Peptide self-assembly at the nanoscale:a challenging target for computationaland experimental biotechnologyGiorgio Colombo1, Patricia Soto2 and Ehud Gazit3

1 Istituto di Chimica del Riconoscimento Molecolare, CNR, via Mario Bianco 9, 20131 Milano, Italy2 Department of Chemistry and Biochemistry 9510, University of California, Santa Barbara, CA 93106 – 9510, USA3 Department of Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv 66978, Israel

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Self-assembly at the nanoscale is becoming increasinglyimportant for the fabrication of novel supramolecularstructures, with applications in the fields of nanobio-technology and nanomedicine. Peptides represent themost favorable building blocks for the design and syn-thesis of nanostructures because they offer a greatdiversity of chemical and physical properties, they canbe synthesized in large amounts, and can be modifiedand decorated with functional elements, which can beused in diverse applications. In this article, we reviewsome of the most recent experimental advances in theuse of nanoscale self-assembled peptide structures andthe theoretical efforts aimed at understanding the micro-scopic determinants of their formation, stability andconformational properties. The combination of exper-imental observations and theoretical advances will befundamental to fully realizing the biotechnologicalpotential of peptide self-organization.

IntroductionThe study of the self-organization properties of peptides hasemerged in recent years as an active and diverse field ofresearch, ranging from biomedicine and biotechnology tomaterial science and nanotechnology. Although in naturepolypeptide self-assembly into assemblies such as amyloidfibrils is often associated with human medical disorders[1–6] and microbial physiological processes [7,8], theseself-organization properties of peptides have been exploitedfor the formation of bio-inspired nanoassemblies, includingnanotubes, nanospheres, nanofibers, nanotapes and hydro-gels, all with nanoscale order [9–15]. Structural elements asshort as dipeptides can form well-ordered assemblies at thenano-scale [16]. Peptides serve as excellent building-blocksfor bionanotechnology owing to the ease of their synthesis,small size, relative stability and chemical and biologicalmodifiability. Understanding the physicochemical determi-nants that underlie peptide self-assembly is a fundamentalstep, in view of the rational design of new nano buildingblocks for biotechnological applications or new drugs. Thisrequires the combined effort of experimental and theoreticalapproaches. In this article, we will describe several recentadvances in the bionanotechnological application of peptide

Corresponding author: Colombo, G. (g.colombo@icrm.cnr.it).Available online 26 March 2007.

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self-assembly and the theoretical efforts aimed atunveiling the essential physicochemical determinants driv-ing this complex process. Combining knowledge from bothfields will improve our understanding of the principlesgoverning the organization of self-assembling peptide sys-tems, leading, eventually, to the real rational design of newnanostructures for targeted applications, or of new drugsthat are able to interfere with the harmful amyloid-for-mation process.

Peptide self-organization and self-assemblyMolecular self-organization and self-assembly are processesby which nature builds complex, three-dimensional, multi-component structures with well-defined functions, startingfrom simple building blocks such as oligonucleotides, oligo-saccharides, phospholipids, proteins or peptides [17]. Pep-tides have a special appeal owing to their simple structure(as compared with nucleic acids, proteins and other largerbiomolecules), their chemical diversity, richness of shapes,relative chemical and physical stability and the possibilityto synthesize them in large amounts (Figure 1).

Peptide structures were used as major building blocksfor the construction of nanostructures more than a decadeago. The first pioneering work by M. Reza Ghadiri and co-workers used the special construction of alternating D- andL-amino acids into small cyclic peptides. These peptidesformed extended b-sheet-like structures, and stacked ontop of each other to form hollow and extended cylinders[18,19].

Other studies were directed towards understanding theformation of fibrils, with the use of short linear peptidesmodels. One of these investigated the formation of genericamyloid fibril formation by a large number of peptides withno sequence homology (Figure 1) [20,21]. Amyloid for-mation is a self-assembly process and is at the basis ofthe aggregation processes that lead to the formation ofoligomers and insoluble fibrils, whose deposition is con-sidered a hallmark of many types of human diseases [22].However, the ability to form ordered amyloid aggregates isnot restricted to disease-related sequences [23]; a largenumber of non-pathogenic polypeptides have been shownto form ordered fibrils under particular solvent, tempera-ture and pH conditions [24,25]. Despite the high sequencediversity, many proteins and peptides aggregate into a

d. doi:10.1016/j.tibtech.2007.03.004

Figure 1. Peptide sequences and nanostructures. Different short peptide sequences can self-assemble into different structures of nanoscale dimensions. (a) Sequences

from naturally occurring peptides or proteins can assemble into ordered fibrils. (b) Self-assembly of well-ordered and elongated peptide nanotubes by a molecular

recognition motif derived from the b-amyloid polypeptide. (c) Formation of nanospheres from designed sequences containing non-natural amino-acids.

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common cross-b-sheet structure, and the resulting fibrilsshow remarkable ultrastructural and biophysical sim-ilarity [1]. Electron and atomic force microscopy analysisof the deposits demonstrate the existence of fibrils with adiameter of 7–10 nm and a length of several micrometers[3]. An intriguing point is the finding that short peptides(penta- or tetrapeptides) can form typical fibrils withthe canonical features of amyloid fibrils (Figure 1) [26].These fibrillar assemblies belong naturally to the realm ofthe nanoscale, and the study of their properties and mech-anisms of formationmight be a source of inspiration for thedevelopment of ordered, rationally designed nanostruc-tures with potentially interesting applications in biotech-nology and other fields, ranging from material sciences totissue engineering, and from molecular electronics to mol-ecular medicine and drug delivery.

Considering the importance and the great promise thatpeptide self-assembly holds for the scientific and techno-logical worlds, much effort is being undertaken to designand synthesize new structures for different applicationsand to unveil the fine details of the mechanisms by whichpeptides aggregate in well-ordered structures. Many nov-el building blocks that are based on either natural orsynthetic amino-acids and on linear or cyclic configur-ations are being developed. The diversity of the side-chains enables the control of both conformation andfunctionality.

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Biotechnological applications of peptidenanostructuresBiomedicine

The technological use of peptide nanostructures has alreadybeen demonstrated for various applications. One of the keyapplications is the use of peptide assemblies for tissueengineering applications. Peptide scaffolds proved to beexcellent templates for the growth of functional nerve cellnetworks, which can even form active synapses (Figure 2)[27–29]. One of the key advantages of the peptide structuresis the ability to decorate them with various molecularrecognition peptide motifs, which direct the spatial organ-ization of the cells within the tissue (Figure 2) [27,28].

One of the most exciting applications in tissueengineering and regeneration is the ability of the nanos-tructures to provide a permissive environment for axonalregeneration in the central nervous system (CNS) afterinjury [29]. When the peptide scaffold was applied todamaged optic tracts in hamsters, regenerated axons couldreconnect, and target tissues with sufficient density as toenable the functional return of vision. [29]

Biosensor applications

Other studies have used peptide nanostructures forvarious biosensors applications. Modified peptide nano-tubes were used for the construction of various high-sen-sitivity sensors. Once again, the biocompatibility and the

Figure 2. Self-organization into three-dimensional scaffolds. Designed peptide sequences can form ordered assemblies that self-assemble into three-dimensional nanofiber

scaffolds. These designer scaffolds can be used as matrices for the growth of cells for tissue engineering. (This figure was kindly provided by S. Zhang and F. Gelain.)

Review TRENDS in Biotechnology Vol.25 No.5 213

chemical flexibility of the structures enables their use inapplications that range from immunoassays [30] to elec-trochemical detection. [31]

In this application [30], the authors exploited peptideself-assembly in nanometer-sized building blocks to obtainbottom-up fabrications in a reproducible, efficient andeconomic manner. In particular, they suggested that bio-logical molecular recognition, such as antibody–antigeninteractions, can be exploited in the reproducible assemblyof building blocks with complex functions and structures atroom temperature. With this idea in mind, it was possibleto immobilize antibody-coated nanotubes at specific comp-lementary binding positions patterned on surfaces. Thehypothesis was proved by using two types of nanotubescoated with different antibodies and selectively anchoredonto areas decorated with their complementary antigen,which was patterned using the tip of an atomic forcemicroscope (AFM). Because those nanotubes could becoated with various metals and semiconductors with con-trolled morphologies, these results opened the possibilityto accomplish unconventional device fabrication throughantibody nanotubes coatedwith different types ofmetals orsemiconductors that could be self-assembled on antigen-patterned surfaces using biological molecular recognition.

In one application [31], the self-assembly offunctionalized diphenylalanine peptide nanotubes wasused to fabricate and improve the performances of compo-site electrodes. In particular, peptide nanotubes wereattached to gold electrodes, and the resulting electroche-mical behavior was studied using cyclic voltammetry andchronoamperometry. The peptide-modified, nanotube-based electrodes demonstrated a direct and unmediatedresponse to hydrogen peroxide andNADH, at a potential of+0.4 V [versus saturated calomel electrode (SCE)]. This

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new biosensor enabled the sensitive determination ofglucose by monitoring the hydrogen peroxide produced byan enzymatic reaction between glucose oxidase, attached tothe peptide nanotubes, and glucose. In addition, themarkedelectrocatalytic activity towardNADHenabled the sensitivedetection of ethanol using ethanol dehydrogenase andNAD(+). The results of these studies suggest that peptidenanotube-based electrochemical detectors represent apotential tool for sensitive biosensors and biomoleculardiagnostics.

Computational approaches toward understandingthe formation of peptide nanostructuresThe great promises that peptide-based nanostructureshold for many applications could be expanded if weimprove our knowledge of the mechanisms and phy-sico–chemical determinants of peptide self-assembly.However, the high degree of complexity of self-assemblyitself, and the difficulties in obtaining high-resolution X-ray or NMR structures of the aggregates, have severelyhampered the experimental characterization of the pro-cess. In this context, theoretical and computationalmethods have had, and will have, important roles, bothin the development of a framework for understanding themechanisms leading to the formation of ordered aggre-gates and in the design of new sequences with selectedproperties for nanobiotechnological applications (Box 1;Table 1).

Simulations of monomers

Several studies usedmolecular dynamics (MD) simulationsto monitor the dynamics and the effects of mutations andthe solvent used in the conformational transitions fromthe soluble to aggregating b-sheet-rich conformations of

Box 1. Molecular Simulations

Computer simulations of biochemical systems are having an increas-

ingly important role in the realm of modern biomolecular sciences.

The development of algorithms and theories, combined with the

constant increase in computer power, has made it possible to

investigate the properties of complex (bio)molecular systems at

different levels of resolution. This, in turn, should be chosen to be

consistent with the type of property or process under investigation.

Computational techniques are, at present, the only possibility for

atomic-resolution investigation of many complex processes, despite

recent progresses in the development of experimental analysis

techniques. In this box, we review two of the main methods discussed

in the text and in Table 1.

Coarse-grained models

The complexity, time and length scales of peptide self-assembly

processes implies that to follow directly the actual process, coarse-

grained models have to be used. In these models, the finest resolution

atomic details are neglected, and only relevant degrees of freedom of

the peptide molecule are retained, Appropriate interaction potentials

are chosen to compensate for such resolution reduction. An example

of one of these simulation techniques is the ART (activation relaxation

technique) simulation technique. [51]. In this approach, the interac-

tions among several peptide chains can be simulated ab initio, with

no bias on the initial orientations or conformations. For each chain, all

backbone atoms are included and all side chains are modeled by a

bead. The optimized potential for efficient peptide-structure predic-

tion (OPEP) energy model [51], which includes solvent effects

implicitly, is expressed as a function of three types of interactions:

excluded-volume potential between all particles and quadratic

potentials for maintaining stereochemistry (bond lengths and bond

angles connecting all particles and improper dihedral angles of the

side chains with respect to the backbone); contact potential between

side chains; and backbone two-body and four-body (cooperative)

hydrogen-bonding interactions. ART is specifically designed to

generate new configurations of the system by efficiently crossing

high-energy barriers through a four step procedure: starting from a

minimum, the system is first distorted along a direction taken at

random in the 3N-dimensional space, N being the number of degrees

of freedom in the system. The distortion is slowly increased until the

lowest eigenvalue in the Hessian matrix representing the curvature of

the energy landscape becomes negative. The system is then pushed

along the eigenvector associated with the negative eigenvalue, while

the energy is minimized in the hyperplane perpendicular to this

direction until the total force on all atoms vanishes, indicating the

convergence to a first-order saddle point. Subsequently, the system is

pushed slightly beyond the saddle point and is relaxed (minimized) to

a new minimum. Finally, the newly generated configuration is

accepted or rejected using the Metropolis criterion. More details on

the method can be found in [51] and references therein.

Molecular dynamicsAt the opposite extreme of resolution lies molecular dynamics (MD).

MD simulation is a well-established method to study protein

dynamics, and recently it was proven to be useful to address peptide

self-assembly. In all-atom approaches, all atoms in the system,

including the solvent, are described explicitly. In principle this should

enable the complete characterization of complex physico–chemical

processes at a high degree of resolution. MD relies on a description of

the system based on classical mechanics, where the motion of the

molecule atoms can be described by Newton’s equation of motion,

and the interactions between atoms can be described by empirical

pair-additive potentials. With these assumptions, protein atoms are

modeled as rigid spheres with a fixed charge that interact through

bonded and non-bonded interactions. By numerical integration of the

classical equations of motion, the positions and velocities of the

atoms can be obtained. A direct link between the atomic description

of both monomer peptides and ordered assemblies obtained from the

simulations and macroscopic properties can be established using

statistical mechanics methods. In practice, the ab initio simulation of

self-assembly processes, starting from completely random initial

conditions and accessing time scales similar to the experimental

ones, is still out of reach for all-atom MD simulations, owing to the

intrinsic low efficiency of these methods to efficiently sample

configurational space. However, important information can be gained

using different strategies, such as those outlined in Table 1. An ample

discussion of the problems and perspective connected with MD

simulation techniques can be found elsewhere [52].

In our view, the combination of coarse-grained and atomic

resolution approaches might hold great promise in the simulation

of biomolecular processes.

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peptides such as the H1 peptide from the prion protein,different Ab stretches [Ab(12–28), Ab(25–35) or Ab(21–30)]or polyglutamine [32–36]. These calculations establish con-nections between sequences and aggregation propensitiesand suggest that the structure and stability of the inter-mediates can be targeted in drug design.

Table 1. Summary of different computational techniques used in

Process Level ofmolecular model

resolution

Computationaltechnique

Advantages

Peptide

oligomerization

Coarse Grain ART Efficient cro

relatively hi

barriers of t

landscape.

Peptide

oligomerization

Fully

atomistic

Monte

Carlo

Able to mim

assembly of

chains.

Monomer

stability

Molecular

Dynamics

Provides str

information

of the peptid

Ordered peptide

assemblies

Provides a d

model at an

the ordered

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Simulations of self-assembly

Compared with the conformational analysis of monomers,the direct simulation of peptide aggregation, self-organiz-ation and the formation of initial oligomers is still anextreme challenge for all-atommodels because simulationsmust handle many chains and find ways to follow the

the simulation of peptide self-assembly

Limitations Refs

ssing of

gh energy

he energy

Limited resolution, neglect

of possibly important fine

chemical interactions.

[38,39,51]

ic the actual

several peptide

Limited to sample few basins

of the energy landscape.

[40]

uctural

at an atomic level

e ensemble.

Quality of the predictions

depends strongly on the size

of the peptide.

[32,34,35,41]

ynamic molecular

atomic level of

assembly.

Limited by the size of the

monomer peptide and the

number of peptide chains

assembled.

[45]

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dynamics during some of the crucial steps. However, thehurdle can be passed successfully by neglecting the finestatomic details in favor of models that catch only theessential physical properties of the systems. The use of acoarse-grained level of representation of the sequencesdecreases the number of particles, degrees of freedomand interactions to compute, and results in a definite gainin the time required to generate physically meaningfulconfigurations. Within this theoretical framework, Derreu-maux and co-workers [37–39] ran simulations of differentcopies of the amyloidogenic sequences and showed thatalthough monomers are disordered, the presence ofmultiple copies of the peptide in the simulation box couldinduce the formation of a variety of oligomeric states, withfully antiparallel or mixed parallel–antiparallel configur-ations. By increasing the chains to a minimum of sixpeptides, they could observe the formation of double-layerb-sheet assemblies with a 10 A distance between twolayers and a 4.5 A distance between peptide chains inone layer, consistent with experimental X-ray data. Thesemethods were also applied to study the oligomerization ofAb(16–22). These results predicted the formation of in-register antiparallel sheets, consistent with NMR data.The oligomerization of Ab(16–22) into mainly antiparallelb-sheets was also observed by Favrin and co-workers [40]using a sequence-based atomic model with an effective

Figure 3. Mechanism for peptide self-assembly reconstructed using computer simulatio

of short peptides from the Ab amyloid could be reconstructed. Initial amorphous agg

Approximate timescales for the events could be inferred from simulation results. (This

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potential based on hydrogen bonds and hydrophobicattractions and unbiased Monte Carlo simulations forsampling. More importantly, these approaches could shedlight on aggregation routes, suggesting the formation of b-barrel states between the amorphous aggregates and thefinal fibrils (Figure 3).

The results of simulations point to hydrophobic andstacking interactions as the determining factors in definingthe relative orientation, directionality and the supramole-cular ordering of the peptides.Moreover, all the simulationsshowed a considerable conformational heterogeneity, help-ing to explain the phenomenon of fibril polymorphism,which is observed in many supramolecular structures.

Structure and sequence dependence of assembly

stability

Although many crucial aspects of peptide self-assemblycan be observed only at a coarse-grained level, it is possibleto investigate the effects on the stability of a certainassembly of different hypothetic arrangements [14,41] orthe effects of sequence mutations on a certain supramole-cular conformation. This approach was applied, forexample, by Nussinov and co-workers to several peptidesof unrelated origin, such as polyglutamines, the 113–120stretch from the SyrianHamster prion, the hIAPP22–27 andhIAPP22–29 and several peptides from the Alzheimer’s Ab,

ns. Through coarse-grained computer simulations, the full self-assembly pathway

regates can evolve into b-barrrel and b-sheet structures, which can interconvert.

figure was kindly provided by P. Derreumaux.)

Figure 4. Molecular simulations of sequence dependence of fibril stability. Different fibrillogenic and non-fibrillogenic sequences can be simulated with molecular

dynamics and their effects on fibril stability can be evaluated by analyzing the conservation in time of ordered b-sheet structure represented as a continuous red band in the

graphs on the left. On the right, the corresponding representative structures with their stabilizing interactions are highlighted.

Figure 5. Collective properties of fibrils. Time evolution of the twisting of a protofibril model.

216 Review TRENDS in Biotechnology Vol.25 No.5

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showing how the final organization of the fibrils depends,in a specific way, on the protein sequence [41–43]. In thiscontext, de la Paz et al. carried out several explicit solventMD simulations on a series of single point-mutants of thede novo designed amyloidogenic STVIIE peptide, startingfrom different initial conformations of a preformed, poly-meric, six-stranded b-sheet [44]. The results providedevidence for the influence of a small number of site-specifichydrophobic interactions on the packing and stabilizationof the aggregates, as well as on the interplay between side-chain interactions and the net charge of the molecule onthe strand arrangement of polymeric b-sheets. Impor-tantly, this MD analysis has shed light on the origin ofthe position dependence on mutation of b-sheet polymer-ization, defining a direct link between the sequence,dynamics and stability of the final peptide aggregateand opening the possibility to use MD for the rationaldesign of new sequences that are able to form supramole-cular assemblies (Figure 4) [44].

Finally, MD simulations could also be applied to thestudy of the collective properties of large-scale aggregates.Starting from a non-twisted model of a fibril of the SIVgp32 fusion peptide, Daura and co-workers observed thatthe parallel b-sheet aggregates spontaneously adopted ahelical suprastructure in the simulations [45]. A dynamicequilibriumwas observed involving partial unwinding andrewinding of the suprastructure. The chirality of the con-stituent chains rendered this structure more thermodyna-mically stable than a helical ribbon. This study provides anovel view of the dynamic nature of self-assembled aggre-gates (Figure 5).

Conclusions and future perspectivesRecent advances and successes in the application ofpeptide self-assembly to the fabrication of nano-scaleobjects open up many new scientific and technologicalchallenges and opportunities for the experimental andtheoretical fields. There is certainly great confidence thatdevelopments in this field will have a huge impact in thefuture advancement of high-tech industry, biomedicineand biotechnology. The recent emphasis on nanobiotech-nology demonstrated by governmental funding agencies inEurope, US and Japan is one example of the growingimportance of the field.

Obstacles still need to be overcome before self-assembledpeptide structures with different modifications or decora-tions turn into useful products and devices. In this context,obtaining full and rational control of the final spatial organ-ization of aggregating peptides at the nanoscale is the keychallenge. For example, short sequences can be assembledinto nanotubes that can be grown in an essentially uni-directional way and aligned vertically or horizontally [46] toform two-dimensional arrays. The next natural step wouldbe the rational and controlled fabrication of three-dimen-sional architectures, which might have applications in thedevelopment of new materials, analytical sensors anddevices. Designed nanostructures based on naturally bio-compatiblematerials such as peptides could, in fact, be usedfor in vivo recognition of particularmarkers or analytes [47].

A second prospective advancement in the fieldis represented by the rational design and synthesis of

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chemically active nanoscale aggregates, in whichpeptides are decorated with catalytic groups, light-har-vesting moieties, electron donating and accepting groupswith optimized geometries for electron transfer, and evenenzymes. All these new entities would clearly find appli-cations in diverse fields such as chemical synthesis,energy and electronics. Self-aggregated fibrils have alsorecently been shown to possess mechanical propertiessimilar to those of steel in terms of strength, and to thoseof silk in terms of mechanical stiffness [48,49]. Being ableto realize tailored structures with such remarkable prop-erties is highly attractive for future technological appli-cations.

In all cases, great advantages are guaranteed by the factthat the building blocks for construction are readily avail-able and relatively inexpensive. Peptides actually havegreat promise in the ’bottom up’ approach, owing to theirlow cost, simplicity and the ability to decorate them readilywith chemical and biological elements. Peptide nanotech-nology could become widespread not only for niche appli-cations but also for consumer goods because peptidesynthesis could be performed at large scales and low cost.Because ordered peptide assembly is already observedwith peptides as short as dipeptides, simple solution-phasesynthesis methods could be used. The low cost of large-scale peptide synthesis is demonstrated in the case of theN-L-a-aspartyl-L-phenylalanine 1-methyl ester dipeptide(the sweetener Aspartame), which costs a few cents pergram.

The control and understanding of the sequence–structure–properties relationships of these molecular sys-temswill be crucial to take the necessary steps towards fullexploitation of the potential of peptide self-assembly. Thisis still an unresolved problem. Computational and theor-etical approaches already have a fundamental role in thisfield because they can provide a reliable qualitative frame-work for the rationalization of experimentally observedphenomena. The main obstacle in the development ofquantitative theoretical methods for the study and predic-tion of the structures and properties of peptide assembliesis represented by the limited time and length scales thatcan be accessed at the moment. These can be overcome bythe combination of coarse-grained and all-atom approaches[50], the large-scale analysis of peptide sequences and theiraggregating properties and, finally, by the development ofphysics-based interaction functions to mimic realisticallythe forces that underlie peptide–peptide and peptide–sol-vent interactions.

We believe that the combination of informationexchange between the experimental and theoreticalworld, the development of new theories and algorithms,the rapid improvement in the technology for the charac-terization and fabrication of self-assembledmaterials andthe development of fast computer power will make therational design and discovery of new structures withinreach.

AcknowledgementsWe gratefully acknowledge Philippe Derreumaux, S. Zhang and F. Gelainfor kindly providing the materials for Figures 2 and 3. J.E. Shea isgratefully acknowledged for supporting PS during the preparation of thismanuscript.

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