Amyloid-β(29-42) Dimeric Conformations in Membranes Rich in

Publication Date (Web): February 27, 2019. Copyright © 2019 American Chemical Society. Cite this:J. Phys. Chem. B XXXX, XXX, XXX-XXX ...
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Amyloid-#(29-42) Dimeric Conformations in Membranes Rich in Omega-3 and Omega-6 Polyunsaturated Fatty Acids Yan Lu, Xiaofeng Shi, Phuong Hoang Nguyen, Fabio Sterpone, Freddie R. Salsbury Jr., and Philippe DERREUMAUX J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.9b00431 • Publication Date (Web): 27 Feb 2019 Downloaded from http://pubs.acs.org on March 2, 2019

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Amyloid-β(29-42) Dimeric Conformations in Membranes Rich in Omega-3 and Omega-6 Polyunsaturated Fatty Acids Yan Lu,∗,† Xiao-Feng Shi,† Phuong H Nguyen,‡ Fabio Sterpone,‡ Freddie R. Salsbury Jr.,¶ and Philippe Derreumaux∗,§,k †School of Physics and Optoelectronic Engineering, Xidian University, Xi’an, 710071, China ‡Laboratoire de Biochimie Theorique, Institut de Biologie Physico-Chimique (IBPC), UPR9080 CNRS, Universite Paris Diderot, Sorbonne Paris Cite, 13 rue Pierre et Marie Curie, 75005 Paris, France ¶Department of Physics, Wake Forest University, Winston-Salem, NC 27106, USA §Laboratory of Theoretical Chemistry, Ton Duc Thang University, Ho Chi Minh City, Vietnam kFaculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam E-mail: [email protected]; [email protected]

Abstract The omega-3 and omega-6 polyunsaturated fatty acids are two important components of cell membranes in human brains. When they are incorporated into phospholipids, omega-3 slows the progression of Alzheimer’s disease (AD) while omega-6 is linked to increased risk of AD. Little is known on the amyloid-beta (Aβ) conformations in membranes rich in omega-3 and omega-6 phospholipids. Herein, the structural

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properties of the Aβ29−42 dimer embedded in both fatty acid membranes were comparatively studied to a POPC bilayer using all-atom molecular dynamics (MD) simulations. Starting from alpha-helix, both omega-6 and omega-3 membranes promote new orientations and conformations of the dimer, in agreement with the observed dependence of Aβ production upon addition of these two fatty acids. This conformational result is corroborated by atomistic MD simulations of the dimer of the 99 amino acid C-terminal fragment of Amyloid Precursor Protein spanning the residues 15-55. Starting from beta-sheet, omega-6 membrane promotes helical and disordered structures of Aβ29−42 dimer, while omega-3 membrane preserves beta-sheet structures differing however from those observed in POPC. Remarkably, the mixture of the two fatty acids and POPC depicts another conformational ensemble of Aβ29−42 dimer. This finding demonstrates that variation in the abundance of the molecular phospholipids, which changes with age, modulates membrane-embedded Aβ oligomerization.

Introduction Alzheimer’s disease (AD) has been studied for decades, but its exact molecular mechanism is not completely understood, although oligomers of Aβ1−40/1−42 and the tau protein of 441 amino acids are key players. 1 Determining the structures of the transient oligomers is very difficult experimentally and theoretically due to their heterogeneity and transient characters. 2–7 Although Aβ and tau assemblies can interact together, 8 with membrane 9,10 and many membrane proteins in the extracellular space, hundreds of small molecules are present in the brain. Dietary PUFA (polyunsaturated fatty acids) supplementation causes change in molecular phospholipids from different brain regions. 11 When incorporated into phospholipids, there is evidence that increased intake of omega-3 PUFA slows the progression of AD and omega-6 PUFA is linked to higher risk of AD. 12 It is of interest to note that DHA (docosahexaenoic acid, 22:6n-3) belonging to the omega-3 family, and ARA (arachidonic acid, 20:4n-6) belonging to the omega-6 family also decrease and increase, respectively in

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most cancer tissues compared to normal ones, 13 indicating that their actions are not limited to AD, Parkinson’s disease, and amyotrophic lateral sclerosis. To date, little is known about how the abundance of omega-3 and omega-6 species is affected by differing levels of AD pathology in the brain, 12,14–18 and how intake of these two PUFA species from nutrition may have different impacts on AD development. 19,20 Yet, this knowledge is very important as all drugs have failed thus far for AD. 21–23 The problem increases in complexity since human prefrontal cortex phospholipids containing DHA increase during normal adult aging, whereas those containing ARA decrease. 15 In the last decade, it has been demonstrated that DHA inhibits Aβ1−42 fibrillation in vitro and reduces toxicity in SH-SY5Y cells, and also stimulates the phagocytosis of Aβ1−42 by microglia. 24 DHA has a higher inhibitory effect on Aβ1−42 amyloid fibril formation than at higher concentrations in vitro. 25 A recent molecular dynamics (MD) simulation targeting the interaction between Aβ16−22 trimer and a single DHA molecule in explicit aqueous solution provides a mechanism by which DHA redirects the peptides to unstructured trimer. 26 We know that DHA (omega-3) reduces Aβ production and increases the non-amyloid processing, 27 while ARA, the most important omega-6 fatty acid, results in higher secretion of both Aβ1−40 and Aβ1−42 . 28,29 Also the membrane omega-3 fatty acid modulates the oligomerisation kinetics of membrane proteins. 30 Overall, one important question is how membranes rich in omega-3 and omega-6 fatty acids impact at the structural level (a) the cleavage of the amyloid precursor protein (APP), and (b) the oligomerisation of Aβ protein. To address this issue, the structural properties of the Aβ29−42 dimer embedded in membranes containing DHA and ARA were comparatively studied to a POPC environment using all-atom MD simulations. The Aβ29−42 peptide was chosen because the C-terminus plays a critical role in Aβ42 aggregation kinetics, 31,32 and it can form fibrils in vitro. 33 Also Aβ29−42 is the transmembrane fragment of C99, the 99-residue C-terminal of APP, which upon β- and γ-secretases leads to Aβ isoforms. For our purpose, we used two starting dimer structures for Aβ29−42 dimer in the different membranes: alpha-helical as C99 is a helical homodimer,

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and a beta-sheet structure with parallel beta-strands as it is observed in the Aβ40/42 amyloid fibrils in aqueous solution. 34 Note that the Aβ29−42 dimer has already been subject to coarse-grained simulations 35 based on the OPEP force field, 36–38 extensive atomistic simulations in aqueous solution 39 and all-atom MD simulations in a POPC bilayer with and without a static electric field. 40,41 Because the dimer is only transient during aggregation, 7,42 our MD-generated conformation ensemble starting from the beta-sheet structure is not at equilibrium in the various lipid types. As the structure of C99 consists of a transmembrane domain (residues 29-52) with residues on the extracellular and intracellular faces of the membrane making extensive contacts that help define the dimer structure, 43 we also performed atomistic MD simulations of C99(15-55) dimer in POPC, omega-6 and omega-3 lipids to guarantee that our findings about helical reorientation in Aβ29−42 are real. Note that the structural ensemble of monomeric C99(15-55) has already been investigated in POPC lipid bilayer using coarse-grained models followed by 100 ns atomistic simulations. 44 Overall, our study reveals the early conformational reorganization steps of Aβ29−42 dimer in omega-3 and omega-6 membranes, providing new insights into their role in Aβ processing and oligomerization.

Methods The Aβ29−42 sequence is GAIIGLMVGGVVIA. Following our previous works, 40,41 the initial β-sheet dimeric structure was extracted from the Protein Data Bank (PDB) ID 2BEG 34 and placed perpendicular to the membrane. Although newer studies indicate very different fibril architectures for the Aβ42 protein in aqueous solution with a turn at residues 34-35 in 2MXU, 45 embedding Aβ29−42 with full beta-strands in a membrane is physical as it is consistent with the property of other sequences to form either beta-barrels or cross-beta sheet structures within membranes. 7,46–49 The initial structure for the helical dimer and its orientation from the membrane were

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extracted from the Orientation of Proteins in Membrane (OPM) database (PDB: 2LOH). 50 The N- and C- extremities were capped by acetyl and N-methyl groups to avoid any charges effect. This capping, rather than a zwitterion form, makes our peptide a better template for the Aβ43 peptide and the C99 peptide which is cleaved by the γ-secretase to form Aβ lengths of 38 to 43 amino acids. The C99(15-55) sequence is QKLVFFAEDVGSNKGAIIGLMVGGVVIATVIVITLVMLKKK and the initial structure was also taken from PDB 2LOH, with the termini capped by acetyl and N-methyl groups. All systems were built by using Charmm-GUI 51–53 server with an upper-leaflet and lower-leaflet ratio of approximately 1:1, i.e., a slightly different numbers of lipids in each leaflet to prevent the membrane to be strained and curved. The Aβ29−42 dimer was studied in membranes of three types starting from helix and beta-sheet structures: POPC, SAPCω6 and SDPCω3 and the C99(15-55) dimer was studied in the same membranes starting from helix. The subscripts are added for simplicity to recognize them. “PC” is the phosphocholine head group. POPC is 1-palmitoyl-2-oleoyl-snglycero-3-phosphocholine. SAPCω6 is 1-stearoyl-2-arachidonoyl-sn-glycero-3-phosphocholine (PC 18:0/20:4, with 4 double bonds within 20 carbon atoms), and SDPCω3 is 1-stearoyl-2docosahexaenoyl-sn-glycero-3-phosphocholine (PC 18:0/22:6, with six double bonds among 22 carbon atoms). The chemical structures of the lipids are shown in Figure 1. In the case of the beta-sheet structure, we also studied a membrane composed of mixed lipids with a ratio of 1:1:1 for POPC, SAPCω6 and SDPCω3 . Note that by using the same head group in the three lipids, differences in conformations come from the variation of the hydrophobic tails. Molecular dynamics simulations were performed by using GROMACS 5.1.2. 54 The protein force field is Amber ff99SB*-ILDN. 55 The force field for the membrane with POPC is Slipids, 56–58 and we use the extension of Slipids for polyunsaturated fatty acids. 59 The TIP3P water model was used. 60 For the Aβ29−42 dimer, the membrane thickness is 3.8 (POPC), 3.9 (SAPCω6 ), 4.1 (SDPCω3 ) and 4.0 nm (mixed lipid), with 2 nm thickness of water molecules on each side of the membrane. For C99(15-55) dimer, the membrane thickness is the same as

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for Aβ29−42 dimer, with a water layer of around 2.7 nm on each side of the membrane. The temperature was kept at 310 K, by using V-rescale thermostat 61 and a coupling constant of 0.5 ps, i.e. above the gel-liquid transition temperature of POPC, SAPCω6 , and SDPCω3 at 271.6 K, 260.2 K, and 266 K, respectively. 62 Pressure was kept semi-isotropically at 1 atm by using Parrinello-Rahman barostat 63 with a coupling constant of 2ps. All bonds were constrained using LINCS algorithm 64 with a 2 fs integration time step. A cutoff of 1.0 nm was used for Van der Waals interactions, and the particle-mesh Ewald method 65 with a cutoff of 1.0 nm was used for long-range electrostatic interactions. For each of the three lipid compositions, we perform for Aβ29−42 peptide five 200 ns MD simulations from the helical dimer and five 200 ns MD simulations from the beta-sheet dimer, all simulations using different initial velocity distributions. We also run five 200 ns MD simulations with mixed lipids from beta-sheet dimer. Overall this represents a total simulation time of 7.0 µs. For the C99(15-55) dimer, we perform five 500 ns MD simulations for each lipid composition, representing a total simulation time of 7.5 µs. The initial structure and a summary of the simulations are shown in Table 1. Note that each simulation on each system do not reach the same final conformations as we used various initial velocities. The first 50 ns of all simulations were discarded for analysis. The non-equilibrium structures were analyzed by various parameters depending on the initial structure. For the helical conformations, we used the terminology of Gly-in, Gly-out, and Gly-side for the G33xxxG37 motif as reported by Dominguez et al. 66 and our previous study. 41 Note that the initial helical dimeric structure has the Gly-out substate. For all simulations, the peptide conformations were clustered either with a backbone RMSD cutoff of 0.20 nm using the algorithm as described in Daura et al., 67 or the identifications of the clusters, populations and centers of the 2D free energy landscape (FEL) were performed using the Hartigan-Wong k-means algorithm 68 as described in Refs 69,70. Other order parameters for describing the peptides are given in the results and discussion section. The lipid properties were determined by the order parameter SCD = 23 hcos2 θz i − 21 , with

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θz the angle between the z axis and vector Cn−1 to Cn+1 , and h· · · i representing the ensemble mean over the last 10 ns. This order parameter can vary from 1 (being parallel to the z axis) to -1/2 (fully align perpendicular to the z axis). Average membrane thickness was calculated by using GRIDMAT. 71 O

O O

POPC

O O

H

P O O-

N+

O

O

O O

SAPC

O O H

P O O-

N+

O O

O O

SDPC

O O

H

P O O-

N+

O

Figure 1: The chemical structures of POPC, SAPCω6 and SDPCω3 .

Results and discussion The impact of the two fatty polyunsaturated acids membranes on the non-equilibrium conformations of the Aβ29−42 and C99(15-55) dimers are compared to the results in POPC starting from helical structures, followed by the simulation results of the Aβ29−42 dimer starting beta-sheet structures.

SAPCω6 and SDPCω3 promote new conformations and orientations of Aβ29−42 helical dimer We first calculated the secondary structure of the peptides using the Define Secondary Structure of Proteins (DSSP) algorithm 72 and found invariance of the composition in the three 7

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Table 1: A summary of the simulation details including the name, initial structure, lipid composition, simulation time and the number of runs for each system. Name

Initial Structure

G29

Aβ29−42 helical dimer

Lipid Composition

Simulation Time

No. of Runs

POPC

200 ns

5

SAPCω6

200 ns

5

SDPCω3

200 ns

5

POPC

500 ns

5

SAPCω6

500 ns

5

SDPCω3

500 ns

5

POPC

200 ns

5

SAPCω6

200 ns

5

SDPCω3

200 ns

5

mixed

200 ns

5

G29 G33 G37

G33 G37 A42

Q15

Q15

G29 G33 G37

G29 G33 G37

C99(15-55)

K55 K55

G29

G29

Aβ29−42 β-sheet dimer A42 A42

0.02

0.04

POPC SAPCω6 SDPCω3

0.00

Density

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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0

10

20

30

40

50

60

Crossing Angle°

Figure 2: Distributions of the crossing angle (in degrees) between the two helices in Aβ29−42 . The crossing angle in the initial structure is 50°.

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lipids; the Aβ29−42 peptides have 80% of alpha-helix and 15% of coil with error bars of 1%. We calculated the distributions of the crossing angle between the two helices, defined as the angle between the two vectors G29 → A42 . Figure 2 shows that the distribution in POPC is rather broad varying between 10° and 40 °, and the distributions in SAPCω6 and SDPCω3 are nearly superposable and are shifted to lower values. The population of conformations with crossing angles between 0 and 10 ° is 20.7% in SAPCω6 , 17.9% in SDPCω3 and 8.6% in POPC indicating that the two chains are more parallel to each other in omega-3 and omega-6 than in POPC. We next determined the free energy landscape (FEL) projected onto Φ4G , the dihedral angle spanning the Cα residues of G29-G37-G37-G29, and dGG , the Cα distance between G33 of the two chains, schematically shown in Fig. 3(a). Figure 3(b), (c), and (d) show the resulting FELs in POPC, SAPCω6 and SDPCω3 , respectively. The FELs in POPC and in SAPCω6 membranes display one dominant minimum: centered at (Φ4G , dGG ) = (−18o , 1.4nm) and called well 1, and centered at (0o , 1nm) and called well 2, respectively. In contrast, the FEL in SDPCω3 membrane displays three minima, where the centers of wells 1 and 2 are similar to those found in POPC and SAPCω6 , respectively, and a third minimum, well 3, centered at (Φ4G , dGG ) = (−22o , 0.7nm), which is unique to this PUFA. Using an energy smaller than 0.5 kcal/mol around each well, the population of well 1 is 46% in POPC, that of well 2 is 57% in SAPCω6 , and those of wells 1, 2 and 3 are 13%, 13% and 1% in SDPCω3 . The errors bars on these populations are on the order of 2%. This indicates that conformations are dominated by much shorter intermolecular distances in both PUFAs than in POPC. To further analyze the conformational-induced changes in Aβ29−42 , the conformations were clustered with a backbone RMSD of 0.2 nm. Fig. 4 show the centers of the first five clusters with their populations embedded in SAPCω6 and SDPCω3 membranes. Results for the clusters in POPC are given in our previous study. 41 Note these five clusters represent 77.6%, 68% and 78.3% in POPC, SAPCω6 and SDPCω3 , respectively, and the first ten clusters represent 90% of the full conformational ensembles in the three types of lipids.

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G29

(a)

2.0

G37

2.5

(b)

1

1.5

dGG G29

G33

1.0

1.0

0.5

POPC

0.5 −60

G37

−40

−20

2 2.5

(c)

2 3

1.0 0.5 −60

2.0 1.5

1.5

1

2.0

−20

0 Φ4G

20

40

40

0.5 −60

0.0

0.0

2.5

(d)

1.0

0.5 −40

20

1

2.0 1.5

1.5

1.0

SAPC

0 Φ4G

dGG

2.0

2.0

1.5

G33

dGG

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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2

3

SDPC −40

−20

0 Φ4G

20

40

1.0 0.5 0.0

Figure 3: (a) The order parameters Φ4G and dGG in the helical Aβ29−42 dimer. The panels (b), (c), and (d) show the FEL projected on Φ4G (in degrees) and dGG (in nm) of Aβ29−42 dimer embedded in a membrane composed of POPC, SAPCω6 , and SDPCω3 , respectively. The free energy scale is kcal/mol. Though there is not a one-to-one correspondence between the clusters and the FEL shown in Figure 3, the first and second clusters in SDPCω3 are representative of the conformations belonging to the wells 1 and 3 in FEL, and the first cluster in SAPCω6 is representative of the conformations belonging to the well 2 in FEL. Using the first 10 clusters, when POPC is used, the G33xxxG37 motif has a population of 69.7% to display Gly-out substate (see clusters 1, 2 and 3 in Ref. 41) and 20.8% of Gly-side susbstate. Gly-out substate means the motif faces the outside of the interface between the two helices, and Gly-side means the two motifs face both the inside and outside of the interface. When the dimer is embedded in SDPCω3 , the population of Gly-out (clusters 1, 3 and 4 in Fig.4b) and Gly-side (clusters 2 and 5) substates remains at 56.7% and 32.4%, respectively. The order of these two substates completely changes in SAPCω6 , where the Gly-out substates represent only 27.6% (cluster 2, clusters 6 and 7) and the Gly-side substates represent 53.4% (clusters 1, 3 and 4 in Fig. 4a). Overall, the omega-3 and omega-6 membranes promote new conformations and orienta10

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(a)

24.67%

13.89%

13.19%

9.18%

6.81%

24.23%

8.65%

6.82%

5.61%

SAPC

2

(b)

33.06%

SDPC

1

3

Figure 4: The central structures of the first five clusters of Aβ29−42 dimer in SAPCω6 (a) and SDPCω3 (b) membranes. The population of each cluster is given, and the circled numbers 1, 2, and 3 indicate their locations in the FELs shown in Figure 3. Cα atoms of G33 are shown in green, Cα atoms of G37 in cyan, α helix in purple and 310 helix in blue. tions of the Aβ29−42 dimer compared to POPC membrane. Omega-6 stabilizes the Gly-side substate of the G33xxxG37 motif, while omega-3 stabilizes the Gly-out substate of the G33xxxG37 motif. This conversion between the Gly-out and Gly-side substates has already been reported by atomistic MD simulations of Aβ29−42 dimer with a static electric field 41 and coarse-grained replica exchange molecular dynamics (REMD) simulations of the dimer of the residues 23-55 of C99 from an implicit DMPC to an implicit POPC membrane. 66 The differences in the conformation ensemble with thickness we observe are also consistent with recent coarse-grained simulations of the C99 monomer in implicit membranes of 3.0, 3.5 and 4.0 nm thickness, 73 and experimental studies reporting that generation of the Aβ1−42 peptide by γ-secretase can be inhibited by variation of membrane thickness. 74 Averaged over all simulations, we did not find any significant differences in the mean and fluctuation values of the order parameter SCD along the sn-1 chain between the three lipids as shown on Figure 5, indicating isotropic orientation in all environments. There is however a change in the lateral diffusion of the lipids, with diffusion constants at 310 K of 12.1 ± 4.0 in SAPCω6 , 12.9 ± 3.2 in SDPCω3 , and 8.6 ± 2.5 in POPC (×10−8 cm2 /s). 11

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0.3 POPC SAPC SDPC

0.2 − SCD

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

0.1

0.0

5

10 Carbon atoms

15

Figure 5: The order parameter SCD for the 14 sn-1 carbon atoms of POPC, and 16 sn-1 carbon atoms of omega-3 and omega-6 starting from a helical Aβ29−42 dimer. Solid curves show the averages and shaded areas show the standard deviation.

SAPCω6 and SDPCω3 impact the conformation of the C99(15-55) helical dimer We analyzed the MD results of C99(15-55) dimer in the three lipid compositions starting from the structure shown in Table 1. Fig.6(a)(b) and (c) show the FEL projected onto Φ4G and dGG . As for the Aβ29−42 dimer, the structural ensemble of C99(15-55) dimer is impacted by both omega-3 and omega-6 compared to POPC. SAPCω6 allows the formation of structures with Φ4G varying between -75° to 50° and Φ4G in SDPCω3 spans the interval -35° to 50° vs. -35° to 20° in POPC. This increased sampling of Φ4G was already observed in Aβ29−42 dimer (see Fig. 3C). The conformational impact of both PUFAs is also illustrated by the FEL projected onto two other variables (Fig.7) defined by Pantelopulos et al.: 73 the tilt angle between the vector of best fit through the Cα positions of residues 30-52 and the z-axis, and the GG kink angle. We observe that C99(15-55) dimer has a much higher population to be more kinked in SAPCω6 than in POPC (80° vs. 40°) and to be slightly more tilted in SDPCω3 than in POPC (30° vs. 20 °). Since this GG hinge at G37G38 has been conjectured to be important to processing by γ-secretase, 44,75,76 our simulations suggest that the observed increase of Aβ production upon omega-6 is linked in part to the higher fluctuations of the G37G38 kink, 12

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facilitating therefore the interaction of C99 with the active site of γ-secretase. 76 Cross RMSD between all conformations of the three ensembles using residues 15-55 does not show high similarity with RMSD varying between 0.33 and 0.98 nm indicating that the structural ensemble of C99(15-55) is strongly influenced by omega-6 and omega-3. The first five clusters shown in Figure 8 are illustrative and cannot represent the full conformational space difference, indeed using a backbone RMSD of 0.2 nm, there are about 500 clusters representing 90% of the total population for each lipid composition. The secondary structure composition in C99(15-55) is rather invariant in the three lipid compositions, averaging 17.5% of coil and 66% of helix, and 17% of bend+turn. There is, however, differences in the region 15-28 with 23% of helix in SDPCω3 , 25% of helix in POPC and 32% of helix in SAPCω6 , accompanied by a change of bend percentage varying between 10% in SAPCω6 , 14% in SDPCω3 and 17% in POPC. It is known that the positions of several residues contribute to the initiation and termination of γ-secretase, including K28, the epsilon-site (T48/L49) and K53. 73 We found that K28 forms significant intermolecular contacts with both E22 and N27 (60% of the time) in POPC, with mainly N27 (60% of the time) in SAPCω6 and mainly S26 and E22 (40% of the time) in SDPCω3 . In contrast, we did not find any significant different intermolecular contact maps involving T48/L49 and K53 in the three lipid compositions. Kcal/mol

(b) SAPCω6 2.0

1.8

2.0

1.6

1.5

1.4

1.0

1.2 1.0

−80

−40

Φ4G

0

20 40 60

Kcal/mol

(c) SDPCω3

Kcal/mol

2.5

2.0

1.8

2.0

1.8

2.0

1.6

1.5

1.6

1.5

1.4

1.0

1.4

1.0

0.5

1.2

0.5

1.2

0.5

0.0

1.0

0.0

1.0

dGG

2.5

−80

−40

Φ4G

0

20 40 60

2.5

dGG

(a) POPC 2.0

dGG

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˚ for C99(15-55) Figure 8: The first five clusters by using a backbone RMSD cutoff of 2 A dimer with their populations. The blue spheres are Cα atoms of Q15 (N-terminal) and Cα atoms of G25, in between Q15 and G25, there is α helix initially. Orange spheres are Cα atoms of T48, at which cleavage of γ-secretase is initiated. Red spheres are the Cα atoms of K55 (C-terminal). Cyan spheres are the G29, G33 and G37.

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SAPCω6 leads to more disordered Aβ29−42 structures starting from a beta-sheet dimer The mean and standard deviation of the contents of coil, beta, bend/turn, and helix of the dimer in the three pure lipids and the mixed lipids are given in Table 2. The composition of secondary structures is very similar in SDPCω3 and POPC membranes, with 59% of beta, 34% of coil and 0% of helix. The composition is drastically different in SAPCω6 where coil and beta have similar values (42% and 44%) and there is a helix signal of 7%. Remarkably, the mixing of the three lipids at a ratio 1:1:1 anneals the effect of SAPCω6 and gives a composition similar to SDPCω3 and POPC. Table 2: Secondary structure composition starting from beta-sheet dimer % SAPCω6 SDPCω3 POPC Coil 42.2 ± 0.5 33.4 ± 0.8 34.5 ± 1.1 Beta 44.0 ± 1.2 59.2 ± 0.7 59.2 ± 0.5 Bend/Turn 11.0 ± 0.3 8.1 ± 0.1 6.3 ± 0.3 Helix 7.2 ± 0.8 0 0

mixed lipid 32.4 ± 0.3 62.7 ± 0.1 4.8 ± 0.2 0

The distribution of the β-content along the sequence in the two chains is shown in Fig. 9. Compared to POPC membrane, SAPCω6 reduces the beta-character of residues 31-35 in both chains from 70% to 40% on average. In contrast, SDPCω3 increases the beta-character of residues 31-35 by 15% and decreases that of residues 37-42 by 20% on average compared to POPC. Consistent with the secondary structure composition, there is almost no change in the beta-character of all residues between POPC and mixed membranes. To characterize the conformational ensembles in the four simulations, we perform cluster analysis using a backbone RMSD cutoff of 0.2 nm. POPC has 36 clusters, SAPCω6 has 69 clusters, SDPCω3 has 40 clusters and mixed lipid has 37 clusters. Figure 10 shows the central structures of the five largest clusters, representing 69% in POPC, 61% in SAPCω6 , 78.3% in SDPCω3 , and 74.6% of the full conformational ensemble in mixed lipid. Error bars on the populations are on the order of 2%. In both POPC and SDPCω3 , the five clusters are

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Figure 9: Statistics of the β content on each residue for the Aβ29−42 dimer embedded in POPC, SAPCω6 , SDPCω3 , and mixed lipid membranes. The residues 29 and 42 have no β content. characterized by various twisted and kinked beta-sheet structures with beta-strands covering partly or totally the amino acid sequence. In SAPCω6 , we also find beta-sheet like structures (clusters 1 and 3), but cluster 2 (10%) shows some alpha-beta structures, and clusters 4 and 5 (11%) are disordered structures with the two C-termini interacting and the two Ntermini detached. The Cα distance between the two G29 is 1.45 nm and 2.0 nm in clusters 4 and 5, respectively. Looking at the clusters in mixed lipids, we recover twisted and kinked beta-sheet structure with high or low (cluster 4) beta-strand contents. We further analyzed the conformations by performing cross-RMSD between the first five clusters of all systems and all conformations of each cluster and we defined uniqueness if the backbone RMSD is below 0.2 nm. We find that all clusters are recovered by all conformations with different weights, and only the clusters 4 and 5 of SAPCω6 largely disordered are unique. Finally, we calculated the order parameter SCD of the membrane lipids and found that the mean and standard deviation along the carbon chain are very similar to that determined for the alpha-helix simulations (data not shown).

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Figure 10: Cluster analysis results. Cα atoms of residue 29 are shown in cyan spheres. The peptides are shown in cartoon representation with beta sheets in yellow, turn in cyan, coil in white, and 310 helix in blue.

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Conclusions We have studied the dimer of Aβ29−42 embedded in POPC, SAPCω6 , and SDPCω3 membranes by means of extensive atomistic MD simulations so as to provide new insights into the role of omega-3 and omega-6 membrane in Aβ processing and oligomerization. To verify the results of the helical Aβ29−42 dimer, we also performed simulations of the dimer of C99(15-55). Starting from alpha-helix, both SAPCω6 and SDPCω3 membranes stabilize new Aβ29−42 and C99(15-55) dimeric states. SAPCω6 induces a reorientation of the GxxxG motif in Aβ29−42 and an increased kink at G37G38 in C99(15-55), important in the cleavage of the amyloid precursor protein and providing therefore some physical insights into the increase of Aβ production upon omega-6. SDPCω3 membranes also impact the conformations of Aβ29−42 and C99(15-55) dimeric states, but it is not possible to explain from the conformational ensembles how omega-3 reduces Aβ production. Two reasons are possible. Our conformational sampling is not long enough and we may resort either to coarsegrained (CG) simulations prior to all-atom simulations, 77 but thus far current CG simulations keep protein secondary structures constant, or to enhanced sampling methods such as simulated tempering. 78,79 A more likely explanation is that the extracellular N-terminal sequence impacts conformations. It has been shown that all familial Alzheimer disease (FAD) mutations in the extracellular sequence of C99 spanning residues A2 to D23 in Aβ modulate the Aβ42/Aβ40 ratio and increase or decrease Aβ production. Of particular interest is that solid state NMR spectroscopy reveals a beta-hairpin located outside the membrane covering Y10-E11-V12 and L17-V18-F19 that regulates amyloidogenic processes. 80 We are currently exploring the full C99 dimer in the omega-3 and omega-6 lipid compositions with its wild-type sequence and some FAD mutants. Starting from a beta-sheet structure, we find that omega-6 leads to a higher population of disordered Aβ29−42 structures, while omega-3 gives rather similar Aβ29−42 structures, albeit not identical to POPC. This result indicates that the observed risk of AD upon omega-6 does not seem to result from higher beta-structures in the membrane. Finally, mixing the 18

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two fatty acids and POPC leads to another conformational ensemble of Aβ29−42 starting from beta-sheet structure. This finding demonstrates that variation in the abundance of the molecular phospholipids, which changes with age, modulates membrane-embedded Aβ oligomerization.

Acknowledgement This research was supported by National Natural Science Foundation of China (Grant No. 11804262) and Fundamental Research Funds for the Central Universities. Computations were performed on the Wake Forest University DEAC Cluster, a centrally managed resource with support provided in part by the University, and on the HPC system of Xidian University. PhD thanks the support of University of Denis Diderot (Paris 7), UPR9080 CNRS, IBPC, Paris, and the the French Grant ”DYNAMO”, ANR-11-LABX-0011-01.

References (1) Selkoe, D. J.; Hardy, J. The Amyloid Hypothesis of Alzheimer’s Disease at 25 Years. EMBO molecular medicine 2016, 1–14. (2) Tarus, B.; Tran, T. T.; Nasica-Labouze, J.; Sterpone, F.; Nguyen, P. H.; Derreumaux, P. Structures of the Alzheimer’s Wild-Type Aβ1-40 Dimer From Atomistic Simulations. The Journal of Physical Chemistry B 2015, 119, 10478–10487. (3) Man, V. H.; Nguyen, P. H.; Derreumaux, P. High-Resolution Structures of the Amyloidβ 1–42 Dimers From the Comparison of Four Atomistic Force Fields. The Journal of Physical Chemistry B 2017, 121, 5977–5987. (4) Zheng, W.; Tsai, M.-Y.; Wolynes, P. G. Comparing the Aggregation Free Energy Landscapes of Amyloid Beta(1–42) and Amyloid Beta(1–40). Journal of the American Chemical Society 2017, 139, 16666–16676. 19

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(5) Li, X.; Dong, X.; Wei, G.; Margittai, M.; Nussinov, R.; Ma, B. The Distinct Structural Preferences of Tau Protein Repeat Domains. Chem. Commun. 2018, 54, 5700–5703. (6) Viet, M. H.; Nguyen, P. H.; Ngo, S. T.; Li, M. S.; Derreumaux, P. Effect of the Tottori Familial Disease Mutation (D7N) on the Monomers and Dimers of Aβ40 and Aβ42. ACS Chemical Neuroscience 2013, 4, 1446–1457. (7) Nasica-Labouze, J.; Nguyen, P. H.; Sterpone, F.; Berthoumieu, O.; Buchete, N.-V.; Cot´e, S.; De Simone, A.; Doig, A. J.; Faller, P.; Garcia, A. et al. Amyloid β Protein and Alzheimer’s Disease: When Computer Simulations Complement Experimental Studies. Chemical Reviews 2015, 115, 3518–3563. (8) Wallin, C.; Hiruma, Y.; Warmlander, S. K. T. S.; Huvent, I.; Jarvet, J.; Abrahams, J. P.; Graslund, A.; Lippens, G.; Luo, J. The Neuronal Tau Protein Blocks in Vitro Fibrillation of the Amyloid-Beta (A Beta) Peptide at the Oligomeric Stage. Journal Of The American Chemical Society 2018, 140, 8138–8146. (9) Yu, X.; Wang, Q.; Pan, Q.; Zhou, F.; Zheng, J. Molecular Interactions of Alzheimer Amyloid-β Oligomers With Neutral and Negatively Charged Lipid Bilayers. Phys Chem Chem Phys 2013, 15, 8878–8889. (10) Yi, X.; Zhang, Y.; Gong, M.; Yu, X.; Darabedian, N.; Zheng, J.; Zhou, F. Ca(2+) Interacts With Glu-22 of Aβ(1-42) and Phospholipid Bilayers to Accelerate the Aβ(142) Aggregation Below the Critical Micelle Concentration. Biochemistry 2015, 54, 6323–6332. (11) Bascoul-Colombo, C.; Guschina, I. A.; Maskrey, B. H.; Good, M.; O’Donnell, V. B.; Harwood, J. L. Dietary DHA Supplementation Causes Selective Changes in Phospholipids From Different Brain Regions in Both Wild Type Mice and the Tg2576 Mouse Model of Alzheimer’s Disease. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids 2016, 1861, 524–537. 20

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Page 21 of 30 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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(12) Snowden, S. G.; A., E. A.; Abdul, H.; Yang, A.; Olga, P.; Richard, O.; John, T.; Cristina, L.-Q.; Madhav, T. Association Between Fatty Acid Metabolism in the Brain and Alzheimer Disease Neuropathology and Cognitive Performance: A Nontargeted Metabolomic Study. PLOS Medicine 2017, 14, 1–19. (13) Z´arate, R.; el Jaber-Vazdekis, N.; Tejera, N.; P´erez, J. A.; Rodr´ıguez, C. Significance of Long Chain Polyunsaturated Fatty Acids in Human Health. Clinical and Translational Medicine 2017, 6, 25. (14) Dyall, S. C. Interplay Between n-3 and n-6 Long-Chain Polyunsaturated Fatty Acids and the Endocannabinoid System in Brain Protection and Repair. Lipids 2017, 52, 885–900. (15) Norris, S. E.; Friedrich, M. G.; Mitchell, T. W.; Truscott, R. J. W.; Else, P. L. Human Prefrontal Cortex Phospholipids Containing Docosahexaenoic Acid Increase During Normal Adult Aging, Whereas Those Containing Arachidonic Acid Decrease. Neurobiology of Aging 2015, 36, 1659–1669. (16) Freund-Levi, Y.; Eriksdotter-J¨onhagen, M.; Cederholm, T.; et al, Ω-3 Fatty Acid Treatment in 174 Patients With Mild to Moderate Alzheimer Disease: Omegad Study: A Randomized Double-Blind Trial. Archives of Neurology 2006, 63, 1402–1408. (17) van de Rest, O.; Geleijnse, J. M.; Kok, F. J.; van Staveren, W. A.; Dullemeijer, C.; OldeRikkert, M.; Beekman, A. T.; de Groot, C. P. Effect of Fish Oil on Cognitive Performance in Older Subjects. Neurology 2008, 71, 430–438. (18) Johnson, E. J.; Mcdonald, K.; Caldarella, S. M.; Chung, H.-y.; Troen, A. M.; Snodderly, D. M. Cognitive Findings of an Exploratory Trial of Docosahexaenoic Acid and Lutein Supplementation in Older Women. Nutritional Neuroscience 2008, 11, 75–83. (19) Ravi, S. K.; Narasingappa, R. B.; Vincent, B. Neuro-Nutrients as Anti-Alzheimer’s

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Disease Agents: A Critical Review. Critical Reviews in Food Science and Nutrition 2018, 0, 1–66. (20) Calon, F.; Lim, G. P.; Yang, F.; Morihara, T.; Teter, B.; Ubeda, O.; Rostaing, P.; Triller, A.; Salem, N.; Ashe, K. H. et al. Docosahexaenoic Acid Protects From Dendritic Pathology in an Alzheimer’s Disease Mouse Model. Neuron 2004, 43, 633–645. (21) Nguyen, P.; Derreumaux, P. Understanding Amyloid Fibril Nucleation and Aβ Oligomer/Drug Interactions From Computer Simulations. Accounts of Chemical Research 2014, 47, 603–611. (22) Doig, A. J.; Derreumaux, P. Inhibition of Protein Aggregation and Amyloid Formation by Small Molecules. Current Opinion in Structural Biology 2015, 30, 50–56. (23) 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.; Derreumaux, P. Why Is Research on Amyloid-β Failing to Give New Drugs for Alzheimer’s Disease? ACS Chemical Neuroscience 2017, 8, 1435–1437. (24) Shahdat, H.; Michio, H.; Masanori, K.; Koji, M.; Toshio, S.; Osamu, S. Mechanism of Docosahexaenoic Acidinduced Inhibition of in Vitro Aβ1–42 Fibrillation and Aβ1– 42induced Toxicity in SHS5Y5 Cells. Journal of Neurochemistry 2009, 111, 568–579. (25) Lee, B. Y.; Attwood, S. J.; Turnbull, S.; Leonenko, Z. Effect of Varying Concentrations of Docosahexaenoic Acid on Amyloid Beta (1-42) Aggregation: An Atomic Force Microscopy Study. Molecules 2018, 23, 3089. (26) Zhou, H.; Liu, S.; Shao, Q.; Ma, D.; Yang, Z.; Zhou, R. Mechanism by Which DHA Inhibits the Aggregation of KLVFFA Peptides: A Molecular Dynamics Study. The Journal of Chemical Physics 2018, 148, 115102.

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(27) Grimm, M. O. W.; Kuchenbecker, J.; Gr¨osgen, S.; Burg, V. K.; Hundsd¨orfer, B.; Rothhaar, T. L.; Friess, P.; de Wilde, M. C.; Broersen, L. M.; Penke, B. et al. Docosahexaenoic Acid Reduces Amyloid Beta Production via Multiple Pleiotropic Mechanisms. J. Biol. Chem. 2011, 286, 14028–14039. (28) Amtul, Z.; Uhrig, M.; Rozmahel, R. F.; Beyreuther, K. Structural Insight Into the Differential Effects of Omega-3 and Omega-6 Fatty Acids on the Production of Abeta Peptides and Amyloid Plaques. J. Biol. Chem. 2011, 286, 6100–6107. (29) Amtul, Z.; Uhrig, M.; Wang, L.; Rozmahel, R. F.; Beyreuther, K. Detrimental Effects of Arachidonic Acid and Its Metabolites in Cellular and Mouse Models of Alzheimer’s Disease: Structural Insight. Neurobiol. Aging 2012, 33, 831.e21–31. (30) Guix`a-Gonz´alez Ramon,; Javanainen Matti,; G´omez-Soler Maricel,; Cordobilla Bego˜ na,; Domingo Joan Carles,; Sanz Ferran,; Pastor Manuel,; Ciruela Francisco,; Martinez-Seara Hector,; Selent Jana, Membrane Omega-3 Fatty Acids Modulate the Oligomerisation Kinetics of Adenosine A2A and Dopamine D2 Receptors. Scientific Reports 2016, 6, 19839. (31) Li, K. S.; Rempel, D. L.; Gross, M. L. Conformational-Sensitive Fast Photochemical Oxidation of Proteins and Mass Spectrometry Characterize Amyloid Beta 1–42 Aggregation. Journal of the American Chemical Society 2016, 138, 12090–12098. (32) Roche Julien,; Shen Yang,; Lee Jung Ho,; Ying Jinfa,; Bax Ad, Monomeric Aβ(1–40) and Aβ(1–42) Peptides in Solution Adopt Very Similar Ramachandran Map Distributions That Closely Resemble Random Coil. Biochemistry 2016, 55, 762–775. (33) Barrow, C. J.; Yasuda, A.; Kenny, P. T.; Zagorski, M. G. Solution Conformations and Aggregational Properties of Synthetic Amyloid β-Peptides of Alzheimer’s Disease. Journal of Molecular Biology 1992, 225, 1075–1093.

23

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(34) L¨ uhrs, T.; Ritter, C.; Adrian, M.; Riek-Loher, D.; Bohrmann, B.; D¨obeli, H.; Schubert, D.; Riek, R. 3D Structure of Alzheimer’s Amyloid-Beta(1-42) Fibrils. Proceedings of the National Academy of Sciences of the United States of America 2005, 102, 17342– 17347. (35) Lu, Y.; Wei, G.; Derreumaux, P. Effects of G33A and G33I Mutations on the Structures of Monomer and Dimer of the Amyloid-β Fragment 29-42 by Replica Exchange Molecular Dynamics Simulations. Journal of Physical Chemistry B 2011, 115, 1282–1288. (36) Derreumaux, P. Generating Ensemble Averages for Small Proteins From Extended Conformations by Monte Carlo Simulations. Phys. Rev. Lett. 2000, 85, 206–209. (37) Melquiond, A.; Boucher, G.; Mousseau, N.; Derreumaux, P. Following the Aggregation of Amyloid-Forming Peptides by Computer Simulations. J Chem Phys 2005, 122, 174904. (38) Sterpone, F.; Melchionna, S.; Tuffery, P.; Pasquali, S.; Mousseau, N.; Cragnolini, T.; Chebaro, Y.; St-Pierre, J.-F.; Kalimeri, M.; Barducci, A. et al. The OPEP Protein Model: From Single Molecules, Amyloid Formation, Crowding and Hydrodynamics to DNA/RNA Systems. Chem Soc Rev 2014, 43, 4871–4893. (39) Itoh, S. G.; Okumura, H. Dimerization Process of Amyloid-β(29-42) Studied by the Hamiltonian Replica-Permutation Molecular Dynamics Simulations. Journal of Physical Chemistry B 2014, 118, 11428–11436. (40) Lu, Y.; Shi, X.-F.; Salsbury, F. R.; Derreumaux, P. Small Static Electric Field Strength Promotes Aggregation-Prone Structures in Amyloid-β(29-42). The Journal of Chemical Physics 2017, 146, 145101. (41) Lu, Y.; Shi, X.-F.; Salsbury, F. R.; Derreumaux, P. Influence of Electric Field on the Amyloid-β(29-42) Peptides Embedded in a Membrane Bilayer. Journal of Chemical Physics 2018, 148, 045105. 24

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(42) Nasica-labouze, J.; Meli, M.; Derreumaux, P.; Colombo, G.; Mousseau, N. A Multiscale Approach to Characterize the Early Aggregation Steps of the Amyloid-Forming Peptide GNNQQNY From the Yeast Prion Sup-35. PLOS Computational Biology 2011, 7, 1–18. (43) Barrett, P. J.; Song, Y.; Van Horn, W. D.; Hustedt, E. J.; Schafer, J. M.; Hadziselimovic, A.; Beel, A. J.; Sanders, C. R. The Amyloid Precursor Protein Has a Flexible Transmembrane Domain and Binds Cholesterol. Science 2012, 336, 1168–1171. (44) Dominguez, L.; Meredith, S. C.; Straub, J. E.; Thirumalai, D. Transmembrane Fragment Structures of Amyloid Precursor Protein Depend on Membrane Surface Curvature. J. Am. Chem. Soc. 2014, 136, 854–857. (45) Xiao, Y.; Ma, B.; McElheny, D.; Parthasarathy, S.; Long, F.; Hoshi, M.; Nussinov, R.; Ishii, Y. Aβ(1-42) Fibril Structure Illuminates Self-Recognition and Replication of Amyloid in Alzheimer’s Disease. Nat. Struct. Mol. Biol. 2015, 22, 499–505. (46) Kandel, N.; Zheng, T.; Huo, Q.; Tatulian, S. A. Membrane Binding and Pore Formation by a Cytotoxic Fragment of Amyloid β Peptide. J Phys Chem B 2017, 121, 10293– 10305. (47) Stroobants, K.; Kumita, J. R.; Harris, N. J.; Chirgadze, D. Y.; Dobson, C. M.; Booth, P. J.; Vendruscolo, M. Amyloid-Like Fibrils From an α-Helical Transmembrane Protein. Biochemistry 2017, 56, 3225–3233. (48) Zhang, M.; Ren, B.; Chen, H.; Sun, Y.; Ma, J.; Jiang, B.; Zheng, J. Molecular Simulations of Amyloid Structures, Toxicity, and Inhibition. Israel Journal Of Chemistry 2017, 57, 586–601. (49) Martinez Hernandez, A.; Urbanke, H.; Gillman, A. L.; Lee, J.; Ryazanov, S.; Agbemenyah, H. Y.; Benito, E.; Jain, G.; Kaurani, L.; Grigorian, G. et al. The Diphenylpyrazole Compound anle138b Blocks Aβ Channels and Rescues Disease Phenotypes in a Mouse Model for Amyloid Pathology. EMBO Mol Med 2018, 10, 32–47. 25

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(50) Lomize, M. A.; Lomize, A. L.; Pogozheva, I. D.; Mosberg, H. I. OPM: Orientations of Proteins in Membranes Database. Bioinformatics 2006, 22, 623–625. (51) Jo, S.; Taehoon, K.; Wonpil, I. Automated Builder and Database of Protein/Membrane Complexes for Molecular Dynamics Simulations. PLoS ONE 2007, 2, 1–9. (52) Jo, S.; Lim, J. B.; Klauda, J. B.; Im, W. CHARMM-GUI Membrane Builder for Mixed Bilayers and Its Application to Yeast Membranes. Biophysical Journal 2009, 97, 50–58. (53) Wu, E. L.; Cheng, X.; Jo, S.; Rui, H.; Song, K. C.; D´avila-Contreras, E. M.; Qi, Y.; Lee, J.; Monje-Galvan, V.; Venable, R. M. et al. CHARMM-GUI Membrane Builder Toward Realistic Biological Membrane Simulations. Journal of Computational Chemistry 2014, 35, 1997–2004. (54) Berendsen, H.; van der Spoel, D.; van Drunen, R. GROMACS: A Message-Passing Parallel Molecular Dynamics Implementation. Computer Physics Communications 1995, 91, 43–56. (55) Lindorff-Larsen, K.; Piana, S.; Palmo, K.; Maragakis, P.; Klepeis, J. L.; Dror, R. O.; Shaw, D. E. Improved Side-Chain Torsion Potentials for the Amber ff99SB Protein Force Field. Proteins: Structure, Function and Bioinformatics 2010, 78, 1950–1958. (56) J¨ambeck, J. P. M.; Lyubartsev, A. P. Derivation and Systematic Validation of a Refined All-Atom Force Field for Phosphatidylcholine Lipids. Journal of Physical Chemistry B 2012, 116, 3164–3179. (57) J¨ambeck, J. P. M.; Lyubartsev, A. P. An Extension and Further Validation of an All-Atomistic Force Field for Biological Membranes. Journal of Chemical Theory and Computation 2012, 8, 2938–2948. (58) J¨ambeck, J. P. M.; Lyubartsev, A. P. Another Piece of the Membrane Puzzle: Extending Slipids Further. Journal of Chemical Theory and Computation 2013, 9, 774–784. 26

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(59) Ermilova, I.; Lyubartsev, A. P. Extension of the Slipids Force Field to Polyunsaturated Lipids. The Journal of Physical Chemistry B 2016, 120, 12826–12842. (60) 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. (61) Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; DiNola, A.; Haak, J. R. Molecular Dynamics With Coupling to an External Bath. The Journal of Chemical Physics 1984, 81, 3684–3690. (62) Ichimori, H.; Hata, T.; Matsuki, H.; Kaneshina, S. Effect of Unsaturated Acyl Chains on the Thermotropic and Barotropic Phase Transitions of Phospholipid Bilayer Membranes. Chemistry and Physics of Lipids 1999, 100, 151–164. (63) Parrinello, M.; Rahman, A. Polymorphic Transitions in Single Crystals: A New Molecular Dynamics Method. Journal of Applied Physics 1981, 52, 7182–7190. (64) Hess, B.; Bekker, H.; Berendsen, H. J. C.; Fraaije, J. G. E. M. LINCS: A Linear Constraint Solver for Molecular Simulations. Journal of Computational Chemistry 1997, 18, 1463–1472. (65) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A Smooth Particle Mesh Ewald Method. The Journal of Chemical Physics 1995, 103, 8577–8593. (66) Dominguez, L.; Foster, L.; Straub, J. E.; Thirumalai, D. Impact of Membrane Lipid Composition on the Structure and Stability of the Transmembrane Domain of Amyloid Precursor Protein. Proceedings of the National Academy of Sciences 2016, 113, E5281– E5287.

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(67) Daura, X.; Gademann, K.; Jaun, B.; Seebach, D.; van Gunsteren, W. F.; Mark, A. E. Peptide Folding: When Simulation Meets Experiment. Angewandte Chemie International Edition 1999, 38, 236–240. (68) Hartigan, J. A.; Wong, M. A. Algorithm AS 136: A K-Means Clustering Algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics) 1979, 28, 100–108. (69) Nguyen, P. H.; Tarus, B.; Derreumaux, P. Familial Alzheimer A2V Mutation Reduces the Intrinsic Disorder and Completely Changes the Free Energy Landscape of the Aβ1– 28 Monomer. The Journal of Physical Chemistry B 2014, 118, 501–510. (70) Nguyen, P. H.; Sterpone, F.; Campanera, J. M.; Nasica-Labouze, J.; Derreumaux, P. Impact of the A2V Mutation on the Heterozygous and Homozygous Aβ1–40 Dimer Structures From Atomistic Simulations. ACS Chemical Neuroscience 2016, 7, 823– 832. (71) Allen, W. J.; Lemkul, J. A.; Bevan, D. R. GridMAT-MD: A Grid-Based Membrane Analysis Tool for Use With Molecular Dynamics. Journal of Computational Chemistry 2009, 30, 1952–1958. (72) Kabsch, W.; Sander, C. Dictionary of Protein Secondary Structures. Biopolymers 1983, 22, 2577–2637. (73) Pantelopulos, G. A.; Straub, J. E.; Thirumalai, D.; Sugita, Y. Structure of APP-C99(199) and Implications for Role of Extra-Membrane Domains in Function and Oligomerization. Biochimica Et Biophysica Acta-Biomembranes 2018, 1860, 1698–1708. (74) Winkler, E.; Kamp, F.; Scheuring, J.; Ebke, A.; Fukumori, A.; Steiner, H. Generation of Alzheimer Disease-Associated Amyloid β42/43 Peptide by γ-Secretase Can Be Inhibited Directly by Modulation of Membrane Thickness. Journal of Biological Chemistry 2012, 287, 21326–21334.

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The Journal of Physical Chemistry

(75) Miyashita, N.; Straub, J. E.; Thirumalai, D. Structures of Beta-Amyloid Peptide 140, 1-42, and 1-55-The 672-726 Fragment of APP-in a Membrane Environment With Implications for Interactions With Gamma-Secretase. J. Am. Chem. Soc. 2009, 131, 17843–17852. (76) Pester, O.; Barrett, P. J.; Hornburg, D.; Hornburg, P.; Pr¨obstle, R.; Widmaier, S.; Kutzner, C.; D¨ urrbaum, M.; Kapurniotu, A.; Sanders, C. R. et al. The Backbone Dynamics of the Amyloid Precursor Protein Transmembrane Helix Provides a Rationale for the Sequential Cleavage Mechanism of γ-Secretase. J. Am. Chem. Soc. 2013, 135, 1317–1329. (77) Li, C.-D.; Junaid, M.; Chen, H.; Ali, A.; Wei, D.-Q. Helix-Switch Enables C99 Dimer Transition Between the Multiple Conformations. J Chem Inf Model 2019, 59, 339–350. (78) Nguyen, P. H.; Okamoto, Y.; Derreumaux, P. Communication: Simulated Tempering With Fast On-The-Fly Weight Determination. J Chem Phys 2013, 138, 061102. (79) Zhang, T.; Nguyen, P. H.; Nasica-Labouze, J.; Mu, Y.; Derreumaux, P. Folding Atomistic Proteins in Explicit Solvent Using Simulated Tempering. J Phys Chem B 2015, 119, 6941–6951. (80) Hu, Y.; Kienlen-Campard, P.; Tang, T.-C.; Perrin, F.; Opsomer, R.; Decock, M.; Pan, X.; Octave, J.-N.; Constantinescu, S. N.; Smith, S. O. Beta-Sheet Structure Within the Extracellular Domain of C99 Regulates Amyloidogenic Processing. Scientific Reports 2017, 7, 17159.

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