Effects of side chains in helix nucleation differ fromhelix propagationStephen E. Miller, Andrew M. Watkins, Neville R. Kallenbach, and Paramjit S. Arora1

Department of Chemistry, New York University, New York, NY 10003

Edited* by S. Walter Englander, University of Pennsylvania, Philadelphia, PA, and approved March 25, 2014 (received for review December 11, 2013)

Helix–coil transition theory connects observable properties of theα-helix to an ensemble of microstates and provides a foundationfor analyzing secondary structure formation in proteins. Classicalmodels account for cooperative helix formation in terms of anenergetically demanding nucleation event (described by the σ con-stant) followed by a more facile propagation reaction, with corre-sponding s constants that are sequence dependent. Extensivestudies of folding and unfolding in model peptides have led tothe determination of the propagation constants for amino acids.However, the role of individual side chains in helix nucleation hasnot been separately accessible, so the σ constant is treated as in-dependent of sequence. We describe here a synthetic model thatallows the assessment of the role of individual amino acids in helixnucleation. Studies with this model lead to the surprising conclu-sion that widely accepted scales of helical propensity are not pre-dictive of helix nucleation. Residues known to be helix stabilizersor breakers in propagation have only a tenuous relationship toresidues that favor or disfavor helix nucleation.

synthetic helices | helix propensity

The α-helix is the most prevalent secondary structure in pro-teins and can form extremely rapidly. Helix formation is thuscrucial in early steps of protein folding, and a complete de-scription of the kinetics and thermodynamics of α-helix for-mation is fundamental for understanding protein folding (1).Theoretical models of the helix–coil transition consider helixformation to proceed in two steps: initial nucleation of a helicalsequence, denoted by the parameter σ in the Zimm–Braggnotation (2), followed by more favorable helix propagation,denoted by s parameters. This distinction identifies the ener-getically unfavorable organization of three consecutive aminoacid residues to form a helical nucleus as the slow step in helixformation (2–4). Helix propagation, in contrast, refers to theaddition of the next hydrogen bond to a preformed helix (Fig.1A). Zimm–Bragg or equivalent theories posit that formationof short peptide helices in water is unfavorable because thelarge decrease in entropy required for nucleation is not adequatelycompensated by the enthalpic gain from forming a small numberof hydrogen bonds.The ability of different peptide sequences to adopt helical

conformations has been rigorously investigated, and the stabilityof α-helices can be estimated from widely used scales of helicalpropensity (5). These scales are important for our understandingof protein structure, folding, and function. The classical studiesfor determination of helix propensities have used peptides,coiled-coils, and protein models for host–guest studies in whicha guest residue is systematically substituted at a site in a hoststructure (6–12). Helix–coil transition theory then relates changesin the conformational stability to microscopic helix propensities ors constants for individual residues. The results provide a quanti-tative basis for evaluating the behavior of peptide and proteinhelices; for example, the s constant for alanine is strongly helixstabilizing, whereas those of valine and other β-branched residuesare destabilizing (11, 13). However, even the most detailedinvestigations of the stability and dynamics of helix formationtreat the energetic contribution of helix nucleation as independent

of local sequence effects (14). The ability to differentiate indi-vidual σ values from individual s values could provide a deeperunderstanding of the impact of individual side chains on helixformation than provided by current models (6, 12).Here, we describe an approach that estimates the population

of N-terminal tripeptide sequences organized in an α-helixnucleus as a function of individual guest residues. The keydifference between this investigation and classical measures ofpropensity is that our approach assesses the ability of a givenresidue to favor or disfavor nucleation; literature propensitiesare largely derived by measuring how the stability of a preformedhelix responds to different residues in a peptide sequence. Nu-cleation and propagation effects are intrinsically convoluted. Thecurrent approach offers a direct measure of helix nucleation andallows nucleation effects to be interrogated independently ofpropagation. Although previous studies have implemented cor-rection factors to account for structural effects on nucleation incalculations of helix propensities, such as N-caps and C-caps(15), no independent and general measure of nucleation hasbeen available (6, 12, 16, 17). The results of our study are in factsurprising, as they suggest that steric effects in alkyl side chains,such as those from β-branching, do not have a strong impact onhelix nucleation. This result stands in contrast to the observednegative effects of β-branched residues on helix propagation (13,18, 19).

Results and DiscussionOur approach to assess helix nucleation uses hydrogen bondsurrogate (HBS) α-helices in which the N-terminal main-chainhydrogen bond is replaced with a covalent bond (Fig. 1B) (20). Inearlier reports, we described HBS helices in which the hydrogenbond is replaced with a carbon–carbon bond (21). Characterization

Significance

Complete description of the kinetics and thermodynamics ofα-helix formation is fundamental to the understanding ofprotein folding because α-helices are the most abundant classof secondary structures and are implicated in the earliest stepsof the folding process. Kinetic models of protein folding sug-gest that helix folding is rate-limited by formation of a nucleusfollowed by rapid propagation. The influence of individualresidues on propagation has been evaluated in numerousmodel peptides and proteins. Here, we describe a syntheticmodel that enables experimental assessment of the role ofindividual residues in helix nucleation. Our results suggestthat amino acids contribute differently to nucleation thanto propagation.

Author contributions: P.S.A. designed research; S.E.M. and A.M.W. performed research;S.E.M., A.M.W., N.R.K., and P.S.A. analyzed data; and S.E.M., A.M.W., N.R.K., and P.S.A.wrote the paper.

The authors declare no conflict of interest.

*This Direct Submission article had a prearranged editor.1To whom correspondence should be addressed. E-mail: arora@nyu.edu.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1322833111/-/DCSupplemental.

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of these synthetic helices by CD and 2D-NMR spectroscopy, aswell as single crystal X-ray diffraction analysis, reveals that they

faithfully mimic the conformation of canonical α-helices (21, 22).Importantly, HBS helices are able to inhibit intracellular pro-tein–protein interactions mediated by α-helical domains, sup-porting the hypothesis that these compounds reproduce thestructure and function of protein α-helices (23, 24). To analyzethe effect of different residues on α-helix formation, we preparedan HBS analog with a disulfide linkage whose rates of formationcould be monitored under aqueous conditions (25). We con-jectured that the rates of formation of this linkage would providea unique probe for examining biophysical parameters related tohelix formation. Because the disulfide–HBS (dsHBS) linkagemimics the intramolecular hydrogen bond in α-helices, we hy-pothesized that the bisthiol (bt) to disulfide (ds) oxidation wouldprovide a direct measure of helix nucleation (Fig. 1C). Rates ofhelix formation for model peptides have been measured by ul-trafast spectroscopies and fall in the nanosecond range (14, 26–29). The rates of disulfide formation are much slower (on theorder of minutes) under our reaction conditions (30). The dra-matically slower timescale for disulfide formation suggests thatsequence-dependent differences in the rate of disulfide forma-tion reflect preequilibrium populations: residues with highernucleating propensity favor disulfide formation.Disulfide-linked HBS helices can be derived from oxidation of

the parent bisthiol peptides allowing a facile approach to controlthe conformation of the peptide (31–34). We based our initialpeptide design on a short segment from the p53 activation do-main: XQEG*FSDLWKLLS (1), where X and G* represent thedsHBS-constrained residues (35). The p53 sequence was chosenbecause it has relatively few side-chain contacts such as ionicbridges, which may bias the results. We have previously charac-terized a number of p53 HBS analogs by CD and NMR spec-troscopies allowing us to predict potential aggregation issues thatcan affect stabilized constructs (36–38). The bisthiol p53 peptideis weakly helical in aqueous buffers at 295 K. CD spectroscopy(Fig. 2A) shows that the p53 dsHBS 1 is highly helical com-pared with the parent bt-peptide (25). We selected A, G, D, I,K, L, P, and V as the guest residues for this investigation. Thisselection includes representative aliphatic straight chain andβ-branched residues along with positively and negatively chargedside chains.After initial experiments, peptide 1 was modified by replacing

the native glutamic acid and phenylalanine residues with lysineand alanine, respectively, to obtain 2Λ: XΛKG*ASDLWKLLS.The new sequence was designed to avoid potential side-chaininteractions between the guest residues (Λ) and the corre-sponding i + 3 position; lysine was incorporated to increase watersolubility of the host. The second position was chosen for theintroduction of guests because the conformation of this residueis implicated in helix induction near the N terminus (39, 40).The helical conformation of ds-2A: XAKG*ASDLWKLLS wasassessed using a combination of 1D NMR, total correlationspectroscopy, and rotating-frame nuclear Overhauser effectcorrelation spectroscopy (ROESY) studies in aqueous solutions(SI Text, Table S1, and Fig. S1). The ROESY spectra revealednuclear Overhauser effect (NOE) cross-peaks indicative of ahelical structure, including sequential NH-NH (i and i + 1) andseveral longer range NOEs (between i and i + 3/i + 4) (SI Text,Table S2). Importantly, all backbone ϕ dihedral angles, calcu-lated from 3JNHCHα coupling constants, are in the expected rangefor helical conformations (SI Text, Table S1) (41, 42). The cou-pling constants observed for the residues within the macrocycledo not differ from the rest of the chain, indicating that thedisulfide constraint is faithfully inducing an α-helical conforma-tion. The solution structure of ds-2A was determined from 48ROESY cross-peaks and 11 calculated ϕ angles using MonteCarlo conformational search in Macromodel 2014. An overlayof the 20 lowest energy structures for ds-2A is shown in Fig. 2B.Notably, the disulfide-constrained macrocycle does not perturb the

Fig. 1. Preorganization of three residues into an α-turn conformation is theenergy-demanding step in helix formation. (A) Models of the helix–coiltransition consider helix formation to proceed in two steps consisting ofnucleation and propagation steps. (B) In hydrogen bond surrogate (HBS)α-helices, the nucleus is organized by replacement of a main chain i to i + 4hydrogen bond with a covalent bond. The dsHBS helices feature a reversibledisulfide linkage. (C) Possible intermediates for the conversion of bisthiol I todsHBS IV include bisthiol II in α-turn conformation and disulfide III as theconstrained helix nucleus. Rates of conversion of bisthiol to disulfide weremeasured as a function of variable residue Λ.

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N terminus of the α-helix. Overall, together with CD spectroscopy,the NMR studies confirm stabilization of a major α-helicalconformation in dsHBS-constrained peptides.The bisthiol and HBS peptides were synthesized as shown in

SI Text, Fig. S2. We used mild oxidation conditions consisting of2% (vol/vol) DMSO to oxidize the bisthiols (Fig. 2C) (25, 30). Toseparate the closely related bisthiol and dsHBS peptides onHPLC and to quench the thiol groups, we treated the reactionmixture with a maleimide derivative (43). Adequate separationof the bisthiol and disulfide peptides on HPLC allowed us toquantify the rates of disulfide formation for each sequence from

analysis of HPLC peak areas (Fig. 3A and Fig. S3). The initialrates of disulfide formation are plotted in Fig. 3B, and the tab-ulated data are presented in Table 1.We find that the nucleation propensity of alanine is stronger

than that of glycine, whereas the disulfide bond formation withproline as guest is too slow to measure accurately. These resultsare consistent with known relationships: glycine is a highly flex-ible residue, whereas proline aids helicity only as an N-cap res-idue and not at other positions in the helix. These results alsoindicate that conformation of the macrocycle influences rates ofthe disulfide formation. If the rates of the bond formation were

Fig. 2. Conformational analysis and synthesis of unconstrained peptides. (A) CD spectroscopy suggests that the disulfide-linked (ds) HBS peptide is highlyhelical compared with the parent bisthiol (bt). The CD studies were performed with 50 μM peptides in 1 mM PBS. (B) NMR-derived structures of ds-2A. Viewsof 20 lowest energy structures are shown with carbon, nitrogen, and oxygen atoms in gray, blue, and red, respectively. The disulfide linkage is shown inyellow color. (C) Schematic for the oxidation reaction. The conversion of bt-2Λ → ds-2Λ was affected under mild oxidative conditions; the unreacted bisthiolwas quenched with maleimide 3.

Table 1. Comparison of dsHBS rate of formation to literature helix propensity values

Peptide†Rate of bt → ds conversion,

μM/min‡ Rates relative to 2GΔΔG from propensity,

kcal/mol§

XAKG*ASDLWKLLS (2A) 0.20 ± 0.02 2.86 −1.88-–D––––––––––––––– (2D) 0.06 ± 0.01 0.86 −1.00-–G––––––––––––––– (2G) 0.07 ± 0.005 1.00 0.00-–I–––––––––––––––– (2I) 0.15 ± 0.01 2.14 −1.18-–K––––––––––––––– (2K) 0.08 ± 0.01 1.14 −1.52-–L––––––––––––––– (2L) 0.19 ± 0.01 2.71 −1.60-–P––––––––––––––– (2P) –– –– >5.00-–V––––––––––––––– (2V) 0.20 ± 0.01 2.86 −0.83

†X and G* represent the dsHBS constraint.‡Calculated from HPLC analysis.§From ref. 19.

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independent of the macrocycle conformation, substitutionof a single glycine in place of an alanine would not causea significant effect. It is likely that the peptide chain beyondthe putative macrocycle is influencing the preequilibriumconformation but because the bisthiol peptide is largely non–α-helical, we expect this effect to be subtle and equivalent forevery mutant.Leucine and alanine sequences are similar in their disulfide

formation rates, as might be expected from the literature pro-pensity values (Table 1) (6). These results provide useful metricsto gauge the potential of our synthetic model as a probe of helix

nucleation. Surprisingly, our investigations reveal that β-branchedresidues are not detrimental to α-helix nucleation. Indeed, therate of the disulfide formation with valine is nearly the same asthat of alanine and leucine, whereas isoleucine leads to a slightdecrease. Charged residues, lysine and aspartate, slow down thereaction rate to the level of glycine. Because aspartic acid is aknown helix breaker whereas lysine is considered to be a helixstabilizing residue (44, 45), these results suggest that chargedresidues potentially participate in long-range interactions. Al-though the sequences of this study were designed to minimizecontext dependence, backbone interactions cannot be completelyruled out. CD spectroscopy shows that five of the eight dsHBSsequences have very similar helical content; substitution of gly-cine, proline, and aspartic acid lowers the helicity (Fig. 3C). Weconjecture that helical stability of the constrained sequence is nota major determinant of disulfide rate formation. Comparison ofthe lysine and aspartic acid sequences provides support for thishypothesis, because these sequences display similar rates of disul-fide formation, whereas the constrained peptides show differenthelical stabilities. Charged residues at the end of helices canpositively or negatively influence helix stability based on theirinteractions with the helix macrodipole (46). However, suchmacrodipolar interactions should not influence the process ofhelix nucleation because the helix is not yet organized.To obtain theoretical support for our experimental observa-

tions, we calculated activation barriers to formation of an i toi + 4 hydrogen bond in peptide sequences using metadynamicssimulations (47, 48). Helix–coil transitions have been previouslyinvestigated using molecular-dynamics simulations to analyze helixpropensity and nucleation timescales, but, to our knowledge, theeffect of point mutations on helix nucleation has not been ex-plored systematically (28, 39, 49). We determined the impact ofdifferent residues on the formation of an α-turn in an acetylatedand methylamidated model peptide sequence, Ac-AΛA-NHMe.We used Schrodinger’s 2012 distribution of Desmond 3.1 (50) toconduct 50-ns metadynamics simulation on the tripeptide usingthe Amber forcefield ff12SB and associated monovalent ionparameters (51, 52). Two-dimensional free-energy surfaceswere determined and activation energies were identified by in-spection (Fig. 4). The activation energies stabilize as simulationlength increases, suggesting that the simulation converged at 15 ns(Fig. S4). We also performed the simulations in triplicate andmeasured the average rmsd between the resulting free-energy sur-faces (Fig. S4). Analysis reveals that all guest (Λ) residues, exceptproline, sample dihedral angles corresponding to left- and right-handed α-helix, β-strand, and polyproline II (PPII) regions of theRamachandran plot (Fig. 4A). The plot of the proline containingtripeptide features only the α and PPII minima (Fig. 4B). The [ϕ,ψ]plots for the other 18 guest residues in Ac-AΛA-NHMe are shownin Fig. S5. The weighted fraction of α, β, and PPII populationsfor different guest residues is plotted in Fig. 4C. To calculatethe barrier for helix formation, we compared the height of theshortest peak between the lowest energy basin correspondingto the PPII or β dihedral angles to the α-helical dihedral foreach residue (Fig. 4D). The PPII dihedral angles were foundto be the lowest energy conformation for most guest residuesin our calculations.The results of these calculations correlate with the experi-

mental data and suggest that the barrier to preorganization ofthe α-helical conformation does not follow propensity scales.Although the activation energies reflect starting populations andenergy profiles of the α and β or PPII conformations, they pro-vide a gauge for estimating the residue-dependent difficulty ofadopting an α-helical conformation. The calculated ΔG‡ valuesidentify guest residues with fast and slow folding rates butsuggest that rates of several others are not readily distin-guishable. Overall, the calculations support the experimental

Fig. 3. Analysis of bisthiol to disulfide conversion. (A) Rates of the bt-to-dsconversion were analyzed by HPLC, with tryptophan as an internal control.Representative HPLC results for peptide 2 with alanine (Λ = A) as the guestresidue are shown. (B) Plots of bt-to-ds conversion for different guest resi-dues. (C) CD spectra of sequences with different guest residues illustrate thatthe helical content of most sequences, with the exception of sequences withΛ = G, P, and D, is identical. The CD studies were performed with 50 μMpeptides in 5 mM KF, pH 7.3.

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observations that helical propensity scales are not applicableto helix nucleation.

ConclusionsWe have developed a synthetic model to evaluate propensitiesfor helix nucleation. Although the organization of an α-turnleading to an intramolecular hydrogen bond between the C=Oof the ith residue and the amide NH of the i + 4th residueis considered the slow step in helix formation, there are noreported experimental attempts to segregate effects of individualside chains on helix nucleation. A large number of studies havefocused on the propensity of amino acid residues to propagatea preformed helix in peptide and protein models. To experi-mentally interrogate the nucleation step, we replaced the intra-molecular hydrogen bond at the N-terminus of a short α-helix bya disulfide linkage whose rates of formation from the analogousbisthiol could be measured as a function of individual residues inthe turn. We also performed metadynamics simulations on tri-peptide sequences to estimate the barrier to formation of a hy-drogen bond between the ith and the i + 4th residues.The thrust of these experimental and computational studies

reveals for the first time (to our knowledge) that helix nucleationdiffers from propagation in an important aspect: although fold-ing of a chain to create a nucleus is sensitive to the effects ofa rigid template (as observed in crystal packing and growth), theprocess of nucleation minimizes what must be relatively minorenthalpic and entropic penalties due to side-chain packing. Thelarge entropic barrier that must be overcome to organize threeconsecutive residues predominates in nucleation in markedcontrast to the side-chain steric constraints that impact helixpropagation (18).

MethodsGeneral. Commercial-grade reagents and solvents were used without furtherpurification, except as indicated. Peptides were purified using a BeckmanCoulter HPLC equipped with a System Gold 168 Diode array detector,

equipped with a reversed-phase C-18 column, and buffers containing 0.1%TFA in acetonitrile and 0.1% TFA inwater. Purified peptideswere analyzed byliquid chromatography (LC)/MS on an Agilent 1100 Series LCMSD system.High-resolution MS data were obtained using an Agilent 6224 Accurate-Mass TOF LC/MS. HPLC analysis for the conversion of bt to ds peptides wasperformed using an Agilent 1200 series HPLC system with a Thermo HypersilC-8 column (50 × 2 mm, 3 μm; 5–65% acetonitrile in water over 10 min). CDspectra for dsHBS helices were recorded on an AVIV 202SF CD spectrometerequipped with a temperature controller using a 1-mm length cell and a scanspeed of 5 nm/min. Samples were run in 5 mM KF buffer (pH 7.3) or 0.1× PBSbuffer (pH 7.3) at a concentration of 50 μM ds-2Λ (concentration determinedby Trp residue absorbance, e = 5,560 cm−1·M−1 at 280 nm). The spectra wereaveraged over 10 scans with the baseline subtracted from analogous con-ditions to those of the samples. NMR experiments were performed usinga Bruker Avance 600-MHz spectrometer. IR analysis was performed usinga Thermo Nicolet 6700 FT-IR spectrometer, equipped with Smart ITR. Solidswere dissolved in methanol and dried on smart sensor.

Representative Procedure for the Oxidation of bt-2Λ → ds-2Λ. Disulfide pep-tides are prone to oxidation and were stored under inert atmosphere aslyophilized powders. Concentrations of purified bt-2Λ peptides were de-termined under acidic conditions (0.1% aqueous TFA) to minimize oxidation.Lyophilized bisthiol peptides (200 nmol) were dissolved in 40 μL of DMSO ina centrifuge tube, and oxidation was initiated by addition of 2 mL of oxi-dation buffer (800 mM ammonium bicarbonate, 840 mM acetic acid, pH 6.0).The oxidation buffer was supplemented with 50 μM tryptophan as aninternal control for HPLC studies. Fifty-microliter aliquots were removedfrom the reaction mixture after set intervals (T = 0, 1, 2, 5, 10, 20, and 30min), quenched with 25 μL of 1.4 mM maleimide 3 in H2O, and analyzedby HPLC.

Metadynamics Simulations. Acetylated and methylamidated peptide struc-tures were initialized with tleap (AmberTools12) using the ff12SB force fieldand monovalent ion parameters from Joung and Cheatham (51, 52). Struc-tures were neutralized by adding chloride or sodium ions and surrounded bya truncated octahedron of TIP3P water with a buffer distance of 8.0 Å. Theresulting topology and input coordinates were converted to Desmond cmsformat for simulations with Desmond 3.1.

The ϕ and ψ dihedral angles of the guest residue were chosen as thereaction coordinates for metadynamics column variables. The standard

Fig. 4. Results of metadynamics simulation to evaluate barrier to the formation of an i to i + 4 hydrogen bond in a model peptide (AcAΛA-NHMe) asa function of different guest residues. (A and B) Two-dimensional free-energy surfaces for Λ = alanine and proline are shown with the others included in SIText. The Ramachandran plots of all residues show low energy basins for the α, β, and polyproline II (PPII) dihedral space with the exception of proline, wherethe PPII and α spaces dominate. (C) Weighted populations of all low-energy basins corresponding to the α, β, and PPII dihedral angles. (D) The activationenergy barrier between the lowest energy region corresponding to the PPII space and α-helical dihedral angles.

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Desmond relaxation protocol was conducted on each tripeptide: 2,000 stepsminimization with 10 steps steepest descent with 50 kcal/mol restraints onpeptides, 2,000 steps minimization with 10 steps steepest descent withoutrestraints, 12 ps of Berendsen NVT simulation at 10 K, and finally 24 ps ofBerendsen NVT equilibration at 300 K. A 50-ns metadynamics simulation wasconducted on each peptide, depositing 5°-wide, 0.01-kcal-high Gaussiansevery 12 fs. The resulting 2D free-energy surfaces were analyzed manually.The transition state connecting the α-helical conformation to the nonhelical

minimum energy conformation was identified and the activation energywas calculated.

ACKNOWLEDGMENTS. We thank David Rooklin and Yingkai Zhang for theiradvice on metadynamics calculations, Stephen Joy for assistance withthe structure calculations, and the National Institutes of Health (GrantR01GM073943) for financial support. A.M.W. is supported by a MargaretStrauss Kramer fellowship.

1. Dill KA, MacCallum JL (2012) The protein-folding problem, 50 years on. Science338(6110):1042–1046.

2. Zimm BH, Bragg JK (1959) Theory of the phase transition between helix and randomcoil in polypeptide chains. J Chem Phys 31(2):526–535.

3. Qian H, Schellman JA (1992) Helix-coil theories: A comparative study for finite lengthpreferences. J Phys Chem 96(10):3987–3994.

4. Lifson S, Roig A (1961) On the theory of helix-coil transitions in polypeptides. J ChemPhys 34(6):1963–1974.

5. Munoz V, Serrano L (1997) Development of the multiple sequence approximationwithin the AGADIR model of alpha-helix formation: Comparison with Zimm-Braggand Lifson-Roig formalisms. Biopolymers 41(5):495–509.

6. Rohl CA, Chakrabartty A, Baldwin RL (1996) Helix propagation and N-cap propensitiesof the amino acids measured in alanine-based peptides in 40 volume percent tri-fluoroethanol. Protein Sci 5(12):2623–2637.

7. Blaber M, et al. (1994) Determination of alpha-helix propensity within the context ofa folded protein. Sites 44 and 131 in bacteriophage T4 lysozyme. J Mol Biol 235(2):600–624.

8. Wojcik J, Altmann KH, Scheraga HA (1990) Helix-coil stability constants for the nat-urally occurring amino acids in water. XXIV. Half-cystine parameters from randompoly(hydroxybutylglutamine-CO-S-methylthio-L-cysteine). Biopolymers 30(1-2):121–134.

9. Padmanabhan S, Marqusee S, Ridgeway T, Laue TM, Baldwin RL (1990) Relative helix-forming tendencies of nonpolar amino acids. Nature 344(6263):268–270.

10. O’Neil KT, DeGrado WF (1990) A thermodynamic scale for the helix-forming ten-dencies of the commonly occurring amino acids. Science 250(4981):646–651.

11. Lyu PC, Liff MI, Marky LA, Kallenbach NR (1990) Side chain contributions to the sta-bility of alpha-helical structure in peptides. Science 250(4981):669–673.

12. Richardson JM, Lopez MM, Makhatadze GI (2005) Enthalpy of helix-coil transition:Missing link in rationalizing the thermodynamics of helix-forming propensities of theamino acid residues. Proc Natl Acad Sci USA 102(5):1413–1418.

13. Lyu PC, Sherman JC, Chen A, Kallenbach NR (1991) Alpha-helix stabilization by naturaland unnatural amino acids with alkyl side chains. Proc Natl Acad Sci USA 88(12):5317–5320.

14. Neumaier S, Reiner A, Büttner M, Fierz B, Kiefhaber T (2013) Testing the diffusingboundary model for the helix-coil transition in peptides. Proc Natl Acad Sci USA110(32):12905–12910.

15. Aurora R, Rose GD (1998) Helix capping. Protein Sci 7(1):21–38.16. Lopez MM, Chin D-H, Baldwin RL, Makhatadze GI (2002) The enthalpy of the alanine

peptide helix measured by isothermal titration calorimetry using metal-binding toinduce helix formation. Proc Natl Acad Sci USA 99(3):1298–1302.

17. Sun JK, Penel S, Doig AJ (2000) Determination of α-helix N1 energies after addition ofN1, N2, and N3 preferences to helix/coil theory. Protein Sci 9(4):750–754.

18. Creamer TP, Rose GD (1992) Side-chain entropy opposes alpha-helix formation butrationalizes experimentally determined helix-forming propensities. Proc Natl Acad SciUSA 89(13):5937–5941.

19. Chakrabartty A, Kortemme T, Baldwin RL (1994) Helix propensities of the amino acidsmeasured in alanine-based peptides without helix-stabilizing side-chain interactions.Protein Sci 3(5):843–852.

20. Patgiri A, Jochim AL, Arora PS (2008) A hydrogen bond surrogate approach for sta-bilization of short peptide sequences in alpha-helical conformation. Acc Chem Res41(10):1289–1300.

21. Wang D, Chen K, Kulp JL, III, Arora PS (2006) Evaluation of biologically relevant shortalpha-helices stabilized by a main-chain hydrogen-bond surrogate. J Am Chem Soc128(28):9248–9256.

22. Liu J, Wang D, Zheng Q, Lu M, Arora PS (2008) Atomic structure of a short alpha-helixstabilized by a main chain hydrogen-bond surrogate. J Am Chem Soc 130(13):4334–4337.

23. Kushal S, et al. (2013) Protein domain mimetics as in vivo modulators of hypoxia-in-ducible factor signaling. Proc Natl Acad Sci USA 110(39):15602–15607.

24. Patgiri A, Yadav KK, Arora PS, Bar-Sagi D (2011) An orthosteric inhibitor of the Ras-Sos interaction. Nat Chem Biol 7(9):585–587.

25. Miller SE, Kallenbach NR, Arora PS (2012) Reversible α-helix formation controlled bya hydrogen bond surrogate. Tetrahedron 68(23):4434–4437.

26. Serrano AL, Tucker MJ, Gai F (2011) Direct assessment of the α-helix nucleation time.J Phys Chem B 115(22):7472–7478.

27. Lin MM, Mohammed OF, Jas GS, Zewail AH (2011) Speed limit of protein foldingevidenced in secondary structure dynamics. Proc Natl Acad Sci USA 108(40):16622–16627.

28. De Sancho D, Best RB (2011) What is the time scale for α-helix nucleation? J Am ChemSoc 133(17):6809–6816.

29. Huang C-Y, Klemke JW, Getahun Z, DeGrado WF, Gai F (2001) Temperature-

dependent helix-coil transition of an alanine based peptide. J Am Chem Soc 123(38):

9235–9238.30. Tam JP, Wu CR, Liu W, Zhang JW (1991) Disulfide bond formation in peptides by

dimethyl sulfoxide. Scope and applications. J Am Chem Soc 113(17):6657–6662.31. Haney CM, Loch MT, Horne WS (2011) Promoting peptide α-helix formation with

dynamic covalent oxime side-chain cross-links. Chem Commun 47(39):10915–10917.32. Bredenbeck J, Helbing J, Kumita JR, Woolley GA, Hamm P (2005) α-Helix formation in

a photoswitchable peptide tracked from picoseconds to microseconds by time-re-

solved IR spectroscopy. Proc Natl Acad Sci USA 102(7):2379–2384.33. Ihalainen JA, et al. (2008) α-Helix folding in the presence of structural constraints. Proc

Natl Acad Sci USA 105(28):9588–9593.34. Li M, Yamato K, Ferguson JS, Gong B (2006) Sequence-specific association in aqueous

media by integrating hydrogen bonding and dynamic covalent interactions. J Am

Chem Soc 128(39):12628–12629.35. Kussie PH, et al. (1996) Structure of the MDM2 oncoprotein bound to the p53 tumor

suppressor transactivation domain. Science 274(5289):948–953.36. Patgiri A, Joy ST, Arora PS (2012) Nucleation effects in peptide foldamers. J Am Chem

Soc 134(28):11495–11502.37. Mahon AB, Arora PS (2012) Design, synthesis and protein-targeting properties of

thioether-linked hydrogen bond surrogate helices. Chem Commun (Camb) 48(10):

1416–1418.38. Henchey LK, Porter JR, Ghosh I, Arora PS (2010) High specificity in protein recognition

by hydrogen-bond-surrogate α-helices: Selective inhibition of the p53/MDM2 com-plex. ChemBioChem 11(15):2104–2107.

39. Young WS, Brooks CL, 3rd (1996) A microscopic view of helix propagation: N and C-

terminal helix growth in alanine helices. J Mol Biol 259(3):560–572.40. Cochran DAE, Doig AJ (2001) Effect of the N2 residue on the stability of the α-helix for

all 20 amino acids. Protein Sci 10(7):1305–1311.41. Wang Y, Nip AM, Wishart DS (1997) A simple method to quantitatively measure

polypeptide JHNH α coupling constants from TOCSY or NOESY spectra. J Biomol NMR10(4):373–382.

42. Pardi A, Billeter M, Wüthrich K (1984) Calibration of the angular dependence of the

amide proton-C alpha proton coupling constants, 3JHN alpha, in a globular protein.

Use of 3JHN alpha for identification of helical secondary structure. J Mol Biol 180(3):

741–751.43. Brantley RK, Haeffner-Gormley L, Wetlaufer DB (1984) Preparation of a positively

charged maleimide and its application to the high-performance liquid chromato-

graphic separation of the tryptic peptides of lysozyme. J Chromatogr A 295(1):

220–225.44. Huyghues-Despointes BM, Scholtz JM, Baldwin RL (1993) Effect of a single aspartate

on helix stability at different positions in a neutral alanine-based peptide. Protein Sci

2(10):1604–1611.45. Yang JX, Zhao K, Gong YX, Vologodskii A, Kallenbach NR (1998) Alpha-helix nucle-

ation constant in copolypeptides of alanine and ornithine or lysine. J Am Chem Soc

120(41):10646–10652.46. Shoemaker KR, Kim PS, York EJ, Stewart JM, Baldwin RL (1987) Tests of the helix

dipole model for stabilization of alpha-helices. Nature 326(6113):563–567.47. Laio A, Gervasio FL (2008) Metadynamics: A method to simulate rare events and re-

construct the free energy in biophysics, chemistry and material science. Rep Prog Phys

71(12):126601.48. Ensing B, De Vivo M, Liu Z, Moore P, Klein ML (2005) Metadynamics as a tool for

exploring free energy landscapes of chemical reactions. Acc Chem Res 39(2):73–81.49. Daggett V, Levitt M (1992) Molecular dynamics simulations of helix denaturation.

J Mol Biol 223(4):1121–1138.50. Bowers KJ, et al. (2006) Scalable algorithms for molecular dynamics simulations on

commodity clusters. Proceedings of the 2006 ACM/IEEE Conference on Super-

computing (ACM, Tampa, FL), p 84.51. Case DA (2012) AMBER 12 (Univ of California, San Francisco).52. Joung IS, Cheatham TE, 3rd (2008) Determination of alkali and halide monovalent ion

parameters for use in explicitly solvated biomolecular simulations. J Phys Chem B

112(30):9020–9041.

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