Characterizing the First Steps of Amyloid Formation for the ccβ Peptide

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Characterizing the First Steps of Amyloid Formation for the cc Peptide Birgit Strodel, Anthony W. Fitzpatrick, Michele Vendruscolo, Christopher M. Dobson, and David J. Wales* ,† UniVersity Chemical Laboratories, Lensfield Road, Cambridge CB2 1EW, United Kingdom and CaVendish Laboratory, UniVersity of Cambridge, Madingley Road, Cambridge CB3 0HE, United Kingdom ReceiVed: February 11, 2008; ReVised Manuscript ReceiVed: May 27, 2008 We employ constant-temperature and replica exchange molecular dynamics to survey the free energy landscape of the cc peptide using a united-atom potential and an implicit solvent representation. Starting from the experimental coiled-coil structure we observe R to conversion on increasing the temperature, in agreement with experiment. Various -sheet trimers are identified as free energy minima, including one that closely resembles the amyloid -sheet model previously proposed from experimental data. We characterize two alternative pathways leading to -sheets. The first proceeds via direct R to conversion without dissociation of the trimer, and the second can be classified as a dissociation/reassociation pathway. 1. Introduction Many human diseases are known to arise as a consequence of protein misfolding, and the largest group of these is associated with protein aggregation into amyloid fibrils. 1–3 Well known examples include Alzheimer’s and Parkinson’s diseases, the transmissible Creutzfeldt-Jakob Disease, and type II diabetes. Amyloid aggregates are known to be fibrillar in nature with a cross -sheet structure, where the -strands are perpendicular to the long fiber axis with the backbone hydrogen bonds stabilizing the sheets propagating along the direction of the fiber. 4–9 Although considerable progress has been made toward the elucidation of the structure and properties of amyloid fibrils, less is known about the process of amyloid formation. It has been suggested that amyloid formation is a generic feature of polypeptide chains and is not limited to the 20 or so proteins associated with clinical disorders. 10 Despite the diversity among the primary sequences and native secondary structures of amyloidogenic polypeptides, the characteristics shared by all amyloid fibrils suggest that there are common physicochemical origins for the aggregation process and related assembly pathways. 9,11 To test this suggestion de novo protein design provides a powerful tool, which helps to elucidate the funda- mentals of the sequence-to-structure relationship of proteins. 12–14 To explore the mechanistic details of amyloid formation it is useful to find short peptide sequences 15 that adopt a native-like fold and can be converted to amyloid fibrils. On the basis of these considerations Kammerer et al. designed a 17-residue peptide, cc, for which the R-helical coiled-coil design was chosen as the native-fold motif. 13 The validity of the cc design was established by determining its crystal structure at 277 K, which revealed a bundle of three parallel R-helices that coil around each other, as shown in Figure 1a (Protein Data Bank code 1s9z). It was demonstrated that cc converts into amyloid fibrils on increasing the temperature to 310 K, and a detailed molecular model for the fibrillar state was proposed. 13 We used the experimental data of Kammerer et al. to construct a -sheet model for the cc trimer using the CNSsolve software. 16 The resulting structure is shown in Figure 1b and will be referred to as the amyloid -sheet model in the remainder of this paper. From kinetic studies and small sequence changes for cc, 13 as well as from the design of a dimeric cc variant, 17 the importance of specific interactions for the kinetics of amyloid formation have been examined. However, the exact R to conversion and aggregation pathways have yet to be characterized. * To whom correspondence should be addressed. E-mail: dw34@ cam.ac.uk. University Chemical Laboratories. Cavendish Laboratory. Figure 1. Structure of the cc trimer in (a) the experimental coiled- coil structure and (b) the amyloid -sheet model, which was constructed from experimental data 13 employing the CNSsolve software. 16 The residues are colored according to their physicochemical properties: blue, basic; red, acidic; gray, hydrophobic; green, polar. J. Phys. Chem. B 2008, 112, 9998–10004 9998 10.1021/jp801222x CCC: $40.75 2008 American Chemical Society Published on Web 07/23/2008

Transcript of Characterizing the First Steps of Amyloid Formation for the ccβ Peptide

Characterizing the First Steps of Amyloid Formation for the cc� Peptide

Birgit Strodel,† Anthony W. Fitzpatrick,‡ Michele Vendruscolo,† Christopher M. Dobson,† andDavid J. Wales*,†

UniVersity Chemical Laboratories, Lensfield Road, Cambridge CB2 1EW, United Kingdom and CaVendishLaboratory, UniVersity of Cambridge, Madingley Road, Cambridge CB3 0HE, United Kingdom

ReceiVed: February 11, 2008; ReVised Manuscript ReceiVed: May 27, 2008

We employ constant-temperature and replica exchange molecular dynamics to survey the free energy landscapeof the cc� peptide using a united-atom potential and an implicit solvent representation. Starting from theexperimental coiled-coil structure we observe R to � conversion on increasing the temperature, in agreementwith experiment. Various �-sheet trimers are identified as free energy minima, including one that closelyresembles the amyloid �-sheet model previously proposed from experimental data. We characterize twoalternative pathways leading to �-sheets. The first proceeds via direct R to � conversion without dissociationof the trimer, and the second can be classified as a dissociation/reassociation pathway.

1. Introduction

Many human diseases are known to arise as a consequenceof protein misfolding, and the largest group of these is associatedwith protein aggregation into amyloid fibrils.1–3 Well knownexamples include Alzheimer’s and Parkinson’s diseases, thetransmissible Creutzfeldt-Jakob Disease, and type II diabetes.Amyloid aggregates are known to be fibrillar in nature with across �-sheet structure, where the �-strands are perpendicularto the long fiber axis with the backbone hydrogen bondsstabilizing the sheets propagating along the direction of thefiber.4–9 Although considerable progress has been made towardthe elucidation of the structure and properties of amyloid fibrils,less is known about the process of amyloid formation. It hasbeen suggested that amyloid formation is a generic feature ofpolypeptide chains and is not limited to the 20 or so proteinsassociated with clinical disorders.10 Despite the diversity amongthe primary sequences and native secondary structures ofamyloidogenic polypeptides, the characteristics shared by allamyloid fibrils suggest that there are common physicochemicalorigins for the aggregation process and related assemblypathways.9,11 To test this suggestion de novo protein designprovides a powerful tool, which helps to elucidate the funda-mentals of the sequence-to-structure relationship of proteins.12–14

To explore the mechanistic details of amyloid formation it isuseful to find short peptide sequences15 that adopt a native-likefold and can be converted to amyloid fibrils.

On the basis of these considerations Kammerer et al. designeda 17-residue peptide, cc�, for which the R-helical coiled-coildesign was chosen as the native-fold motif.13 The validity ofthe cc� design was established by determining its crystalstructure at 277 K, which revealed a bundle of three parallelR-helices that coil around each other, as shown in Figure 1a(Protein Data Bank code 1s9z). It was demonstrated that cc�converts into amyloid fibrils on increasing the temperature to310 K, and a detailed molecular model for the fibrillar statewas proposed.13 We used the experimental data of Kammereret al. to construct a �-sheet model for the cc� trimer using the

CNSsolve software.16 The resulting structure is shown in Figure1b and will be referred to as the amyloid �-sheet model in theremainder of this paper. From kinetic studies and small sequencechanges for cc�,13 as well as from the design of a dimeric cc�variant,17 the importance of specific interactions for the kineticsof amyloid formation have been examined. However, the exactR to � conversion and aggregation pathways have yet to becharacterized.

* To whom correspondence should be addressed. E-mail: [email protected].

† University Chemical Laboratories.‡ Cavendish Laboratory.

Figure 1. Structure of the cc� trimer in (a) the experimental coiled-coil structure and (b) the amyloid �-sheet model, which was constructedfrom experimental data13 employing the CNSsolve software.16 Theresidues are colored according to their physicochemical properties: blue,basic; red, acidic; gray, hydrophobic; green, polar.

J. Phys. Chem. B 2008, 112, 9998–100049998

10.1021/jp801222x CCC: $40.75 2008 American Chemical SocietyPublished on Web 07/23/2008

Additional insights into the amyloid formation pathway canbe obtained from computational studies. Various simulationtechniques combined with an all-atom or a coarse-graineddescription have been applied to aggregation in systems suchas the A�16-22 fragment of the Alzheimer’s peptide,18–25 theamyloidogenic KFFE peptide,26–29 the peptide fragmentTTR105-115 of transthyretin,30 and the peptide sequenceGNNQQNY from the yeast prion Sup35.31–35 A temperature-dependent R to � transition and subsequent assembly into�-hairpin aggregates has previously been observed in moleculardynamics (MD) simulations of cc� represented by a coarse-grained potential.36 However, in this study Ding et al. found noevidence to support the amyloid �-sheet model of Kammereret al.13

In the present work we employ replica exchange moleculardynamics37 (REMD) and constant-temperature MD to surveythe free energy landscape of the cc� trimer using theCHARMM19 force field38 as an atomistic representation of thepeptide and the implicit solvent potential EEF1.39 It has beendemonstrated that this combination of potentials reliably modelsthe secondary structure of a broad range of proteins40–42 andalso provides a balanced description for the detailed interplaybetween the solvation and intermolecular forces governing theprocess of protein aggregation.43 Starting from the experimentalcoiled-coil structure, we observe the R to � conversion of thepeptides and characterize various stable �-sheet trimers, includ-ing one that agrees with the experimental model. We alsoidentify two alternative, temperature-dependent pathways for�-sheet formation.

2. Methods

The N-acetylated cc� peptide, CH3CO-Ser-Ile-Arg-Glu-Leu-Glu-Ala-Arg-Ile-Arg-Glu-Leu-Glu-Leu-Arg-Ile-COO-, was rep-resented by a united-atom force field, CHARMM19,38 and theimplicit solvent model EEF1.39 The dynamics were propagatedusing the Langevin method with a time step of δt ) 1 fs and areduced friction coefficient of � ) 1 ps-1, which acceleratesthe conformational sampling.44 It has been shown recently thata reduced friction coefficient mainly enhances local conforma-tional exploration without the crossing of significant barriers,whereas solvent viscosity appears to play a less important rolewhen the crossing of substantial kinetic barriers is involved.45

Similar conclusions were drawn from studies examining howviscosity affects the barrier crossing kinetic rates in isomerizationtransitions46 and protein folding.47–50 One of the studies alsoreported that there is no evidence that different pathways maybe sampled as a function of solvent viscosity.50 These findingsprovide confidence that a reduced friction coefficient of� ) 1 ps -1 results in a thermodynamically accurate descriptionof the system and also does not affect the conformationalpathways. To model constant concentration conditions andprevent the peptides from drifting away it was necessary toconfine the system by repulsive walls. We used a sphericalcontainer to impose a confining potential for an atom locatedat r with the form51

Vc(r)) 4πεR5r [( σ

r-R)10- ( σ

r+R)10] (1)

where r ) |r| and r ) 0 is the center of the sphere with radiusR. The parameters σ and ε were chosen to be 1 Å and1 kcal mol-1, respectively.29 The potential (1) guarantees short-range repulsive interactions between peptide atoms and the innerwalls of the container. The container radius was chosen to beR ) 50 Å, which corresponds to a molecular concentration of

10 mM. This concentration is about 2 orders of magnitude higherthan in the experiment of Kammerer et al.13 to reduce thecomputational cost.

We used REMD,37 as implemented in the MMTSB tool set,52

to explore the conformational space of the cc� trimer. In theREMD protocol multiple simulations of the same system(replicas) are run simultaneously at different temperatures. Everyτ time steps an attempt is made to swap temperatures betweentwo different replicas i and j. The exchanges are accepted withprobability min{1, exp(-∆)}, where ∆ ) (1/kBTi - 1/kBTj)× (Ej - Ei) kB is the Boltzmann constant, Ti and Ei denote thetemperature and potential energy of replica i, respectively, andj is typically replica i + 1 at the same time step. Thetemperatures for the replicas were exponentially spaced betweena minimum value, Tmin, and a maximum value, Tmax. Thisprocedure allows for an improved sampling of the conforma-tional space at low temperatures since crossing potential energybarriers is facilitated at higher temperatures, and the resultingconformational changes migrate into the lower T replicas.53

We considered 16 replicas between 220 and 600 K, whichwere started from the experimental coiled-coil structure of thecc� trimer. Twenty thousand MD steps were performed forequilibration before data collection followed by a productionphase of 200 ns at each temperature, involving 100 000 replicaexchange cycles. The acceptance ratio for exchanges wasuniform in the temperature range considered with valuesbetween 0.15 and 0.2. Several order parameters, such as thepotential energy, the radius of gyration, and the CR root-mean-square distance (rmsd) from the coiled-coil structure and fromthe amyloid �-sheet model (Figure 1), were collected duringthe REMD simulations and analyzed using the weightedhistogram analysis method.54 The latter methodology combinesthe data from all replicas to extract the multicanonical ensembleaverages and calculates the heat capacity and free energy surface(FES) at a given temperature as a function of the specified orderparameters. For some of the structures collected during theREMD simulation we performed a secondary structure analysisemploying the continuous assignment implementation of thedefined secondary structure method (DSSPcont).55,56

3. Results and Discussion

Stability of the Coiled-Coil Structure. Starting from theexperimental coiled-coil structure of the cc� trimer we per-formed 10 independent 40 ns MD simulations at temperaturesranging from 280 to 420 K to investigate the stability of thisstructure for the potential in question. To this end, we calculatedthe time dependence of the CR rmsd from the coiled-coilstructure, rmsdR, which is shown for the MD trajectories at 280,300, 320, 340, 380, and 420 K in Figure 2a. To check whetherthe amyloid �-sheet in Figure 1b is formed, we also monitoredthe CR rmsd from this structure (rmsd�), which is shown inFigure 2b.

At 280 K the coiled-coil structure is stable withinrmsdR < 2 Å, whereas for the trajectories at 300 and 320 KrmsdR increases to about 5 Å. This deviation from the initialstructure has only a small effect on rmsd�, which fluctuatesslightly around its average value of 17 Å at these temperatures.Inspection of structures sampled along the MD trajectory at300 K reveals that the individual R-helices undergo thermalmotion causing distortions of the coiled-coil structure, whilethe R-helices stay intact. The stability of the R-helices preventsthe coiled-coil structure from complete disruption due to theattractive interhelical interactions. At T ) 320 K the R-helicesstart to unwind, causing the breakdown of the coiled-coil

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structure. However, at this temperature and also at 330 K (datanot shown) this is a slow process. Even after 40 ns about 70%of the residues are still in the R state and rmsdR has not risenabove 6 Å. For temperatures of 340 K and higher, the increasedthermal motion of the individual peptides causes a substantialbreakdown of the coiled-coil structure before the R-helices startto unwind. However, we emphasize that the trimer nevercompletely dissociates for any of the MD trajectories attemperatures up to 420 K. Inspection of structures sampled alongthe MD trajectory at 340 K shows that for the first 10 ns theR-helices are stable but thermal fluctuations result in an increaseof rmsdR to 10 Å. Thereafter, the R-helices begin to transforminto structures exhibiting bends as well as � character. For thehigher temperatures of 380 and 420 K the R-helices convertwithin nanoseconds into partially extended conformations withsignificant �-sheet content. The time dependence of rmsd�reveals that at these temperatures structures are formed thatapproach the amyloid �-sheet geometry with rmsd� < 10 Å.The conformations around t ) 7.5 ns from the 380 K run comeclosest to the model structure, and snapshots from this trajectoryare shown in Figure 3. After only 3 ns the R-helices are partiallyconverted to the � state at the C-termini of the three peptides,which start to form an antiparallel �-sheet at t ) 3.5 ns. Att ) 7.5 ns a �-sheet is formed that closely resembles the amyloid�-sheet but with the neighboring �-strands aligned differentlyfrom the reference structure.

From these results we conclude that for temperatures below300 K the coiled-coil structure is stable for the potential inquestion, which agrees well with the experimental result.13 Thetemperature of 380 K, for which the R to � transition is observedin our MD simulations, will overestimate TRf�. As mentionedabove, at 340 K the peptides already partially adopt the � state,which might eventually lead to formation of a �-sheet. However,at this temperature the completed R to � transition will probablytake place on a microsecond time scale, which would require acomputation time of around a couple of months for standardMD simulation techniques. Even longer simulation times wouldbe necessary to explore the long-time behavior of the coiled-coil trimer at temperatures between 300 and 340 K, for whichour MD simulations show small instabilities of the crystal

structure and where the R to � transition is observed experi-mentally.13 To explore the energy landscape of the cc� systemmore effectively, simulation techniques are needed to acceleratethe MD method, such as umbrella sampling,57 REMD,37

conformational flooding,58 metadynamics,59 or acceleratedMD,60 just to name a few. An alternative approach would be touse sampling methods based upon geometry optimization andunimolecular rate theory, such as discrete path sampling.61–63

Conformational Space of the cc� Trimer. We performedfurther REMD simulations to explore the conformational spaceof the cc� trimer more extensively. The resulting configurationalheat capacity of the system, CV(T), is plotted together with Rg(T)in Figure 4. At T ) 440 K the radius of gyration rises sharplyto Rg ) 22.5 Å, which is associated with a peak in CV(T).Inspection of the free energy minima for temperatures above440 K reveals that the system is a mixture of individual cc�peptides resulting from dissociation of the trimer and various�-sheet-rich aggregates, which are still present even at theseelevated temperatures. For the dissociated phase the distance

Figure 2. Forty nanosecond trajectories from molecular dynamicssimulations ranging from T ) 300 to 420 K (the color code is given atthe bottom), which were started from the coiled-coil structure of thecc� trimer. The plots show the time dependence of (a) the CR rmsdfrom the initial coiled-coil structure and (b) the CR rmsd from theamyloid �-sheet.

Figure 3. Snapshots from the molecular dynamics trajectory at380 K showing R to � conversion of the cc� trimer.

Figure 4. Temperature dependence of (a) the radius of gyration, Rg,and (b) the configurational heat capacity, CV, computed from replicaexchange molecular dynamics simulations for the cc� trimer. Thedissociation temperature, Td ) 440 K, is inferred from the peak in CV.

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between the three monomers is mainly controlled by theconfining sphere with radius R ) 50 Å. Thus, Rg ) 22.5 Åreflects the coexistence of cc� monomers and aggregates above440 K, which we will refer to as the dissociation temperature,Td, of the coiled-coil state. For T < Td the configurational heatcapacity is CV ≈ 2 kcal mol-1/K, which suggests that substantialstructural changes in the cc� trimer take place. For T > Td theheat capacity is significantly lower, suggesting that more gradualchanges in the structure are occurring.

To identify the free energy minima at 340 K (our estimateof TRf� from standard MD), several free energy surfaces wereinspected as a function of various order parameters. We findthat a combination of the CR rmsd from the amyloid �-sheettrimer and from the coiled-coil structure discriminates bestbetween the various free energy minima. The resulting FES isshown for the last 100 ns of the REMD simulation in Figure 5.For this time window and temperature the coiled-coil structureor structures similar to it are not apparent as free energy minima.Analysis of the structures collected during the last 100 ns ofthe REMD simulation reveals that during that time the R-helicalstate is scarcely sampled. From our constant-temperature MDsimulations we know that the coiled-coil structure is stable attemperatures below 300 K. These results indicate that thesampling time of 200 ns is not sufficient to obtain a globallyequilibrated result for the system in question despite using anaccelerated MD technique and implicit solvent model. The FESreveals the existence of multiple free energy minima in the rangeof 4 < rmsd� < 22 Å and 9 < rmsdR < 16 Å, for which typicalstructures are shown in Figure 5 and labeled A-F. Structure Fis an antiparallel �-sheet trimer, which is close to the amyloid�-sheet model in Figure 1b. Both structures have the peptidesorganized in the same way with an optimal pairing of hydro-phobic with hydrophobic residues, acidic with basic residues,and the polar N-termini solvent exposed. The rmsd� value of6 Å is due to the flexibility of the N-termini of the three�-strands, which is not accounted for in the ideal amyloid�-sheet model in Figure 1b. We expect that this flexibility willbe reduced for larger �-sheets and even more in the amyloidfibril, where several sheets are stacked forming the protofibril.

The other structures A-E are also cc� trimers rich in �-sheetstructure, where the strands are not as optimally aligned as forstructure F. These structures contain unfavorable residue pairs,such as hydrophobic with acidic or basic, acidic with acidic, orbasic with basic. One would expect these structures to be lessstable than the �-sheet F due to the proximity of like charges.However, a deficiency of the EEF1 potential is that it overes-timates the attraction between like-charged side chains.43,64

Another difference compared to structure F is that most of thestructures A-E have two neighboring strands aligned parallelwith the third one antiparallel. Unlike structures D, E, and F,which are fully extended �-sheets, structures A, B, and C areonly partially in the �-sheet conformation with the other residuesadopting irregular conformations (B and C) or turn motifs (A),producing additional conformational flexibility. Structure B isparticularly flexible, giving rise to several minima on the FES,which differ in their parallel/antiparallel alignment. StructureA is very similar to the �-hairpin aggregates of cc� that wereobserved by Ding et al.36

Stability of the �-Sheet Trimers. To investigate the stabilityof the �-sheet trimers A-F we performed constant-temperature20 ns MD simulations at T ) 300, 340, 380, and 420 K, startingfrom the structures shown in Figure 5. During the simulationswe monitored the CR rmsd from the initial structure, rmsd0, theCR rmsd from the amyloid �-sheet, rmsd�, and the radius ofgyration, Rg. The time-dependent behavior of rmsd� shows thatnone of the structures transformed to the amyloid �-sheet Fduring these runs. We also found that the � to R transformationdoes not occur at temperatures of 300 K or above and that allthe �-sheet trimers are stable against dissociation for temper-atures up to 420 K since Rg < 18 Å throughout each run.

The time dependence of rmsd0 is shown in Figure 6 for thesix structures A-F. The �-sheets A, B, and C are less stablethan D, E, and F. A is most flexible, with rmsd0 > 5 Å for eachtemperature. However, inspection of the structures along thefour trajectories reveals that the �-sheet is stable throughouteach one, and the rmsd0 fluctuations are caused by the peptide,for which only one half is in the � state. The other half of thispeptide is able to move significantly and switches between fully

Figure 5. Free energy surface at 340 K for the cc� trimer in terms of the CR rmsd from the �-sheet model, rmsd�, and from the experimentallyobserved coiled-coil structure, rmsdR. The energy scale (in kcal mol-1) is given on the left. Typical structures for the free energy minima are shownand labeled A-F.

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extended and �-hairpin conformations. Structures B and C arestable at 300 and 340 K but unstable above 340 K, with rmsd0

rising from 5 to 10 Å. Structure B transforms to structure Cand back for T ) 380 K and to the fully extended �-sheet ofstructure C. Structure C, on the other hand, converts to structureB at t > 10 ns for 380 K and also to the fully extended �-sheetat 420 K. Thus, structures B and C are not formed independentlyand elevated temperatures promote their transformation into thefully extended �-sheet. Structures D, E, and F, on the otherhand, are �-sheet conformations, which are stable at all thetemperatures in question. Occasionally rmsd0 rises above 5 Å,which can be explained by fluctuations in the overlaying partsof the peptides in the off-register �-sheets. On the time scale ofthese runs conversion between the �-sheet trimers C, D, E, andF was not observed, suggesting that these structures are formedindependently from each other.

Pathways for r to � Conversion of the cc� Trimer.Understanding the aggregation pathways involved in amyloidformation at an atomistic level will provide information aboutthe intra- and intermolecular interactions that promote andstabilize the highly organized amyloid fibrils. In the case ofcc� we found several pathways for the R to � conversiontransforming the native-like coiled-coil structure into a �-sheettrimer. One such pathway is shown in Figure 3 using snapshotsfrom the 40 ns MD trajectory at T ) 380 K, which was startedfrom the coiled-coil structure. This pathway proceeds withoutdissociation of the trimer and without formation of interveningirregular structures, i.e., it is a direct R to � conversion. Similarpathways can be found by extracting trajectories from theREMD simulation, which led to the �-sheet structures A-F.Two different types of pathways have been characterized: aninternal pathway, as shown in Figure 3, and a pathwayproceeding via dissociation and then reassociation of themonomers, which are at least partially in a � state.

Examples of these two pathway types are shown in Figure 7for the formation of the �-sheets D and F. Formation of Dfollows the internal pathway with the temperature of the REMDtrajectory lying in the range 220 K < T < 450 K andRg < 15 Å throughout the run. The temperature for the REMDtrajectory varies with time as replicas exchange betweendifferent values. Hence, this is not a true dynamical path; wesimply present the time sequences from REMD as plausiblesuggestions of likely behavior. Analysis of the secondarystructure of the cc� peptides along this pathway shows that the

R-helices of the coiled-coil trimer are directly converted into�-sheets without sampling other structures. For two of thepeptides this conversion happens within 5 ns, and the thirdpeptide adopts a partial �-sheet conformation commencing fromthe N-terminus after only 1 ns. The final structure D is thenformed after 38 ns without disruption of the already formed�-sheet. Visual inspection of the early structures reveals thatonce parts of the cc� peptides are converted into the � state,these regions are very prone to aggregate to form a �-sheet,which then further promotes the R to � transformation.

The similarity between the internal pathways found fromconstant-temperature MD and REMD shows that it is possibleto suggest mechanistic details from REMD even though thepathways extracted from REMD do not provide a true dynamicalpath. The instantaneous temperature jumps along such a REMDpathway are relatively small since only neighboring replicas areallowed to exchange according to the REMD protocol. For thesystem in question the average instantaneous change in tem-perature is 20 K below Td and 30 K above it. However, tem-perature changes of this order probably serve to facilitate escapefrom kinetic traps rather than opening up unrealistic pathways.

A dissociation/reassociation pathway is shown for the forma-tion of the �-sheet F in the right column of Figure 7. For thefirst 50 ns the temperature for this REMD trajectory is abovethe dissociation temperature of the coiled-coil structure withvalues between 450 and 600 K. The value of Rg(t) ≈ 30 (10 Å for 0 < t < 50 ns shows that the system is dissociatedduring this time. From the secondary structure analysis we seethat the cc� monomers at elevated temperatures prefer irregularconformations with bends, but as soon as the temperature islowered they adopt the � state. Most of the structures in thesequence are then �-hairpins, as for times between 2 and 5 ns,25 and 30 ns, or 40 and 42 ns. When the temperature is furtherlowered for t > 50 ns the three cc� peptides remain in the �state and then aggregate, yielding the �-sheet F.

From the temperatures of the two trajectories consideredabove we conclude that the R to � transition from the coiled-coil cc� to the amyloid fibril at the experimental temperatureof 310 K is more likely to follow the internal pathway ratherthan the dissociation/reassociation pathway. This conclusion isstrengthened when we take into account the fact that the cc�concentration in our simulation is about 2 orders of magnitudehigher than in the experiment.13 This elevated concentration willraise the reassociation probability in the MD simulation.

Figure 6. CR rmsd from the initial structure observed in 20 ns molecular dynamics trajectories at T ) 300 (black), 340 (red), 380 (green), and420 K (blue). These molecular dynamics simulations were started from �-sheets A-F.

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Sampling methods that allow us to extract approximate rateconstants and identify the rate-limiting steps, such as discretepath sampling,61–63 will be used to analyze the two types ofpathways in future work. This approach has recently providednew insight for aggregation of the GNNQQNY peptide,35 anda similar analysis should be possible for cc�. It also remains tobe seen whether new pathways become feasible if two or morecc� trimers interact with each other. In particular, we wouldlike to know what the critical sheet size is for formation of aprotofibril consisting of two �-sheets. For example, do two cc�coiled-coil trimers form a �-sheet consisting of six strands or aprotofibril made of two �-sheet trimers? Further work is alsoplanned to explore the role of individual water molecules alongthe assembly pathways, and whether new pathways and �-sheetstructures become feasible as a result of the inclusion of explicitsolvent.

4. Conclusions

We have carried out replica exchange and constant temper-ature molecular dynamics simulations combined with an ato-mistic protein description and an implicit solvent model toexplore the free energy landscape of the cc� trimer. Fortemperatures above 340 K we observed the transformation ofthe native-like three-stranded coiled-coil structure into differenttypes of �-sheets, which correspond to free energy minima. TheR to � conversion at elevated temperatures agrees with theexperimental amyloid formation13 and with previous moleculardynamics simulations that employed a coarse-grained model todescribe the cc� peptide.36 The different �-sheet trimers that

we detect differ in the parallel/antiparallel alignment of the�-strands and in the residue pairings of neighboring strands.One of the observed �-sheets closely resembles the amyloid�-sheet model that was constructed for the cc� trimer based onexperimental results.13 Future simulations will be needed toverify that this �-sheet trimer indeed forms amyloid fibrils. Itwould also be interesting to see whether the other �-sheets thatwe observe in our simulation aggregate into amyloid fibrils, andif so, whether the resulting fibrils would give rise to differentmorphologies. Alternative amyloid fibril morphologies aredetected experimentally and may be linked to competingassembly pathways65,66 and perhaps different toxicity in vivo.67,68

Two different pathways have been characterized for theformation of the various �-sheet trimers from the coiled-coilstructure. Below the dissociation temperature of the coiled-coiltrimer we observe an internal pathway, which involves the directconversion of the R-helices into �-sheets without samplingirregular structures. As soon as parts of the peptides haveadopted the � state, these sections then propagate the confor-mational change to the rest of the peptides, leading to formationof a �-sheet. Above the dissociation temperature the �-sheetsare formed via a pathway involving dissociation into monomers,which are mostly of irregular structure at elevated temperature.As soon as the temperature is lowered the cc� peptides transforminto the � state with a high aggregation propensity, resulting in�-sheets. From temperature and concentration considerationswe conclude that formation of amyloid fibrils from the coiled-

Figure 7. Trajectories constructed from the REMD simulation showing conversion from the coiled-coil structure to the �-sheet trimers D (leftcolumn) and F (right column). (a) Temperature variation. (b) Time dependence of (black) the radius of gyration and (red) the CR rmsd from the�-sheet trimers D (left column) and F (right column). (c) Secondary structure analysis for cc� structures along the trajectories. The color code isgiven on the bottom.

Amyloid Formation for the cc� Peptide J. Phys. Chem. B, Vol. 112, No. 32, 2008 10003

coil cc� at the experimental temperature of 310 K is more likelyto follow the internal pathway than the dissociation/reassociationpathway.

The dissociation/reassociation pathway is consistent with atwo-stage dock-lock mechanism for the growth of amyloidfibrils, which was experimentally69,70 and theoretically25 ob-served for the A� peptide. In the first dock phase a monomeradds to a nucleation seed, which may be an existing fibril or�-sheet, but can also be another monomer with a high �-strandcontent, as in our simulation. In ref 25 it was shown that the�-strand content increases during the initial dock phase, inagreement with our results. We note, however, that the �-strandcontent of the monomer that is added to the nucleation seed isalready high at the first docking event. Hence, the dock stagedoes not involve condensation of a monomer of irregularstructure to the nucleation seed. It is really a template-mediatedgrowth process where the template seed induces conformationalchanges in those parts of the added monomer that are not yetin the � state. The second lock stage is the rate-limitingprocess,25,69,70 which can be interpreted as an optimization ofthe �-strand registers.35

Acknowledgment. B.S. gratefully acknowledges the BBSRCfor financial support.

References and Notes

(1) Selkoe, D. J. Nature 2003, 426, 900–904.(2) Chiti, F.; Dobson, C. M. Annu. ReV. Biochem. 2006, 75, 333–366.(3) Uversky, V. N.; Fink, A. L. Protein misfolding, aggregation and

conformational disease; Springer: New York, 2006.(4) Sipe, J. D.; Cohen, A. S. J. Struct. Biol. 2000, 130, 88–98.(5) Eanes, E. D.; Glenner, G. G. J. Histochem. Cytochem. 1968, 16,

673–677.(6) Geddes, A. J.; Parker, K. D.; Atkins, A. D.; Beighton, E. J. Mol.

Biol. 1968, 32, 343–358.(7) Sunde, M.; Serpell, L. C.; Bartlam, M.; Fraser, P. E.; Pepys, M. B.;

Blake, C. C. F. J. Mol. Biol. 1997, 273, 729–739.(8) Makin, O. S.; Serpell, L. C. Fib. Diffr. ReV. 2004, 12, 29–35.(9) Knowles, T. P.; Fitzpatrick, A. W.; Meehan, S.; Mott, H. R.;

Vendruscolo, M.; Dobson, C. M.; Welland, M. E. Science 2007, 318, 1900–1903.

(10) Dobson, C. M. Trends Biochem. Sci. 1999, 24, 329–332.(11) Chiti, F.; Stefani, M.; Taddei, N.; Ramponi, G.; Dobson, C. M.

Nature 2003, 424, 805–808.(12) Kuhlman, B.; Dantas, G.; Ireton, G. C.; Varani, G.; Stoddard, B. L.;

Baker, D. Science 2003, 302, 1364–1368.(13) Kammerer, R. A.; Kostrewa, D.; Zurdo, J.; Detken, A.; Garcıa-

Echeverrıa, C.; Green, J. D.; Muller, S. A.; Meier, B. H.; Winkler, F. K.;Dobson, C. M.; Steinmetz, M. O. Proc. Natl. Acad. Sci. U.S.A. 2004, 101,4435–4440.

(14) Lope de la Paz, M.; Serrano, L. Proc. Natl. Acad. Sci. U.S.A. 2004,101, 87–92.

(15) Rousseau, F.; Schymkowitz, J.; Serrano, L. Curr. Opion. Struct.Biol. 2006, 16, 118–126.

(16) Brunger, A. T.; Adams, P. D.; Clore, G. M.; Delano, W. L.; Gros,P.; Grosse-Kunstleve, R. W.; Jiang, J.-S.; Kuszewski, J.; Nilges, M.; Pannu,N. S.; Read, R. J.; Rice, L. M.; Simonson, T.; Warren, G. L. ActaCrystallogr., Sect. D 1998, 54, 905–921.

(17) Kammerer, R. A.; Steinmetz, M. O. J. Struct. Biol. 2006, 155, 146–153.

(18) Klimov, D. K.; Thirumalai, D. Structure 2003, 11, 295–307.(19) Favrin, G.; Irback, A.; Mohanty, S. Biophys. J. 2004, 87, 3657–

3664.(20) Hwang, W.; Zhang, S.; Kamm, R. D.; Karplus, M. Proc. Natl. Acad.

Sci. U.S.A. 2004, 101, 12916–12921.(21) Santini, S.; Wei, G.; Mousseau, N.; Derreumaux, P. Structure 2004,

12, 1245–1255.(22) Santini, S.; Mousseau, N.; Derreumaux, P. J. Am. Chem. Soc. 2004,

126, 11509–11516.(23) Gnanakaran, S.; Nussinov, R.; Garcıa, A. E. J. Am. Chem. Soc.

2006, 128, 2158–2159.(24) Derreumaux, P.; Mousseau, N. J. Chem. Phys. 2007, 126, 025101.

(25) Nguyen, P. H.; Li, M. L.; Stock, G.; Straub, J. E.; Thirumalai, D.Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 111–116.

(26) Melquiond, A.; Boucher, G.; Mousseau, N.; Derreumaux, P.J. Chem. Phys. 2005, 122, 174904.

(27) Wei, G.; Mousseau, N.; Derreumaux, P. J. Phys. Condens. Matter2004, 16, 5047–5054.

(28) Wei, G.; Mousseau, N.; Derreumaux, P. Biophys. J. 2004, 87, 3648–3656.

(29) Baumketner, A.; Shea, J.-E. Biophys. J. 2005, 89, 1493–1503.(30) Paci, E.; Gsponer, J.; Salvatella, X.; Vendruscolo, M. J. Mol. Biol.

2004, 340, 555–569.(31) Gsponer, J.; Haberthur, U.; Caflisch, A. Proc. Natl. Acad. Sci. U.S.A.

2003, 100, 5154–5159.(32) Cecchini, M.; Rao, F.; Seeber, M.; Caflisch, A. J. Chem. Phys.

2004, 121, 10748.(33) Lipfert, J.; Franklin, J.; Wu, F.; Doniach, S. J. Mol. Biol. 2005,

349, 648–658.(34) Zhang, Z.; Chen, H.; Bai, H.; Lai, L. Biophys. J. 2007, 93, 1484–

1492.(35) Strodel, B.; Whittleston, C. S.; Wales, D. J. J. Am. Chem. Soc.

2007, 129, 16005–16014.(36) Ding, F.; LaRocque, J. J.; Dokholyan, N. V. J. Biol. Chem. 2005,

280, 40235–40240.(37) Sugita, Y.; Okamoto, Y. Chem. Phys. Lett. 1999, 314, 141–151.(38) Brooks, B. R.; Bruccoleri, R. E.; Olafson, B. D.; States, D. J.; S.,

S.; Karplus, M. J. Comput. Chem. 1983, 4, 187–217.(39) Lazaridis, T.; Karplus, M. Proteins: Struct., Funct. Genet. 1999,

35, 133–152.(40) Steinbach, P. J. Proteins: Struct., Funct., Bioinf. 2004, 57, 665–

677.(41) Lazaridis, T.; Karplus, M. J. Mol. Biol. 1998, 288, 477–487.(42) Huang, A.; Stultz, C. M. Biophys. J. 2007, 92, 34–45.(43) Strodel, B.; Wales, D. J. J. Chem. Theor. Comput. 2008, 4, 657–

672.(44) Honeycutt, J. D.; Thirumalai, D. Biopolymers 1992, 32, 695–709.(45) Feig, M. J. Chem. Theor. Comput. 2007, 3, 1734–1748.(46) Loncharich, R. J.; Brooks, B. R.; Pastor, R. W. Biopolymers 1992,

32, 523–535.(47) Zagrovic, B.; Pande, V. J. Comput. Chem. 2003, 24, 1432–1436.(48) Hagen, S. J.; Qiu, L.; Pabit, S. A. J. Phys. Condens. Matter 2005,

17, S1503–S1514.(49) Gee, P. J.; van Gunsteren, W. F. Chem.-Eur. J. 2005, 12, 72–75.(50) Jagielska, A.; Scheraga, H. A. J. Comput. Chem. 2007, 28, 1068–

1082.(51) Klimov, D. K.; Newfield, D.; Thirumalai, D. Proc. Natl. Acad. Sci.

U.S.A. 2002, 99, 8019–8024.(52) Feig, M.; Karanicolas, J.; Brooks, C. L. J. Mol. Graph. Mod. 2004,

22, 377–395.(53) Swendsen, R. H.; Wang, J.-S. Phys. ReV. Lett. 1986, 57, 2607–

2609.(54) Kumar, S.; Bouzida, D.; Swendsen, R. H.; Kollman, P. A.;

Rosenberg, J. M. J. Comput. Chem. 1992, 13, 1011–1021.(55) Kabsch, W.; Sander, C. Biopolymers 1983, 22, 2577–2637.(56) Carter, P.; Andersen, C. A.; Rost, B. Nucleic Acids Res. 2003, 31,

3293–3295.(57) Torrie, G. M.; Valleau, J. P. J. Comp. Phys. 1977, 23, 187–199.(58) Grubmuller, H. Phys. ReV. E 1995, 52, 2893–2906.(59) Bussi, G.; Gervasio, F. L.; Laio, A.; Parrinello, M. J. Am. Chem.

Soc. 2006, 128, 13435–13441.(60) Hamelberg, D.; Mongan, J.; McCammon, J. A. J. Chem. Phys. 2004,

120, 11919–11929.(61) Wales, D. J. J. Mol. Phys. 2002, 100, 3285–3306.(62) Wales, D. J. Mol. Phys. 2004, 102, 891–908.(63) Wales, D. J. Int. ReV. Phys. Chem. 2006, 25, 237–282.(64) Masunov, A.; Lazaridis, T. J. Am. Chem. Soc. 2003, 125, 1722–

1730.(65) Gosal, W. S.; Morten, I. J.; Hewitt, E. W.; Smith, D. A.; Thomson,

N. H.; Radford, S. E. J. Mol. Biol. 2005, 351, 850–864.(66) Elgersma, R. C.; Rijkers, D. T. S.; Liskamp, R. M. J. Biopolymers

2007, 88, 577–577.(67) Olofsson, A.; Ostman, J.; Lundgren, E. Clin. Chem. Lab. Med. 2002,

40, 1266–1270.(68) Bergstrom, J.; Gustavsson, A.; Hellman, U.; Sletten, K.; Murphy,

C. L.; Weiss, D. T.; Solomon, A.; Olofsson, B. O.; Westermark, P. J. Pathol.2005, 206, 224–232.

(69) Esler, W. P.; Stimson, E. R.; Jennings, J. M.; Vinters, H. V.;Ghilardi, J. R.; Lee, J. P.; Mantyh, P. W.; Maggio, J. E. Biochemistry 2000,39, 6288–6295.

(70) Cannon, M. J.; Williams, A. D.; Wetzel, R.; Myszka, D. G. Anal.Biochem. 2004, 328, 67–75.

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10004 J. Phys. Chem. B, Vol. 112, No. 32, 2008 Strodel et al.