Conformations of Phenylalanine in the Tripeptides AFA and GFG

J. Phys. Chem. B 2010, 114, 3965–3978

3965

Conformations of Phenylalanine in the Tripeptides AFA and GFG Probed by Combining MD Simulations with NMR, FTIR, Polarized Raman, and VCD Spectroscopy Silvia Pizzanelli,*,† Claudia Forte,† Susanna Monti,† Giorgia Zandomeneghi,⊥ Andrew Hagarman,† Thomas J. Measey,† and Reinhard Schweitzer-Stenner† Istituto per i Processi Chimico Fisici, Consiglio Nazionale delle Ricerche, Area della Ricerca di Pisa, Via G. Moruzzi, 1 56124 Pisa, Italy, Department of Chemistry, Drexel UniVersity, 3141 Chestnut Street, Philadelphia, PennsylVania 19104, and Laboratory of Physical Chemistry, ETH-Zurich, Wolfgang-Pauli-Strasse 10, CH-8093 Zurich, Switzerland ReceiVed: August 4, 2009; ReVised Manuscript ReceiVed: January 6, 2010

Conformational properties of small, flexible peptides are a matter of ongoing interest since they can be considered as models for unfolded proteins. However, the investigation of the conformations of small peptides is challenging as they are ensembles of rapidly interconverting conformers; moreover, the different methods used are prone to different approximations and errors. In order to obtain more reliable results, it is prudent to combine different techniques; here, molecular dynamics (MD) simulations together with nuclear magnetic resonance (NMR), fourier transform IR (FTIR), polarized Raman, and vibrational circular dichroism (VCD) measurements were used to study the conformational propensity of phenylalanine in the tripeptides AFA and GFG, motivated by the relevance of phenylalanine for the self-aggregation of peptides. The results of this analysis indicate that the F residue predominantly populates the β-strand (β) and polyproline II (PPII) conformations in both AFA and GFG. However, while phenylalanine exhibits a propensity for β-strand conformations in GFG (0.40 e β population e 0.69 and 0.29 e PPII population e 0.42), the substitution of terminal glycines with alanine residues induces a higher population of PPII (0.31 e β population e 0.50 and 0.37 e PPII population e 0.57). Introduction The unfolded state of peptides and proteins has attracted considerable interest over the last 10 years,1–5 motivated in part by the observation that regular compact structures like short helices and turns can be formed in the unfolded state, in contrast to what the canonical random coil model suggests.3,6 Moreover, the analysis of a variety of coil libraries revealed that the φ,ψ distributions differ for each amino acid, owing to different backbone-side chain and residue-solvent interactions,7–11 which suggests different structural propensities of amino acid residues in the unfolded state. However, the distributions obtained considering the entire database of folded protein structures are different from those obtained using only a subset of residues, namely, those located outside of regular secondary structures. A review of the respective literature reveals that the obtained distributions depend on which types of secondary structures were actually considered. This observation is at variance with the notion that coil libraries provide per se suitable models for the individual conformational propensities of amino acid residues.10,11 Even if one infers conformational propensities from restricted coil libraries, for which helices, sheets, and turns are excluded,8 the obtained distributions might not reflect the intrinsic propensities of amino acids, owing to nearest-neighbor interactions between residues,12 which have been inferred from theoretical studies as well as from a detailed analysis of the context dependence of amino acid propensities in restricted coil * To whom correspondence should be addressed. E-mail: silvia.pizzanelli@ ipcf.cnr.it. † Area della Ricerca di Pisa. † Drexel University. ⊥ ETH-Zurich.

libraries.13–15 This context dependence of the amino acid propensity might explain why NMR J coupling constants of residues in unfolded peptides and proteins do not always reflect predictions from coil libraries. The structural analysis of short peptides in solution by a combination of experimental and computational methods has emerged as an important tool for determining the conformational propensity of amino acid residues in an aqueous environment.1,16 The investigation of the conformations adopted by small peptides is challenging as they form ensembles of rapidly interconverting conformers. Various computational17–21 and experimental methods have been used to describe such conformational sampling.22–29 Thus far, many investigations have focused on alanine,18,19,22–25,27,28,30–34 owing to its abundance in proteins and to the capability of relatively short polyalanine peptides to form helical structures outside of a protein context.35,36 The results of these studies are conflicting,1 but most recent NMR and vibrational spectroscopic data strongly suggest a very high PPII propensity (with populations between 0.8 and 0.9) for unfolded polyalanine oligomers,37,38 which exceeds even the highest values derived from coil libraries8,39 but agrees well with MD simulations performed with a modified Amber force field.19 Studies of other amino acids are more limited in number. Circular dichroism and vibrational spectroscopic studies indicate a high PPII propensity for ionized polylysine and polyglutamic acid,40,41 but this is not reflected by the propensity of, for example, isolated K residues in polyalanines.33 Trivaline has been shown to exhibit a strong preference for a β-strand structure.23,38 Qualitative information about structural propensities of a broader set of amino acid residues was obtained for AX, XA, AXA, GGXGG and PlXnPm (X: guest residue; l, n, m: number of residues).29,42–44 Some of these data indicate that

10.1021/jp907502n  2010 American Chemical Society Published on Web 02/25/2010

3966

J. Phys. Chem. B, Vol. 114, No. 11, 2010

residues with branched aliphatic side chains (e.g., V and I) and aromatic residues (Y, F, W) have a preference for a β-strandlike conformation,42,44 while others (e.g., NMR data for GGXGG)29 suggest that nearly all residues exhibit a PPII fractional population greater than 0.5, thus making it the preferred conformation in the unfolded state. The current study is aimed at testing and combining different techniques in the determination of the conformational propensity of phenylalanine in AFA and GFG. Determining the propensity of this amino acid residue is important for a variety of reasons. First, phenylalanine represents a class of amino acid residues which are generally considered as helix breakers, owing to their high β-sheet propensity in folded proteins.45 The question arises as to whether this preference also exists in the unfolded state when nonlocal interactions are absent. Second, phenylalanine is the simplest aromatic residue in that it is sterically less demanding than W and does not contain a polar group like Y. Third, F has been identified as a pivotal residue for many selfaggregation processes. For example, it has been suggested that the segment LVFFA of the amyloid beta proteins Aβ1-40 and Aβ1-42 make up the β-sheet core of the fibrils formed by these proteins.46 The isolated segment itself is prone to aggregation above a certain peptide concentration.47 Generally, it has been convincingly demonstrated that short F-containing segments of amyloidogenic peptides have a very high propensity for aggregation.48,49 Phenylalanine is such a strong promoter of peptide aggregation that even a small unit like F2 can aggregate and, depending on the solution conditions, may form either hydrogels or nanotubes.50 The number of structural studies on short, F-containing peptides is limited, and the results are conflicting. Eker et al. used IR, Raman, and VCD spectroscopy to study the average conformation of AXA peptides and found that F prefers a more β-strand-like conformation in this context, more than alanine but less than valine.43 A more quantitative study on GGXGG peptides by Shi et al. yielded a rather high PPII fraction for F (∼0.64).29 This result emerged from analyzing the 3JNH-RH NMR coupling constant of F in terms of a two-state model comprising representative conformations for PPII and β-strand. Theoretical calculations carried out by Tran et al.14 revealed a rather heterogeneous distribution of F in a variety of host-guest systems, characterized by PPII and right-handed R helix (RR) fractional populations of about 0.35 and 0.2, respectively, the remaining fraction being a mixture of β-turn and β-strand conformers. More recently, in a study combining UV-CD and NMR, AFA was reported to populate inverse γ-turn (γinv) and β-strand conformations, with fractions of 0.6 and 0.4, respectively, at 280 K.51 This is a very surprising result in view of the fact that none of the thus far conducted studies on phenylalanine-containing peptides even remotely indicate such a substantial sampling of a turn-structure region. The current study is the first attempt to combine experimental techniques, such as NMR and vibrational spectroscopy, and computational means, that is MD simulations, to explore the conformational propensity of phenylalanine in the unfolded peptides AFA and GFG in aqueous solution. The collection of data from different techniques is important given the uncertainty and approximations of each method. In this perspective, the combined use of NMR and optical spectroscopy is especially relevant due to the different time scales probed by the two techniques. It is known that in small peptides, the thermal populations of the main conformations, that is, RR, β, and PPII, derived from MD simulations strongly depend on the employed theoretical

Pizzanelli et al. model.30,52 Nevertheless, different force fields give comparable mean values and widths of φ,ψ distributions. Therefore, we utilized the MD structural distributions, where the molecules were clustered into different conformational states according to the backbone dihedral angles of the central residue, and utilized the experimental data to obtain the possible thermal populations of these conformers. The φ,ψ backbone angle distributions were experimentally probed by NMR via NOEs and spin-spin coupling constants. NOEs are related to average distances between molecular nuclei, while spin-spin coupling constants report directly on a conformational ensemble around a specific torsion angle via Karplus relationships.53 Several methods have been adopted for quantitatively analyzing multiple conformations using NMR data.54–57 Most of these methods involve the generation of a large number of possible conformations, for example, using a grid search or molecular mechanics and selecting a subset consistent with the experimental results. Sometimes, the time-averaged restraints method is employed, which affords enhanced conformational sampling.58 Here, the unrestrained MD data have been used to calculate theoretical proton-proton NOE distances and 3JNH-RH(F) coupling constants of a given conformational state. The possible thermal populations were identified by comparing the experimental constraints with the corresponding values calculated by varying the populations of different conformers on a grid. Additionally, we measured the amide I′ band profiles of the FTIR, isotropic Raman, anisotropic Raman, and VCD spectra of cationic GFG in D2O and analyzed them together with previously published data of zwitterionic AFA by exploiting the excitonic coupling between the two amide I′ modes as described earlier.59 We combined the excitonic coupling formalism with a recently developed algorithm which describes the conformational distributions of amino acid residues in terms of Gaussian distributions, centered at regions associated with PPII, β-strand, R-helical, and turn-like conformations. Altogether, the results obtained with these techniques provide a rather consistent picture concerning the conformational propensity of phenylalanine. Materials and Methods Materials. All of the NMR samples were prepared using H-alanylphenylalanylalanine-OH (AFA) and H-glycylphenylalanylglycine-OH (GFG) (both peptides >95% purity; customsynthesized by Peptide International), without further purification. In the NMR experiments, the AFA conformation was studied in aqueous solution at pH 4.0, obtained by dissolving the peptide in a 90 mM potassium phthalate aqueous buffer at a peptide concentration of 8.8 mM. The choice of this pH was motivated by the necessity to compare the NMR conformational results with those reported for zwitterionic AFA in ref 43. As explained in details in the Results section, this analysis is not possible at higher pH values. In order to obtain information about the peptide protonation state at pH 4.0 and on the conformation of AFA in different protonation states, AFA was also studied at pH 1.6 in an aqueous solution of HCl, at pH 5.6 in a 32 mM acetate buffer and at pH 7.3 in an 18 mM sodium phosphate buffer, the peptide concentrations being 10.2, 12.6, and 10.6 mM, respectively. The sample at pH 7.3 was prepared also to compare our results with those shown in ref 51. No significant differences were observed between 1H spectra of AFA in the concentration range of 0.15-10 mM, which suggests that peptide self-aggregation does not occur in our conditions (see Supporting Information). GFG was studied in aqueous solution at pH 1.4, prepared by dissolving the peptide in a KCl/HCl aqueous solution to yield a peptide concentration of 7.2 mM.

Conformations of Phenylalanine in AFA and GFG At this pH, GFG is cationic. In order to obtain information on the conformation of GFG in different protonation states, the molecule was also studied at pH 4.0 in a 90 mM potassium phthalate aqueous buffer and at pH 7.3 in an 18 mM sodium phosphate buffer to yield concentrations of 6.2 and 7.0 mM. All of the NMR samples contained a H2O/D2O ratio of 90/10 v/v. In the following, AFA will be used to indicate an AFA sample at pH 4.0 and GFG to indicate a GFG sample at pH 1.4. The choice of the pH values for the spectroscopic experiments was dictated by the fact that GFG becomes insoluble at neutral pH at concentrations necessary for VCD and Raman measurements. The data for neutral AFA and acidic GFG have been obtained earlier.43,60 Previous spectroscopic data for a variety of tripeptides have shown that terminal charges and end groups have a negligible influence on the conformation of their central residue.23,25,43 Moreover, the IR, VCD, and Raman spectra do not show evidence of peptide aggregation even at the relatively high concentrations used in these experiments. To confirm this notion, IR spectra were obtained for neutral AFA and acidic GFG at high (0.2 M) and low (20 mM) peptide concentrations. The amide I′ band shapes for high and low concentrations were indeed similar, which indicates no appreciable aggregation at these concentrations (data not shown). NMR Spectroscopy. 1H NMR experiments were performed on a Bruker DMX 400 spectrometer operating at a proton frequency of 400.13 MHz. Spectra were measured with a 5 mm triple resonance inverse TXI probehead equipped with zgradient. The π/2 pulse was 10 µs, the recycle delay was 2 s, and WATERGATE solvent suppression was used.61 1D 1H spectra were measured acquiring 40 scans. These spectra were used for the assignment of the peptide signals in the case of GFG and for the determination of 3JNH-RH values after deconvolution of the amide signal. In the case of AFA, the assignment required the acquisition of a DQF-COSY spectrum measured at 299 K; this was recorded in TPPI mode acquiring 32 scans for each t1 increment. The NOESY experiments were conducted at 299 K with mixing times ranging between 100 and 300 ms and WATERGATE solvent suppression. The 2D NMR spectra were obtained with spectral widths of 9 ppm in both dimensions; 32 scans were acquired for 256 and 200 t1 increments in the NOESY and DQF-COSY experiments, respectively. Data were apodized in both dimensions with squared sine multiplication with 90° phase. In the t1 dimension, a linear prediction of (2048-256) experiments was applied. Data were zero-filled to yield a 2k × 2k matrix and baseline-corrected in both dimensions using a polynomial function of degree 5. The values of the 3JRH-β′H(F) and 3JRH-β′′H(F) coupling constants were determined from the 1D spectra through a fitting procedure implemented in the program SpinWorks, written and made available by Dr. Kirk Marat.62 The amide temperature coefficients were measured varying the temperature in the range of 283-317 K. The 1H frequency scale was referenced to the signal of acetone (2.218 ppm), added to the solution as an internal reference.63,64 Vibrational Spectroscopy. Raman, VCD, and IR experiments on GFG and AFA which were previously published43,60 were performed in the Biospectroscopy Laboratory of the Department of Chemistry at Drexel University, Philadelphia, PA. The instrumentation, experimental setup, and spectral analysis for the Raman scattering experiments have been previously described in detail.65 The FTIR and VCD spectra were recorded with a ChiralIR fourier transform VCD spectrometer from BioTools (Jupiter, FL). The concentrationdependent IR spectra were collected with a resolution of 4 cm-1

J. Phys. Chem. B, Vol. 114, No. 11, 2010 3967 and 50 scans for each the background and the peptide solution. The peptide sample was placed into a 20 µm CaF2 Biocell (BioTools). All spectra were solvent-corrected by subtracting the D2O spectrum from the peptide spectra. Molecular Dynamics Simulations. Nanosecond molecular dynamics simulations in water of AFA and GFG peptides were performed with the AMBER9 simulation programs66 employing the ff03 all-atom force field,52,67 which is known to compensate for the propensity of the ff99 force field68 to oversample the right-handed helix conformation.69 The peptides were placed in a periodic truncated octahedral box of TIP3P water molecules (960)70 extending approximately 10 Å in each direction from the peptide atoms. AFA was in the zwitterionic form, while GFG was in the cationic form. All of the simulations were run using the sander module of AMBER9 with SHAKE (tolerance ) 0.0005 Å) on the hydrogen atoms, a 2 fs time step, and a temperature of 299 K, held constant using Andersen’s coupling scheme71,72 (time constant ) 0.2 ps). A 10 Å cutoff was applied to the Lennard-Jones interactions, and long-range electrostatic interactions were treated using the particle mesh Ewald (PME) correction. The total system was coupled to an external bath of pressure with a coupling constant of 0.5 ps,73 and the nonbonded list was updated every 10 steps. Equilibration was performed by first holding the position of the peptide fixed and running 500 steps of minimization followed by constant pressure dynamics for 10 ps, during which the system was heated to 299 K. Afterward, solute constraints were released, and the NpT equilibration was continued for 10 ps. Starting from the equilibrated configuration, MD trajectories were recorded for a maximum of 17.5 ns, and the system coordinates were collected every 0.5 ps for analysis (35000 configurations). In our analysis, we focused on the conformational behavior of the central phenylalanine residue and classified the conformations as RR, β, PPII, γinv, left-handed R-helix (RL), and classic γ-turns (γcl), according to the following φF and ψF Ramachandran regions: for RR, -180 < φF < 0°, -120 < ψF < 30°; for β, -180 < φF < -100°, 90 < ψF < 180° and -180 < φF < -100°, -180 < ψF < -120°; for PPII, -100 < φF < -50°, 100 < ψF < 180°; for γinv, -120 < φF < -40°, 30 < ψF < 120°; for RL, 0 < φF < 180°, -30 < ψF < 120°; for γcl, 40 < φF < 120°, -120 < ψF < -30°.7 The potentials of mean force along the dihedral angles φF and ψF are shown in the Supporting Information. Data Analysis. Distance and Dihedral Constraints. All cross-peaks in the NOESY spectra are negative, indicating that the peptides are in the fast-motion limit. With the different mixing times, temperatures, and pH values, cross-peaks ranging in number between 8 and 21 and between 13 and 15 were observed for AFA and GFG, respectively. Stereospecific assignment of F methylene proton resonances was accomplished by qualitatively evaluating 3JRH-β′H(F), 3JRH-β′′H(F), and the intraresidue NOE derived distances between NH of F and each βF proton.74 The F aromatic protons δ′, δ′′, ε′, ε′′, and ζ were not assigned. For GFG, R′ and R′′ proton signals due to G1 and G3 were also not assigned. The interproton distances have been calculated by assuming that cross-relaxation is dominated by dipole-dipole interaction and that the overall molecular tumbling is described by a single correlation time. In the initial rate approximation, the distance rNOE between two protons is related to the corresponding crosspeak intensity Γ by the relationship

rNOE )

(

Γgeminal Γ

)

1/6

rgeminal

(1)

3968


Pizzanelli et al.

Γgeminal represents the F β′/β′′ cross-peak intensity and was determined for each mixing time. rgeminal was fixed to 1.8 Å. The conditions to be fulfilled for the above equality to be valid are discussed in the following paragraph. The uncertainty in the distance, ∆r, was calculated as the maximum deviation from the average distance for the NOESY spectra at different mixing times. Restraints on the dihedral angle φF were imposed on the basis of the measured 3JNH-RH coupling constant of the F residue for both AFA and GFG.75 Conformer Populations of the F residue. Two types of internal motions involving the F backbone dihedral angles occur. For the first type, the angles before and after the motional process belong to the same conformational state, and the rate of change is fast compared to the overall rotational tumbling. For the second one, the angles belong to different states, and the rate of change is slow with respect to tumbling. Both types of motion influence a NOE distance depending on φF and ψF angles. Of the conformational states defined in the Molecular Dynamics Simulations section, only RR, β, and PPII have been considered, as we will discuss in the Results. Typically, the fast internal motion occurs on a time scale of 1 ps,76 while an estimate of the lifetime of a given conformational state from our MD data provided a value on the order of 1 ns, in agreement with the energy barriers for transitions between states ranging from tenths of a kcal/mol to a few kcal/mol (see Supporting Information). On the other hand, tumbling occurs on a time scale of tens of ps, as calculated in ref 77 from the MD trajectory of AFA (tumbling correlation time ) 50 ps). If a single conformational state i occurred, only the fast motion within the state should be considered. Then, Γi can be calculated from our ensemble of MD molecules and will be proportional to76 2

Γi ∝

∑

|

Ni

∑

1 4π 5 m)-2 Ni k)1

Y2m(θi,k, φi,k) 3 ri,k

|

For backbone proton pairs, we assumed that in eq 2 the radial and angular dependences can be separated in different contributions according to 2

|

with i ) RR, β, PPII

(2)

where ri,k represents the relevant distance for the MD molecule k belonging to the ith-state, Ni is the number of molecules within the state, Y2m(θi,k,φi,k) are second-order spherical harmonics expressing the interaction between the two nuclei with separation ri,k in ri,k, with θi,k and φi,k defining the orientation of the vector b a molecular fixed frame. It has been shown that eq 2 holds true when the generalized order parameter

∑

∑

S2 ≡

(

∑

) | -1

1 4π 1 5 Ni k)1 r6

i,k

2

∑

m)-2

Ni

2

S2Ω

∑

|

Y2m(θi,k, φi,k) 1 Ni k)1 r3

∑

i,k

|

∑ piΓi i

where pi is the relative population of each state.

|

Ni

∑

1 4π Y (θ , φ ) ≡ 5 m)-2 Ni k)1 2m i,k i,k 〈ri-3〉2

(5)

(

Ni

∑

1 1 ≡ Ni k)1 r3

i,k

2

)

(6)

2

(7)

Strict equality holds only when the radial and angular motions are statistically independent. In real molecules, the correlation between radial and angular dynamics is usually weak due to the presence of many motional degrees of freedom.76 Angular fluctuations, described by the order parameter S2Ω, have been considered not to appreciably vary for vectors connecting different backbone proton pairs. S2Ω of the F β′/β′′ vector was assumed to be comparable to that characterizing backbone proton pairs. Thus, only the effect of radial averaging is considered here. Therefore, using eqs 1, 2, and 7, and within the assumptions clarified above, we calculated the NOE distance that we would observe if the single state i occurred and if it was subject to fast internal motion


(8)

If, on the other hand, the slow internal motion involving the exchange between different conformers also occurs54

r)

( ) p

∑ r6i i

-1/6

(9)

i

Analogously, 3JNH-RH(F) is the population weighted average of the coupling constants Ji characterizing each i state

JNH-RH(F) )

∑ piJi

(10)

i

2

(3) where Ji results from the average of the coupling constants, Ji,k, of all of the MD molecules within the i state according to

is significantly different from zero.76 If the slow conformational changes are also taken into account, the cross-relaxation rate results from the populationweighted average of the relaxation rates of the different states i

Γ)

i,k

with

3 Ni

2

ri ) (〈ri-3〉2)-1/6

2

|

Ni

Y2m(θi,k, φi,k) 4π 1 = S2Ω · 〈ri-3〉2 3 5 m)-2 Ni k)1 r

(4)

Ni

Ji )

∑

1 J Ni k)1 i,k


(11)

For each molecule, the constant was calculated from its dihedral angle φF using a Karplus relationship.75 The values for the AFA NOE distances RF-NA3, NF-NA3, NA3-RA1, and NA3-βA1 and 3JNH-RH(F) were compared to the corresponding calculated values, with the populations, pi, varying on a grid of 0.01. The same comparison was performed

Conformations of Phenylalanine in AFA and GFG

J. Phys. Chem. B, Vol. 114, No. 11, 2010 3969

for the values of the experimentally available GFG NOE distances and 3JNH-RH(F). The values of the distances depending on the dihedral angle χ1 were used as additional constraints. Therefore, information about the population of the rotamers differing in χ1 was also obtained. The motion involving the conversion between different χ1 rotamers is considered slow with respect to tumbling and angular fluctuations of proton pairs involving a backbone proton, and β′ or β′′ F protons are assumed comparable to those shown by backbone proton pairs and by β′ /β′′ F protons. Therefore, analogous to eq 9, the NOE distance is

ri )

(

∑

pipi,χ1 6 ri,χ 1

i,χ1

)

[(

1 1 Ni,χ1 k)1 r3

JRH-β′H(F) )

i,χ1,k

3

JRH-β′′H(F) )

)]

(18)

with

fi )

(√ ) pi

2π |Vî |

exp[-0.5(→ F -→ F i0)TVî-1(→ F -→ F i0)]

(19a)

()

φ → F ) ψ

(13)

(14)

∑ pi3JRH-β′′H (F)

(15)

i

π

where

∑ pi3JRH-β′H (F) i

π

i

(12)

where ri,χ1,k represents the relevant distance for the molecule k belonging to the conformational state i and characterized by χ1, and Ni,χ1 is the number of molecules characterized by χ1 within the conformational state i. pi,χ1 is the population of the rotamer χ1 in the conformational state i. We considered χ1 values centered at 180, -60, and 60° and looked for sets of populations of the χ1 angle (pi,χ1)180°, pi,χ1)-60°, pi,χ1)60°) giving distances within the experimental ranges by varying pi,χ1 in steps of 0.1. pi values fulfilling all of the distance and angular constraints were accepted. Among the pi,χ1 sets fulfilling the abovementioned constraints, we selected those compatible with the 3 JRH-β′H(F) and 3JRH-β′′H(F) experimental values. 3JRH-β′H(F) and 3 JRH-β′′H(F) were calculated according to 3

∑ ∫-π ∫-π fi(φ, ψ)dφdψ

2 -1/6

Ni,χ1

∑

Z)

-1/6

with

ri,χ1 )

band profiles, we used the distributions obtained from the MD simulations. For each conformational state, the distributions were fitted using sets of two-dimensional Gaussian functions. The partition sum for the central residue ensemble can be written as

i

i

and

Vî )

JRH-β′Hi(F) ) 12.9pi,χ1)180 + 3.4pi,χ1)-60 + 3.4pi,χ1)60 (16)

JRH-β′′Hi(F) ) 3.4pi,χ1)180 + 12.9pi,χ1)-60 + 3.4pi,χ1)60 (17)

3

Considering errors in the parametrization of the Karplus equation, the possibility of restricted motional averaging, and the digital resolution of the spectra, the sets of pi,χ1 for which each |Jobserved - Jpredicted| was less than 2 Hz were accepted. Analysis of Amide I′ Band Profiles. The excitonic coupling model utilized to simulate the amide I′ band profiles has been previously described in detail.59 We recently extended our approach by explicitly considering the superposition of different distributions per residue.38 For the simulation of the amide I′

(

σφ,i σφψ,i σφψ,i σψ,i

)

(19c)

The vector b F0i points to the position of the maximum of the ith distribution in the Ramachandran coordinate system, pi is the corresponding fraction, and the diagonal elements of the matrix Vî are the full widths at half-maximum (fwhm) of the ith distribution along the coordinates φ and ψ. The corresponding off-diagonal element σφψ,i ) σψφ,i reflects correlations between variations along the two coordinates. If Vî is diagonal, the φ,ψ projection of the distribution is an ellipse with its main axis parallel to the φ and ψ axes. Correlation effects rotate the ellipse in the (φ,ψ) plane. The expectation value of any observable x depending on φ and ψ (IR and Raman intensities, rotational strengths) can be written as

〈x〉 )

with 3JRH-β′Hi(F) and 3JRH-β′′Hi(F) calculated using the parametrization given in ref 78 3

(19b)

∫-ππ ∫-ππ xf(φ, ψ)dφdψ Z

(20)

As shown by ab initio and DFT-based calculations for diglycine and dialanine peptides, the nearest-neighbor coupling between amide I modes exhibits a very strong dependence on the dihedral angles of the central residue.79 We have recently developed a mathematical algorithm which reproduces the φ and ψ dependence of the nearest-neighbor coupling constants as derived from the above-mentioned DFT studies.38 The same formalism is used in the present study. Considering such dependence is important, particularly in the PPII region of the Ramachandran space, for which all coupling constant maps computed thus far suggest a rather large gradient. Results In order to obtain the conformational distribution for AFA and GFG, we used the following procedure. First, structural distributions of AFA and GFG were obtained from our MD simulations. In a second step, all of the MD conformers were

3970


Figure 1. Ramachandran (φF,ψF) probability distribution of AFA and GFG in water (angles in degrees) from the MD simulations.

clustered in different conformational states, according to the backbone dihedral angles of the central residue. Using the MD data, the experimentally available 3J coupling constants and NOE distances were calculated for each conformational state. Subsequently, the experimental NMR data were used as constraints to obtain the thermal populations of the central F residue, together with the populations of different χ1 rotamers. The computed Ramachandran maps were decomposed into twodimensional Gaussian distributions and the results used to simulate the amide I′ band profiles of the respective IR, polarized Raman, and VCD spectra. The results obtained were then compared with those from NMR. MD Simulations. The conformational behavior of the central F residue in AFA and GFG is discussed on the basis of the probability distribution of the backbone dihedral angles φF and ψF, considering the different regions of the Ramachandran maps outlined in the Materials and Methods section. Figure 1 shows the Ramachandran map of the probability distribution of (φF,ψF) dihedral angles for AFA and GFG obtained from the MD simulations. To better visualize the details of the distribution for the relatively low population of the RR conformational state, which are not clearly obtainable from Figure 1, the same data are presented as two-dimensional histograms (Figures 2 and 3), showing the one-dimensional projections of the distributions with respect to both dihedral angles for the significantly populated states (i.e. RR, β, and PPII). For AFA, the probability distribution exhibits a wellpronounced peak centered at about (-73°,151°) which corresponds to the PPII conformation and a smaller broad peak in the β region. A very small contribution in the RR sector is also observed. The histograms in Figure 2a and b show that there are two φF maxima at about -160 and -70° in this sector, while ψF is centered at -40°. This distribution is quite different from that of a nondistorted RR, for which φ) -57° and ψ) -47°. From the volume of the peaks in Figure 1, we conclude that F is predominantly in an extended conformation, populating both PPII (57%) and β (31%) conformations, to a minor extent (8%) RR, and only insignificantly γinv, RL, and γcl (4, 0, and 0%, respectively). For the computation of the relative populations, in the case of overlapping regions in the Ramachandran plot

Pizzanelli et al.

Figure 2. Histograms showing the distribution of φF (left-hand side) and ψF (right-hand side) torsion angles for the central F residue of AFA in the RR, β, and PPII conformations. Note that the relative MD populations of the different conformations are not reflected by the ordinate axis, which is in arbitrary units to better visualize the details of each distribution.

Figure 3. Histograms showing the distribution of φF (left-hand side) and ψF (right-hand side) torsion angles for the central F residue in GFG for the RR, β, and PPII conformations. Note that the relative MD populations of the different conformations are not reflected by the ordinate axis, which is in arbitrary units to better visualize the details of each distribution.

(i.e., γinv with β and PPII), the number of conformations was ascribed to the different types of structures according to the relative volumes of the corresponding nonoverlapping regions. Thus, the results suggest a surprisingly high PPII propensity of F in an alanine-based context. Figure 1 shows two well-pronounced peaks for GFG, centered at about (-158°,157°) and (-73°,152°), corresponding to β and



TABLE 1: Relative Populations of the Conformational States rR, β, PPII, and γinv in the Canonical Ramachandran Regions from MD, NMR, and Vibrational Spectroscopy (VS) Data of AFA and GFGa AFA

GFG

conformational state

MD

NMR

VS

MD

NMR

VS

RR β PPII γinv γcl

0.08 0.31 0.57 0.04 0.00

0.13 0.39-0.50 0.37-0.48 0 0

0.08 0.35 0.57 0 0

0.13 0.58 0.29 0.00 0.00

0 0.63-0.69 0.31-0.37 0 0

0.10 0.40 0.42 0.04 0.04

a For GFG with VS also, γcl was included in the simulation, as explained in the text.

TABLE 2: 1H Chemical Shifts (ppm) of AFA and GFG in Aqueous Solution at 299 K residue AFA GFG

NH

1

A F A3 G1 F G3

8.56 7.97 8.58 8.44

R

β

4.00 4.63 4.14 3.82/3.71 4.72 3.96/3.92

1.49 3.19 pro-S/3.01 pro-R 1.33 3.19 pro-S/3.01 pro-R

PPII conformational states, respectively, and a smaller and broader peak at about (-78°,-28°) corresponding to RR. From the peak volumes, the relative values of the populations are 13, 58, and 29% for RR, β, and PPII, respectively. These results indicate a significant β-strand propensity of F in a glycine-based context. In Figure 3, the respective φF and ψF distributions of GFG are shown. For PPII, the distributions are close to those obtained for AFA (Figure 3e and f). In addition, the φF distribution of RR shows a maximum at about -70°, with a tail extending to 180° (Figure 3a), in contrast to AFA, which is characterized by two distinct maxima in this region, as previously observed. For β-strands, the φF distribution (Figure 3c) is narrower for GFG than that for AFA, while the ψF distributions of β-strand and RR-type conformations are rather similar (Figures 2b,d and 3b,d). The relative populations of the conformational states for the two molecules are listed in Table 1. NMR. The resonances in the 1H NMR spectra were assigned on the basis of signal multiplicity in the case of GFG and a DQF-COSY experiment in the case of AFA. The assignment is shown in Table 2. 1D spectra showing the signals due to R, β, and NH protons for the two samples are shown in Figure 4. We also measured the AFA chemical shifts at pH 1.6, 5.6, and 7.3 (not shown) and observed an appreciable variation for the NA3 signal. The values observed indicate approximately a 20% population of the cationic form together with the zwitterion at pH 4.0. The population was estimated assuming that the chemical shift is given by the population weighed average of the values due to the cation (recorded at pH 1.6) and to the zwitterion (recorded at pH 7.3) and that the chemical shift difference is only due to the protonation of the C-terminal carboxylate. The 1D NMR spectra were used to determine 3JNH-RH, 3 JRH-β′H(F), and 3JRH-β′′H(F) coupling constants (Table 3), and these data were used to set conformational constraints, as explained in the Materials and Methods section. The amide NH temperature coefficients (∆δ/∆T) of the second and third residues were determined from the corresponding chemical shift variation as a function of temperature (Table 3). We also measured ∆δ/∆T for the C-terminal residue in the case of AFA

at pH 7.3 (not shown) and observed only minor variations from the values reported in Table 3. At this pH, we could not measure ∆δ/∆T of F as the amide signal is not observable due to fast proton exchange with water. Where observable, the amide temperature coefficients of the central residue are comparable to those reported in similar conditions,51,80 while for the C-terminal residue of AFA, our value is significantly different from that reported in ref 51. The high absolute values of the coefficients suggest that NH groups are exposed to solvent exchange and not involved in intramolecular hydrogen bonds. 3 JNH-RH(F) coupling constants were measured at temperatures between 286 K and the highest value at which the amide signal was still a narrow doublet (302 and 317 K for AFA and GFG, respectively). The values increase less than 0.1 Hz/10 K, suggesting the slightly progressive population of the β conformer, characterized by a larger 3J value, at higher temperatures. Similar trends were shown by short peptides subject to conformational redistributions from PPII toward β conformations22,29,42,81 and by many polypeptides, progressively populating the β conformational state upon heating.82 An accurate investigation of the effect of temperature on the conformational equilibrium of AFA and GFG is beyond the scope of this work. The NOE proton distance constraints used in the conformational analysis of the F residue are shown in Table 4a for AFA and Table 5a for GFG. For both peptides, all of the constraints are interresidue sequential NOEs, apart from the intraresidue ΝF-β′F and ΝF-β′′F and the interresidue medium-range NOE ΝΑ3-βΑ1 of AFA. We also considered the antidistance constraints ΝΑ3-RΑ1 for AFA and NF-NG3 and NG3-RG1 for GFG, corresponding to unobserved NOEs.54 For AFA, we performed our conformational analysis using the sample with pH 4.0, although there is a significant population of the cationic form at this pH. The cationic form is less and less populated as the pH increases, but the NF signal is either weak or not observable, as previously noted, with the result that the angular restraint from 3JNH-RH is absent and the number of distance constraints is too small to limit the possible conformational state populations. As a working hypothesis, we assumed that the conformation of phenylalanine in AFA is not affected by the protonation state based on the fact that the NOE cross-peak intensities measured at pH 4.0 are not significantly different from those observable at pH values of 7.3, 5.6, and 1.6. The assumption can be verified in retrospect by comparing NMR results with MD and VCD data which were acquired on the zwitterions and is also supported by the literature.23,25,51 Also for GFG at different pH values, we did not observe significant differences in the NOE cross-peak intensities. In a previous NMR study of AFA in aqueous solution, a cross-peak between ΝΑ3 and RΑ1 protons was observed at 280 K and pH 7.2 and attributed to the γinv conformational state.51 Since we did not observe this peak, even at our lowest temperature, that is, 283 K, we argue that the population of this state is negligibly small in our experimental conditions (as also indicated by MD results). This conclusion is also supported by the relatively high absolute value of the NA3 temperature coefficient (Table 3), indicating exposure to solvent exchange and no intramolecular hydrogen bond. We clustered all of the MD molecules in the three conformational states RR, β, and PPII, defined in the Materials and Methods section, which are reasonably the most populated. It is assumed that the MD simulations give a reasonable description of the structural distribution within a conformational state. This assumption is based on the fact that, according to the literature, different force fields yield comparable mean values

3972


Pizzanelli et al.

Figure 4. 1H NMR spectra of AFA (lower trace) and GFG (upper trace) at 299 K. The NH resonances are shown in (a), the F β protons and A (G) R protons for AFA (GFG) are shown in (b), and the A β protons for AFA, with an intensity reduced by a factor 0.5, are shown in (c).

TABLE 3: Amide Proton Temperature Coefficients (ppb/K) and 1H Coupling Constants (Hz) of AFA and GFG in Aqueous Solution at 299 K AFA GFG

-∆δ/∆TF(ppb/K)

-∆δ/∆TA3 or G3(ppb/K)

6.9 6.7

7.9 7.5

3

JNH-RH(F) (Hz) 7.3 7.3

3

JNH-RH(A3 or G3) (Hz)

3

JRH-β′H(F) (Hz)

7.1 5.9, 5.9

3

JRH-β′′H(F) (Hz)

9.1 9.0

6.2 5.9

TABLE 4: Distance (a) and Angular (b) Constraints for the Central F Residue of AFA at 299 Ka (a)

1 2 3 4 5 6 7 8 9 10

protons

angles involved

rRR

rβ

rPPII

rNOE

RF-NA ΝF- ΝΑ3 ΝΑ3-RΑ1 ΝΑ3-βΑ1 β′F-NA3 β′′F-NA3 ΝF-β′F ΝF-β′′F RA1sNF βA1sNF

ψF φ F, ψ F ψA1, φF, ψF ψA1, φF, ψF ψ F, χ 1 ψ F, χ 1 φ F, χ1 φ F, χ1 ψA1 ψA1

3.52 2.13 4.04 3.82 3.67, 2.59, 3.97 2.57, 3.95, 3.69 3.74, 2.58, 2.88 2.60, 2.85, 3.74 2.28 3.46

2.27 4.34 6.41 6.37 2.57, 3.78, 3.93 3.76, 3.95, 2.58 3.85, 2.72, 3.23 2.74, 3.21, 3.85 2.28 3.46

2.24 4.58 6.25 6.42 2.65, 3.85, 3.95 3.82, 3.97, 2.65 3.60, 2.43, 2.65 2.46, 2.62, 3.60 2.28 3.46

2.2-2.3 3.0-3.5

angle involved

JRR

Jβ

JPPII

7.03

8.61

6.02

3

4.6-5.1 3.1-3.2 3.4-3.5 2.7-2.9 2.4-2.7 2.1-2.3 3.3-3.5

(b)

11

φF

3

JNH-RH(F) 7.3

a The angles involved in each constraint are also reported, together with the calculated average NOE distances ri and coupling constants Ji for states i ) RR, β, and PPII. Distances are given in Å and coupling constants in Hz. For the distances which are dependent on χ1, the three values calculated, assuming that a single χ1 rotamer is populated, are shown in each column, in the order pi,χ1)-60° ) 1, pi,χ1)180° ) 1, and pi,χ1)60° ) 1.

TABLE 5: Distance (a) and angular (b) Constraints for the Central F Residue of GFG at 299 Ka (a)

1 2 3 4 5 6 7 8

protons

angles involved

rRR

rβ

rPPII

rNOE

RF-NG ΝF- ΝG3 ΝG3-RG1 β′F-NG3 β′′F-NG3 ΝF-β′F ΝF-β′′F RG1sNF

ψF φF , ψ F ψG1, φF, ψF ψ F, χ1 ψ F, χ1 φ F , χ1 φ F , χ1 ψG1

3.47 2.25 3.98 3.81, 2.73, 4.07 2.71, 4.06, 3.83 3.67, 2.51, 2.79 2.53, 2.76, 3.68 2.53

2.29 4.30 6.35 2.61, 3.80, 3.94 3.78, 3.95, 2.61 3.91, 2.84, 3.35 2.85, 3.33, 3.92 2.54

2.25 4.59 6.15 2.70, 3.88, 3.97 3.86, 3.99, 2.70 3.60, 2.43, 2.66 2.45, 2.64, 3.60 2.55

2.2-2.3

angle involved

JRR

Jβ

JPPII

7.24

7.74

6.29

3

3.1-3.3 3.3-3.4 2.8-3.0 2.6-2.8 2.4-2.5

(b)

9

φF

3

JNH-RH(F) 7.3

a The angles involved in each constraint are also reported, together with the calculated average NOE distances ri and coupling constants Ji for states i ) RR, β, and PPII. Distances are given in Å and coupling constants in Hz. For the distances which are dependent on χ1, the three values calculated, assuming that a single χ1 rotamer is populated, are shown in each column in the order pi,χ1)-60° ) 1, pi,χ1)180° ) 1, and pi,χ1)60° ) 1.

and widths of φ,ψ distributions for small peptides, in contrast to the populations of the states that depend considerably on the employed theoretical model.19–21,37,83 Therefore, our aim was to derive the relative populations, pi, of each i state, where i ) RR, β, and PPII, compatible with the experimental distance and angular constraints.

Each NOE distance, rNOE, is the population weighted average of the distances of all of the conformational states present according to eq 9, whereas the distance of a given i state is 2 54 averaged over the fast motion as 〈r-3 i 〉 according to eq 7. The treatment assumes equal correlation times, τc, for the peptide in any conformational state and is valid when the degree of

Conformations of Phenylalanine in AFA and GFG angular restriction of the NOE internuclear vector is the same for all of the states and significantly different from zero, as previously discussed. In Tables 4 and 5, for each measured constraint depending on φF and/or ψF and on φF, ψF, ψA1, and ψG1 angles, the NOE distance ri, or the coupling constant Ji, calculated for the i ) RR, β, and PPII, according to eq 8 or 11, are shown. The distances β′F-NA3, β′′F-NA3, β′F-NG3, β′′F-NG3, ΝF-β′F, and ΝF-β′′F are determined by ψF or φF and χ1. Since the latter angle may assume a value of about -60, 180, or 60°, the corresponding distances also depend on the populations of these three rotamers. For these distances, the values calculated according to eq 13, assuming that a single χ1 rotamer is populated, are shown in the tables. According to the MD simulations, for AFA, the ψA1 angular distribution is centered at a single value of about 150° for all of the conformers. Such a value agrees with the measured RA1sNF and βA1sNF experimental distances. GFG shows a ψG1 distribution centered at (150°, which is compatible with the value of the RG1sNF distance observed. Since these distances are insensitive to the conformation of the central residue, they were not used in the determination of relative populations. Our JRR values are significantly larger than 4.8 Hz, the value predicted for R helices from the populations of torsional angles in a database of 85 high-resolution protein structures by Dobson and co-workers.10 This difference is due to the fact that our MD angular distributions of RR conformation show that the φ region ranging between -180 and -120° is considerably populated (Figures 2a and 3a), together with the typical region characterized by φ = -70°. This is not the case in the cited database. On the contrary, Jβ values compare fairly well with the Dobson value of 8.5 Hz for β-strands. Using the procedure outlined in Materials and Methods, we found that the experimental data for AFA are compatible with relative populations 0.13, 0.39-0.50, and 0.37-0.48 for conformers RR, β, and PPII, respectively. RR has a strong preference for χ1 ) -60° (pRR,χ1)-60° g 0.6, pRR,χ1)180° e 0.2, pRR,χ1)60° e 0.3), which qualitatively agrees with data from the backbonedependent rotamer library for proteins.84 In fact, the library records large populations of χ1 ) -60° in the range of φ angles populated by RR, according to our MD simulations, with the dependence on ψ being less critical. For β conformers, our data are compatible with a rather wide range of pβ,χ1)180° and pβ,χ1)-60° values (0.3 e pβ,χ1)180° e 0.8 and 0.1 e pβ,χ1)-60° e 0.7) with a minor population of the rotamer characterized by χ1 ) 60° (pβ,χ1)60° e 0.1). For this conformational state, the rotamer library suggests a more pronounced preference for χ1 ) -60° with respect to that observed here and agrees with our experimental data in finding a non-negligible pβ,χ1)60°. The PPII conformational state tends to preferentially populate χ1 ) 180 and -60°, while χ1 ) 60° is completely disfavored (0.4 e pPPII,χ1)180° e 1, 0 e pPPII,χ1)-60° e 0.6, pPPII,χ1)60° ) 0). According to the library and considering our MD φ,ψ distribution, χ1 ) -60° should be slightly favored over χ1 ) 180°, and a nonsignificant population of the rotamer with χ1 ) 60° is obtained from the library for PPII, in agreement with pPPII,χ1)60° ) 0 obtained from our experiments. The small discrepancies observed between the rotameric preferences illustrated here and those of the backbonedependent rotamer library for proteins could be due to the fact that phenylalanine is exposed to solvent, given the small size of AFA. In fact, it has been shown that the predictive accuracy of side-chain rotamers from the library is smaller for exposed residues than that for buried ones.85

J. Phys. Chem. B, Vol. 114, No. 11, 2010 3973 GFG was treated analogously using the constraints shown in Table 5 and the JRH-β′H(F) and 3JRH-β′′H(F) experimental values shown in Table 3. We found that only β and PPII conformational states are populated, with relative populations of 0.63-0.69 and 0.31-0.37, respectively. The possible sets of populations of χ1 angle are close to those shown by AFA for β (0.3 e pβ,χ1)180° e 0.8, 0 e pβ,χ1)-60° e 0.4, 0.2 e pβ,χ1)60° e 0.3). PPII covers larger ranges of populations in all three rotamers, with values of 0 e pPPII,χ1)180° e 0.8, 0.2 e pPPII,χ1)-60° e 0.9, and 0 e pPPII,χ1)60° e 0.2. A comparison of the populations of the different conformers of AFA and GFG shows that in both cases, β and PPII conformers are significantly populated, with AFA showing a more pronounced population of PPII together with a small fraction of RR. In addition, for states β and PPII, our experimental data are compatible with large ranges of populations of the rotamers characterized by χ1 ) 180 and -60°, while χ1 ) 60° is always significantly less populated. On the contrary, the ranges of rotameric populations for RR are much narrower. All of these results suggest that β and PPII are entropically favored over RR. Vibrational Spectroscopy. The spectra of AFA and GFG have both been reported earlier.43,60 Figure 5 exhibits the 1580-1750 cm-1 region of the IR, isotropic Raman, anisotropic Raman, and VCD spectra of AFA, measured at pD 7.3. Besides the amide I′ band, which covers the region between 1620 and 1690 cm-1, the IR and VCD spectra display a band at 1590 cm-1 assignable to the COO- antisymmetric stretch. In Raman scattering, this stretching gives rise to a totally depolarized band, so that it is only depicted in the anisotropic Raman spectrum. Both Raman spectra exhibit an additional, rather depolarized band at 1610 cm-1, assignable to a (nearly) degenerate ring mode of the phenylalanine side chain. Figure 6 shows the corresponding spectra for GFG, measured at pH 1.7.60 The spectra display a band arising from the C-terminal CO stretching mode, above 1700 cm-1. For both peptides, the isotropic Raman and IR spectra show a clear noncoincidence, in that the higher wavenumber band (mostly assignable to the N-terminal amide I′) is more intense in the isotropic Raman spectrum, whereas the lower wavenumber band (predominantly the C-terminal amide I′) is slightly more intense in the IR spectrum. The anisotropic Raman amide I′ profiles are equally distributed over both bands. The VCD spectra display a clear negative couplet. Altogether, these spectral properties already indicate that the peptides predominantly sample extended conformations, with a substantial fraction adopting PPII-like conformations.79 In a first step, we simulated the amide I′ band profiles of both AFA and GFG, utilizing the distributions obtained from the MD simulations. To this end, we fitted these distributions to a set of two-dimensional Gaussian functions, whose parameters are listed in the Supporting Information. Two Gaussian functions are associated with both the RR (denoted by the subscripts RR1 and RR2) and β-sheet trough (denoted by the subscripts β1 and β2) of the Ramachandran plot, while the PPII distribution is fitted with a single Gaussian. The solid lines in Figure 5 display the result of the spectral simulation for AFA assuming the MD distribution function, neglecting the γinv conformation. The populations are reported in Table 1. The agreement with the experimental data is satisfactory, though not perfect; the corresponding 3JNH-RH(F) coupling constant is 6.9 Hz, which is sensibly lower than the experimental value of 7.3 Hz. The very good reproduction of the VCD signal is particularly meaningful since it is normally verysensitivetosmallchangesoftheconformationaldistribution.38,60

3974


Figure 5. Amide I′ band profile of AFA in the isotropic Raman, anisotropic Raman, IR, and VCD spectra (as indicated) of AFA, measured at a neutral pD and a peptide concentration of 0.2 M. The solid lines result from the simulation described in the text. The spectra have been taken from ref 43.

Generally, a pronounced negative couplet is diagnostic of a substantial fraction in the PPII trough of the Ramachandran plot.65 However, in the case of AFA, one of the β-strand components with φ ) -113.7° and ψ ) 152.7° (i.e., β1) also contributes to this signal since this conformation is on the border between PPII and the β-trough. In fact, the amide I profile of the β1 distribution can be simulated by combining ∼60% of PPII with 40% of β2, though this would not reproduce the 3 JNH-RH coupling constant. Moreover, there is a large uncertainty in the population of the helical conformation since its contribu-

Pizzanelli et al.

Figure 6. Amide I′ band profile of GFG in the isotropic Raman, anisotropic Raman, FTIR, and VCD spectra (as indicated) of GFG, measured at a pD of 2.1 and a peptide concentration of 0.2 M. The solution contained 0.025 M NaClO4, with the ClO4- Raman peak at 934 cm-1 used as an internal wavenumber standard. The spectra and the solid lines resulting from the simulation described in the text were previously reported in ref 60.

tion to the VCD spectrum of the amide I′ band is very small due to the fact that the individual spectra of the two helical distributions produce VCD couplets of opposite sign. We also calculated the amide I profiles assuming fraction values within the ranges obtained from the analysis of the NMR data (Table 1); sampling within such intervals gave amide I profiles quite similar to those obtained using the MD populations.



Figure 7. Experimental (scatter plot) and simulated (solid lines) amide I′ VCD spectra of GFG, measured at acidic pH. The spectra were simulated as described in the text. Different colors represent different secondary structure fractions using the centers and half-widths of distributions obtained from MD simulations: black line: pPPII ) 0.29, pβ1 ) 0.26, pβ2 ) 0.32, pRR1 ) 0.07, pRR2 ) 0.06 (MD populations); red line: pPPII ) 0.34, pβ1 ) 0.30, pβ2 ) 0.36, pRR1 ) 0.00, pRR2 ) 0.00; green line: pPPII ) 0.34, pβ1 ) 0.36, pβ2 ) 0.30, pRR1 ) 0.00, pRR2 ) 0.00; yellow line: pPPII ) 0.34, pβ1 ) 0.41, pβ2 ) 0.25, pRR1 ) 0.00, pRR2 ) 0.00; blue line: pPPII ) 0.34, pβ1 ) 0.46, pβ2 ) 0.20, pRR1 ) 0.00, pRR2 ) 0.00; pink line: pPPII ) 0.34, pβ1 ) 0.51, pβ2 ) 0.15, pRR1 ) 0.00, pRR2 ) 0.00; cyan line: pPPII ) 0.34, pβ1 ) 0.56, pβ2 ) 0.10, pRR1 ) 0.00, pRR2 ) 0.00; gray line: pPPII ) 0.34, pβ1 ) 0.61, pβ2 ) 0.05, pRR1 ) 0.00, pRR2 ) 0.00; dark red line: pPPII ) 0.34, pβ1 ) 0.66, pβ2 ) 0.00, pRR1 ) 0.00, pRR2 ) 0.00; dark green line: pPPII ) 0.41, pβ1 ) 0.59, pβ2 ) 0.00, pRR1 ) 0.00, pRR2 ) 0.00; dark blue line: pPPII ) 0.48, pβ1 ) 0.52, pβ2 ) 0.00, pRR1 ) 0.00, pRR2 ) 0.00.

The amide I′ profiles calculated for GFG using the MD distribution of the φ,ψ angles do not reproduce the experimental data well. This particularly concerns the VCD signal, which has practically zero intensity for the employed conformational mixture, as shown in the first simulation of Figure 7. This poor reproduction is due to the substantial fraction of helical conformations, for which the VCD couplet is positive. Its overlap with the negative couplet of PPII yields a cancellation of the VCD signal. Moreover, the IR band profile is not satisfactorily reproduced either (data not shown). Therefore, in a first step of our analysis, we varied the structural composition and fixed the coordinates of the Gaussian functions to accommodate the amide I′ band profile, as well as the experimental 3JNH-RH(F) coupling constant of the central F residue. In the second simulation, shown in Figure 7 (red line), the RR fraction has been removed and redistributed to the β and PPII regions. The rest of the simulations, excluding the last two, were carried out by varying the two β distributions by 5% each time. The resulting simulation is shown as the dark red curve in Figure 7 and yielded a 3J coupling constant of 7.8 Hz. The amount of β and PPII fractions was varied for the last two simulations to compensate for the rest of the intensity of the VCD profile as well as lower the 3J coupling constant. The best simulation was obtained with pβ1 ) 0.52 and pPPII ) 0.48, producing a 3J coupling constant of 7.5 Hz, which is slightly higher than our experimental value of 7.3 Hz. The isotropic and anisotropic Raman and, to a lesser extent, IR spectra showed negligible change with the procedure. Recently, a comprehensive conformational propensity study combining NMR and vibrational spectroscopic methods concluded that the best simulation (Figure 6) for GFG was characterized by the populations pRR ) 0.10, pβ1 ) 0.40, pPPII ) 0.42, pγinv ) 0.04, and pγcl ) 0.04.60 The structural coordinates of each conformer are given in the Supporting Information. The 3J associated with these parameters is 7.5 Hz. With these populations, we also calculated the

expected NOE distances and found no restraint violations except for the NF-NG3 distance, which is overestimated in the VCD simulation. Discussion The complexity of intrinsically disordered systems, such as those investigated here, requires the use of different experimental and computational techniques to obtain a reliable description of the conformational behavior. To the best of our knowledge, this is the first attempt to reciprocally validate the use of NMR and vibrational spectroscopic data, in combination with results from MD simulations, in the structural studies of flexible oligopeptides. As shown in Table 1, MD simulations for AFA and GFG indicate that the propensity of F is different in AFA and GFG. The simulations predict a dominant PPII sampling for F in AFA, but different types of β-strands are sampled as well. The sampling of R-helical conformations is detectable but not large. For GFG, the conformational equilibrium is shifted toward β-strand conformations. The analysis of the NMR data, including 3 JNH-RH(F), 3JRH-β′H(F), and 3JRH-β′′H(F) coupling constants and NOE distances, together with amide NH temperature coefficients, is in agreement with the MD predictions, although the NMR PPII and RR fractions of AFA and GFG, respectively, are overestimated by the MD simulations. With respect to the amide I′ band profile, we found that the φ,ψ distribution functions derived from MD data reproduced the experimental band profiles satisfactorily for AFA. For GFG, however, the simulated distribution substantially underestimated the amide I′ VCD signal of the amide I′ band and did not satisfactorily reproduce the shape of the IR profile. The measured amide I′ band profile of GFG was eventually fitted with a slightly modified model. On the whole, the different methods give similar results as far as the most populated conformational states are concerned, the discrepancies being within about 15%. This

3976


validates the working hypothesis adopted to analyze the AFA NMR data and concerning the fact that conformation of phenylalanine in AFA is not affected by the protonation state of the molecule. As far as the investigated oligopeptides are concerned, the experimental and computational analysis shows that PPII and β-strand are the most populated conformers; β-strand is dominant in GFG and comparatively less populated in AFA, for which PPII is more favored. These results can be compared with literature data, considering that there is evidence that terminal charges, present in these peptides, have a negligible effect on the conformation of the central residue in tripeptides.23,25,51 For example, Shi et al. derived the propensities of all 20 amino acid residues in a GGXGG host from 3JNH-RH coupling constants.29 They used a two-conformer model with two coexisting conformations assignable to the maxima of PPII and β-strand distributions in the coil libraries reported by Avbelj and Baldwin.7,84 For phenylalanine, they derived a PPII fraction of 0.64. This value is even larger than our highest value of 0.57, obtained for AFA by MD simulations and compatible with the VCD profile. It should be mentioned that our 3JNH-RH(F) coupling value is slightly larger than that reported by Shi et al., but we think that the different models (representative structures versus distributions) are mostly responsible for the discrepancy. Recently, Tran et al. calculated the propensity of amino acid residues in various host-guest systems using a model that describes intrapeptide interactions solely with repulsive terms and strongly emphasizes peptide-solvent interactions.86 For phenylalanine, they found a statistical coil-like distribution with ∼0.35 PPII, 0.20 RR structures, 0.20 β-strand like conformations, and ∼0.1 type II β-turn-like conformations as dominant contributions. Such a high population of RR structures is not in agreement with our data. The amide I′ band profile is particularly sensitive with respect to helical contributions, which exhibit band profiles substantially different from those of PPII and β-strand structures.59 Additionally, in NOESY experiments, such a large helical fraction would result in much larger NF-NA3 and NF-NG3 cross-peak intensities. It is interesting to compare our results with phenylalanine distributions from coil libraries. In doing this, we keep in mind that nearest-neighbor and second-nearest-neighbor effects can influence the propensity of an amino acid residue.8,86 The coil library obtained by Avbelj and Baldwin, for which no restrictions have been applied, suggest a predominance of helical conformations over PPII and β-strand conformations.7,87 The library of the Dobson group gives similar indications.10 However, as shown in detail by Serrano88 and Sosnick and coworkers,8 the distributions of all amino acids depend on which structural motifs of the investigated proteins are considered. Alanine, for example, exhibits a helical propensity when all secondary structures are included but drastically shifts to PPII if helices, sheets, and turns are excluded. For the coil fraction of their library, Jha et al. obtained ∼0.40 PPII and β-strand and ∼0.20 for right-handed R-helical structures.8 Though the helical content is larger than what emerges from our data, these values are closer to our experimental data than what the unrestricted libraries suggest. However, the picture changes if one checks the proposed distributions for phenylalanine, considering only segments with either glycine or alanine as neighbors.89 For AFA, the φ,ψ distributions suggest the dominance of a conformation which at least bears some similarity with an inverse γ-turn with some admixtures of the β-strand, which, as we outlined above, contradicts our data. The

Pizzanelli et al. distribution of GFG exhibits a dominant PPII fraction, with a substantial admixture of right- and even left-handed helical conformations. However, one has to be cautious about these comparisons since the statistical data basis for such segments is generally poor. Altogether, despite their capability to reflect propensities in qualitative terms (if properly restricted), coil libraries cannot substitute for experimental data such as those presented in the current paper. As indicated above, the stabilization of PPII by alanine neighbors is modest, though detectable. The corresponding Gibbs energy is ∼1 kJ/mol, which is approximately 0.5RT. However, this minor contribution comes from a neighbor which is sterically undemanding. The situation is likely to be different if neighbors with more complex side chains are used.8 Moreover, Tran et al. suggest that second-neighbor interactions are even more relevant, particularly for the shifting propensity from helical to extended structures. Generally, their simulations as well as coil library data8 indicate that residues with branched side chains such as valine and isoleucine can increase the β-strand propensity of their respective neighbors. For isoleucine, this has been confirmed experimentally for IAI segments.90 One might argue that the nearest-neighbor interaction between alanine and phenylalanine indicates a violation of the isolated pair hypothesis, which has been considered as a cornerstone of the random coil or statistical coil view of the unfolded state.91 However, two modes of interaction between residues have to be considered. A violation of the isolated pair hypothesis requires that the Gibbs energy difference between different states of a residue X (in our case F) depends on the state adopted by its neighbors (A). This would induce cooperativity into conformational transitions and could stabilize local PPII helices in the unfolded state of proteins. The other possibility is that a change of the neighboring residue (G f A) alters the Gibbs energy landscape of the guest residue (F) independent of its own conformation. In this case, the isolated pair hypothesis still applies, and conformational transitions are noncooperative. Future experiments are necessary to decide which of these two options is valid. Conclusions NMR and vibrational spectroscopic data, in combination with results from MD calculations, were used to obtain information about the conformational distributions of the tripeptides AFA and GFG. They gave similar results, the discrepancies between the populations of conformational states being within about 15%. These results indicate that either NMR or vibrational spectroscopy together with MD data can be confidently used in the structural evaluation even in the case of flexible systems. PPII and β-strand are the most populated conformational states, but β-strand is dominant in GFG and comparatively less populated in AFA, for which PPII is more favored. To the best of our knowledge, the results presented herein provide the first direct experimental evidence for the notion that even such a sterically undemanding residue as alanine, which is likely to exhibit the highest PPII propensity among all natural amino acids (with the exception of proline), can impose its own propensity onto its next neighbor. In view of the abundance of alanine in all types of proteins, this would be, if supported by future studies, a very important finding for the understanding of unfolded peptides and proteins. Acknowledgment. This work was, in part, supported by a research grant from the National Science Foundation (Chem

Conformations of Phenylalanine in AFA and GFG 0804492) to R.S.S. We thank Dr. Franc Avbelj for providing us his coil library distributions. Supporting Information Available: Potential of mean force (PMF) along φF and ψF dihedral angles for AFA and GFG (Figure S1). 1H NMR spectra of AFA at pH 7.3 at 288 K in the peptide concentration range of 0.15-10 mM (Figure S2). Mole fractions and parameters of the φ and ψ distribution functions used to simulate the amide I′ spectra of AFA (Table S1) and GFG (Table S2). Complete refs 4 and 66. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes (1) Shi, Z.; Shen, K.; Liu, Z.; Kallenbach, N. R. Chem. ReV. 2006, 106, 1877. (2) Uversky, V. N. Eur. J. Biochem. 2002, 269, 2. (3) Shortle, D. AdV. Protein Chem. 2002, 62, 1. (4) Dunker, A. K.; et al. J. Mol. Graphics Model. 2001, 19, 26. (5) Uversky, V. N. Natively Unfolded Proteins. In Unfolded Proteins. From Denaturated to Intrinsically Disordered; Creamer, T. P., Ed.; Nova: Nauppauge, NY, 2008. (6) Wright, P. E.; Dyson, H. J.; Lerner, R. A. Biochemistry 1988, 27, 7167. (7) Avbelj, F.; Baldwin, R. L. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 5742. (8) Jha, A. K.; Colubri, A.; Zaman, M. H.; Koide, S.; Sosnick, T. R.; Freed, K. F. Biochemistry 2005, 44, 9691. (9) Swindells, M. B.; MacArthur, M. W.; Thornton, J. M. Nat. Struct. Biol. 1995, 2, 596. (10) Smith, L. J.; Bolin, K. A.; Schwalbe, H.; MacArthur, M. W.; Thornton, J. M.; Dobson, C. M. J. Mol. Biol. 1996, 255, 494. (11) Fiebig, K. M.; Schwalbe, H.; Buck, M.; Smith, L. J.; Dobson, C. M. J. Phys. Chem. 1996, 100, 2661. (12) Meier, S.; Grzesiek, S.; Blackledge, M. J. Am. Chem. Soc. 2007, 129, 9799. (13) Jha, A. K.; Kolubri, A.; Freed, K. F.; Sosnick, T. R. Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 13099. (14) Tran, H. T.; Wang, X.; Pappu, R. V. Biochemistry 2005, 44, 11369. (15) Zaman, M. H.; Shen, M.-Y.; Berry, R. S.; Freed, K. F.; Sosnick, T. R. J. Mol. Biol. 2003, 331, 693. (16) Schweitzer-Stenner, R. Conformational Analysis of Unfolded Peptides by Vibrational Spectroscopy. In Unfolded Proteins. From Denatured States to Intrinsically Disordered; Creamer, T. A., Ed.; Novalis Press: New York, 2008; p 101. (17) Mu, Y.; Stock, G. J. Phys. Chem. B 2002, 106, 5294. (18) Garcia, A. E. Polymer 2004, 120, 885. (19) Gnanakaran, S.; Garcia, A. E. J. Phys. Chem. B 2003, 107, 12555. (20) Mezei, M.; Fleming, P. J.; Srinivasan, R.; Rose, G. D. Proteins: Struct., Funct., Genet. 2004, 55, 502. (21) Hu, H.; Elstner, M.; Hermans, J. Proteins: Struct., Funct., Genet. 2003, 50, 451. (22) Shi, Z.; Olson, C. A.; Rose, G. D.; Baldwin, R. L.; Kallenbach, N. R. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 9190. (23) Eker, F.; Cao, X.; Nafie, L.; Schweitzer-Stenner, R. J. Am. Chem. Soc. 2002, 124, 14330. (24) Eker, F.; Griebenow, K.; Schweitzer-Stenner, R. J. Am. Chem. Soc. 2003, 125, 8178. (25) Eker, F.; Cao, X.; Nafie, L.; Griebenow, K.; Schweitzer-Stenner, R. J. Phys. Chem. B 2003, 107, 358. (26) Park, S.-H.; Shalongo, W.; Stellwagen, E. Protein Sci. 1997, 6, 1694. (27) Woutersen, S.; Hamm, P. J. Phys. Chem. B 2000, 104, 11316. (28) Woutersen, S.; Hamm, P. J. Chem. Phys. 2001, 114, 2727. (29) Shi, Z.; Chen, K.; Liu, Z.; Ng, A.; Bracken, W. C.; Kallenbach, N. R. Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 17964. (30) Zagrovic, B.; Lipfert, J.; Sorin, E. J.; Millett, I. S.; van Gunsteren, W. F.; Doniach, S.; Pande, V. S. Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 11698. (31) Makowska, J.; Rodziewicz-Motowidlo, S.; Baginska, K.; Vila, J. A.; Liwo, A.; Chmurzynski, L.; Scheraga, H. A. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 1744. (32) Makowska, J.; Rodziewicz, S.; Baginska, K.; Makowski, M.; Vila, J. A.; Liwo, A.; Chmurzynˇski, L.; Scheraga, H. A. Biophys. J. 2007, 92, 2904. (33) Schweitzer-Stenner, R.; Measey, T.; Kakalis, L.; Jordan, F.; Pizzanelli, S.; Forte, C.; Griebenow, K. Biochemistry 2007, 46, 1587. (34) Schweitzer-Stenner, R.; Measey, T. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 6649.

J. Phys. Chem. B, Vol. 114, No. 11, 2010 3977 (35) Scholtz, J. M.; Marqusee, S.; Baldwin, R. L.; York, E. J.; Stewart, J. M.; Santoro, M.; Bolen, D. W. Proc. Natl. Acad. Sci. U.S.A. 1991, 88, 2854. (36) Scholtz, J. M.; Baldwin, R. L. Annu. ReV. Biophys. Biomol. Struct. 1992, 21, 95. (37) Graf, J.; Nguyen, P. H.; Stock, G.; Schwalbe, H. J. Am. Chem. Soc. 2007, 129, 1179. (38) Schweitzer-Stenner, R. J. Phys. Chem. B 2009, 113, 2922. (39) Sreerama, N.; Woody, R. W. Protein Sci. 2003, 12, 384. (40) Eker, F.; Griebenow, K.; Cao, X.; Nafie, L.; Schweitzer-Stenner, R. Biochemistry 2004, 43, 613. (41) Rucker, A. L.; Creamer, T. P. Protein Sci. 2002, 11, 980. (42) Hagarman, A.; Measey, T.; Doddasamayajula, R. S.; Dragomir, I.; Eker, F.; Griebenow, K.; Schweitzer-Stenner, R. J. Phys. Chem. B 2006, 110, 6979. (43) Eker, F.; Griebenow, K.; Cao, X.; Nafie, L.; Schweitzer-Stenner, R. Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 10054. (44) Rucker, A. L.; Pager, C. T.; Campbell, M. N.; Qualls, J. E.; Creamer, T. P. Proteins: Struct., Funct., Genet. 2003, 53, 68. (45) Chou, P. Y.; Fasman, G. D. Biochemistry 1974, 13, 211. (46) Wood, S. J.; Wetzel, R.; Martin, J. D.; Hurle, M. R. Biochemistry 1995, 13, 211. (47) Petty, S. A.; Decatur, S. M. J. Am. Chem. Soc. 2005, 127, 13488. (48) Azriel, R.; Gazit, E. J. Biol. Chem. 2001, 36, 34156. (49) Tsai, H.-H.; Zanuy, D.; Haspel, N.; Gunasekaran, K.; Ma, B.; Tsai, C.-J.; Nussinov, R. Biophys. J. 2004, 87, 146. (50) Reches, M.; Gazit, E. Science 2003, 300, 625. (51) Motta, A.; Reches, M.; Pappalardo, L.; Andreotti, G.; Gazit, E. Biochemistry 2005, 144, 14170. (52) Duan, Y.; Wu, C.; Chowdury, S.; Lee, M. C.; Xiong, G.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T.; Caldwell, J.; Wang, J.; Kollman, P. J. Comput. Chem. 2003, 24, 1999. (53) Karplus, M. J. Chem. Phys. 1959, 30, 11. (54) Bru¨schweiler, R.; Blackledge, M.; Ernst, R. R. J. Biomol. NMR 1991, 1, 3. (55) Nikiforovich, G. V.; Prakash, O.; Gehrig, O.; Hruby, V. J. J. Am. Chem. Soc. 1993, 115, 3399. (56) Cuniasse, P.; Raynal, I.; Yiotakis, A.; Dive, V. J. Am. Chem. Soc. 1997, 119, 5239. (57) Meirovitch, H.; Meirovitch, E. J. Phys. Chem. 1996, 100, 5123. (58) Aramini, J. M.; Mujeeb, A.; Ulyanov, N. B.; Germann, M. W. J. Biomol. NMR 2000, 18, 287. (59) Schweitzer-Stenner, R. J. Phys. Chem. B 2004, 108, 16965. (60) Hagarman, A.; Measey, T. J.; Mathieu, D.; Schwalbe, H.; Schweitzer-Stenner, R. J. Am. Chem. Soc. 2010, 132, 540. (61) Piotto, M.; Saudek, V.; Sklena´r´, V. J. Biomol. NMR 1992, 2, 661. (62) Marat, K. Spin Works 3, Version 3.0.0.0; University of Manitoba: Winnipeg, 2008. (63) Wishart, D. S.; Sykes, B. D. Methods Enzymol. 1994, 239, 363. (64) van der Velde, F.; Pereira, L.; Rollema, H. S. Carbohydr. Res. 2004, 339, 2309. (65) Measey, T.; Schweitzer-Stenner, R. Chem. Phys. Lett. 2005, 408, 123. (66) Case, D. A.; et al. AMBER 9 University of California: San Francisco, CA, 2006. (67) Lee, M. C.; Duan, Y. Proteins 2004, 55, 620. (68) Wang, J.; Cieplak, P.; Kolman, P. A. J. Comput. Chem. 2000, 24, 1999. (69) Mu, Y.; Kosov, D. S.; Stock, G. J. Phys. Chem. B 2003, 107, 5064. (70) Jorgensen, W. L. J. Am. Chem. Soc. 1981, 103, 335. (71) Andersen, H. C. J. J. Chem. Phys. 1980, 72, 2384. (72) Andrea, T. A.; Swope, W. C.; Andersen, H. C. J. Chem. Phys. 1983, 79, 4576. (73) Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; DiNola, A.; Haak, J. R. J. Chem. Phys. 1984, 81, 3684. (74) Nilges, M.; Clore, G. M.; Gronenborn, M. Biopolymers 1990, 29, 813. (75) Wang, A. C.; Bax, A. J. Am. Chem. Soc. 1996, 118, 2483. (76) Bru¨schweiler, R.; Roux, B.; Blackledge, M.; Griesinger, C.; Karplus, M.; Ernst, R. R. J. Am. Chem. Soc. 1992, 114, 2289. (77) Pizzanelli, S.; Forte, C.; Monti, S.; Schweitzer-Stenner, R. J. Phys. Chem. B 2008, 112, 1251. (78) Gu¨ntert, P.; Braun, W.; Billeter, M.; Wu¨thrich, K. J. Am. Chem. Soc. 1989, 111, 3997. (79) Torii, H.; Tasumi, M. J. Raman Spectrosc. 1998, 29, 81. (80) Merutka, G.; Dyson, H. J.; Wright, P. E. J. Biomol. NMR 1995, 5, 14. (81) Schweitzer-Stenner, R.; Eker, F.; Griebenow, K.; Cao, X.; Nafie, L. J. Am. Chem. Soc. 2004, 126, 2768. (82) Yang, W. Y.; Larios, E.; Gruebele, M. J. Am. Chem. Soc. 2003, 125, 16220. (83) Garcia, A. E.; Sanbonmatsu, K. Y. Proc. Natl. Acad. Sci. U. S. A. 2002, 99, 2782.

3978


(84) Avbelj, F.; Baldwin, R. L. Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 19067. (85) Bower, M. J.; Cohen, F. E.; Dunbrack, R. L., Jr. J. Mol. Biol. 1997, 267, 1268. (86) Tran, H. T.; Wang, X.; Pappu, R. V. Biochemistry 2005, 44, 11369. (87) Avbelj, F. Private communication. (88) Serrano, L. J. Mol. Biol. 1995, 254, 322.

Pizzanelli et al. (89) Sosnick, T. R. Sampling library 2007; http://godzilla.uchicago.edu/cgi. (90) Chen, K.; Liu, Z.; Zhou, C.; Shi, Z.; Kallenbach, N. R. J. Am. Chem. Soc. 2005, 127, 10146. (91) Flory, P. J. Statistical Mechanics of Chain Molecules; Wiley & Sons: New York, 1969.

JP907502N

Conformations of Phenylalanine in the Tripeptides AFA and GFG

Recommend Documents