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Molecular Mechanisms of the Bindings between NonAmyloid # Component (NAC) Oligomers and Amylin Oligomers Yoav Atsmon-Raz, and Yifat Miller J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.6b07731 • Publication Date (Web): 23 Sep 2016 Downloaded from http://pubs.acs.org on October 1, 2016

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The Journal of Physical Chemistry

Molecular Mechanisms of the Bindings between NonAmyloid β Component (NAC) Oligomers and Amylin Oligomers

Yoav Atsmon-Raz1,2,a and Yifat Miller1,2,*

1

Department of Chemistry and 2Ilse Katz Institute for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel

a

Current address: 2500 University Drive, University of Calgary, Center of Molecular Simulation, Calgary, Alberta, Canada T2N 1N4

* Author to whom correspondence should be addressed: [email protected] Yifat Miller, Tel: 972-86428705; Fax: 972-86428709

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Abstract It has been suggested that the connection between amyloidogenic diseases is related to the interactions between aggregates of amyloids which are related to Type 2 Diabetes and Parkinson’s Disease. Herein, we illustrate the interactions between amylin oligomers and the non-amyloid β component (NAC) oligomers. By using molecular dynamics simulations and statistical calculations we studied the mechanisms through which NAC oligomers interact with amylin oligomers to form NAC-amylin heterooligomers. Our simulations have shown that there are more than one possible mechanism pathways which form the NAC-amylin hetero-oligomers. Our structural analyses demonstrate that the interactions in the NAC-amylin hetero-oligomers do not affect the structural features of the NAC oligomers, but they do stabilize the structures of the amylin oligomers. Taken together, our results strongly support the hypothesis that NAC oligomers may interact with amylin oligomers through several pathways, in which some pathways are more preferred, due to the structural stability of the crossseeding NAC-amylin oligomers.


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Introduction Clinical and epidemiological studies have identified type 2 diabetes (T2D) as a risk factor of Alzheimer's disease (AD).1-3 Several studies have shown that there are many similarities between T2D and AD and that both conditions underlie common physiological processes.3 AD is characterized by extracellular senile plaques, mainly composed of amyloid β (Aβ) aggregates, which lead to the loss of neuron cells.4 T2D is characterized by aggregation of the neuroendocrine hormone named "human islet amyloid polypeptide" (hIAPP) or "amylin" that lead to the loss of the pancreatic βcells. Recently, Jackson et al5 identified amylin deposits in the gray matter of the temporal lobe – a major component of the central nervous system, from diabetes patients. In addition to the amylin deposition in the human brain, amylin aggregates are co-localized with Aβ plaques, promoting aggregation and thus contributing to the etiology of AD.6 Over the last 20 years, clinical studies have shown that individuals with T2D are at a higher risk of developing Parkinson's disease (PD).7-10 PD is characterized by the formation of insoluble aggregates that mostly consists of α-synuclein (AS).11-13 Yet, on a structural level, the connection between T2D and PD is not understood. Since amylin deposits were identified in the human brain of patients with T2D, amylin aggregates are co-localized not only with Aβ aggregates, but may also co-localize with AS aggregates. Consequently, since both peptideslocalize to the brain, they may interact with amylin we well as with each other.

Recent clinical studies have

suggested that some PD patients share histopathological symptoms with AD over non-PD patients.14-16 Both in vitro and in vivo studies have shown that Aβ has an inductive effect on oligomerization of AS and can act as seeds for the aggregation of AS fibrils.13,17,18 Therefore, the connection between T2D and AD, T2D and PD as well as between PD and AD, had been proposed via the interactions between the aggregates of these amyloids that are related to these diseases. AS, which consists of 140 residues, is characterized by three domains. The first domain (residues M1-K60) is an amphipatic lysine-rich amino terminus, which plays a crucial role in modulating the interactions of AS with membranes. The second domain (K96-A140) is an acidic carboxyl-terminal tail, which has been implicated in regulating the nuclear localization and interactions of AS with metals, small molecules and proteins.19,20 The third and central domain (residues E61-V95) is



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known as the “non-amyloid β component” (NAC) and contains a highly hydrophobic motif that has been found to be indispensable for AS aggregation by in vitro21,22 as well as cell-based assay23 studies. In these studies, it was found that that deletion of large segments within the NAC domain greatly reduce AS oligomerization and fibrilization. Thus, the NAC domain plays a crucial role on AS aggregation, and it is thus not surprising that it was first purified from amyloid plaques in patients with AD.12,24,25 Recent studies have focused on the link between T2D and neurodegenerative diseases such as AD and PD, by investigating cross-amyloid interactions, i.e. the interactions between two types of amyloids that are related to these diseases.26 Previously, we have shown the specific interactions between amylin and Aβ oligomers27 and between NAC and Aβ oligomers28 in atomistic resolution. In our current study, we aim to investigate the specific interactions between amylin and NAC oligomers at the atomic resolution. In this paper we apply all-atom explicit molecular dynamics (MD) simulations in order to investigate the inteactions between the oligomers of NAC and amylin. Our simulations have showed that the molecular mechanism pathways in which NAC oligomers interact with amylin oligomers favor the formation of single layer conformations of NAC-amylin oligomers. Second, the NAC oligomers affect the packing of amylin oligomers by decreasing the inner core distance among the βstrands and therefore create a more compact cross-β structure. Finally, we have also found that the NAC oligomers induce β-strand properties on residues in the turn region of amylin oligomers.

Methods and Materials System set up and modeling: Constructions of NAC hexamers, amylin hexamers and NAC-amylin dodecamers Recently, we illustrated the interactions between amylin oligomers and Aβ oligomers at the atomic resolution and between Aβ oligomers27 and NAC oligomers also at the atomic resolution.28 In vitro binding assays have shown that the monomers of Aβ binds to the NAC domain of AS.29 We reported a first study of the cross-seeding NAC-Aβ oligomers at the atomistic resolution.28 The structure of NAC oligomers had


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not been solved experimentally. Recently, we have proposed a 3D structure for NAC oligomers using extensive molecular dynamics (MD) simulations and compared them with available experimental parameters.30 Herein, we suggest that amylin oligomers bind to the NAC oligomers, similarly as we have illustrated in NAC-Aβ oligomers. We constructed the models of NAC, amylin and NAC-amylin oligomers with the Accelerys Discovery Studio software. We have chosen the basic oligomer unit of each peptide to be composed of hexamers for both NAC and amylin. It was previously shown in kinetic studies, that hexamers are the minimal oligomeric unit that is necessary for the formation of fibril-like structures for amyloid oligomers.31,32 We chose to construct hexamers for both NAC and amylin, i.e. similar number of monomers for each amyloid. We do not expect a dramatic difference to the structural properties of the cross-β structure by increasing the number of monomers of either NAC or amylin. Furthermore, this study does not focus on investigating the effect of elongation of the oligomeric size of either NAC or amylin or both.

The NAC

hexamer (Figure S1) has been extracted from our previous NAC dodecamer,30 by removing a trimer from each end of the original dodecamer. The monomers within the hexamer were aligned in-register parallel orientation with an averaged inner-core distance of ~ 4.8Å, as previously suggested by NMR experiments.33,34 We have constructed four models of amylin hexamers M1-M4 (Figures S2 and S3) that are derived from our previous single layer conformations of amylin octamers (M1, M2, M5 and M6).35 These four amylin oligomers were derived from experimental ssNMR36 and x-ray crystallography.37 The differences between these four models are the orientations of the residues along the sequence of the selfassembled amylin oligomers. Specifically, in M1 and M2, the orientations of the residues along the two β-strands are similar, while the orientations of the residues along the turn region differ from one another (Figure S2). Similarly, in M3 and M4, the orientations of the residues along the two β-strands are similar to each other while the orientations of the residues along the turn region are also different from each other (Figure S3). Most importantly, the orientations of the residues along the two β-strands in M1 and M2 differ than those of M3 and M4 (Figures S2 and S3). To investigate the cross-seeding between NAC oligomer and each one of the amylin oligomer models, we first applied the COBALT38 and ClustalW239-41 alignment tools 5 ACS Paragon Plus Environment


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in order to compute the sequence alignment between the sequences of NAC and amylin. (Figure S4) Both COBALT38 and ClustalW239-41 have shown that NAC and amylin1-37 have above 60% of similarity and thus we propose that some residues in NAC interact with similar residues in amylin1-37 and participate in the co-assembly of NAC-amylin. Several studies proposed that the sequences of Aβ1-42 and amylin1-37 have 25 % identity and 50 % similarity and thus can co-assemble.42-46 Recently, we investigated the atomic resolution of the molecular structures of Aβ1-42-amylin1-37 and have shown that the identity and the similarity of domains in these two amyloids contribute to the cross-seeding between these amyloids.27 Herein, the relatively high similarity may also contribute to stable NAC-amylin hetero-oligomers. We therefore expect that the initial structures of all 12 simulated complexes will be stable prior to the simulations due to the high similarity between the NAC and amylin. It should be noted that in all simulated models studied here both the N and C terminal ends are charged and uncapped. It has been previously suggested that monomers of the amyloids, including NAC and amylin, when self-assembled arrange in parallel orientation as single layer conformations, and in the double layer conformation of amylin the two single layer conformations interact through their C -termini.33,34,36,37 Therefore, we applied parallel NAC hexamers interacting with each one of the parallel amylin hexamers (M1-M4) in parallel orientation to form two single layer conformations and one double layer conformation (Figures S5-S8). In the first single layer conformation, the N-termini of both NAC and amylin interact directly with one another as well as the the C-termini of both peptides (models N1, O1, P1 and Q1). In the second single layer conformation the N-termini on NAC interact with the C-termini of amylin and vice versa (models N2, O2, P2 and Q2). These are the two optional models that one needs to consider as parallel orientations between the two amyloids. Finally, in the double layer conformation, the C-termini of NAC interacts with the C-termini of amylin (models N3, O3, P3 and Q3). We have constructed models N1, N2 and N3 of NAC-amylin dodecamers from on the amylin hexamer M1, models O1, O2 and O3 from amylin hexamer M2, models P1, P2 and P3 from hexamer M3 and Q1, Q2 and Q3 from amylin hexamer M4. Each of the double layered structures can be characterized by its own set of hydrophobic interactions at the NAC-amylin interface as follows - both in N3 and O3, the 6 ACS Paragon Plus Environment

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contacting residues are F94 of NAC and L27 of amylin While in P3 and Q3, the two contacting resdiues are I88 of NAC and V32 of amylin and F94 of NAC and I26 of amylin. In the double layer conformations we did not consider interactions between the N-termini and the C-termini of these two types of amyloids, because of the disruption of the N-termini (residues 1-7) of amylin oligomers and the N-termini (residues 61-67) of NAC oligomers.

Molecular Dynamics (MD) simulations protocol MD simulations of the solvated oligomers were performed in the NPT ensemble using NAMD47 with the CHARMM27 force field with CMAP correction.48 The oligomers were energy minimized and explicitly solvated in a TIP3P water box49,50 with a minimum distance of 15 Å from each edge of the box. Each water molecule within 2.5 Å of the oligomers was removed, in order to avoid clashes with the oligomers. Counter ions were added at random locations to neutralize the oligomers’ charge. For the pressure coupling scheme, we used the Langevin piston method51,52 with a decay period of 100 fs and a damping time of 50 fs to maintain a constant pressure of 1 atm. The temperature was set at 330 K and controlled by a Langevin thermostat with a damping coefficient of 10 ps. The short-range van der Waals (VDW) interactions were calculated using the switching function, with a twin range cutoff of 10.0 and 12.0 Å. Long-range electrostatic interactions were calculated using the particle mesh Ewald method with a cutoff of 12.0 Å.53,54 The equations of motion were integrated using the leapfrog integrator with a step of 1 fs. The solvated systems were energy minimized for 2000 conjugated gradient steps, where the hydrogen bonding distance between the β-sheets in each oligomer is fixed at the range of 2.2-2.5 Å. All counter ions and water molecules were allowed to move. The hydrogen atoms were constrained to the equilibrium bond using the SHAKE algorithm. The minimized solvated systems were energy minimized for 5000 additional conjugate gradient steps and 20,000 heating steps at 250 K, with all atoms allowed to move. Then, the system were heated from 250 to 330 K for 300 ps and equilibrated at 330 K for 300 ps. The temperature of 330 K (which is higher that room/body temperature) has been chosen in order to investigate the stability of the constructed models. It is expected that the simulated models that are stable at this 7 ACS Paragon Plus Environment


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temperature will be stable also at lower temperatures. All simulations ran for 60 ns. These conditions were applied to all of the studied constructed models.

The simulated 12 models of NAC-amylin dodecamers are seen in Figure 1 and the simulated NAC hexamer and amylin hexamers are seen in Figure S9 and Figure S10, respectively. To examine whether the timescale of 60 ns is a reasonable choice, the root-mean-square deviation (RMSD) has been computed for each one of the 12 models of NAC-amylin dodecamers, the NAC hexamer and the four amylin hexamers (models M1-M4) along the MD simulations (Figures S11-S15). One can see that all these simulated constructed models were converged after 20-30 ns of the simulations, therefore indicating that the timescale of 60 ns is a reasonable choice. Furthermore, to validate the convergence of the simulated models, we computed the conformational energies using the Generalized Born method with Molecular Volume (GBMV) method and population analsyis (see section of GBMV) of all 12 simulated models after 40 ns of simulations. Interestingly, one can see that the relative conformational energies and the populations yielded a similar trend as obtained for 60 ns (Table S1), therefore indicating that 60 ns is definitely a satisfactory timescale.

Generalized Born Method with Molecular Volume (GBMV) To obtain the relative conformational energies of the NAC oligomer, all four amylin oligomers M1-M4 and all 12 simulated NAC-amylin oligomers, the oligomer trajectories of the last 5 ns were first extracted from the explicit MD simulation excluding water molecules. The solvation energies of all systems were calculated using the Generalized Born method with Molecular Volume (GBMV).55,56 In the GBMV calculations, the dielectric constant of water was set to 80. The hydrophobic solvent-accessible surface area (SASA) term factor was set to 0.005 92 kcal/(mol Å2). Each conformer was minimized using 1000 cycles, and the conformational energy was evaluated by grid-based GBMV which accounts for the solvation energies. We note that the internal energy components such as vdw ineractions and electrostatic interactions are not considered in the GBMV calcualtions neither is the entropy of the systems. A total of 2000 conformations (500 conformations for each of the four amylin oligomers M1-M4) were used to construct the energy landscape of amylin oligomers 8 ACS Paragon Plus Environment

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While for the the NAC-amylin hetero-oligomers we used a total of 6000 conformations to construct the energy landscape of the NAC-amylin oligomers (500 conformations for each of NAC-amylin hetero-oligomers). For each of these data sets, we seperatley computed simulations.

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the conformer probabilities via Monte Carlo (MC)

Further, a total of 6000 conformations (500 conformations for each of

the 12 NAC-amylin oligomers were used to construct the energy landscape of the NAC-amylin oligomers and to evaluate the conformer probabilities by using Monte Carlo (MC) simulations. In the first step of the MC simulations, one conformation of conformer i and one conformation of conformer j are randomly selected. Then, the Boltzmann factor is computed as e-( Ej – Ei )/KT, where Ei and Ej are the conformational energies evaluated using the GBMV calculations for the conformation i and j, respectively, K is the Boltzmann constant and T is the absolute temperature (298 K used here). We note that the absolute temperature of 298 K has been used only in the GBMV method while the MD simulations were run under 330 K. If the Boltzmann factor value is larger than the random number, the move from conformation i to conformation j is allowed. After 1 million steps, the conformations visited for each conformer were counted. Finally, the relative probability of conformer n was evaluated as: Pn = Nn / Ntotal, where Pn is the population of conformer n, Nn is the total number of conformations visited for the conformer n, and Ntotal is the total steps. The advantages of using the MC simulations to estimate conformer probability rely on the facts that the MC simulations have good numerical stability and allow transition probabilities among several conformers to be controlled,58 as was previously applied for similar systems.27,28 Using all 4 conformers and 2000 conformations of the amylin oligomers generated from the MD simulations, we estimated the overall stability and computed the populations for each conformer based on the MD simulations with the energy landscape computed with GBMV for all conformers. Using all 12 conformers and 6000 conformations of the NAC-amylin oligomers generated from the MD simulations, we estimated the overall stability and populations for each conformer based on the MD simulations with the energy landscape computed with GBMV for all conformers. The conformational energies and the computed populations are seen in Table 1. Finally, we note that the group that these 12 models are likely to represent may be only a very small percentage of the ensemble. Nevertheless, the carefully selected models cover the most likely structures. 9 ACS Paragon Plus Environment


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The energy difference (∆E) for the formation of NAC-amylin oligomers To investigate the stability of each soluble NAC-amylin oligomers, the conformational energies were computed for all NAC-amylin models (Table S1). The conformational energies for each model are based on the energy computed with the GBMV method. For each model, a total of 500 conformations from the last 5 ns of the simulations were used to evaluate the conformational energy. We estimated the relative stability of each NAC-amylin model by comparing its energy with the energies of each one of the four amylin models (models M1-M4) and the NAC oligomer, as illustrated by the following chemical “reaction”:

( amylin ) n + ( NAC ) n ⇔ ( amylin ) n • ( NAC ) n

where n indicates the number of monomers within each one of the four amylin models and NAC oligomer. In our current study n = 6.

Structural analysis details We examined the structural stability of the studied models by following the changes in the number of the hydrogen bonds between β-strands, with the hydrogen bond cutoff being set to 2.5 Å. This examination was performed by following the root-mean square deviations (RMSDs), root-mean square fluctuations (RMSFs) and by monitoring the change in the inter-sheet distance (Cα backbone-backbone distance) in the core domain of all of the examined structures. The Cα backbone-backbone distance in NAC oligomer was defined as the distance between residue A89 and residue V74 and in amylin oligomers was defined as the distance between residue A8 and residue V32. We further investigated the average number of water molecules around each side-chain Cβ carbon within 4 Å for the NAC oligomer, each one of the four amylin models (M1-M4) and for each one of these oligomers in the 12 NACamylin oligomers.


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Secondary structure The secondary structures of the simulated NAC hexamers, models M1-M4 of amylin hexamers and the 12 models of NAC-amylin oligomers have been determined by computing and averaging the backbone dihedral angles Ψ and Φ of the last 500 frames from the MD simulations, for each residue. The ranges of (-60)°-(-160)° and 90°-170° were defined as the values of a β-strand structure.59

Evaluation of helicity pitch To compute the helicity pitch of amylin in models M1-M4 and in each one of the 12 models of NAC-amylin we used the equation: L=

360

θ

d

Where L is the helicity pitch, θ the torsional angle between the 2nd and 5th monomer within each hexamer and d is the distance between the 2nd and 5th monomer in each hexamer. The torsional angle was measured between the four residues in amylin: N35-L27 of the 2nd monomer and L27-N35 of the 5th monomer.

Results and Discusssion The

NAC-amylin hetero-oligomers

demonstrate

a

similar

scenario

of

polymorphism as in amylin oligomers The simulated 12 models of NAC-amylin dodecamers are seen in Figure 1 and the simulated NAC hexamer and amylin hexamers are seen in Figure S9 and Figure S10, respectively. Figure 2 (and Table 1) demonstrates the relative conformational energies of models M1-M4 of amylin hexamers and all 12 models of NAC-amylin dodecamers. Although there are distributions of the conformations of each structural simulated model, which indicate polymorphic states, yet the averaged conformational energy values show that the models of amylin hexamers M1 and M2 are the most stable hexamers. Interestingly, similar results were previously obtained in our study of of amylin octamers.35 Similarly, the NAC-amylin dodecamers which are composed of the amylin hexamers M1 and M2 are the most stable dodecamers. Figure 3 summarizes the populations of models M1-M4 of amylin hexamers and all 12 models 11 ACS Paragon Plus Environment


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of NAC-amylin dodecamers. One can see that the results of the populations provide a similar trend to the results of the conformational energies. Models M1 and M2 are the most populated amylin hexamers and the NAC-amylin dodecamers that are composed of amylin hexamers M1 and M2 are the most populated NAC-amylin dodecamers. Interestingly, the sum of the populations for M1 and M2 is ~60%, while for M3 and M4 it is ~40% and the sum of the populations in which NAC hexamer interacts with amylin hexamer models M1 and M2 is ~60% and with M3 and M4 it is ~40%.

The NAC-amylin hetero-oligomers strongly favors single layer conformation over double layer conformation There is a great interest to investigate the mechanisms through which amylin oligomers interact with NAC oligomers to form the cross-seeding NAC-amylin oligomers. Among the ensemble of the twelve models of NAC-amylin dodecamers, one can see from Figure 3 that the total percentage of single layer conformations is 71%, while for the double layer conformation it is only 29%. We therefore propose that amylin hexamers prefer to interact with NAC hexamers to form single layer conformations over double layer conformations. Furthermore, we estimated the energy difference (∆E) of the formation of NAC-amylin dodecamers from a NAC hexamer and each one of the amylin hexamers (Figure 4). This analysis illustrates that the formation of single layer conformations is more favored over the formation of double layer conformations, with the exclusion of the double layer conformation – model N3. Yet, one cannot neglect that the double layer conformations models N3 and O3 have relatively low conformational energies and high populations. To examine why only models N3 and O3 show relatively low conformational energies in comparison to the other models of double layer conformations P3 and Q3, we fitted the unimodal Gaussian functions of the GBMV conformational energy values for the NAC hexamer, for the four amylin hexamers (M1-M4) and for each one of the 12 models of NAC-amylin dodecamers (Table 1). The fitting of the unimodal Gaussian functions were agreeable for all models, with the exclusion of models N3 and O3. In models N3 and O3, a fitting of a bimodal Gaussian functions was necessary to get a good fitting which are effectively composed of two subgroups of populations (Tables S2-S3). In model N3 most of the conformers (~77%) have similar conformational energies to the most populated models, while a small percentage of the conformers (~23%) have 12 ACS Paragon Plus Environment

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similar conformational energies to the less populated models. In the case of model O3, ~50% of the conformers have similar conformational energies as the most populated models and ~50% of the conformers have similar conformational energies as the less populated models.

Examination of the structural properties of NAC hetero-oligomers and amylin oligomers One of the questions that need to be answered when investigating cross-seeding between NAC oligomers and amylin oligomers, is how the NAC hexamer affects the structural properties of each one of the amylin hexamers (M1-M4) and vice versa in the NAC-amylin dodecamers. To examine these effects on the structural properties, we computed the root mean square deviation (RMSD) values for NAC hexamer, for amylin hexamers (M1-M4) and for the 12 models of NAC-amylin dodecamers (Table 2 and Figures S11-S15). In general, one can see that the NAC hexamer decreases the RMSD values of amylin hexamers in the NAC-amylin dodecamers that are based on M1 and M2 (with the exclusion of model N1). However, it increases the RMSD values of amylin hexamers in the NAC-amylin dodecamers that are based on M3 and M4. Nevertheless, one can see that in general amylin hexamers decrease the RMSD values of the NAC hexamer in the NAC-amylin dodecamers (with the exclusion of models O3, P3 and Q2). We further investigated the total percentage of the hydrogen bonds between the βstrands in NAC hexamer, amylin hexamers (M1-M4) and the 12 models of NACamylin dodecamers (Table 2 and Figures S16-S21). One can see that the percentage of the hydrogen bonds increases in the NAC-amylin dodecamers in comparison to to the amylin hexamers (models M1-M4). We therefore suggest that the NAC hexamer stabilizes the amylin hexamers in the NAC-amylin dodecamers by forming a more stable cross-β structure than that of the amylin hexamers. Analysis of the secondary structure illustrated that each one of the four models of amylin hexamers does not affect the secondary structure of the NAC hexamer (Figures 5 and 6), i.e. the secondary structure of the NAC hexamer in the NAC-amylin dodecamers is similar to the NAC hexamer. However, the NAC hexamer does induce the formation of β-strand properties for some of the residues in the turn region of most of the amylin hexamers in the NAC-amylin dodecamers.



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To investigate whether the NAC hexamer might also affect the packing of the cross-β structure of the amylin hexamers when interacting together, we computed the Cα-Cα distance between Ala8 (which is the first residue in the N-terminal with β-strand properties) and Val32 (which is the residue in the opposite orientation in the Cterminal domain that has β-strand properties) for all four amylin hexamers (models M1-M4) and for all 12 models of NAC-amylin dodecamers (Figure 7 and Table 2). One can see that this distance in the NAC-amylin dodecamers that are based on M1 and M2 is decreased, while in the NAC-amylin dodecamers that are based on M3 and M4 it is increased (with the exclusion of models Q2 and Q3). Therefore, we propose that the NAC hexamer induces better packing of the amylin hexamers that are based on M1 and M2, but interrupts the packing of the amylin hexamers that are based on M3 and M4. However, all four models of the amylin hexamers do not change the packing of the NAC hexamer (Table 2). Indeed, both root mean square fluctuation (RMSF) analysis (Figures S22-S25) and solvation analysis (Figures S26-S28) showed that there are no differences in the RMSF values and in the solvation values for the residues in the NAC hexamer nor in its residues in the NAC-amylin dodecamers. Interestingly, the RMSF values and the solvation values of each one of the four amylin hexamers in the NAC-amylin dodecamers also do not change. Finally, we have recently 35 shown that all four models of amylin oligomers (M1-M4) have similar helicity pitch values that are in agreement with the experiment.36,37 Herein, by measuring the helicity pitch values of each one of the four models of amylin hexamers within the cross-seeding single layer conformations of NAC-amylin dodecamers we found that the helicity pitch values were increased in comparison to the M1-M4 models of amylin hexamers (Table 3). We therefore suggest that NAC hexamer increases the helicity pitch of the amylin hexamers when they interact together. Furthermore, this result also indicates that the amylin oligomers are less twisted in the NAC-amylin oligomers.

Summary and conclusions T2D has been associated with chronic neurodegeneration, while clinical studies have shown that individuals with T2D are at higher risk of developing AD1-3 and PD,7-10 the mechanisms that link these diseases remain unknown. The main question that needs to be solved is why patients with T2D have a higher risk to develop 14 ACS Paragon Plus Environment

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neurodegenerative diseases. Previous studies have shown that there may be a link between these two diseases due to the cross-amyloid interactions of amylin and Aβ.26,27 However, strucutural insight into these interactions at the atomic resolution is necessary in order to understand their molecular mechanisms. In our previous studies, we have shown the cross-amyloid interactions between amylin and Aβ oligomers27 and between NAC and Aβ oligomers.28 Herein, we present for the first time the interactions between amylin and NAC oligomers at the atomic resolution. Our all-atom MD simulations support the hypothesis that NAC oligomers may interact with amylin oligomers. In the bound states it is suggested that there are more than one molecular mechanism pathways in which NAC oligomers interact with amylin oligomers (Figure 8). Our statistical calculations of the conformational energies and the population analysis led us to conclude that the molecular mechanism pathways in which NAC oligomers interact with amylin oligomers favor the formation of single layer conformations of NAC-amylin oligomers, particularly with a preference towards two amylin oligomers – models M1 and M2 (and less with the other two amylin oligomers: M3 and M4). Our extensive structural analysis has shown that while amylin oligomers have no effect on the structural properties of NAC oligomers, NAC oligomers strongly affect the structural properties of the amylin oligomers. Particularly, NAC oligomers stabilize both the M1 and M2 amylin oligomer models and thus induce the formation of the NAC-amylin hetero-oligomers, in which the amylin oligomers are based on models M1 and M2. This claim is supported by several of our results: First, the RMSD values of these NAC-amylin hetero-oligomers are decreased. Second, their hydrogen bonds percentages are increased. Third, the NAC oligomers affect the amylin oligomers by enhancing the inter-β-strand packing and therefore creates a more compact cross-β structure. Fourth, the NAC oligomers induce β-strand properties on residues in the turn region of amylin oligomers and therefore obtain a more rigid turn region. Similarly to all amyloids, also AS presnts polymorphism. Recently, Rienstra's group60 solved the structure of self-asselmbed AS using ssNMR and Nussinov's group61 predicted the structure of extended NAC oligomers. Future work need to investigate the cross-seedinf between amylin oligomers to the fragments of NAC from these studies.



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We note that in this study, we do not aim to imply of any correlation between the probability to develop T2D in PD patients versus the probability to develop PD for T2D patients as the clinical aspects that underline the link between both diseases have been investigated accordingly through clinical studies.7-10 However, the amyloids that are related to these diseases that interact together and form structurally stable heterooligomers have not been studied at the molecular level. Our current study shows that while amylin oligomers do not change the structural properties of NAC oligomers, NAC oligomers readily present stable packed fibrilar structures and that the NAC oligomers in some cases even stabilize amylin oligomers by yielding a more compact fibril-like structure of amylin. Furthermore, it is possible that the structural stabilization of amylin oligomers in the NAC-amylin oligomeric complexes may be related to the elongation of the chain in the single layer conformations, as was previously shown for Aβ.62 By elongating the oligomer structure, we would increase the number of hydrogen bonds along the fibrilar axis which may certainly contribute to the structural stability of the NAC oligomer which in turn would affect the stability of the NAC-amylin hetero-oligomers. However, these issues need to be proven by further studies. Furthermore, future work needs to be initiated in order to examine whether elongation of either NAC oligomers or amylin oligomers, i.e., not similar number of monomers, may affect the structural properties or the aggregation process. Nevertheless, the structures of the NAC-amylin hetero-oligomers that were studied in the current work can serve as a basis for future in vitro and in vivo studies aimed at learning effect of cross-seeding on aggregation of these amyloids. Moreover, the neurotoxicity of NACamylin cross-seeding versus the aggregation of NAC or aggregation of amylin have never been investigated and future experimental studies can be expected to provide insights into the various mechanisms of these aggregation processes.

Acknowledgments This research was supported by the Israel Science Foundation (grant No. 532/15) and partly by the FP7-PEOPLE-2011- CIG, research grant no. 303741. All simulations were performed using the high-performance computational facilities of the Miller Lab in BGU HPC computational center. The support of the BGU HPC computational center staff is greatly appreciated. 16 ACS Paragon Plus Environment

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Supporting Information The supporting information is available free of charge on the ACS publications website at DOI: Analysis of populations using the Origin Pro 8, Figures S1-S28 and Tables S1-S3.

References: (1) Gotz, J.; Ittner, L. M.; Lim, Y. A. Common features between diabetes mellitus and Alzheimer's disease. Cell Mol Life Sci 2009, 66, 1321-1325. (2) Yang, Y.; Song, W. Molecular links between Alzheimer's disease and diabetes mellitus. Neuroscience 2013, 250, 140-150. (3) Li, L.; Holscher, C. Common pathological processes in Alzheimer disease and type 2 diabetes: a review. Brain Res Rev 2007, 56, 384-402. (4) Gotz, J.; Lim, Y. A.; Eckert, A. Lessons from two prevalent amyloidoses-what amylin and Abeta have in common. Front Aging Neurosci 2013, 5, 38. (5) Jackson, K.; Barisone, G. A.; Diaz, E.; Jin, L. W.; DeCarli, C.; Despa, F. Amylin deposition in the brain: A second amyloid in Alzheimer disease? Ann Neurol 2013, 74, 517-526. (6) Oskarsson, M. E.; Paulsson, J. F.; Schultz, S. W.; Ingelsson, M.; Westermark, P.; Westermark, G. T. In vivo seeding and cross-seeding of localized amyloidosis: a molecular link between type 2 diabetes and Alzheimer disease. Am J Pathol 2015, 185, 834-846. (7) Hu, G.; Jousilahti, P.; Bidel, S.; Antikainen, R.; Tuomilehto, J. Type 2 diabetes and the risk of Parkinson's disease. Diabetes Care 2007, 30, 842-847. (8) Sandyk, R. The relationship between diabetes mellitus and Parkinson's disease. Int J Neurosci 1993, 69, 125-130. (9) Arvanitakis, Z.; Wilson, R. S.; Schneider, J. A.; Bienias, J. L.; Evans, D. A.; Bennett, D. A. Diabetes mellitus and progression of rigidity and gait disturbance in older persons. Neurology 2004, 63, 996-1001. (10) Driver, J. A.; Smith, A.; Buring, J. E.; Gaziano, J. M.; Kurth, T.; Logroscino, G. Prospective cohort study of type 2 diabetes and the risk of Parkinson's disease. Diabetes Care 2008, 31, 2003-2005. (11) Gibb, W. R.; Lees, A. J. The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson's disease. J Neurol Neurosurg Psychiatry 1988, 51, 745-752. (12) Spillantini, M. G.; Schmidt, M. L.; Lee, V. M.; Trojanowski, J. Q.; Jakes, R.; Goedert, M. Alpha-synuclein in Lewy bodies. Nature 1997, 388, 839-840. (13) Spillantini, M. G.; Crowther, R. A.; Jakes, R.; Hasegawa, M.; Goedert, M. alpha-Synuclein in filamentous inclusions of Lewy bodies from Parkinson's



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

disease and dementia with lewy bodies. Proc Natl Acad Sci U S A 1998, 95, 64696473. (14) Hurtig, H. I.; Trojanowski, J. Q.; Galvin, J.; Ewbank, D.; Schmidt, M. L.; Lee, V. M.; Clark, C. M.; Glosser, G.; Stern, M. B.; Gollomp, S. M.; Arnold, S. E. Alpha-synuclein cortical Lewy bodies correlate with dementia in Parkinson's disease. Neurology 2000, 54, 1916-1921. (15) Leverenz, J. B.; Quinn, J. F.; Zabetian, C.; Zhang, J.; Montine, K. S.; Montine, T. J. Cognitive impairment and dementia in patients with Parkinson disease. Curr Top Med Chem 2009, 9, 903-912. (16) Galpern, W. R.; Lang, A. E. Interface between tauopathies and synucleinopathies: a tale of two proteins. Ann Neurol 2006, 59, 449-458. (17) Mandal, P. K.; Pettegrew, J. W.; Masliah, E.; Hamilton, R. L.; Mandal, R. Interaction between Abeta peptide and alpha synuclein: molecular mechanisms in overlapping pathology of Alzheimer's and Parkinson's in dementia with Lewy body disease. Neurochem Res 2006, 31, 1153-1162. (18) Masliah, E.; Rockenstein, E.; Veinbergs, I.; Sagara, Y.; Mallory, M.; Hashimoto, M.; Mucke, L. beta-amyloid peptides enhance alpha-synuclein accumulation and neuronal deficits in a transgenic mouse model linking Alzheimer's disease and Parkinson's disease. Proc Natl Acad Sci U S A 2001, 98, 12245-12250. (19) Eliezer, D.; Kutluay, E.; Bussell, R., Jr.; Browne, G. Conformational properties of alpha-synuclein in its free and lipid-associated states. J Mol Biol 2001, 307, 1061-1073. (20) Rao, J. N.; Dua, V.; Ulmer, T. S. Characterization of alpha-synuclein interactions with selected aggregation-inhibiting small molecules. Biochemistry 2008, 47, 4651-4656. (21) El-Agnaf, O. M.; Jakes, R.; Curran, M. D.; Middleton, D.; Ingenito, R.; Bianchi, E.; Pessi, A.; Neill, D.; Wallace, A. Aggregates from mutant and wild-type alpha-synuclein proteins and NAC peptide induce apoptotic cell death in human neuroblastoma cells by formation of beta-sheet and amyloid-like filaments. FEBS Lett 1998, 440, 71-75. (22) Giasson, B. I.; Murray, I. V.; Trojanowski, J. Q.; Lee, V. M. A hydrophobic stretch of 12 amino acid residues in the middle of alpha-synuclein is essential for filament assembly. The Journal of biological chemistry 2001, 276, 23802386. (23) Luk, K. C.; Song, C.; O'Brien, P.; Stieber, A.; Branch, J. R.; Brunden, K. R.; Trojanowski, J. Q.; Lee, V. M. Exogenous alpha-synuclein fibrils seed the formation of Lewy body-like intracellular inclusions in cultured cells. Proc Natl Acad Sci U S A 2009, 106, 20051-20056. (24) Hashimoto, M.; Takenouchi, T.; Mallory, M.; Masliah, E.; Takeda, A. The role of NAC in amyloidogenesis in Alzheimer's disease. Am J Pathol 2000, 156, 734-736. (25) Ueda, K.; Fukushima, H.; Masliah, E.; Xia, Y.; Iwai, A.; Yoshimoto, M.; Otero, D. A.; Kondo, J.; Ihara, Y.; Saitoh, T. Molecular cloning of cDNA encoding an unrecognized component of amyloid in Alzheimer disease. Proc Natl Acad Sci U S A 1993, 90, 11282-11286. (26) Andreetto, E.; Yan, L. M.; Tatarek-Nossol, M.; Velkova, A.; Frank, R.; Kapurniotu, A. Identification of hot regions of the Abeta-IAPP interaction interface as high-affinity binding sites in both cross- and self-association. Angewandte Chemie 2010, 49, 3081-3085.


Page 18 of 33

Page 19 of 33

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


(27) Baram, M.; Atsmon-Raz, Y.; Ma, B.; Nussinov, R.; Miller, Y. AmylinAbeta oligomers at atomic resolution using molecular dynamics simulations: a link between Type 2 diabetes and Alzheimer's disease. Physical chemistry chemical physics : PCCP 2016, 18, 2330-2338. (28) Atsmon-Raz, Y.; Miller, Y. Non-Amyloid-beta Component of Human alpha-Synuclein Oligomers Induces Formation of New Abeta Oligomers: Insight into the Mechanisms That Link Parkinson's and Alzheimer's Diseases. ACS chemical neuroscience 2016, 7, 46-55. (29) Jensen, P. H.; Hojrup, P.; Hager, H.; Nielsen, M. S.; Jacobsen, L.; Olesen, O. F.; Gliemann, J.; Jakes, R. Binding of Abeta to alpha- and beta-synucleins: identification of segments in alpha-synuclein/NAC precursor that bind Abeta and NAC. The Biochemical journal 1997, 323 ( Pt 2), 539-546. (30) Atsmon-Raz, Y.; Miller, Y. A Proposed Atomic Structure of the SelfAssembly of the Non-Amyloid-beta Component of Human alpha-Synuclein As Derived by Computational Tools. The journal of physical chemistry. B 2015, 119, 10005-10015. (31) Masel, J.; Jansen, V. A.; Nowak, M. A. Quantifying the kinetic parameters of prion replication. Biophys Chem 1999, 77, 139-152. (32) Ma, B.; Nussinov, R. Molecular dynamics simulations of alanine rich beta-sheet oligomers: Insight into amyloid formation. Protein Sci 2002, 11, 23352350. (33) Chen, M.; Margittai, M.; Chen, J.; Langen, R. Investigation of alphasynuclein fibril structure by site-directed spin labeling. The Journal of biological chemistry 2007, 282, 24970-24979. (34) Der-Sarkissian, A.; Jao, C. C.; Chen, J.; Langen, R. Structural organization of alpha-synuclein fibrils studied by site-directed spin labeling. The Journal of biological chemistry 2003, 278, 37530-37535. (35) Wineman-Fisher, V.; Atsmon-Raz, Y.; Miller, Y. Orientations of residues along the beta-arch of self-assembled amylin fibril-like structures lead to polymorphism. Biomacromolecules 2015, 16, 156-165. (36) Luca, S.; Yau, W. M.; Leapman, R.; Tycko, R. Peptide conformation and supramolecular organization in amylin fibrils: constraints from solid-state NMR. Biochemistry 2007, 46, 13505-13522. (37) Wiltzius, J. J.; Sievers, S. A.; Sawaya, M. R.; Cascio, D.; Popov, D.; Riekel, C.; Eisenberg, D. Atomic structure of the cross-beta spine of islet amyloid polypeptide (amylin). Protein Sci 2008, 17, 1467-1474. (38) Papadopoulos, J. S.; Agarwala, R. COBALT: constraint-based alignment tool for multiple protein sequences. Bioinformatics 2007, 23, 1073-1079. (39) Larkin, M. A.; Blackshields, G.; Brown, N. P.; Chenna, R.; McGettigan, P. A.; McWilliam, H.; Valentin, F.; Wallace, I. M.; Wilm, A.; Lopez, R.; Thompson, J. D.; Gibson, T. J.; Higgins, D. G. Clustal W and Clustal X version 2.0. Bioinformatics 2007, 23, 2947-2948. (40) Goujon, M.; McWilliam, H.; Li, W.; Valentin, F.; Squizzato, S.; Paern, J.; Lopez, R. A new bioinformatics analysis tools framework at EMBL-EBI. Nucleic acids research 2010, 38, W695-699. (41) McWilliam, H.; Li, W.; Uludag, M.; Squizzato, S.; Park, Y. M.; Buso, N.; Cowley, A. P.; Lopez, R. Analysis Tool Web Services from the EMBL-EBI. Nucleic acids research 2013, 41, W597-600.



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(42) Schroer, M. A.; Zhai, Y.; Wieland, D. C.; Sahle, C. J.; Nase, J.; Paulus, M.; Tolan, M.; Winter, R. Exploring the piezophilic behavior of natural cosolvent mixtures. Angewandte Chemie 2011, 50, 11413-11416. (43) Banks, W. A.; Kastin, A. J.; Maness, L. M.; Huang, W.; Jaspan, J. B. Permeability of the blood-brain barrier to amylin. Life Sci 1995, 57, 1993-2001. (44) Ida, N.; Hartmann, T.; Pantel, J.; Schroder, J.; Zerfass, R.; Forstl, H.; Sandbrink, R.; Masters, C. L.; Beyreuther, K. Analysis of heterogeneous A4 peptides in human cerebrospinal fluid and blood by a newly developed sensitive Western blot assay. The Journal of biological chemistry 1996, 271, 22908-22914. (45) Sanke, T.; Hanabusa, T.; Nakano, Y.; Oki, C.; Okai, K.; Nishimura, S.; Kondo, M.; Nanjo, K. Plasma islet amyloid polypeptide (Amylin) levels and their responses to oral glucose in type 2 (non-insulin-dependent) diabetic patients. Diabetologia 1991, 34, 129-132. (46) Yan, L. M.; Tatarek-Nossol, M.; Velkova, A.; Kazantzis, A.; Kapurniotu, A. Design of a mimic of nonamyloidogenic and bioactive human islet amyloid polypeptide (IAPP) as nanomolar affinity inhibitor of IAPP cytotoxic fibrillogenesis. Proc Natl Acad Sci U S A 2006, 103, 2046-2051. (47) Kale, L.; Skeel, R.; Bhandarkar, M.; Brunner, R.; Gursoy, A.; Krawetz, N.; Phillips, J.; Shinozaki, A.; Varadarajan, K.; Schulten, K. NAMD2: Greater scalability for parallel molecular dynamics. J Comput Phys 1999, 151, 283-312. (48) MacKerell, A. D.; Bashford, D.; Bellott, M.; Dunbrack, R. L.; Evanseck, J. D.; Field, M. J.; Fischer, S.; Gao, J.; Guo, H.; Ha, S.; Joseph-McCarthy, D.; Kuchnir, L.; Kuczera, K.; Lau, F. T. K.; Mattos, C.; Michnick, S.; Ngo, T.; Nguyen, D. T.; Prodhom, B.; Reiher, W. E.; Roux, B.; Schlenkrich, M.; Smith, J. C.; Stote, R.; Straub, J.; Watanabe, M.; Wiorkiewicz-Kuczera, J.; Yin, D.; Karplus, M. All-atom empirical potential for molecular modeling and dynamics studies of proteins. The journal of physical chemistry. B 1998, 102, 3586-3616. (49) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. Comparison of simple potential functions for simulating liquid water. The Journal of chemical physics 1983, 79, 926-935. (50) Mahoney, M. W.; Jorgensen, W. L. A five-site model for liquid water and the reproduction of the density anomaly by rigid, nonpolarizable potential functions. The Journal of chemical physics 2000, 112, 8910-8922. (51) Feller, S. E.; Venable, R. M.; Pastor, R. W. Computer simulation of a DPPC phospholipid bilayer: structural changes as a function of molecular surface area. Langmuir 1997, 13, 6555-6561. (52) Martyna, G. J.; Tobias, D. J.; Klein, M. L. Constant-Pressure Molecular-Dynamics Algorithms. Journal of Chemical Physics 1994, 101, 41774189. (53) Darden, T.; York, D.; Pedersen, L. Particle Mesh Ewald - an N.Log(N) Method for Ewald Sums in Large Systems. Journal of Chemical Physics 1993, 98, 10089-10092. (54) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A Smooth Particle Mesh Ewald Method. Journal of Chemical Physics 1995, 103, 8577-8593. (55) Lee, M. S.; Feig, M.; Salsbury, F. R.; Brooks, C. L. New analytic approximation to the standard molecular volume definition and its application to generalized born calculations. J Comput Chem 2003, 24, 1348-1356. (56) Lee, M. S.; Salsbury, F. R.; Brooks, C. L. Novel generalized Born methods. J Chem Phys 2002, 116, 10606-10614. 20 ACS Paragon Plus Environment

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(57) Rothman, E. D.; Sing, C. F.; Templeton, A. R. A model for analysis of population structure. Genetics 1974, 78, 943-960. (58) Ma, B.; Levine, A. J. Probing potential binding modes of the p53 tetramer to DNA based on the symmetries encoded in p53 response elements. Nucleic acids research 2007, 35, 7733-7747. (59) Akesson, B.; Panagiotidis, G.; Westermark, P.; Lundquist, I. Islet amyloid polypeptide inhibits glucagon release and exerts a dual action on insulin release from isolated islets. Regul Pept 2003, 111, 55-60. (60) Tuttle, M. D.; Comellas, G.; Nieuwkoop, A. J.; Covell, D. J.; Berthold, D. A.; Kloepper, K. D.; Courtney, J. M.; Kim, J. K.; Barclay, A. M.; Kendall, A.; Wan, W.; Stubbs, G.; Schwieters, C. D.; Lee, V. M.; George, J. M.; Rienstra, C. M. Solid-state NMR structure of a pathogenic fibril of full-length human alpha-synuclein. Nature structural & molecular biology 2016, 23, 409-415. (61) Xu, L.; Nussinov, R.; Ma, B. Coupling of the non-amyloid-component (NAC) domain and the KTK(E/Q)GV repeats stabilize the alpha-synuclein fibrils. European journal of medicinal chemistry 2016, 121, 841-850. (62) Wu, C.; Bowers, M. T.; Shea, J. E. Molecular structures of quiescently grown and brain-derived polymorphic fibrils of the Alzheimer amyloid abeta9-40 peptide: a comparison to agitated fibrils. PLoS computational biology 2010, 6, e1000693.

Figure captions: Figure 1: Twelve final simulated models of NAC-amylin dodecamers (water molecule boxes were removed for calirty of the images). NAC hexamers are colored in blue and amylin hexamers are colored in red. In models N1-N3 the amylin hexamers are based on model M1. In models O1-O3 the amylin hexamers are based on model M2. In models P1-P3 the amylin hexamers are based on model M3. In models Q1-Q3 the amylin hexamers are based on model M4. Residues in NAC: Residues A78, A85 (color: pink), Residues V74, A89, A91 (color: brown). Residues V70, V95 (color: yellow). Residues in amylin: H18 (color: orange). F23 (color: black). Residues R11, N31 (color: purple). Residues A8, F15, V17, A25, L27, V32 (color: yellow).

Figure 2: Distributions of the conformational energy values of the simulated models M1-M4 of amylin hexamers and of the twelve simulated models of the NAC-amylin dodecamers, obtained from the GBMV calculations.55,56 The energy values for each single system were scattered from the last 500 conformations of the MD simulations. 21 ACS Paragon Plus Environment


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Some of the conformations have similar energy values, therefore their energy values are scattered in the x-direction for the same value in the y-direction.

Figure 3: Populations of the simulated models M1-M4 of amylin hexamers and of the twelve simulated models of the NAC-amylin dodecamers by using Monte Carlo simulations.

Figure 4: The relative conformational energies of separated amylin hexamers (M1M4) and NAC hexamers and NAC-amylin dodecamers.

Figure 5: Secondary structure of the simulated NAC hexamer (top), and secondary structure of the NAC hexamers in the 12 simulated NAC-amylin oligomers (below). β-strands are shown in purple arrows.

Figure 6: Secondary structure of models M1-M4 of the simulated amylin hexamers (top), and secondary structure of the amylin hexamers in the 12 simulated NACamylin oligomers (below). β-strands are shown in red arrows.

Figure 7: Calculations of the inner core distance Cα(Ala8)-Cα(Val32) of amylin hexamers in the simulated models M1-M4 of amylin hexamers and in the twelve simulated models of the NAC-amylin dodecamers.

Figure 8: Schematic proposed molecular mechanism pathways (with our computed probabilities) of the formation of NAC-amylin oligomers.


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Figure 7



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Figure 8


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Table 1: The conformational energies (computed using the GBMV calculations)55,56 and the populations of the studied models. Standard deviations are in parenthesis. Model NAC M1 M2 M3 M4 N1 N2 N3 O1 O2 O3 P1 P2 P3 Q1 Q2 Q3

GBMV (kcal/mol) -2507 (99) -5128 (102) -5222 (101) -5042 (93) -5093 (100) -7839 (81) -7869 (169) -7847 (160) -7881 (142) -7889 (152) -7801 (166) -7740 (141) -7733 (180) -7722 (162) -7740 (161) -7679 (172) -7571 (175)

Populations (%) 26 36 16 22 10 11 10 11 11 10 7 7 7 7 6 3



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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Table 2: Structural analysis data of the averaged values from the last 500 conformations of each model.

Model

RMSD amylin [Å]

RMSD NAC [Å]

Hydrogen bond [%]

Cα(A8)-Cα(V32) distance in amylin [Å]

Cα(A89)-Cα(V74) distance in NAC [Å]

NAC

-

3.0

89

-

6.7

M1

3.6

-

69

15.8

-

M2

2.5

-

89

11.8

-

M3

2.4

-

71

12.8

-

M4

4.4

-

72

15.3

-

N1

3.8

0.8

92

13.3

7.0

N2

1.9

2.7

88

11.9

6.2

N3

1.1

2.6

90

5.9

6.6

O1

1.4

2.1

94

11.1

6.7

O2

1.6

2.4

91

8.0

6.9

O3

3.2

4.8

79

9.4

7.0

P1

2.4

2.0

78

19.8

6.6

P2

3.2

2.0

91

27.5

6.6

P3

4.2

3.6

83

21.7

6.6

Q1

3.0

1.9

88

23.6

6.6

Q2

5.1

4.8

77

17.7

6.9

Q3

4.5

3.1

69

15.8

6.3


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Table 3: Helicity pitch values of models M1-M4 of amylin hexamers and of amylin hexamers in the 12 simulated NAC-amylin dodecamer. Standard deviations are in parenthesis. The experimental helicity pitch value is 240 Å.

M1 M2 M3 M4 N1 N2 N3 O1 O2 O3 P1 P2 P3 Q1 Q2 Q3

amylin helicity pitch (Å) 201 (19) 275 (18) 292 (29) 101 (6) 204 (17) 208 (15) 588 (81) 303 (25) 312 (23) 418 (48) 351 (50) 441 (97) 133 (8) 210 (22) 176 (8) 166 (7)

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Molecular Mechanisms of the Bindings between ... - ACS Publications

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