. As the electric field becomes more negative, the interactions with the electron rich phenol ring become more significant. Such types of lone pair - pi electron repulsive interaction have been extensive been documented in prior 68,69,74 literature. The influence of the effect of the beta parameter on the bandwidth does not hold for water and methanol, where a significantly larger bandwidth would be expected according to the beta parameter. Other characteristics of these solvents must be utilized to rationalize the observations captured only by the electric field effect. Taking into account the log of the ratio of the unionized solvent in a mixture of two immiscible phases at equilibrium (i.e. the solvent partition coefficient) gives a measure of the hydrophobicity (see the Supporting Information). Comparing these values with the bandwidth (Figure S8), the solvents partition into two major groups: mostly hydrophobic (ACN, TFE, Et2O, and CHCl3) and hydrophilic (water, MeOH, and DMSO). This data suggests the lack of hydrophobicity of water and methanol preclude their ability to interact with the ring mode transition as effectively as the other solvents, thus explaining their deviation predicted by the electron donating ability alone. It should be mentioned that although DMSO is partitioned in the hydrophilic regime, the large amount of electron donating ability, β, compensates causing the large observed bandwidth.

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Application to a model peptide system, Trp-cage. Upon establishing the linear correlation of the bandwidth and electric field strength, a model peptide system, Trp-cage, was chosen to test the efficacy of the trend line and measure the electric field in the hydrophobic core region of a peptide. Trp-cage is a synthetic 20-residue miniprotein (NLYIQWLK-DGGP-SSGR-PPPS), containing an α-helix, 310-helix and a polyproline II helix; and it is often considered the ‘hy75 drogen atom’ of the folding and unfolding studies. Trp-cage is an ideal model system for our studies because it has a strong hydrophobic core containing the aromatic side chains of Tyr3 and Trp6 packed against Gly11, Pro12, Pro18 75,76 and Pro19 (pictured in Figure 6 inset). The IR spectrum of this tyrosine containing peptide folded state in buffer solution at room temperature exhibits a vibrational bandwidth (~ -1 6.2 cm ) similar to acetonitrile and chloroform. The corresponding value of the electric field was found to be 20.52 MV/cm. Upon temperature or chemical (guanidine hydrochloride) denaturation of the miniprotein, the vibrational bandwidth decreases (see Supporting Information) corresponding to an increase in the electric field of approximately 7.9 and 12.9 MV/cm, respectively. The chemical denaturant has the largest electric field value of 33.37 MV/cm.

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75,78

(GdmHCl), breaks up the hydrophobic pocket and residual structure enough to increase the field to 33.37 MV/cm which closely matches the electric field of tyrosine in bulk water (Figure 6). Overall, these results suggest that temperature denaturation is not as effective at unfolding the miniprotein as chemical 77 denaturation, as reported for other peptide systems. Temperature is capable of destabilizing bonds including electrostatic interactions and hydrogen bonds. However, hydrophobic interactions remain somewhat unaffected resulting in a compact structure at higher temperature. GdmHCl is more capable of perturbing the structure of solvent by affecting its H-bond network around hydrophobic groups providing a 78 destabilizing force to decrease the hydrophobic effect. The denaturant can also interact directly with the protein, particularly by hydrogen bonding to the polar groups competing with intramolecular hydrogen bonding. Protein-denaturant interactions have also been shown to lower the conformational entropy of the protein to more effectively denature the system. 2D IR of tyrosine ring mode. To further quantify the effect of solvation dynamics on the vibrational transition, the 2D IR spectra of the tyrosine ring mode were measured in water and DMSO. The 2D IR spectra of tyrosine in water shows a -1 positive peak along the diagonal at ωt= ωτ =1517 cm corresponding to ν = 0 → ν = 1 transition of ring breathing mode (Figure 7). The negative peak, resulting from the ν = 1 → ν = 2 transition of the ring mode, is shifted along the ωt axis to -1 -1 ωt=1507 cm indicating an anharmonicity of 10 ± 0.82 cm . As a result of the population relaxation (T10), the signal strength of the ν = 0 → ν = 1 transition decays during the waiting time, T, with a time constant of 2.2 ± 0.2 ps (Figure 8). 47

Figure 6. Electric field in hydrophobic pocket of folded Trpcage miniprotein (inset) in water based on the observed bandwidth (red). Influence of temperature (blue) and chemical denaturation (green) on the electric field captured by experimental bandwidth. The electric field strength around the tyrosine residue in the hydrophobic pocket (~20.52 MV/cm) is significantly lower than the field observed around tyrosine in bulk water solution at room temperature (Figure 6.) These results suggest that the hydrophobic pocket of a protein is similar to the local environment found in acetonitrile or chloroform. Prior work has shown that hydrophobic environments have elec4 tric fields similar to acetonitrile supporting the current observations. The infrared spectrum of the tyrosine residue of Trp-cage after raising the temperature to 84.8 °C showed -1 only a moderate decrease in bandwidth (~0.8 cm ) corresponding to an increase in the electric field of ~7.9 MV/cm. This result suggests that some residual structure may be present in the temperature state, as seen in other peptide sys77 tems. On the other hand, the chemical denaturation of the Trp-cage miniprotein, a 2 M Guanidine hydrochloride

This value is in good agreement with prior results. The diagonal peaks are tilted and slightly elongated along the diagonal at the earliest waiting times as a result of the inhomogeneity of the distribution of states (Figure 7). As the waiting time increases, the tilt of the peaks along the diagonal becomes less pronounced until the tangential slope between the positive and negative peak is vertical. These changes are indicative of a loss in frequency correlation (spectral diffu79 sion) due to the dephasing of the vibrational transition. The 2D IR spectra of tyrosine in DMSO exhibits a positive peak along the diagonal at a similar vibrational frequency as

Figure 7. 2D IR spectra of Capped tyrosine in (left) D2O and (right) DMSO at waiting times T=200 fs and T=1.2 ps. -1

found in water, ωt= ωτ =1517 cm . The corresponding negative

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transition is located at ωt=1506 cm , indicating an anhar-1 monic shift of 10.8 ± 0.60 cm . The population relaxation, T10, in DMSO was determined to be 2.4 ± 0.1 ps (Figure 8). At the earliest waiting times, the diagonal peaks are only slightly tilted due to the inhomogeneous broadening. During the evolution of this distribution of the states, the tangential slope at the intersection of the positive and negative peaks goes to zero as a function of the waiting time, T. Both solvent exhibits characteristics of significant spectral diffusion. This loss of correlation is quantified by measuring 80,81 the changes in the center line slope (CLS). This method utilizes the maximum peak intensity found for several vertical slices in the ν=0 → ν=1 contour of the 2D spectrum at different value of ωt. Then the slope of the line connecting each peak maxima is determined as a function of waiting time, T. The correlation decay is plotted as the inverse of the -1 38,82,83 slope, [S(T)] , versus the waiting time (T). The correlation decay time constants were determined to be 1.3 ± 0.2 ps and 0.7 ± 0.2 ps for D2O and DMSO, respectively, using a single exponential fit (Figure 8). When comparing and contrasting the 2D IR results from the two different solvents, the peak positions have the same center frequency with a similar diagonal anharmonicity. However, the bandwidth measured by fitting a diagonal slice along the diagonal through the positive peak indicated the inho-1 mogeneous distribution was larger (~1 cm ) in DMSO compared to water akin to the bandwidth difference in the linear spectrum. In addition, the vibrational lifetimes are similar suggesting the spectral diffusion is likely the major contributor to the larger spectral bandwidth observed in DMSO. Upon examining the correlation decays, the starting value of the inverse slope is 0.6 in water and 0.3 in DMSO. Although wa17,32 ter exhibits a value measured for many other oscillators, the significant difference in the starting value of DMSO is likely a result of spectral dephasing caused by fast solvent motions. The origin of this spectral dephasing is suggested to be a result of the highly perturbing charge-charge interactions between the electron rich tyrosine ring and the lone pairs found on the oxygen of the DMSO, evidenced by the distance dependent computations of the vibrational frequency mentioned above. Finally, the correlation decays occurs in half the time when solvated with DMSO as compared to water. The much faster decay time, 700 fs, indicates that the solvent interactions of DMSO influence the vibrational transitions to a much higher degree. The observed decay time constant in water matches the characteristic time scale, 0.8 2 ps, of hydrogen bond making and breaking within water for 22,84–86 different solutes. The fast dephasing time observed in DMSO suggested a direct repulsive interaction of the electron rich ring and the lone pairs of the solvent. The relationship between the calculated electric fields and the correlation decays is evident from prior studies of solvent 87 interaction with solutes. However, in the case of tyrosine, the overall magnitude of the electric field does not play a significant role in the dephasing process. Instead, as the value approaches a field strength that is more negative, the frequency distribution increases due to a more perturbative effect on the electron rich tyrosine ring.

Conclusion The sensitivity of the tyrosine ring breathing mode as an intrinsic non-perturbing infrared probe is shown by variation in the infrared bandwidth in a variety of solvents. Additional-

ly, the sensitivity of the peak position of ring mode transition to pH in water solutions creates an alternative application as a pH sensor within a protein system. Unlike other infrared probes, a larger inhomogeneous bandwidth is observed in hydrophobic (i.e. DMSO) versus hydrophilic (i.e. water) me-

T10= 2.2 ± 0.2 ps T10= 2.4 ± 0.1 ps

τ= 1.3 ± 0.2 ps τ= 0.7 ± 0.2 ps

a)

b)

Figure 8. a) Lifetime decay of capped tyrosine in D2O (purple) and DMSO (blue) b) correlation decay of capped tyrosine in D2O (purple) and DMSO (blue). dia suggesting hydrogen bonding is not a significant contributor to broadening. DFT calculations illustrate that the observed inhomogeneous bandwidth is due to a repulsive charge-charge interaction between the lone pairs of DMSO and the electron rich ring of tyrosine. A correlation between the calculated electric field induced by a variety of solvents and the observed vibrational bandwidth of the tyrosine ring mode was uncovered. The observed trend can be described by using a combination of only two solvent parameters, electron donating ability and the partition coefficient (measure of hydrophobicity). The variation in the bandwidth arises from the interplay between the weak hydrophobic interactions and the direct repulsive interactions between the lone pairs and the ring. The 2D IR spectra of the tyrosine ring mode in water and DMSO determined the effect of vibrational dynamics on the infrared lineshapes. The vibrational lifetimes do not vary significantly for D2O and DMSO suggesting that the solvent dynamics play a significant role in the vibrational dephasing. The correlation decay times were determined to be 1.3 ± 0.2 ps and 0.7 ± 0.2 ps for D2O and DMSO, respectively. From the frequency-frequency correlation decays in water and DMSO, the spectral diffusion in the DMSO is twice as fast as water suggesting DMSO more effectively interacts with the ring corresponding to the frequency broadening observed in the infrared spectrum.

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The efficacy of the solvation field model was demonstrated through application to the Trp-cage miniprotein. Through the changes in the infrared spectrum, the electric field within the protein was detected under both native and denatured conditions within the hydrophobic core. The electric field strength around the tyrosine in the hydrophobic pocket of the protein was determined to be value (20.52 MV/cm), similar to the field generated by acetonitrile or chloroform and significantly lower than the field observed in bulk water solution. Upon denaturation, the field strength approached the bulk water solution. However, it was shown that temperature denaturation is not as effective at unfolding the miniprotein as chemical denaturation.

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Due to the high sensitivity of the tyrosine ring mode to the changes in its local environment, these infrared results show that the tyrosine moiety has much potential as an intrinsic non-perturbing site-specific probe for measuring dynamics in both peptides and larger protein systems..

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ASSOCIATED CONTENT

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AUTHOR INFORMATION Corresponding Author

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* Matthew J. Tucker. Email address: [email protected]

Present Addresses

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†If an author’s address is different than the one given in the affiliation line, this information may be included here.

Author Contributions

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The manuscript was written through contributions of all authors. / All authors have given approval to the final version of the manuscript.

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SUPPORTING INFORMATION Further details on: Temperature and pH effects on the IR spectrum, Influence of capping groups, solvation parameters, FTIR spectrum of Trp-cage and Molecular dynamic simulations are available. (17)

ACKNOWLEDGMENT We want to thank Andrew J. Schmitz for his help with data collecting and processing. Financial support was made possible by University of Nevada, Reno startup.

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