[Molecular Medicine and Medicinal Chemistry] Alzheimer's Disease: Insights into Low Molecular Weight...

November 26, 2012 10:1 9in x 6in Alzheimer’s Disease: Insights Into Low Molecular … b1377-chB8

8Molecular Insights into the

Assembly of β-Amyloidon Surfaces and Carbon

Nanotubes

Guanghong Wei∗, Yin Luo∗ and Zhaoming Fu∗

The assembly of the normally soluble β-amyloid (Aβ) peptide intooligomers and amyloid fibrils has been strongly linked to Alzheimer’sdisease. During the self-assembling process, environmental conditions suchas salt concentration, pH, and surface characteristics play a critical roleby influencing intermolecular interactions, and hence the structures ofaggregates and the pathway of fibrillation. In this chapter, we reviewstudies that have investigated the impacts of surfaces (including flat surfacesand curved surfaces) on the fibrillation of Aβ peptide in the context ofexperimental data and computer simulations, providing molecular insightsinto the assembly mechanisms on surfaces. We focus here on the influenceof a typical hydrophobic nanoparticle, the single-walled carbon nanotube,on the structural and dynamic aspects of the assembly of amyloidogenicAβ25-35 peptide observed in molecular dynamics simulations.

∗State Key Laboratory of Surface Physics, Key Laboratory for Computational PhysicalSciences (MOE), and Department of Physics, Fudan University, 220 Handan Road, Shanghai,200433, China. Correspondence to: Guanghong Wei, Phone: 86-21-55665231, Fax: 86-21-65104949; E-mail: [email protected].

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382 G. Wei, Y. Luo and Z. Fu

8.1 Introduction

Alzheimer’s disease (AD) is the most common neurodegenerative disorderof aging. The pathogenesis of AD is associated with the assembly ofthe Aβ peptide from the normally soluble monomers into oligomers,protofibrils, and amyloid fibrils (Walsh et al., 1997; Rochet and Lansbury,2000). Aβ, a 39-43 residue peptide, is a product of proteolytic cleavage ofthe transmembrane amyloid precursor protein (Selkoe, 1993). The mosttoxic form of Aβ1-42 and the most abundant form of Aβ1-40 are thepredominant components of intracellular senile plaques in the brains ofAD patients (Small and McLean, 1999). Recent studies suggest that smalloligomers formed early in the aggregation process of Aβ are the mosttoxic agents responsible for neuron death (Dahlgren et al., 2002; Clearyet al., 2005). The mechanism of toxicity of these oligomeric species hasbeen proposed to be associated with the interactions of the membranewith Aβ peptide (Quist et al., 2005; Lashuel and Lansbury, 2006; Sokolovet al., 2006). In addition, amyloid-fibril formation of Aβ is describedby a nucleation-dependent polymerization process characterized by a lagphase associated with the formation of a critical nucleus, after which fibrilelongation proceeds rapidly (Jarrett and Lansbury, 1993; Lomakin et al.,1997). The lag phase during which nucleation occurs is known to be thekey rate-determining step and therefore controlling this step is of utmostimportance.

During the self-assembling process, environmental conditions suchas ionic strength, pH, and temperature usually play a critical role byinfluencing intermolecular interactions, and hence the aggregation processof amyloidogenic peptides (McLaurin et al., 2000; Curtain et al., 2003). Itis emerging that surfaces such as biological membranes and non-biologicalsurfaces can also promote/hinder the fibrillation process of amyloidogenicpeptides by disturbing/stabilizing their native conformations or changingtheir local concentration (Linse et al., 2007; Stefani, 2007; Aisenbrey et al.,2008; Cabaleiro-Lago et al., 2008, 2010). The effects of a surface on proteinaggregation depend on the structural properties of the monomer, the waythat it interacts with the surface, and the physicochemical properties ofthe latter, including its electrostatic potential and hydrophobicity (Stefani,2007; Cabaleiro-Lago et al., 2008).

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Molecular Insights into the Assembly of β-Amyloid on Surfaces 383

8.2 Experimental Studies of the Effects of Surfaces/Nanoparticles on β-Amyloid Fibrillation

In the case of Aβ peptide, due to its relevance to neurotoxicity, itsinteractions with membranes and the influence of membrane surfaceon its aggregation have been extensively studied (Terzi et al., 1994,1995; Bokvist et al., 2004; Verdier et al., 2004). Many studies show thatmembranes containing a charged lipid component induce a dramaticelectrostatically-driven surface accumulation of Aβ peptide, followed byaccelerated misfolding into toxic aggregates at rates much higher than thosein a membrane-free environment (Terzi et al., 1994, 1995; Bokvist et al.,2004; Zhao et al., 2004). Indeed, hydrophobic and electrostatic interactionsbetween Aβ and membrane have been implicated in both the toxicity andaggregation of Aβ (Bokvist et al., 2004; Zhao et al., 2004). A detailedreview about the membrane-modulated Aβ aggregation can be foundin the chapter “Aβ Proteins–Lipid Membrane Interaction: ComputationalSimulation Study.”

This chapter will focus on the interactions of Aβ with non-biologicalsurfaces and resulting surface-mediated aggregation. Previous studies at flatsurfaces indicate that Aβ peptides bind to hydrophobic, hydrophilic, andcharged surfaces to different extents (Kowalewski and Holtzman, 1999;Arimon et al., 2005; Giacomelli and Norde, 2005; Rocha et al., 2005;Ban et al., 2006; Ryu et al., 2008), with a propensity to adsorb onhydrophobic and negatively charged surfaces. These studies also suggestthat the physicochemical properties of surfaces impact the structures andthe morphologies of the aggregates. On hydrophobic graphite surfaces,Aβ1-42 peptides form uniform, elongated β-sheets (Kowalewski andHoltzman, 1999), or a tightly packed dry layer (Rocha et al., 2005), whereasless ordered particulate aggregates appear at hydrophilic mica (Kowalewskiand Holtzman, 1999) and positively charged surfaces (Rocha et al., 2005;Ban et al., 2006).

In comparison with flat surfaces, nanoparticles possess a large surfaceto volume ratio. Due to their relatively large surface area, they havestronger adsorption capacities than flat surfaces. On the one hand, theexposure of a protein to a nanoparticle (such as a single-walled carbonnanotube (SWNT) and polymeric nanoparticle) would cause the protein

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to bind to the particle and promote/inhibit protein aggregation (Colvinand Kulinowski, 2007; Linse et al., 2007; Cabaleiro-Lago et al., 2008, 2010).On the other hand, nanoparticles are so small (1–100 nm) that they canaccess almost every part of the human body (Porter et al., 2007), evenpassing through the blood–brain barrier (Chopra et al., 2008). The protein–nanoparticle interactions and the effects of nanoparticles on fibrillogenesisare drawing growing attention due to the potential applications as drugsto control neurodegenerative diseases and the potential risks to humanhealth.

Most studies on Aβ–nanoparticle interactions indicate that it is thecomposition and the surface properties (such as charge, hydrophobicity,and shape) of nanoparticles that determine their influence on Aβ fib-rillation. Hydrogenated nanoparticles have been found to facilitate thefibrillogenesis of Aβ1-40 by inducing the conversion from random coilto β-sheet conformation (Rocha et al., 2008). However, titanium dioxide(TiO2) nanoparticles promote Aβ1-42 fibrillation by providing a highlocal concentration of Aβ monomer due to the adsorption on the particlesurfaces (Wu et al., 2008). A high local concentration of Aβ could result in ashortened lag time for nucleation of the fibrillation process as fibrillation ishighly concentration-dependent (Lansbury, 1999). On the contrary, in thepresence of polyethylene glycol (PEG) grafted (PEGylated) phospholipidnanomicelles and biocompatible cholesterol-bearing pullulan nanogels,Aβ1-42 exists in a predominantly α-helical conformation hence reducing itsaggregation potential (Pai et al., 2006; Ikeda et al., 2006). Similarly, Teflonand fluorinated nanoparticles prevent the fibril formation of Aβ1-40 byinducing conformational transition from a random coil to an α-helicalstructure (Giacomelli and Norde, 2003; Rocha et al., 2008). In a differentfashion, fullerene is found to inhibit the early stage of Aβ1-40 fibrillationby specifically binding to the central hydrophobic motif, 16KLVFF20, of Aβ

peptides (Kim and Lee, 2003). Although the 25-35 fragment of full-lengthAβ (Aβ25-35, with sequence 25GSNKGAIIGLM35) does not contain the16KLVFF20 motif, it has been revealed by transmission electron microscopythat its fibrillation is inhibited by hydrated fullerene C60 (Podolski et al.,2007), indicating different binding sites from full-length Aβ. In addition,a recent study by Linse et al. (2007) shows that polymeric nanoparticlesretard the fibril formation of Aβ, mainly by slowing down the nucleation

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process. Based on numerical analysis of the kinetic data for Aβ fibrillation,they proposed that binding Aβ monomers or oligomers to nanoparticlesurfaces prevents fibrillation. However, by using surface plasma resonanceexperiments, they could not distinguish between the binding of monomericand oligomeric Aβ1-40 forms on polymeric nanoparticles (Cabaleiro-Lagoet al., 2008).

Most of these studies show that interactions of Aβ with differentsurfaces enhance/retard Aβ fibrillation by decreasing/increasing the lagtime for nucleation, but they leave the elongation phase invariant,suggesting a surface-modulated nucleation mechanism. Elucidating themolecular details of the effect of specific surfaces on peptide aggregationmay contribute toward a mechanistic understanding of the aggregationprocesses, and may open the way to designing nanoparticles that modulatethe formation of toxic amyloid species.

8.3 Computational Studies Toward Understandingthe Assembly of β-Amyloid at Surfaces

Complementary to existing experimental studies, molecular dynamics(MD) simulations can provide detailed information about the interactionsof amyloidogenic peptides with surfaces and characterize the structures ofintermediate aggregates at atomic level. Compared with the computationalstudies of amyloidogenic peptides in solution, much less work has beendone on their assembly dynamics and structures on surfaces. Brovchenkoet al. (2009) have studied the effect of surface hydrophobicity/hydrophilicityon the aggregation of two amyloidogenic peptides by all-atom MDsimulations in explicit water. The surface effect is represented implicitly.Two types of peptides are used in their study: the hydrophobic peptideNFGAIL (residue 22-27 of the human amylin) and the hydrophilicpeptide GNNQQNY (residue 7-13 of the yeast prion Sup35). Their resultsshow that the aggregation of hydrophobic peptides is strongly enhancedonce absorbed on a hydrophobic surface and peptide dehydration has adrastic influence on peptide aggregation. By performing discontinuous MDsimulations with a coarse-grained peptide model on a system consisting ofhundreds of 12-residue peptides, Auer et al. (2009) have characterized themolecular mechanism of peptide aggregation in the presence of spherical

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nanoparticles. Their study shows that nanoparticle surfaces catalyze theself-assembly of peptides into fibrillar structures by a condensation-ordering mechanism. This mechanism involves a first phase in which smallstructurally disordered oligomers assemble on the nanoparticle surface anda second phase in which they evolve into highly ordered β-sheets as theirsize increases. It was also observed that the molecular mechanism associatedwith the condensation ordering transition for peptide–nanoparticle associ-ation is independent of particle size and hydrophobicity. These studies helpin the understanding of the effects of surface properties on the aggregationof short fragments of non-Aβ peptide at the atomic level. Investigations onthe structural dynamics of Aβ monomers and oligomers at surfaces are alsoemerging.

8.3.1 Structural dynamics of β-amyloid monomers and oligomerson a flat surface

The direct simulation of Aβ aggregation at surfaces starting from randomstates is still a challenge using all-atom MD simulations due to the samplingproblem. As a first step in understanding the conformational dynamics ofAβ on surfaces, Zheng et al. (2008) have studied the adsorption behaviorof Aβ1-42 monomers on the self-assembled monolayer (SAM) surfacestarting from two distinctly structured Aβ1-42 conformations: α-helix andβ-hairpin (Wang et al., 2010). Four SAM surfaces with different endgroupsin hydrophobic and charged properties are used to examine the effectof surface chemistry on Aβ1-42 structures and adsorption. Simulationresults show that the α-helix displays greater structural stability than the β-hairpin on all SAMs, suggesting that the preferential conformation of theAβ1-42 monomers could be α-helical or random structure when boundto surfaces. Similarly, this research group has investigated the interactionsof the preformed fibril-like Aβ17-42 pentamers with two model SAMs:hydrophobic CH3-SAM and hydrophilic OH-SAM, particularly focusingon the effects of surface chemistry and Aβ17-42 orientation on theadsorption behavior of Aβ peptides and the underlying driving forces(Wang et al., 2010). Their MD simulations show that the hydrophobicCH3-SAM has a stronger binding affinity to Aβ17-42 pentamers than thehydrophilic OH-SAM, although both surfaces can induce Aβ adsorption.

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Structural and energetic comparison among six Aβ-SAM systems withdifferent orientation of the Aβ17-42 pentamers relative to the SAM surfacefurther reveals that Aβ orientation, SAM surface hydrophobicity, andinterfacial water all play an important role on the adsorption behaviorof the Aβ17-42 pentamers at surfaces (Wang et al., 2010).

8.3.2 Induced β-barrel formation of Aβ25-35 oligomerson carbon nanotube surfaces

Previous experimental studies show that nanoparticles, such as fullereneand polymeric nanoparticles, which provide a more hydrophobic environ-ment than water, inhibit the fibrillation of Aβ25-35, Aβ1-40, and Aβ1-42 peptides (Kim and Lee, 2003; Podolski et al., 2007; Cabaleiro-Lagoet al., 2008). These studies greatly enhance our understanding of theimpact of hydrophobic nanoparticles on the kinetics of amyloid formation;however, the detailed adsorption dynamics are far from understood. Here,we review our all-atom MD study of the structural dynamics of the lowmolecular weight (LMW) Aβ25-35 β-rich oligomers on the surface of atypical hydrophobic nanoparticle–SWNT of different diameters (Fu et al.,2009). This 11-residue fragment forms amyloid fibrils in vitro and retainsthe toxicity of the full-length Aβ (Pike et al., 1995). Hydrogen-deuterium(H/D) exchange nuclear magnetic resonance (NMR) experiments indicatethat Aβ25-35 fibrils display a cross-β-core formed from K28 to M35,with residues I31 and I32 being the most protected (Ippel et al., 2002).As the formation of LMW β-rich oligomers from random states is outof reach using all-atom explicit-solvent MD simulations at physiologicaltemperature (Ma and Nussinov, 2006), and the equilibrium ensemble of anoctamer consists of various bilayer β-sheets and amorphous states (Lopezde la Paz et al., 2005; Melquiond et al., 2006; Lu et al., 2009), we havestudied, as a first step, the detailed interactions between two preformedAβ25-35 β-sheets and SWNT.

Our initial Aβ25-35 states consist of two disjointed β-sheets,each composed of four or five β-strands with the solid-state NMR-derived parallel or mixed antiparallel–parallel out-of-register arrangements(Ippel et al., 2002) and the N- and C-termini charged for each chain(Ippel et al., 2002) (mimicking the experimental neutral pH condi-tion). A series of armchair SWNT(n, n) are constructed with n = 3, 4,

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and 5 yielding the tube diameters of 0.404, 0.542, and 0.677 nm,respectively. All tube lengths are set to 4.25 nm to provide sufficientsurface for Aβ25-35 peptides to adsorb. The simulated systems are Aβ25-35 octamer + SWNT(3,3), octamer + SWNT(4,4), decamer + SWNT(4,4),and decamer + SWNT(5,5). Multiple independent 10–20 ns MD runs arecarried out at 300 K and 1 bar starting from each system. The setup detailsof all MD runs can be found in Fu et al. (2009).

All MD simulations are performed in explicit solvent using theGROMACS software package (Lindahl et al., 2001) and GROMOS96 forcefield (Van Gunsteren et al., 1996). Carbon atoms of SWNT are uncharged inaccordance with Hummer et al. (2001) and the Lennard–Jones parametersfor the peptide–SWNT and water–SWNT interactions are obtained usingthe Lorentz–Berthelot rule (Hirschfelder and Brid, 1954).

Our MD simulations show that initial structures of β-sheets composedof purely parallel β-strands do not form β-barrels at the SWNT–waterinterface due to the geometric constraints imposed by the bulky M35side-chains (Fu et al., 2009). By contrast, adsorption of Aβ octamer anddecamer with mixed antiparallel–parallel strands onto different diametersof SWNT can lead to the formation of open or closed β-barrels wrappingSWNT, independently of the initial orientation of the two disjointed β-sheets (Fu et al., 2009) (see Table 8.1). Here we focus on the results of MDruns that lead to the formation of β-barrels. The initial states and the finalformed open or closed β-barrels are shown in Table 8.1. An open/closed β-barrel is considered to be formed if there are ≥ 3 hydrogen bonds (H-bonds)between the edge strands of one/two sides of the two disjointed β-sheets. Itis noted that the formation of Aβ25-35 β-barrels from two four- and five-stranded β-sheets with mixed parallel–antiparallel strands is not systematicand we find that 30% of the simulations lead to β-barrels surrounding thecarbon nanotube and the others lead to disordered aggregates adsorbingon the tube surface.

8.3.2.1 Free energy landscape of octamer + SWNT(3,3) system

Of a total of 61 independent MD runs starting from the three differentinitial states A, B, and C shown in Table 8.1, 12 independent MDruns show a fast conversion of β-sheets into β-barrels. The free energylandscape as a function of the number of intersheet backbone hydrogen

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Table 8.1. The initial and final structures of each single-walled carbon nanotube(SWNT) + Aβ25-35 oligomer system in molecular dynamics simulations at 300 K.

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Figure 8.1. Analysis of the assembly of two tetrameric Aβ25-35 β-sheets into a eight-stranded β-barrel on a single-walled carbon nanotube (SWNT)(3,3) surface. (a) Free energylandscape along with the structures of SWNT + Aβ25-35 at four different locations. Thesestructures are taken from a representative molecular dynamics (MD) run. a: one of the initialstates; b: curved β-sheet + SWNT; c : open β-barrel + SWNT; d : closed β-barrel + SWNT.The free energy (in kcal/mol) is projected onto the number of intersheet backbone H-bondand radius of gyration of hydrophobic residues (Rg-HP). The data are constructed using12 independent MD runs leading to β-barrel formation. Time evolution of: (b) Rg-HP andbackbone root mean square deviation of the octamer with respect to the β-barrel structuregenerated at 10 ns and (c) number of intersheet H-bonds at the left and right edge of thetwo β-sheets. The inset in (b) gives the total number of water molecules within a cylindricalshell of 1 nm height (z-direction, in the region of −0.5 nm < z < 0.5 nm) and 1 nm radiusfrom z-axis. Here, the coordinates of the geometric center of SWNT are set to (0,0,0).

bonds (inter-H-bond) and the radius of gyration of hydrophobic residues(Rg-HP) is plotted in Fig. 8.1a. The structures at four different minimaare also given, taken from a single MD run. Here, Rg-HP uses only theI31 and M35 side-chains as the A30, I32, and Leu34 side-chains mostlypoint to bulk water during the simulations. Note that our calculation does

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not provide the full free energy surface of Aβ25-35−SWNT, because theAβ25-35 peptides are not initially in randomly chosen conformations andorientations. We observe a first delocalized, continuous basin spanning(inter-H-bond, Rg-HP) values of (0, 0.7 nm)–(6, 0.7 nm) and a secondsmaller basin centered at (11,0.65 nm). These basins correspond to compactassemblies, open β-barrels, and closed β-barrels of Aβ25-35, respectively.The overall “L” shape of the free energy map with the structural descriptionof the minima indicates that β-barrel formation is driven first by stronghydrophobic interactions of Aβ25-35 with SWNT and then by intersheetH-bond formation. This is further demonstrated in Fig. 8.1b and c bythe time evolution of three structural properties in a representative MDrun starting from structure a shown in Fig. 8.1a: Rg-HP and backboneroot mean square deviation (RMSD) with respect to structure d , andthe number of intersheet H-bonds at the left and right edge of the twoβ-sheets. In this MD run, the rapid reduction in Rg-HP is accompaniedby a curving of the two β-sheets (see structure b in Fig. 8.1a), followed bythe formation of an open β-barrel (see structure c in Fig. 8.1a). Finally,we see a gradual increase in the number of intersheet H-bonds up to five(an indication of closed β-barrel formation) and a gradual decrease in theRMSD (Fig. 8.1b) as a function of time. During this process, dehydration isobserved in the ocatmer–SWNT(3,3) interface (see the inset in Fig. 8.1b).Similar phenomena are observed in the other 11 MD runs. The dehydrationprocess is monitored by calculating as a function of time the total numberof water molecules within a cylindrical shell of 1 nm height (z-direction, inthe region of −0.5 nm < z < 0.5 nm) and 1 nm radius from z-axis.

8.3.2.2 β-Barrel formation of larger system–decamer + SWNT(4,4)

Figure 8.2 follows the formation of a closed β-barrel in a representativeMD run of decamer + SWNT(4,4) system, and gives the representativesnapshots generated at six different time points and the time evolution ofthree structural variables (Rg-HP, backbone RMSD, and the number ofintersheet H-bonds). Similar to the assembly process of two tetramericβ-sheets into β-barrel structure shown in Fig. 8.1b and c, the twopentameric β-sheets quickly bind to the SWNT wall due to stronghydrophobic interactions between them, leading to a rapid decrease in

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Figure 8.2. Detailed analysis of the assembly process of two pentameric β-sheets into aten-stranded β-barrel structure on a single-walled carbon nanotube (SWNT)(4,4) surfaceobserved in a representative molecular dynamics run. (a) Six representative snapshots ofAβ25-35 decamer + SWNT(4,4). Time evolution of: (b) radius of gyration of hydrophobicresidues (Rg-HP) and backbone root mean square deviation (RMSD) of the decamer relativeto the barrel structure generated at 10 ns and (c) number of inter-H-bonds at the left andright edge of the two β-sheets.

Rg-HP and a curving of the two β-sheets (see the snapshot at t = 0.2 nsin Fig. 8.2a). This is followed by the formation of an intersheet H-bondat the left edge of the two β-sheets (see the snapshot at t = 0.6 ns). Att = 1 ns, Rg-HP decreases to 0.75 nm and two sheets start to form H-bondsat their right edge (see Fig. 8.2c and the snapshot at t = 1 ns in Fig. 8.2a).Afterwards, the number of intersheet H-bonds increases gradually and aclosed barrel forms after t = 4 ns (see Fig. 8.2c and the snapshot at t = 6 ns

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in Fig. 8.2a). The next step is the rearrangement of the hydrophobic coreand the optimization of the β-barrel structure, leading to a small fluctuationof Rg-HP around 0.75 nm and a constant decrease of RMSD (Fig. 8.2c) vs.simulation time. The conversion of two pentameric β-sheets into a β-barrelon the SWNT(4,4) surface is also accompanied by a dehydration processin the peptide–SWNT interface. The dehydration process is monitored bycalculating as a function of time the number of water molecules withinsuccessive cylindrical shells of 0.5 nm height (z-direction) and 1.0 nmradius from z-axis. As shown in Fig. 8.3a, the number of water molecules atthe SWNT−Aβ25-35 interface in the region of z = −1.0−1.0 nm is ≥ 20at 0 ns and decreases gradually with time, reaching approximately zero at1.0 ns. The four snapshots at times of 0, 0.24, 0.48, and 1 ns in Fig. 8.3b showa clear dehydration process of the SWNT−Aβ25-35 interface. A similarpicture also emerges from other MD runs of the decamer + SWNT(4,4)system.

Figure 8.3. Dehydration process of the Aβ25-35 decamer–single-walled carbon nanotube(SWNT)(4,4) interface observed in the molecular dynamics run analyzed in Fig. 8.2.(a) Time evolution of the number of water molecules within each cylinder along SWNT-axis.The cylinder is 1.0 nm thick from the SWNT-axis and 0.5 nm high. (b) Four snapshots ofSWNT(4,4)–water (view parallel to SWNT-axis) generated within the first 1 ns. To visualizethe dehydration process clearly, the Aβ25-35 decamer is omitted, a circle with a radius of1 nm from the SWNT-axis is drawn as a dotted line, and only the water molecules within2 nm of the SWNT-axis are displayed.

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Figure 8.4. Time evolution of the potential energy components in the moleculardynamics run analyzed in Fig. 8.2. (a) Single-walled carbon nanotube (SWNT)–water andSWNT−Aβ25-35. (b) Aβ25-35−water and Aβ25-35−Aβ25-35. (c) Water–water.

To understand further the physical driving forces underlying theconversion of two pentameric β-sheets into a β-barrel, we plot in Fig. 8.4 thetime evolution of the potential energy contribution of the SWNT−water,SWNT−Aβ25-35, Aβ25-35−water, Aβ25-35−Aβ25-35, and water−waterinteractions in the MD run analyzed in Figs 8.2 and 8.3. Given the factthat the simulation timescales are too short to estimate the entropiccontributions, our analysis is only qualitative and indicative. We see thatthe SWNT−Aβ25-35, Aβ25-35−Aβ25-35, and water–water interactionssuffice to compensate the energy cost to repel water from the SWNT−Aβ25-35 interface and the energy loss associated with the SWNT–water, andAβ25-35−water interactions. Our energy decomposition along with theobservation of dehydration at the SWNT(4,4)-decamer interface suggeststhat Aβ25-35 β-barrel formation on the SWNT surface results from theinterplay of dehydration, SWNT–water, and Aβ25-35–water interactions.

It is noted that the time evolution similarity of Rg-HP, backbone RMSD,and the number of intersheet H-bonds between the SWNT(4,4) + decamer(Fig. 8.2b and c) and SWNT(3,3) + octamer (Fig. 8.1b and c) is strik-ing. Similar results are obtained for the SWNT(4,4) + octamer andSWNT(5,5) + decamer systems (data not shown). Taken together withthe dehydration process in the Aβ25-35 octamer + SWNT(3,3) (inset inFig. 8.1b) and decamer + SWNT(4,4) (Fig. 8.3), we can assess that theformation of open/closed β-barrels involves two steps, independently ofthe SWNT diameter and Aβ25-35 oligomer size: (i) curving of the Aβ25-35β-sheets as a result of hydrophobic interactions of peptides with SWNT

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and dehydration of the SWNT–peptide interface; and (ii) formation ofintersheet backbone H-bonds.

Our MD simulations provide strong evidence that Aβ25-35 oligomericspecies with β-barrel and more disordered characteristics form easilyaround SWNT despite the fact that they do not start from random states ofAβ25-35 peptides and do not explore how carbon nanotubes influencethe nucleation process. These newly formed Aβ25-35 LMW aggregatestherefore block backbone amide sites for further monomer addition to theβ-sheet structure and reduce the population of small oligomers availablefor the next steps of aggregation. Aβ1-40/1-42 also contains two otherhydrophobic cores 17-21 and 36-40/42, which could be potential bindingsites for SWNT. Whether there are multiple binding sites between Aβ

peptides and SWNT remains to be determined. However, the propensity ofresidues 28-35 to form barrels around SWNT is likely to reduce the loop orbent formation for the region Ser26–Ala30 proposed in the Aβ1-42 fibrillar(Luhrs et al., 2005) and Aβ17-42 annular (Zheng et al., 2008) models, andthis would also enhance the lag time for Aβ nucleation in the presenceof SWNT.

Based on the present finding of β-barrel formation of Aβ25-35oligomers on SWNT surfaces and recent findings that fullerene C60 andcylindrical protein substrate inhibited the fibrillation of Aβ1-40 (Kim andLee, 2003; Takahashi and Mihara, 2008) and Aβ25-35 (Podolski et al.,2007), and carbon nanotubes prevented the aggregation of human acidicfibroblast growth factor protein (Ghule et al., 2007), we propose thatcarbon nanotubes are likely to be potent inhibitors of Aβ25-35 fibrilformation. Whether the SWNT + Aβ25-35 aggregates are toxic remainsto be determined, but a recent study suggests that short SWNTs withlengths <5–10 µm (i.e. larger than our SWNT length) are not (Kostarelos,2008).

8.4 Conclusions

Much knowledge has been gained in recent years on the assembly andfibrillation of Aβ peptides on surfaces/nanoparticles from experimentaland computational studies. These studies suggest that the physicochemicalproperties of surfaces/nanoparticles, including charge, hydrophobicity, and

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the shape of nanoparticles, impact the conformation and morphologiesof resulting aggregates of Aβ (Kowalewski and Holtzman, 1999; Kimand Lee, 2003; Rocha et al., 2005; Ban et al., 2006). The interactionsof Aβ peptides with different surfaces can thus promote/inhibit Aβ

fibrillation by accelerating/slowing down the nucleation process, leavingthe elongation phase invariant, suggesting a surface-modulated nucleationmechanism (Cabaleiro-Lago et al., 2008; Wu et al., 2008). All-atom MDsimulation studies on the conformational dynamics of the structured Aβ

monomers and oligomers on surfaces suggest that Aβ orientation, surfacehydrophobicity, and interfacial water all play an important role in theadsorption behavior (Wang et al., 2010). Strikingly, we observe, in ourMD simulations in explicit water, that LMW Aβ25-35 β-rich oligomerscan form β-barrels wrapping SWNT (Fu et al., 2009). The formation of β-barrels might block the binding sites for monomer addition and may offerthe prospect of using carbon nanotubes as a new type of therapeutic agent toretard/prevent Aβ25-35 fibrillation. These findings suggest that appropriatesurfaces could be used as a platform on which to form new Aβ assemblies tocontrol the rate of peptide self-assembly. Finally, these results will providenew insights into the assembly of Aβ on surfaces/nanoparticles and willenhance our understanding of the fibrillation process at the molecularlevel.

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[Molecular Medicine and Medicinal Chemistry] Alzheimer's Disease: Insights into Low Molecular Weight...

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