Norepinephrine Inhibits Alzheimer's Amyloid-β Peptide Aggregation

Jan 3, 2019 - The abnormal self-assembly of amyloid-β (Aβ) peptides into toxic fibrillar aggregates is associated with the pathogenesis of Alzheimer...
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Norepinephrine Inhibits Alzheimer's Amyloid-# Peptide Aggregation and Destabilizes Amyloid-# Protofibrils: A Molecular Dynamics Simulation Study Yu Zou, Zhenyu Qian, Yujie Chen, Hongsheng Qian, Guanghong Wei, and Qingwen Zhang ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.8b00537 • Publication Date (Web): 03 Jan 2019 Downloaded from http://pubs.acs.org on January 5, 2019

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Norepinephrine

Inhibits

Alzheimer's

Amyloid-β

Peptide

Aggregation and Destabilizes Amyloid-β Protofibrils: A Molecular Dynamics Simulation Study

Yu Zou,a Zhenyu Qian,b Yujie Chen,c Hongsheng Qian,a Guanghong Wei,c and Qingwen Zhanga

a

College of Physical Education and Training, Shanghai University of Sport, 399

Changhai Road, Shanghai 200438, People’s Republic of China b

Key Laboratory of Exercise and Health Sciences (Ministry of Education) and School

of Kinesiology, Shanghai University of Sport, 399 Changhai Road, Shanghai 200438, People’s Republic of China c

State Key Laboratory of Surface Physics, Key Laboratory for Computational

Physical Science (Ministry of Education), Collaborative Innovation Center of Advanced Microstructures, and Department of Physics, Fudan University, Shanghai 200433, People’s Republic of China

ABSTRACT: The abnormal self-assembly of amyloid-β (Aβ) peptides into toxic fibrillar aggregates is associated with the pathogenesis of Alzheimer’s disease (AD). The inhibition of β-sheet-rich oligomer formation is considered as the primary therapeutic strategy for AD. Previous experimental studies reported that norepinephrine (NE), one of the neurotransmitters, is able to inhibit Aβ aggregation and disaggregate the preformed fibrils. Moreover, exercise can markedly increase the level of NE. However, the underlying inhibitory and disruptive mechanisms remain elusive. In this work, we performed extensive replica-exchange molecular dynamic (REMD) simulations to investigate the conformational ensemble of Aβ1-42 dimer with and without NE molecules. Our results show that without NE molecules, Aβ1-42 dimer 1

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transiently adopts a β-hairpin-containing structure, and the β-strand regions of this β-hairpin (residues 15QKLVFFA21 and 33GLMVGGVV40) strongly resemble those of the Aβ fibril structure (residues 15QKLVFFA21 and 30AIIGLMVG37) reported in an electron paramagnetic resonance spectroscopy study. NE molecules greatly reduce the inter-peptide β-sheet content and suppress the formation of the above-mentioned β-hairpin, leading to a more disordered coil-rich Aβ dimer. Five dominant binding sites are identified, and the central hydrophobic core 16KLVFFA21 site and C-terminal 31IIGLMV36 hydrophobic site are the two most favorable ones. Our data reveal that hydrophobic, aromatic stacking, hydrogen-bonding and cation-π interactions synergistically contribute to the binding of NE molecules to Aβ peptides. MD simulations of Aβ1-42 protofibril show that NE molecules destabilize Aβ protofibril by forming H-bonds with residues D1, A2, D23, and A42. This work reveals the molecular mechanism by which NE molecules inhibit Aβ1-42 aggregation and disaggregate Aβ protofibrils, providing valuable information for developing new drug candidates and exercise therapy against AD. KEYWORDS: replica exchange method, molecular dynamics simulations, Amyloid-β,

protein

aggregation,

norepinephrine,

inhibitory

and

disruptive

mechanisms

TOC INTRODUCTION The fibrillar aggregates of proteins are associated with a range of human systemic disorders, such as Alzheimer’s diseases, Parkinson’s diseases and type 2 diabetes.1-3 Alzheimer’s disease (AD) is the most common neurodegenerative disorder currently 2

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affecting more than 12 million people worldwide.4 The histological hallmark of AD is the presence of extracellular senile plaques and intracellular neurofibrillary tangles (NFTs) formed respectively by amyloid β (Aβ) and tau protein.5,

6

The two most

abundant Aβ isoforms are Aβ1-40 and Aβ1-42. Aβ1-42 is more prone to aggregation and has higher neurotoxicity than Aβ1-40.7-9 Soluble Aβ monomer is mainly disordered, and it can self-assemble into amyloid fibrils through a complex multistep process, containing the formation of oligomers, protofibrils, and mature fibrils.10-12 Both small aggregates (soluble oligomers and protofibrils) and mature fibrils are neurotoxic agents.13, 14 The Aβ dimer, the smallest toxic species isolated from cerebral tissue of AD patients, could impair the normal functions of neuron cells.15 The Belfort group16-18 have studied the formation of dimer and the effects of variants on long term potentiation inhibition, and showed that the N-terminal residue A2 is important in Aβ dimerization. Several structural models of Aβ fibrils have been reported and they display both LS- and U-shaped structures with two-fold or three-fold symmetries,19-21 revealing molecular-level structural polymorphism of Aβ fibrils. Search of potential inhibitors has become the focus of active studies, and finding the effective inhibitors is crucial for the development of AD drug design.22, 23 Several potential inhibitors were reported to be able to impede Aβ aggregation and dissociate preformed fibrils, such as short peptides,24, antibodies,30,

31

and small molecules32,

33.

25

nanoparticles,26-28 metal ions,29

Inspired by these experimental studies,

computational researchers examined the molecular mechanism by which these inhibitors impede the aggregation34-37 of different Aβ fragments and full-length Aβ and dissociate preformed fibrils38-41 using molecular dynamic (MD) simulations. For example, the work by Mu et al showed that the binding of EGCG to Aβ1−42 dimer reduces the CHC/CHC and C-terminal/C-terminal interactions and the β-sheet content of Aβ.35 Derreumaux et al found that NQTrp molecules inhibit the formation of β-sheet of Aβ1−42 dimer by binding to ten residues R5, D7, Y10, H13, K16, K18, F19, F20, L34 and M35.37 The simulation study by Li et al suggested that the LPFFD peptide inhibits the fibrillogenesis of Aβ9−40 by mostly forming backbone hydrogen 3

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bonds with residues F20, D23 and V24.40 Gazova et al reported that fullerenol interferes with Aβ1−40 aggregation through enhancing the flexibility of the D23-K28 salt bridge.41 These results reveal distinct binding modes and inhibitory/disruptive mechanisms of different inhibitors, which greatly enhances our understanding of Aβ-inhibitor interactions at atomic level. Norepinephrine (NE), one of the neurotransmitters, has received great attention in the research field of the anti-amyloid aggregation and AD treatment.42,

43

NE is

essential for contextual and spatial memory retrieval in both AD mouse models and AD patients.44-46 A number of studies show that exercise can stimulate the release of NE and increase its concentration.47-49 Increased levels of NE are associated with the reduced neurotoxic of early accumulating Aβ oligomers.46 Moreover, NE can effectively inhibit the formation of Aβ fibril and disrupt the preformed fibrils.42 However, the inhibitory and disruptive mechanisms remain elusive. In this study, we investigated the effect of NE molecules on conformational ensembles of Aβ dimer by carrying out 300-ns all-atom explicit-solvent replica exchange molecular dynamic (REMD) simulations starting from disordered coil states. The results show that NE molecules strongly inhibit the formation of β-sheet of Aβ1-42 dimer. We identified five dominant binding sites of NE molecules to Aβ1-42 dimer and analyzed the crucial interactions. We also examined the influence of NE molecules on the structural stability of Aβ protofibrils by performing three 1-μs conventional MD simulations, and found that NE molecules have a preference to form hydrogen bonds (H-bonds) with the backbone atoms of residues residues D1, A2, D23, and A42 and thus destabilize Aβ protofibril.

RESULTS AND DISCUSSION We first verified the convergence of the two REMD simulations by comparing several parameters within two different time interval using 150-225 and 225-300 ns data for Aβ-dimer and Aβ-dimer+NE systems at 310 K. As shown in Figures S1-S4, REMD simulations are reasonably converged within 300 ns. The convergence of the 4

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simulations indicates that the analysis using the data generated at 310 K can provide an appropriate estimate to the conformational space of Aβ dimer and we do not need to reweight the conformations at different temperatures, as shown previously by us50-52 and many other groups53-55. NE molecules markedly reduce the β-sheet probability and enhance the coil probability of Aβ dimer. To investigate the influence of NE molecules on the secondary structure propensity, we calculated the secondary structure compositions (including coil, β-sheet, β-bridge, bend, turn and helix) over all residues and the residue-based secondary structure probability of Aβ dimer in these two systems. As shown in Figure 1, starting from disordered states, the probability of β-sheet in the Aβ dimer without NE molecules is 12.43%, quite close to that (11.7%) generated in the REMD study using the force field of Amber ff99SB-ILDN for Aβ1-42 dimer.56 With the addition of NE molecules, the β-sheet content markedly decreases to 7.76% in the Aβ-dimer+NE system, while the probability of helix increases significantly from 2.46% to 6.87%. The helix and β-sheet probabilities in the Aβ-dimer system are consistent with those (~3% and ~13%) from previous CD experiments on Aβ1-42 at pH 7.5 at time zero.57 The coil and turn contents are also enhanced with the addition of NE molecules. The contents of β-bridge and bend are similar in the two systems. Interestingly, α-helix structures of serum albumin protein placed on an apolar surface may transform into β-sheet, while the reverse process that β-sheet structures of an Aβ dimer was observed to partially transform to α-helix in our REMD simulations. These distinct phenomena are attributed to the differences of molecular polarity, interfacial properties and amino acid sequences of the two proteins in two systems.58 We then calculated the dominant secondary structure probability per amino acid residue. As shown in Figure 1(e), in the Aβ-dimer system, the β-sheets are mostly located in two regions: the central hydrophobic core (CHC) -spanning region (14HQKLVFFA21) and the C-terminal region encompassing residues 33GLMV36 and 38GVVI41. In the Aβ-dimer+NE system, the β-sheet content in most regions is greatly reduced, including 4FRH6, 10YEVHHQKLVFFA21, 27NKGA30, and 34LMVGGVVI41. 5

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The coil and helix probabilities of most residues are increased (Figure 1(f, g)). These data demonstrated that the β-sheet formation of Aβ peptides could be significantly inhibited by the NE molecules.

Figure 1. Initial states of Aβ dimer (a), Aβ dimer in the presence of NE molecules (b), and the chemical structure of an NE molecule (c). The Cα-atom in the N-terminal of Aβ dimer is represented by a blue bead. Analysis of secondary structure contents of Aβ dimer in the absence (black) and presence (red) of NE molecules. The average probability of each secondary structure (coil, β-sheet, β-bridge, bend, turn and helix) over all residues (d). The β-sheet (e), coil (f) and helix (g) probability as a function of amino acid residue.

NE molecules inhibit the formation of long β-strands and alter the free energy surface of Aβ dimer. To examine the effect of NE molecules on the three-dimensional (3D) structures of Aβ dimer, we performed a cluster analysis for 75000 conformations sampled in Aβ-dimer and Aβ-dimer+NE systems. With a Cα-root-mean-square-deviation (Cα-RMSD) cutoff of 0.35 nm, the dimer 6

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conformations were separated into 158 clusters for isolated Aβ and 95 clusters for Aβ in the complex. Figure 2 shows the center conformations of the top nine most-populated clusters. These clusters represent 50.2% and 55.0% of all conformations of the isolated Aβ dimer and the dimer in Aβ-dimer+NE system, respectively. As shown in Figure 2(a, b), the Aβ dimer in the top nine clusters for the two systems mainly adopts disordered coil-rich conformations. However, the length of β-strand in the isolated Aβ dimer is much longer than that in the complex. To examine whether this difference is statistically significant, we calculated the probability of β-strand length for all the conformations. As shown in Figure 2(c), in the absence of NE molecules, the majority of β-strands has a length of 2-5 residues, and the total probability is 84% (with a probability of 36%, 19%, 13% and 16% for 2-, 3-, 4- and 5-residue long β-strands, respectively). The long β-strands with a length of 6-9 residues also exist in the Aβ-dimer system. In the Aβ-dimer+NE system, β-strands with a length of 2-4 residues become the most abundant structures, while long β-strands with 5-9 residues in length are significantly inhibited, particularly for the 8-residue long β-strand. These results indicate that NE molecules greatly reduce the population of long β-strands, which prevent Aβ peptides from forming larger β-sheet-rich oligomers. To have an overall view of NE molecules on the full conformational distribution of the Aβ dimer, we plotted in Figure 2(d, e) the potential of mean force (PMF) as a function of the number of main chain H-bonds and the radius of gyration (Rg) of the Aβ dimer in these two different systems. The locations of the top nine most-populated clusters are labelled on each free-energy surface. As shown in Figure 2(d), the minimum-energy basin in the Aβ-dimer system is centered at the (Rg, H-bond number) value of (1.22 nm, 25), corresponding to the β-hairpin structure in cluster 5. In the presence of NE molecules (Figure 2(e)), it is located at the value of (1.34 nm, 21), corresponding to the β-hairpin structure in cluster 5 and the disordered coil-rich conformation in cluster 3. The increased value of Rg and the decreased number of H-bonds indicate that NE molecules impede the formation of main chain H-bond and induce the formation of loosely packed coil-rich 7

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conformations, thus changing the free energy landscape.

Figure 2. Representative conformations of the first nine most-populated clusters of Aβ dimer in Aβ-dimer (a) and Aβ-dimer+NE (b) systems. The parentheses show the corresponding population of each cluster. The two Aβ chains A and B are separately colored in red and blue. The Cα atom in the N-terminal of each Aβ chain is represented by the green bead. The probability of the β-strand length in the Aβ dimer with and without NE molecules (c). Potential of mean force (PMF) (kcal/mol) as a function of the Rg of the Aβ peptides and the number of backbone H-bonds for the Aβ-dimer (d) and Aβ-dimer+NE (e) systems.

We also notice that β-hairpin motifs exist in two of the top nine clusters. The β-hairpin motifs were reported to be the precursor of Aβ fibril.59 Thus, we analyzed all β-hairpins sampled in the last 150 ns REMD simulation to identify the most-populated β-hairpin motifs in these two systems. Representative structures of the top four most populated β-hairpins (yellow) in the Aβ-dimer system are shown in Figure 3(a). The first most-populated β-hairpin (15.8%) comprising two strands (β1: residues 15QKLVFFA21, β2: residues 33GLMVGGVV40) has the longest β-strands among all the β-hairpins. The β-strand regions resemble those of the Aβ1-42 fibril model (β1: residues 15QKLVFFA21, β2: residues 30AIIGLMVG37) proposed by Langen by means of the electron paramagnetic resonance spectroscopy.60 The 8

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probability of the first most-populated β-hairpin is close to those of the β-hairpin (residues 17LVFFA21 and 30AIIGLMV36, with a probability of 13%) observed in a recent REMD study by Derreumaux et al.61 The second most-populated β-hairpin (9.5%) consists of two β-strands: residues 17LVFFA21 and 26SNKGA30, partially resembling those of the Aβ1-42 fibril model (β1: residues 15QKLV18, β2: residues 26SNK28) proposed by Riek.62 This β-hairpin conformation is also quite similar to the one reported in a recent REMD study (β1: residues 18VFFAE22, β2: residues 28KGAII32) using the Gromos53A6 force field.63 Hairpin structures formed by the N-terminal residues (β1: 4FRHD7, β2: 10YEVHH14) or C-terminal residues (β1: 28KGAI31, β2: 35MVGGV39) were also populated, with a probability of 2.5% or 1.8%, respectively. The regions of β-strands resemble those of the Aβ1-42 fibril model (β1: residues 15QKLVFFA21, β2: residues 30AIIGLMVG37) resolved using solid-state NMR by Ishii and Griffin groups.20, 64 The representative structures of the top four most-populated β-hairpins in the Aβ-dimer+NE system are shown in Figure 3(b). We found that the majority of the most-populated β-hairpins in the Aβ-dimer system are completely suppressed, and the emerging β-hairpin motifs become much shorter than those in Aβ-dimer system. These data suggest that Aβ1-42 dimers, as the smallest oligomer, can form β-hairpin containing conformations that display the similar β-strand regions as toxic Aβ fibrils. And the addition of NE molecules to Aβ-dimer system can strongly suppress the formation of these β-hairpin structures, thus inhibiting Aβ fibrillization.

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Figure 3. Representative structures of the most-populated β-hairpins found in the Aβ-dimer (a) and Aβ-dimer+NE (b) systems. The most-populated β-hairpin is colored in yellow.

Binding of NE molecules to Aβ peptides interferes with peptide-peptide interaction. In order to probe the effect of NE molecules on the inter-peptide interaction, we calculated the probability distribution function (PDF) of the solvent accessible surface area (SASA) of the Aβ dimer and the contact surface area (CSA) between the two Aβ peptide chains. As shown in Figure 4(a), the peptides in Aβ-dimer+NE system display a larger SASA peak value than those in the Aβ-dimer system. The average inter-chain CSA value is 9.5 nm2 in the Aβ-dimer system, while it decreases to 7.5 nm2 with the addition of NE molecules (Figure 4(b)). This reduction of inter-chain CSA value is attributed to the binding of NE molecules to the Aβ peptides, as seen from the large CSA value (14.5 nm2) between Aβ and NE molecules in Figure 4(c). We also plotted the distribution of inter-chain main chain H-bond number in Figure 4(d) for both systems. The presence of NE molecules leads to the peak of the main chain H-bond number shifting from 8 to 5. All of these data demonstrate that the binding of NE molecules to Aβ peptides interferes with the peptide-peptide interaction, and prevents the inter-peptide hydrogen bonding formation.

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Figure 4. PDF of the solvent accessible surface area (SASA) (a), the inter-peptide contact surface area (CSA) (b), the CSA between NE molecules and Aβ dimer (c), and the number of inter-chain main chain H-bonds (d) for Aβ dimer in the absence and presence of NE molecules.

To further understand the roles of NE molecules on the dominant Aβ interactions, we calculated the contact probability between each pair of residues in the absence and presence of NE molecules to estimate the inter-peptide and intra-peptide main chain-main chain (MC-MC) and side chain-side chain (SC-SC) interactions. As shown in Figure 5, the MC-MC interaction patterns in the two systems are remarkably different. Without NE molecules, the dominant inter-peptide interactions occur between 18VFFAED23 and 22EDVGS26. However, the contacts between these residues were significantly reduced in the presence of NE molecules. Quantitatively similar results are observed in the SC-SC contact map in Figure S5. The intra-chain MC-MC interaction is also affected by the presence of NE molecules. In the absence of NE molecules, strong left-diagonal contacts between residues 15QKLVFFA21 and 33GLMVGGV39, or residues 17LVFFA21 and 26SNKGA30 are observed in Figure 5(a), corresponding to the top two populated β-hairpin structures in Figure 3(a). However, most of these residue pairs display a reduced contact probability in the Aβ-dimer+NE system (Figure 5(b)). Especially, the contacts between the residues in the β-hairpin (β1: residues 15QKLVFFA21, β2: residues 33GLMVGGV39) almost disappear. Two key regions of Aβ play critical roles in aggregation: the CHC region (17LVFFAED23) and the C-terminal hydrophobic region (30AIIGLMV36).65, 66 The disappeared β-hairpin structures formed by residues in these two regions indicate that the interaction of NE molecules with Aβ dimer could effectively prevent the β-sheet formation and the subsequent fibrillization.

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Figure 5. MC–MC contact probability maps for Aβ dimer without (a) and with (b) NE molecules.

Binding modes and dominant binding sites of NE molecules with Aβ dimer. To examine the dominant binding sites of NE molecules on the surface of Aβ dimer, we calculated the binding free energy of NE molecules with each amino acid residue. As seen in Figure 6(a), NE molecules have the lowest binding energy with hydrophobic residues I41, I31 and L17, and aromatic residues Y10, F4 and F20, indicating the important roles of hydrophobic and aromatic stacking interactions in the NE-Aβ interaction. Previous studies showed that hydrophobic and aromatic stacking interactions play important roles in the formation and stabilization of Aβ fibrils.67, 68 The NE molecules preferentially interact with Aβ dimer at five different sites: 3EFRHD7, 10YEVHH14, 16KLVFFA21, 31IIGLMV36 and 39VVIA42. Through the binding energy analysis at each site (Table S2), we found that residues 16KLVFFA21 and 31IIGLMV36 have the lowest binding energy, indicating these two regions are the most favorable binding sites for NE molecules. Considering that the CHC and C-terminal hydrophobic regions play key roles in the Aβ aggregation,69 it is conceivable that the binding of NE molecules to these two regions can effectively prevent Aβ fibrillization. We also calculated the number of H-bonds formed between NE molecules and each amino residue of Aβ peptides. As shown in Figure 6(b), NE molecules form H-bonds most with the negatively charged residues E11, E22, D7, E3, D23 and D1, demonstrating the important role of H-bonding interaction between NE 12

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molecules and negatively charged residues in the interaction of Aβ dimer with NE molecules. To examine the existence of cation-π interactions between Aβ peptides and NE molecules, we then analyzed the distribution of the minimum distance between the side-chain NH3+ group of residue R5 and the geometry center of each aromatic ring of NE molecules. As seen in Figure 6(c), there exists a sharp peak centered at 0.48 nm, similar to the peak value (0.47 nm) of amino-aromatic contact distance distribution curve reported in an early study,70, 71 indicating the existence of the cation-π interaction between R5 and NE molecules. A representative snapshot (see Figure 6(d)) shows the cation-π interaction observed in our REMD simulations. The cation-π interactions play a crucial role in the protein-protein and protein-ligand association.51,

72, 73

Taken together, our data reveal that hydrophobic and aromatic

stacking interactions, and to a lesser extent, hydrogen-bonding and cation-π interactions, contribute to the binding of NE molecules to Aβ peptides, thus impeding the inter-peptide interactions responsible for Aβ aggregation.

Figure 6. The binding free energy (in kcal/mol) of NE molecules with each residue (a) and H-bond number (b) between Aβ dimer and NE molecules. Cation-π interactions analysis: the PDF of the minimum distance between the side chain NH3+ group of residue R5 and the geometry center of each aromatic ring (c), and a representative snapshot (d) showing the cation-π interaction between the side chain NH3+ group of R5 and the aromatic ring of an NE molecule (red).

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To investigate the binding modes between aromatic residues (F4, Y10, F19 and F20) and NE molecules, we calculated the PDF of the centroid distance between the ring of aromatic residues and the ring of their closest NE molecules, and the PDF of the angles between these two rings. As shown in Figure 7(a, b), a peak exists both in the distance distribution (at ~0.49 nm) and the angle distribution (at ~25°), indicating the two rings are close to each other and have a strong preference to be parallel-aligned. A representative snapshot of this parallel-aligned aromatic stacking in Aβ-dimer+NE system is presented in Figure 7(c). This parallel-aligned aromatic stacking interaction between aromatic residues in Aβ peptides and amyloid inhibitors was also reported in previous studies.34, 36

Figure 7. The detailed aromatic-stacking interactions analysis. The PDF of the centroid distance (a) and the angle (b) between the aromatic residues ring (each aromatic residue is considered) and their closest NE molecular ring. A representative snapshot (c) showing parallel-aligned aromatic stacking orientation between the aromatic ring of F20 and the ring of an NE molecule (red).

NE molecules destabilize the preformed Aβ protofibrils by forming H-bonds with main chain atoms of Aβ peptides. A recent experimental study reported that NE is also able to disaggregate the preformed Aβ fibrils.42 To understand the underlying disaggregation mechanism, we carried out two independent 1-μs MD simulations on the Aβ1-42 protofibril with 100 NE molecules. For comparison, we also performed one 1-μs MD simulation without NE molecules. We first analyzed the percentages of secondary structures using the last 100 ns trajectory data. As shown in Figure 8(a), the β-sheet content of Aβ protofibril decreases from 66.7% in the Aβ-protofibril system to 62.0% in the Aβ-protofibril+NE system, while the coil 14

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content of Aβ protofibril increases from 19.2% to 23.6%. The percentages of the other secondary structures (β-bridge and bend) do not change much. We also calculated the β-sheet probabilities for each residue, and the results are given in Figure 8(b). The β-sheet probabilities of residues A2, E11 and 26SNKGA30 in the Aβ-protofibril system have an obvious reduction compared to that in the Aβ-protofibril+NE system. Interesting, recent studies by the Belfort group16-18 showed that A2 is important in Aβ dimerization - the first step of Aβ fibrillization. To examine the effect of NE molecules on the backbone H-bonds of Aβ protofibril, we calculated the PDF of the H-bond number (Figure 8(c)). The number of H-bonds in the Aβ protofibril is reduced in the presence of NE molecules, and the peak value decreases from 239 to 233, indicating the disruptive tendency of NE molecules on backbone H-bonds. The number of H-bonds formed between NE molecules and each amino acid residue (Figure 9(d)) show that the NE molecules form H-bonds most with residues D1, A2, D23, and A42. These results indicate that NE molecules remodel the structure of Aβ protofibril by forming H-bonds with residues D1, A2, D23, and A42, hence destabilizing preformed Aβ protofibrils. Taken together, our REMD and MD simulation data show that NE molecules can effectively inhibit the aggregation of Aβ1-42 peptide, consistent with in vitro study reported previously42. It is noted that our work is a simulation study and is focused on the microscopic mechanism by which NE inhibits the Aβ fibrillization. Whether NE molecules have the inhibitive effect on in vivo aggregation of Aβ remains to be determined in future studies. Meanwhile, our MD simulation data show that it is hardly to observe a significant disruption of Aβ protofibrils even in μs-long MD simulations, indicating that the disruption process of NE molecules on Aβ protofibrils is quite slow. Hence tens of microsecond or millisecond-long MD simulations might be needed to see the disaggregation of Aβ1-42 fibrils by NE molecules, which is beyond the current computer capacity.

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Figure 8. Effect of NE molecules on the secondary structure of Aβ protofibril. The average probability of each secondary structure over all residues (a) and the β-sheet (b) probability as a function of amino acid residue. PDF of the number of main chain H-bonds for Aβ protofibril with and without NE molecules (c). The backbone H-bond number between Aβ protofibril and NE molecules (d). The representative structures at three different time points for Aβ-protofibril (e) and Aβ-protofibril+NE (f) systems . The data were averaged over the last 100 ns of all MD runs.

CONCLUSION In this study, we performed extensive atomistic REMD and MD simulations to dissect the inhibitory and disruptive mechanisms of NE molecules on Aβ1-42 aggregation. To the best of our knowledge, this is the first REMD and MD simulation study to investigate the molecular mechanism of NE molecules in inhibiting the aggregation of full length Aβ1-42 peptide. Our 300 ns REMD simulations show that NE molecules can significantly inhibit the β-sheet formation of Aβ peptides and suppress the formation of β-hairpin structures. The interaction of NE molecules with Aβ peptides interferes with the peptide-peptide interaction, and prevents the inter-peptide hydrogen bond formation. Five dominant binding sites are identified: the N-terminal sites (residues 3EFRHD7 and 10YEVHH14), the CHC site (residues 16KLVFFA21), and the C-terminal sites (31IIGLMV36 and 39VVIA42). The calculation of binding energy on these binding sites shows that the CHC 16KLVFFA21 region and C-terminal 31IIGLMV36 hydrophobic region are the two 16

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most favorable binding sites. The hydrophobic and aromatic stacking interactions, and to a lesser extent, hydrogen-bonding and cation-π interactions, together contribute to the binding of NE molecules to Aβ peptides, thus impeding the inter-peptide interactions. MD simulations were carried out to examine the effect of NE molecules on Aβ protofibril. The results show that NE molecules can destabilize the preformed Aβ protofibril by forming H-bonds with residues D1, A2, D23, and A42. In summary, this study provides a better understanding of the inhibitory and disruptive mechanisms of NE molecules on Aβ aggregation, which is helpful for the design of drug candidates for the treatment of AD. This work also enhances our understanding of the beneficial effect of exercise on AD as exercise can increase the level of NE.

MATERIALS AND METHODS Aβ-dimer

and

Aβ-dimer+NE

systems.

The

Aβ1-42

sequence

is

DAEFRHDSGY10EVHHQKLVFF20AEDVGSNKGA30IIGLMVGGVV40IA. In the REMD simulations, we studied two systems: an isolated Aβ dimer (named as Aβ-dimer) and an Aβ dimer in the presence of NE molecules (named as Aβ-dimer+NE). The two peptide chains in the initial state of the Aβ dimer both have random characteristics. The peptide chains in Aβ dimer were obtained by running high temperature MD simulations on the solution NMR resolved Aβ monomer (PDB ID: 1Z0Q).74 We take the initial structure of a NE molecule from ChemSpider. The molecular structure was optimized using Spartan’1075, followed by an energy minimization by GAMESS software76. The topology of an NE molecule was obtained using the GlycoBioChem PRODRG2 Server77, and the partial charges of NE atoms were generated by the Amber Tools REP package78. For the Aβ-dimer+NE system, 20 NE molecules were randomly around the Aβ dimer, with a molar ratio of 10:1 (NE to Aβ molecules), which is consistent with previous experimental study.42 The minimum distance between NE molecules and the Aβ dimer in initial states is at least 1.5 nm. The initial states of Aβ-dimer and Aβ-dimer+NE systems, and the NE molecular structure are presented in Figure 1(a-c). 17

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Aβ-protofibril and Aβ-protofibril+NE systems. The Aβ1-42 protofibril consisting of two pentameric protofibril was constructed on the basis of the cryoEM-derived Aβ1-42 fibril (PDB ID: 5OQV),21 named as Aβ-protofibril, and the protofibril with NE molecules is named as Aβ-protofibril+NE. The molar ratio of NE molecules to Aβ protofibril is 10:1, equal to that of an experimental study.42 The initial states of Aβ-protofibril system, Aβ-protofibril+NE system are given in Figure 8(e, f). REMD and MD Simulations. Simulations and analysis were carried out within the GROMACS-4.5.3 package.79 AMBER99SB-ILDN force field80 was used to model proteins, because a recent study61 reported that this force field can generate secondary structure contents in agreement with CD data. There are 54 replicas in the REMD simulations, each of 300 ns duration, with a temperature range of 306~417 K. The temperature list is shown in Table S1. The Aβ dimer was placed in the center of a cubic box with a box length of 7.15 nm, fully solvated with TIP3P water molecules.81 There are 35701 and 35606 atoms in the Aβ-dimer and Aβ-dimer+NE systems, respectively. Cl− ions were added to keep the systems neutrally charged. Bond lengths of peptides were constrained using LINCS82 algorithms with an integration time step of 2 fs. An isotropic pressure coupling at 1 bar by Parrinello-Rahman’s method was used with a coupling constant of 1.0 ps.83 The temperature of each replica was maintained constant using velocity rescaling method with a coupling constant of 0.1 ps.84 The van der Waals interactions were cut off at 1.4 nm, and the electrostatic interactions were calculated by particle mesh Ewald (PME) method85 with a real space cutoff of 1.0 nm. The attempt swap time between two neighboring replicas is 2 ps and the acceptance ratio is 17~18%. Two independent 1-μs MD simulations on the Aβ1-42 protofibril with 100 NE molecules and one 1-μs MD simulation without NE molecules as a control group were performed to examine the influence of NE molecules on the preformed Aβ protofibrils. The Aβ protofibril was in the center of a cubic box with the side length of 9.84 nm, fully solvated with TIP3P water molecules. There are 94531 and 94368 atoms in the two different systems, respectively. 18

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Analysis methods. The secondary structure was investigated utilizing the DSSP tool.86 The Daura analysis method87 was applied to classify the conformations sampled using a Cα-RMSD cutoff of 0.35 nm. PMF was calculated by the formula -RTln P(x, y), where P(x, y) is the histogram of two reaction coordinates: Rg of peptides and the number of backbone H-bonds. The peptide interactions were analyzed by calculating the residue-residue contact probabilities. A hydrogen bond was taken into consideration if the N···O distance is less than 0.35 nm and the N-H···O angle is larger than 150°. The binding free energy (in units of kcal/mol) of NE molecules with Aβ dimer was calculated using the method of molecular mechanics/linear Poisson-Boltzmann surface area (MM/PBSA) implemented in the GROMACS package.88, calculate

the

89

A python script kindly provided by Kumari was used to

contribution

of

per

residue

to

the

binding

energy

(http://rashmikumari.github.io/g_mmpbsa/). The binding free energy (ΔGbind) between Aβ dimer and NE was calculated as: ΔGbind = ΔEMM + ΔGsolvation - TΔS, ΔEMM = ΔEvdw + ΔEele, ΔGsolvation = ΔGpolar + ΔGnonpolar. Here, ΔEMM refers to potential energy, consisting of electrostatic (ΔEele) and Van der Waals (ΔEvdw) terms. ΔGsolvation is the solvation free energy, including polar solvation term ΔGpolar and nonpolar solvation term ΔGnonpolar. ΔGpolar and ΔGnonpolar were estimated by PB model and SASA, repectively. According to previous computational studies,36, 63, 90, 91 the contribution of conformational entropy of peptides was ignored, and the binding free energy represents the relative binding free energy.

ASSOCIATED CONTENT Supporting Information. Temperature lists used in the REMD simulations of of Aβ-dimer and Aβ-dimer+NE systems; the binding free energy of each binding site between NE molecules and the Aβ dimer; simulation convergence assesments for the Aβ-dimer and Aβ-dimer+NE systems; SC–SC contact probability maps for Aβ dimer in the absence and presence of NE molecules. 19

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AUTHOR INFORMATION Corresponding Authors *E-mail: [email protected] *E-mail: [email protected]

Author Contributions G.W., Q.Z., and Y.Z. conceived the project. Y.Z., H.Q., Q.Z., and Y.C. performed simulations and analyzed all of the simulation data. Y.Z. and Q.Z. drafted the manuscript. The manuscript was written through contributions of all authors and all authors have given approval to the final version of the manuscript.

Funding This work is supported by the financial support from the National Natural Science Foundation of China (Grant No. 11674065 and 11704256) and the Ministry of Science and Technology of China (Grant No. 2016YFA0501702). All simulations were performed using the High-Performance Computing Server at Shanghai University of Sport and and National Supercomputer Center in Guangzhou.

Notes The authors declare no competing financial interest.

REFERENCE 1. Chiti, F., and Dobson, C. M. (2006) Protein misfolding, functional amyloid, and human disease. Annu. Rev. Biochem. 75, 333-366. 2. Chiti, F., and Dobson, C. M. (2017) Protein misfolding, amyloid formation, and human disease: a summary of progress over the last decade. Annu. Rev. Biochem. 86, 27-68. 3. Eisenberg, D. S., and Sawaya, M. R. (2017) Structural studies of amyloid proteins at the molecular level. Annu. Rev. Biochem. 86, 69-95. 4. Lobello, K., Ryan, J. M., Liu, E., Rippon, G., and Black, R. (2012) Targeting beta amyloid: a clinical review of immunotherapeutic approaches in Alzheimer's disease. Int. J. Alzheimers Dis. 2012, 628070. 20

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Page 20 of 26

Page 21 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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5. LaFerla, F. M., Green, K. N., and Oddo, S. (2007) Intracellular amyloid-beta in Alzheimer's disease. Nat. Rev. Neurosci. 8, 499-509. 6. Stancu, I. C., Vasconcelos, B., Terwel, D., and Dewachter, I. (2014) Models of beta-amyloid induced Tau-pathology: the long and "folded" road to understand the mechanism. Mol. Neurodegener. 9, 51. 7. Hardy, J., and Selkoe, D. J. (2002) The amyloid hypothesis of Alzheimer's disease: progress and problems on the road to therapeutics. Science 297, 353-356. 8. Haass, C., and Selkoe, D. J. (2007) Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid beta-peptide. Nat. Rev. Mol. Cell Biol. 8, 101-112. 9. Ahmed, M., Davis, J., Aucoin, D., Sato, T., Ahuja, S., Aimoto, S., Elliott, J. I., Van Nostrand, W. E., and Smith, S. O. (2010) Structural conversion of neurotoxic amyloid-beta(1-42) oligomers to fibrils. Nat. Struct. Mol. Biol. 17, 561-567. 10. Kayed, R., Bernhagen, J., Greenfield, N., Sweimeh, K., Brunner, H., Voelter, W., and Kapurniotu, A. (1999) Conformational transitions of islet amyloid polypeptide (IAPP) in amyloid formation in Vitro 1. J. Mol. Biol. 287, 781-796. 11. Stefani, M., and Dobson, C. M. (2003) Protein aggregation and aggregate toxicity: new insights into protein folding, misfolding diseases and biological evolution. J. Mol. Med. 81, 678-699. 12. Michaels, T. C. T., Saric, A., Habchi, J., Chia, S., Meisl, G., Vendruscolo, M., Dobson, C. M., and Knowles, T. P. J. (2018) Chemical kinetics for bridging molecular mechanisms and macroscopic measurements of amyloid fibril formation, Annu. Rev. Phys. Chem. 69, 273-298. 13. Kirkitadze, M. D., Bitan, G., and Teplow, D. B. (2002) Paradigm shifts in Alzheimer's disease and other neurodegenerative disorders: the emerging role of oligomeric assemblies. J. Neurosci. Res. 69, 567-577. 14. Thompson, L. K. (2003) Unraveling the secrets of Alzheimer's beta-amyloid fibrils. Proc. Natl. Acad. Sci. U. S. A. 100, 383-385. 15. Shankar, G. M., Li, S., Mehta, T. H., Garcia-Munoz, A., Shepardson, N. E., Smith, I., Brett, F. M., Farrell, M. A., Rowan, M. J., Lemere, C. A., Regan, C. M., Walsh, D. M., Sabatini, B. L., and Selkoe, D. J. (2008) Amyloid-beta protein dimers isolated directly from Alzheimer's brains impair synaptic plasticity and memory. Nat. Med. 14, 837-842. 16. Murray, B., Sorci, M., Rosenthal, J., Lippens, J., Isaacson, D., Das, P., Fabris, D., Li, S., and Belfort, G. (2016) A2T and A2V Abeta peptides exhibit different aggregation kinetics, primary nucleation, morphology, structure, and LTP inhibition, Proteins 84, 488-500. 17. Das, P., Chacko, A. R., and Belfort, G. (2017) Alzheimer's protective cross-interaction between wild-type and A2T variants alters Abeta42 dimer structure, ACS Chem. Neurosci. 8, 606-618. 18. Sharma, B., Ranganathan, S. V., and Belfort, G. (2018) Weaker N-terminal interactions for the protective over the causative Abeta peptide dimer mutants, ACS Chem. Neurosci. 9, 1247-1253. 19. Lu, J. X., Qiang, W., Yau, W. M., Schwieters, C. D., Meredith, S. C., and Tycko, R. (2013) Molecular structure of beta-amyloid fibrils in Alzheimer's disease brain tissue. Cell 154, 1257-1268. 20. Xiao, Y., Ma, B., McElheny, D., Parthasarathy, S., Long, F., Hoshi, M., Nussinov, R., and Ishii, Y. (2015) Abeta(1-42) fibril structure illuminates self-recognition and replication of amyloid in Alzheimer's disease, Nat. Struct. Mol. Biol. 22, 499-505. 21

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ACS Chemical Neuroscience 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

21. Gremer, L., Scholzel, D., Schenk, C., Reinartz, E., Labahn, J., Ravelli, R. B. G., Tusche, M., Lopez-Iglesias, C., Hoyer, W., Heise, H., Willbold, D., and Schroder, G. F. (2017) Fibril structure of amyloid-beta(1-42) by cryo-electron microscopy, Science 358, 116-119. 22. Doig, A. J., Del Castillo-Frias, M. P., Berthoumieu, O., Tarus, B., Nasica-Labouze, J., Sterpone, F., Nguyen, P. H., Hooper, N. M., Faller, P., and Derreumaux, P. (2017) Why is research on amyloid-beta failing to give new drugs for Alzheimer's disease? ACS Chem. Neurosci. 8, 1435-1437. 23. Nasica-Labouze, J., Nguyen, P. H., Sterpone, F., Berthoumieu, O., Buchete, N. V., Cote, S., De Simone, A., Doig, A. J., Faller, P., Garcia, A., Laio, A., Li, M. S., Melchionna, S., Mousseau, N., Mu, Y., Paravastu, A., Pasquali, S., Rosenman, D. J., Strodel, B., Tarus, B., Viles, J. H., Zhang, T., Wang, C., and Derreumaux, P. (2015) Amyloid beta protein and Alzheimer's disease: when computer simulations complement experimental studies, Chem. Rev. 115, 3518-3563. 24. Chen, Z., Krause, G., and Reif, B. (2005) Structure and orientation of peptide inhibitors bound to beta-amyloid fibrils, J. Mol. Biol. 354, 760-776. 25. Takahashi, T., and Mihara, H. (2008) Peptide and protein mimetics inhibiting amyloid beta-peptide aggregation, Acc. Chem. Res. 41, 1309-1318. 26. Zhang, M., Mao, X., Yu, Y., Wang, C. X., Yang, Y. L., and Wang, C. (2013) Nanomaterials for reducing amyloid cytotoxicity. Adv. Mater. 25, 3780-3801. 27. Radic, S., Davis, T. P., Ke, P. C., and Ding, F. (2015) Contrasting effects of nanoparticle-protein attraction on amyloid aggregation. RSC Adv. 5, 105489-105498. 28. Wang, B., Pilkington, E. H., Sun, Y., Davis, T. P., Ke, P. C., and Ding, F. (2017) Modulating protein amyloid aggregation with nanomaterials. Environ. Sci. Nano 4, 1772-1783. 29. Liao, Q., Owen, M. C., Bali, S., Barz, B., and Strodel, B. (2018) Abeta under stress: the effects of acidosis, Cu(2+)-binding, and oxidation on amyloid beta-peptide dimers, Chem. Commun. (Camb) 54, 7766-7769. 30. Bohrmann, B., Baumann, K., Benz, J., Gerber, F., Huber, W., Knoflach, F., Messer, J., Oroszlan, K., Rauchenberger, R., Richter, W. F., Rothe, C., Urban, M., Bardroff, M., Winter, M., Nordstedt, C., and Loetscher, H. (2012) Gantenerumab: a novel human anti-Abeta antibody demonstrates sustained cerebral amyloid-beta binding and elicits cell-mediated removal of human amyloid-beta. J. Alzheimers Dis. 28, 49-69. 31. Sevigny, J., Chiao, P., Bussiere, T., Weinreb, P. H., Williams, L., Maier, M., Dunstan, R., Salloway, S., Chen, T., Ling, Y., O'Gorman, J., Qian, F., Arastu, M., Li, M., Chollate, S., Brennan, M. S., Quintero-Monzon, O., Scannevin, R. H., Arnold, H. M., Engber, T., Rhodes, K., Ferrero, J., Hang, Y., Mikulskis, A., Grimm, J., Hock, C., Nitsch, R. M., and Sandrock, A. (2016) The antibody aducanumab reduces Abeta plaques in Alzheimer's disease. Nature 537, 50-56. 32. Young, L. M., Saunders, J. C., Mahood, R. A., Revill, C. H., Foster, R. J., Tu, L. H., Raleigh, D. P., Radford, S. E., and Ashcroft, A. E. (2015) Screening and classifying small-molecule inhibitors of amyloid formation using ion mobility spectrometry-mass spectrometry. Nat. Chem. 7, 73-81. 33. Saunders, J. C., Young, L. M., Mahood, R. A., Jackson, M. P., Revill, C. H., Foster, R. J., Smith, D. A., Ashcroft, A. E., Brockwell, D. J., and Radford, S. E. (2016) An in vivo platform for identifying inhibitors of protein aggregation. Nat. Chem. Biol. 12, 94-101. 34. Li, H., Luo, Y., Derreumaux, P., and Wei, G. (2011) Carbon nanotube inhibits the formation of beta-sheet-rich oligomers of the Alzheimer's amyloid-beta(16-22) peptide. Biophys. J. 101, 22

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Page 22 of 26

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2267-2276. 35. Zhang, T., Zhang, J., Derreumaux, P., and Mu, Y. (2013) Molecular mechanism of the inhibition of EGCG on the Alzheimer Abeta(1-42) dimer. J. Phys. Chem. B 117, 3993-4002. 36. Xie, L., Luo, Y., Lin, D., Xi, W., Yang, X., and Wei, G. (2014) The molecular mechanism of fullerene-inhibited aggregation of Alzheimer's beta-amyloid peptide fragment. Nanoscale 6, 9752-9762. 37. Zhang, T., Xu, W., Mu, Y., and Derreumaux, P. (2014) Atomic and dynamic insights into the beneficial effect of the 1,4-naphthoquinon-2-yl-L-tryptophan inhibitor on Alzheimer's Abeta1-42 dimer in terms of aggregation and toxicity. ACS Chem. Neurosci. 5, 148-159. 38. Andujar, S. A., Lugli, F., Hofinger, S., Enriz, R. D., and Zerbetto, F. (2012) Amyloid-beta fibril disruption by C60-molecular guidance for rational drug design. Phys. Chem. Chem. Phys. 14, 8599-8607. 39. Zhao, L. N., Chiu, S. W., Benoit, J., Chew, L. Y., and Mu, Y. (2012) The effect of curcumin on the stability of Abeta dimers. J. Phys. Chem. B 116, 7428-7435. 40. Viet, M. H., Ngo, S. T., Lam, N. S., and Li, M. S. (2011) Inhibition of aggregation of amyloid peptides by beta-sheet breaker peptides and their binding affinity. J. Phys. Chem. B 115, 7433-7446. 41. Bednarikova, Z., Huy, P. D., Mocanu, M. M., Fedunova, D., Li, M. S., and Gazova, Z. (2016) Fullerenol C60(OH)16 prevents amyloid fibrillization of Abeta40-in vitro and in silico approach. Phys. Chem. Chem. Phys. 18, 18855-18867. 42. Huong, V. T., Shimanouchi, T., Shimauchi, N., Yagi, H., Umakoshi, H., Goto, Y., and Kuboi, R. (2010) Catechol derivatives inhibit the fibril formation of amyloid-beta peptides. J. Biosci. Bioeng. 109, 629-634. 43. Liu, X., Ye, K., and Weinshenker, D. (2015) Norepinephrine protects against Amyloid-beta toxicity via TrkB. J. Alzheimers Dis. 44, 251-260. 44. Murchison, C. F., Zhang, X. Y., Zhang, W. P., Ouyang, M., Lee, A., and Thomas, S. A. (2004) A distinct role for norepinephrine in memory retrieval. Cell 117, 131-143. 45. Kalinin, S., Polak, P. E., Lin, S. X., Sakharkar, A. J., Pandey, S. C., and Feinstein, D. L. (2012) The noradrenaline precursor L-DOPS reduces pathology in a mouse model of Alzheimer's disease. Neurobiol. Aging 33, 1651-1663. 46. Woodling, N. S., Colas, D., Wang, Q., Minhas, P., Panchal, M., Liang, X., Mhatre, S. D., Brown, H., Ko, N., Zagol-Ikapitte, I., van der Hart, M., Khroyan, T. V., Chuluun, B., Priyam, P. G., Milne, G. L., Rassoulpour, A., Boutaud, O., Manning-Bog, A. B., Heller, H. C., and Andreasson, K. I. (2016) Cyclooxygenase inhibition targets neurons to prevent early behavioural decline in Alzheimer's disease model mice. Brain 139, 2063-2081. 47. Greiwe, J. S., Hickner, R. C., Shah, S. D., Cryer, P. E., and Holloszy, J. O. (1999) Norepinephrine response to exercise at the same relative intensity before and after endurance exercise training. J. Appl. Physiol. 86, 531-535. 48. Zouhal, H., Jacob, C., Delamarche, P., and Gratasdelamarche, A. (2008) Catecholamines and the effects of exercise, training and gender. Sports Med. 38, 401-423. 49. Kraemer, W. J., Gordon, S. E., Fragala, M. S., Bush, J. A., Szivak, T. K., Flanagan, S. D., Hooper, D. R., Looney, D. P., Triplett, N. T., DuPont, W. H., Dziados, J. E., Marchitelli, L. J., and Patton, J. F. (2015) The effects of exercise training programs on plasma concentrations of proenkephalin Peptide F and catecholamines, Peptides 64, 74-81. 23

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50. Zou, Y., Sun, Y., Zhu, Y., Ma, B., Nussinov, R., and Zhang, Q. (2016) Critical nucleus structure and aggregation mechanism of the C-terminal fragment of copper-ainc superoxide dismutase protein. ACS Chem. Neurosci. 7, 286-296. 51. Mo, Y., Lei, J., Sun, Y., Zhang, Q., and Wei, G. (2016) Conformational ensemble of hIAPP dimer: Insight into the molecular mechanism by which a green tea extract inhibits hIAPP aggregation. Sci. Rep. 6, 33076. 52. Chen, Y., Chen, Z., Sun, Y., Lei, J., and Wei, G. (2018) Mechanistic insights into the inhibition and size effects of graphene oxide nanosheets on the aggregation of an amyloid-beta peptide fragment, Nanoscale 10, 8989-8997. 53. Ganguly, P., Do, T. D., Larini, L., LaPointe, N. E., Sercel, A. J., Shade, M. F., Feinstein, S. C., Bowers, M. T., and Shea, J. E. (2015) Tau assembly: the dominant role of PHF6 (VQIVYK) in microtubule binding region repeat R3. J. Phys. Chem. B 119, 4582-4593. 54. Nguyen, P. H., Sterpone, F., Campanera, J. M., Nasica-Labouze, J., and Derreumaux, P. (2016) Impact of the A2V mutation on the heterozygous and homozygous Abeta1-40 dimer structures from atomistic simulations. ACS Chem. Neurosci. 7, 823-832. 55. Watts, C. R., Gregory, A., Frisbie, C., and Lovas, S. (2018) Effects of force fields on the conformational and dynamic properties of amyloid beta(1-40) dimer explored by replica exchange molecular dynamics simulations. Proteins 86, 279-300. 56. Man, V. H., Nguyen, P. H., and Derreumaux, P. (2017) Conformational ensembles of the wild-type and S8C Abeta1-42 dimers. J. Phys. Chem. B 121, 2434-2442. 57. Kirkitadze, M. D., Condron, M. M., and Teplow, D. B. (2001) Identification and characterization of key kinetic intermediates in amyloid beta-protein fibrillogenesis. J. Mol. Biol. 312, 1103-1119. 58. Sethuraman, A., Han, M., Kane, R. S., and Belfort, G. (2004) Effect of surface wettability on the adhesion of proteins, Langmuir 20, 7779-7788. 59. Sandberg, A., Luheshi, L. M., Sollvander, S., Pereira de Barros, T., Macao, B., Knowles, T. P., Biverstal, H., Lendel, C., Ekholm-Petterson, F., Dubnovitsky, A., Lannfelt, L., Dobson, C. M., and Hard, T. (2010) Stabilization of neurotoxic Alzheimer amyloid-beta oligomers by protein engineering. Proc. Natl. Acad. Sci. U. S. A. 107, 15595-15600. 60. Torok, M., Milton, S., Kayed, R., Wu, P., McIntire, T., Glabe, C. G., and Langen, R. (2002) Structural and dynamic features of Alzheimer's Abeta peptide in amyloid fibrils studied by site-directed spin labeling. J. Biol. Chem. 277, 40810-40815. 61. Man, V. H., Nguyen, P. H., and Derreumaux, P. (2017) High-resolution structures of the Amyloid-beta 1-42 dimers from the comparison of four atomistic force fields. J. Phys. Chem. B 121, 5977-5987. 62. Walti, M. A., Ravotti, F., Arai, H., Glabe, C. G., Wall, J. S., Bockmann, A., Guntert, P., Meier, B. H., and Riek, R. (2016) Atomic-resolution structure of a disease-relevant Abeta(1-42) amyloid fibril, Proc. Natl. Acad. Sci. U. S. A. 113, E4976-4984. 63. Sun, Y., Qian, Z., and Wei, G. (2016) The inhibitory mechanism of a fullerene derivative against amyloid-beta peptide aggregation: an atomistic simulation study. Phys. Chem. Chem. Phys. 18, 12582-12591. 64. Colvin, M. T., Silvers, R., Ni, Q. Z., Can, T. V., Sergeyev, I., Rosay, M., Donovan, K. J., Michael, B., Wall, J., Linse, S., and Griffin, R. G. (2016) Atomic resolution structure of monomorphic Abeta42 amyloid fibrils. J. Am. Chem. Soc. 138, 9663-9674. 24

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65. Liu, R., McAllister, C., Lyubchenko, Y., and Sierks, M. R. (2004) Residues 17-20 and 30-35 of beta-amyloid play critical roles in aggregation. J. Neurosci. Res. 75, 162-171. 66. Truex, N. L., Wang, Y., and Nowick, J. S. (2016) Assembly of peptides derived from beta-sheet regions of beta-amyloid. J. Am. Chem. Soc. 138, 13882-13890. 67. Gazit, E. (2002) A possible role for pi-stacking in the self-assembly of amyloid fibrils. FASEB J. 16, 77-83. 68. Makin, O. S., Atkins, E., Sikorski, P., Johansson, J., and Serpell, L. C. (2005) Molecular basis for amyloid fibril formation and stability. Proc. Natl. Acad. Sci. U. S. A. 102, 315-320. 69. Qian, Z., Zhang, Q., Liu, Y., and Chen, P. (2017) Assemblies of amyloid-beta30-36 hexamer and its G33V/L34T mutants by replica-exchange molecular dynamics simulation. PLoS One 12, e0188794. 70. Burley, S. K., and Petsko, G. A. (1986) Amino-aromatic interactions in proteins. FEBS Lett. 203, 139-143. 71. Dougherty, D. A. (2013) The cation-pi interaction. Acc. Chem. Res. 46, 885-893. 72. Dougherty, D. A. (1996) Cation-pi interactions in chemistry and biology: a new view of benzene, Phe, Tyr, and Trp. Science 271, 163-168. 73. Myslinski, J. M., Clements, J. H., and Martin, S. F. (2014) Protein-ligand interactions: probing the energetics of a putative cation-pi interaction. Bioorg. Med. Chem. Lett. 24, 3164-3167. 74. Tomaselli, S., Esposito, V., Vangone, P., van Nuland, N. A., Bonvin, A. M., Guerrini, R., Tancredi, T., Temussi, P. A., and Picone, D. (2006) The alpha-to-beta conformational transition of Alzheimer's Abeta-(1-42) peptide in aqueous media is reversible: a step by step conformational analysis suggests the location of beta conformation seeding. Chembiochem 7, 257-267. 75. Shao, Y., Molnar, L., Jung, Y., Kussmann, J., Ochsenfeld, C., Brown, S., Gilbert, A., Slipchenko, L., Levchenko, S., O'Neill, D., and DiStasio RA Jr. (2006) Advances in methods and algorithms in a modern quantum chemistry program package. Phys. Chem. Chem. Phys. 8, 3172-3191. 76. Schmidt, M. W., Baldridge, K. K., Boatz, J. A., Elbert, S. T., Gordon, M. S., Jensen, J. H., Koseki, S., Matsunaga, N., Nguyen, K. A., and Su, S. (1993) General atomic and molecular electronic structure system. J. Comput. Chem. 14, 1347–1363. 77. Schüttelkopf, A. W., and Van Aalten, D. M. F. (2004) PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. Acta. Crystallogr. D. Biol. Crystallogr. 60, 1355-1363. 78. François-Yves, D., Adrien, P., Thomas, Z., Corentin, S., Rodolphe, L., Nicolas, G., Dimitri, L., Wilfried, R., and Piotr, C. (2010) The R.E.D. tools: advances in RESP and ESP charge derivation and force field library building. Phys. Chem. Chem. Phys. 12, 7821-7839. 79. Van, D. S. D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., and Berendsen, H. J. (2005) GROMACS: fast, flexible, and free. J. Comput. Chem. 26, 1701-1718. 80. Lindorfflarsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J. L., Dror, R. O., and Shaw, D. E. (2010) Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins 78, 1950-1958. 81. Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., and Klein, M. L. (1983) Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926-935. 82. Hess, B., Bekker, H., Berendsen, H. J., Fraaije, J. G. . (1997) LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463-1472. 25

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83. Parrinello, M., Rahman, A. (1981) Polymorphic transitions in single crystals: a new molecular dynamics method. J. Appl. Phys. 52, 7182-7190. 84. Bussi, G., Donadio, D., and Parrinello, M. (2007) Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 014101. 85. Darden, T., York, D., and Pedersen, L. (1998) Particle mesh Ewald: An N·log(N) method for Ewald sums in large systems. J. Chem. Phys. 98, 10089-10092. 86. Kabsch, W., and Sander, C. (1983) Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 22, 2577–2637. 87. Daura, X., Gademann, K., Jaun, B., Seebach, D., Gunsteren, W. F. V., Mark, A. E. (1999) Peptide folding: when simulation meets experiment. Angew. Chem. Int. Edit. 38, 236-240. 88. Luo, R., Laurent, D., and Gilson, M. K. (2002) Accelerated Poisson-Boltzmann calculations for static and dynamic systems. J. Comput. Chem. 23, 1244-1253. 89. Kumari, R., Kumar, R., and Lynn, A. (2014) g_mmpbsa--a GROMACS tool for high-throughput MM-PBSA calculations. J. Chem. Inf. Model. 54, 1951-1962. 90. Berhanu, W. M., and Hansmann, U. H. (2013) The stability of cylindrin beta-barrel amyloid oligomer models-a molecular dynamics study. Proteins 81, 1542-1555. 91. Lei, J., Qi, R., Xie, L., Xi, W., and Wei, G. (2017) Inhibitory effect of hydrophobic fullerenes on the beta-sheet-rich oligomers of a hydrophilic GNNQQNY peptide revealed by atomistic simulations. RSC Adv. 7, 13947-13956.

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