Abstract

Selective photosensitized oxidation of amyloid protein aggregates is being investigated as a possible therapeutic strategy for treating Alzheimer’s disease (AD). Photo-oxidation has been shown to degrade amyloid-β (Aβ) aggregates and ameliorate aggregate toxicity in vitro and reduce aggregate levels in the brains of AD animal models. To shed light on the mechanism by which photo-oxidation induces fibril destabilization, we carried out an all-atom molecular dynamics (MD) simulation to examine the effect of methionine (Met35) oxidation on the conformation and stability of a β-sheet-rich Aβ9–40 protofibril. Analyses of up to 1 μs simulations showed that the oxidation of the Met35 residues, which resulted in the addition of hydrophilic oxygens in the fibril core, reduced the overall conformational stability of the protofibril. Specifically, Met35 disrupted the hydrophobic interface that stabilizes the stacking of the two hexamers that comprise the protofibril. The oxidized protofibril is more solvent exposed and exhibits more backbone flexibility. However, the protofibril retained the underlying U-shaped architecture of each peptide upon oxidation, and although some loss of β-sheets occurred, a significant portion remained. Our simulation results are thus consistent with our experimental observation that photo-oxidation of Aβ40 fibril resulted in the dis-agglomeration and fragmentation of Aβ fibrils but did not cause complete disruption of the fibrillar morphology or β-sheet structures. The partial destabilization of Aβ aggregates supports the further development of photosensitized platforms for the targeting and clearing of Aβ aggregates as a therapeutic strategy for treating AD.
Introduction
The abnormal aggregation and deposition of the amyloid-beta (Aβ) peptides into extracellular amyloid plaques is a major pathological event in the development of Alzheimer’s disease (AD).1−3 It is linked to the progressive neurodegeneration in AD4−8 that involves the impairment of synaptic transmission and the loss of long-term potentiation.9,10 Amyloid plaques are formed by the misfolding and aggregation of Aβ into small oligomers that subsequently grow into large fibrils rich in cross β-sheets.11,12 Aβ oligomers have been found to be cytotoxic,13−16 and Aβ fibrils also contribute to neurodegeneration by impairing axonal transport10,13 and seeding the aggregation of the tau protein to form intracellular neurofibrillary tangles.14 Additionally, Aβ aggregates are also involved in the spatiotemporal disease progression through cell-to-cell transmission.15−17 Because of the central roles Aβ aggregates play in AD pathogenesis, modulating the peptide’s aggregation and inducing the selective degradation and clearance of Aβ aggregates is an attractive therapeutic strategy.
Among the many approaches that have been studied, photodynamic therapy (PDT) has drawn the attention of researchers18−20 because it is spatiotemporally controllable and minimally invasive.21,22 PDT has been used to treat diseases since the 1960s23 and is currently being used to treat many types of skin, lung, and esophageal cancers or pre-cancers.24 PDT requires a photosensitizer to produce singlet oxygens, which lead to the generation of reactive oxygen species (ROS) that subsequently oxidize cellular components, including cell membranes and organelles, and induce apoptosis, which destroys diseased tissues.25−27 In recent years, a number of studies have investigated the potential of PDT for treating AD by specifically targeting the Aβ peptide.28,29 A range of photosensitizers have been tested, and these studies have shown that photo-oxidation of monomeric (or soluble) Aβ can inhibit the peptide’s aggregation and that photo-oxidation of fibrillar Aβ can cause fibril fragmentation and disintegration in vitro.18,30−38 Encouragingly, Aβ aggregate degradation induced by photo-oxidation has also been found to attenuate aggregate toxicity39 and reduce aggregate levels in the brains of AD mouse models.40 In transgenic AD models of Caenorhabditis elegans, photo-oxidation of Aβ fibrils has been found to reduce Aβ neurotoxicity and extend the longevity of C. elegans.30,41
Most of the compounds that have been studied are known photosensitizers and are non-selective, including polyoxometalate31, 1,2,4-oxadiazole35, tetra(4-sulfonatophenyl) porphyrin34, rose bengal36, methylene blue38, and porphyrinic metal–organic frameworks30, and induce the photo-oxidation of both Aβ monomers and aggregates, as well as other biomolecules in the vicinity of the photosensitizers. This causes off-target oxidation and is a major drawback of PDT.42,43 Recently, several aggregate-selective photosensitizers have been developed and tested, including those based on fibril-binding dyes thioflavin T and curcumin39,40,44 and highly amyloid aggregate-selective p-phenylene ethynylene-based florescence sensors.45−47 These new aggregate-selective photosensitizers can potentially overcome off-target oxidation and minimize side effects in future clinical applications.
To further develop photoactive platforms that target the degradation and clearance of Aβ amyloids, a fundamental understanding of the effect of photo-oxidation on Aβ aggregates is needed. Many studies have documented the morphological changes to Aβ fibrils upon photo-oxidation, including fibril fragmentation, rupture, and disintegration.38,39,45 Photo-oxidation sites have also been identified. However, molecular-level details of the conformational changes that lead to fibril destabilization have not been fully elucidated.
For Aβ monomers, several studies have shed light on the mechanism by which photo-oxidation attenuates the monomer’s aggregation of Aβ monomers. Thioflavin T sensitized the oxidation of Tyr10, His13, His14, and Met35 residues,48 which reduced the aggregation propensity of the monomers and delayed aggregation. An NMR study demonstrated that oxidation of Met35 in Aβ monomers considerably impeded aggregation and the propensity of β-strand formation as the addition of a hydrophilic oxygen disrupted the hydrophobic interactions that stabilize the β-strands.49 These findings are consistent with others that found that oxidation of Met35 inhibited coil-to-β-sheet transition,50 significantly reduced trimer and tetramer formation,51 and slowed the rate of fibrillation.52 In an in vivo experiment, oxidation of Met35 in Aβ1–42 prevented the formation of a paranucleus53 and thereby inhibited further fibrillation. Computational studies corroborated experimental findings and indicated that the oxidation of Met35 in Aβ impeded aggregation by reducing the β-strand content on the C-terminal hydrophobic region.54
For Aβ1–40 fibrils, we and others have shown that photosensitization results in the oxidation of His13, His14, and Met35.18,45,48 The histidine residues are located on the surface of Aβ fibrils, whereas Met35 residues are located in the hydrophobic core region of the fibrils. Concomitant with photo-oxidation, we observed that clumps of long fibrils disaggregated and fragmented into shorter fibrils. The shorter oxidized fibrils are non-toxic and largely retained the β-sheet structures that were present in the native fibrils and the ability to seed fibrillation of Aβ monomers.45 Photo-oxidation of Aβ fibrils thus destabilized some structural aspects of Aβ fibrils but did not completely disassemble the aggregates. The partial stabilization can be advantageous for future therapeutic development as more complete disruption of fibrils can generate smaller oligomers that are more neurotoxic. Here, we carried out an all-atom molecular dynamics (MD) study to gain an understanding of the effect of photo-oxidation on fibril structure and stability. Although MD simulation has not been used to analyze the structures of photo-oxidized Aβ aggregates, the effects of oxidation caused by other pathways, such as through the reactive oxygen and nitrogen species produced by cold atmospheric plasma that lead to different patterns (Met35, Phe19, Phe20, Lys 16, and Lys28) and degrees of oxidation (3–15%),55 have been investigated computationally.56 Razzokov and co-workers found that 3% of Met35 oxidation of an Aβ11–42 pentamer led to a small destabilization in the structure of the pentamer and further increases of oxidation levels (9 and 15%) led to higher structural fluctuations and destabilization.56 MD simulation has also been used to study early steps of Aβ oligomer destabilization by the binding of a number of ligands.57−60
In this study, we carried out longer simulations (up to 1 μs) on a larger 12-chain Aβ protofibril where all Met35 residues were replaced with Met35ox. The larger protofibril with complete Met35 oxidation better mimics photo-oxidation studies that have been carried out on fibrils, and the longer simulation time allows us to capture dynamics at longer time scales. A number of analyses were carried out to assess the effects of Met35 oxidation on protofibril conformation and dynamics. Specifically, we monitored the deviation of the protofibril from its initial structure and analyzed changes to secondary structures that stabilize the protofibril.61−64 Global changes to the protofibril conformation were also monitored through analyzing the number of hydrogen bonds and solvent-accessible surface areas. Overall, we sought to characterize the dynamic destabilization of an Aβ protofibril due to Met35 oxidation to better understand the underlying mechanism of photo-oxidation-induced partial fibril destabilization.
Methods
System Setup
The initial structure of the Aβ protofilament (Aβ9–40) was obtained from the Protein Data Bank (PDB ID: 2LMN), which consisted of two stacked hexamers.65 Peptide chains are designated from A to F for the top hexamer and G to L for the bottom hexamer (Figure 1A). The Met35 residues in yellow are located in the middle of the protofibril where the hydrophobic surfaces of the two hexamers meet. The structures of Met and Metox are shown in Figure 1B. Protofibrils containing either Met35 (Aβ9–40-Met35) or oxidized Met35 (Aβ9–40-Met35ox) were set up.
Figure 1.
(A) Structure of dodecameric Aβ protofibril (2LMN), which consists of two hexamers. Individual Aβ9–40 chains are denoted as A to L, and Met35 residue side chains are shown in yellow. Purple and gray in the protofibril represent β-sheets and coils, respectively. (B) Chemical structures of Met and Metox.
Simulation Methods
The initial structure and parameterization of Met35ox were obtained using the SWISS-PARAM web server.66 After parameterization, MD simulations were prepared and run using Gromacs v201867 in isothermal (NVT) and isobaric ensembles (NPT). For water, the TIP3P model was used. Per SWISS-PARAM web server’s instructions to users when we started this simulation project in 2018, the CHARMM27 force field was used. We note that CHARMM27 has been found to have an α-helical bias68 and CHARMM36m is an improved model for modeling intrinsically disordered proteins and conformational changes.68,69 The limitation of the CHARMM27 is somewhat mitigated since the protofibril structures simulated in this study are ordered and contains very little α-helix during the simulation (see Table S1 in the Supporting Information). To prepare Aβ9–40-Met35ox, each of the 12 Met35 residues in the native Aβ protofibril was substituted with a Met35ox. A cubic simulation box of 10.8 nm in each dimension with periodic boundary conditions was used for the native and oxidized Aβ protofibrils. Sodium ions were then added to maintain charge balance.
Energy minimization of the systems was carried out using the steepest descent minimization method to reach a maximum force <1000.0 kJ/mol/nm. The energy-minimized systems were then equilibrated for 1 ns in NVT and NPT ensembles using LINCS70 constraints for hydrogen bonds (H-bonds) with a standard leap-frog integrator selected with a 2 fs time step. van der Waals interactions were treated with a cutoff distance of 1.0 nm, and long-range electrostatic interactions were calculated using particle mesh Ewald (PME) with a 1.0 nm cutoff length.71 For NVT equilibration, the modified Berendsen thermostat coupling was used to keep the temperature constant at 310 K. For NPT equilibration, the temperature (310 K) and pressure (1 bar) coupling was applied via the modified Berendsen thermostat coupling72 and Parrinello–Rahman method,73 respectively. MD productions of equilibrated systems were performed at NPT. For each system, three trajectories of 300 ns were run. The last trajectory of each system continued to run to 1 μs. UCSF chimera74 was used for visualization, and further analyses were done using Gromacs v2018. All simulations were run on the Comet hybrid computing cluster at the Extreme Science and Engineering Discovery Environment (XSEDE) digital service at the San Diego Supercomputer Center (SDSC).75
Analysis of Simulation Results
A number of different tools provided by the Gromacs v2018 package67 were utilized to analyze the simulation results to assess the structural stability of the protofibrils. The evaluated parameters include root mean square deviation (RMSD), root mean square fluctuation (RMSF), the radius of gyration (Rg), solvent-accessible surface area (SASA), the number of H-bonds (total, inter-chain, and intra-chain), and Asp23 (D23)–Lys28 (K28) salt bridge distances (inter-chain and intra-chain). Moreover, the secondary structures of the protofibrils were investigated via the Dictionary of Secondary Structure of Protein (DSSP)76 program to assess any conformational changes to the protofibril with Met35ox substitutions.
RMSD was obtained based on the Cα atoms of the peptides for the two hexamers. The Rg values of native and oxidized Aβ protofibrils were computed using the gmx gyrate tool. To supplement RMSD analysis, principal component analysis (PCA) was carried out via gmx covar and gmx anaeig for the last 50 ns (2500 frames) of the simulations. The GROMACS utility gmx hbond tool was used to compute the number of H-bonds between all main chains of the protofibril where a 0.35 nm donor–acceptor cutoff distance was assigned. To calculate the inter-chain hydrogen bonds, an index for each chain was made and the number of H-bonds between adjacent chains (for example, AB, BC, CD) was counted and added. For intra-chain H-bonds, the number of H-bonds associated with each chain was counted and added. SASA values of the protofibrils were calculated for all simulations. The distance between Met35 residues of opposing chains (A and G, B and H, C and I, D and J, E and K, F and L) in native and oxidized protofibrils was determined and compared. gmx mak_ndx was used to create appropriate index files separating Met35 residues of opposing Aβ chain pairs for all simulation trajectories. For contact map analysis, gmx mdmat was used to generate minimal distance matrices between pairs of residues.
Results
The fibrillar conformation of the Aβ peptide is highly thermodynamically stable and is primarily stabilized by the extended β-sheet core. To gain insights into the early structural changes to Aβ fibrils caused by photo-oxidation, which ultimately lead to fibril destabilization, we focused our analysis on the oxidation of Met35 as it is located in the fibril core and is expected to have the most significant impact on fibril structure and stability. A large Aβ9–40 protofibril with two stacked hexamers was chosen in this study as it contains the salient structural features of Aβ amyloid polymorphs, the U-shaped architecture of each Aβ peptide, extended inter-sheet chain-to-chain contacts, and hydrophobic strand-to-strand contacts.77 We first examined snapshots of native and oxidized protofibril trajectories. Then, we calculated RMSD, Rg, SASA, and RMSF values to evaluate structural fluctuations and possible expansion of the protofibril. Secondary structures, the number of H-bonds, and salt bridge interactions were also analyzed to gain more insights into the effects of Met35 oxidation.
Dynamics of Native and Oxidized Aβ Protofibrils
Snapshots of native (Aβ40-Met35) and oxidized (Aβ40-Met35ox) Aβ protofibrils from the 1 μs simulations are shown in Figure 2. Snapshots from the 300 ns trajectories are shown in Figure S1 of the Supporting Information. As shown, both protofibrils undergo structural changes with simulation time and become less ordered compared to the energy-minimized structures at the beginning of the simulations (0 ns). The extended β-sheets started to twist along the protofibril axis such that some of the β-strands are no longer co-planar by the end of the simulations. Chains located at the edges of the protofibrils appeared to have moved the most.
Figure 2.
Snapshots of native (A) and oxidized (B) Aβ protofibrils from 1 μs simulations. Met35 and Met35ox are shown in yellow and green, respectively. β-Strands, α-helices, and coils are shown in purple, orange, and gray, respectively.
To better visualize chain movements of the Aβ40-Met35 and Aβ40-Met35ox protofibrils, the end chains (A and L) in both protofibrils were highlighted and compared at the end of the 1 μs simulations (Figure 3). As shown, chain A (magenta) in the native protofibril is twisted but largely retained its β-hairpin structure (Figure 3A) whereas the same chain in the oxidized protofibril is also twisted but the β-hairpin is less aligned (Figure 3C). At the other end of the protofibril, chain L (blue) in the native protofibril is twisted along the protofibril axis and lost some of its β-sheet characteristics (Figure 3B). In comparison, chain L in the oxidized protofibril is more twisted along the protofibril axis (Figure 3D). Although this chain largely retained its hairpin structure, intra-chain β-sheet contacts are lost as well as the inter-chain β-sheet contacts with the adjacent chain K in the protofibril. Note that a few α-helices were observed to form in the turn region of both the native and oxidized protofibril (Figures 2 and 3, Figure S1, and Table S1). Because of the α-helical bias of the CHARMM27 force field,68 these α-helices can be potential artifacts.
Figure 3.

Visualization of end chains A (magenta) and L (blue) of the native (A and B) and the oxidized (C and D) Aβ protofibrils at 1000 ns of simulation time. Structures in A and C are each rotated at 180° to visualize the other ends of the protofibrils. The rest of the chains are colored gray for better visualization of the end chains.
Overall, snapshots of the protofibrils showed that both protofibrils largely retained their aggregated structure. Although the difference between Aβ40-Met35 and Aβ40-Met35ox protofibrils in these snapshots is not large, the twisting of chains was observed more frequently and at a higher degree in the Aβ40-Met35ox protofibril compared to the Aβ40-Met35 protofibril.
Structural Stability of Native and Oxidized Aβ Protofibrils
To assess the global conformational stabilities of the two protofibrils, we performed several analyses, including calculating the Cα-RMSD, Rg, SASA, and RMSF values of the 300 ns and 1 μs trajectories. RMSD values of the short (300 ns) and long (1 μs) simulations are shown in Figure 4A and B, respectively. Averaged RMSD values from the last 50 ns of each simulation are summarized in Table 1. Our results show that the oxidized protofibril generally exhibited higher RMSD values compared to the native protofibril, particularly at longer simulation times. This trend is also generally supported by PCA, where the oxidized protofibril occupies increased phase space (Figure S2 and S3), indicating increased flexibility.
Figure 4.

RMSD (A, B) and Rg (C, D) plots of native and oxidized protofibrils from 300 ns (A, C) and 1 μs (B, D) simulations. RMSD and Rg values shown for the 300 ns simulations (A and C) are averages from three simulation trajectories.
Table 1. Averaged Values, with Associated Standard Deviations of Backbone RMSD, Rg, SASA, and Number of H-Bonds for the Native and Oxidized Aβ Protofibrils from the Last 50 ns (2500 Frames) of Trajectories.
| protofibril and simulation trajectory | RMSD (nm) | Rg (nm) | SASA of protofibril (nm2) | number of inter-chain H-bonds | number of intra-chain H-bonds | total number of H-bonds | |
|---|---|---|---|---|---|---|---|
| native Aβ9–40 | trajectory 1 (300 ns) | 0.63 ± 0.011 | 1.51 ± 0.007 | 184.73 ± 3.67 | 177.2 ± 4.4 | 46.9 ± 4.2 | 242.8 ± 7.0 |
| trajectory 2 (300 ns) | 0.64 ± 0.010 | 1.53 ± 0.012 | 189.91 ± 3.95 | 174.9 ± 4.4 | 43.8 ± 4.5 | 234.0 ± 6.1 | |
| trajectory 3 (300 ns) | 0.63 ± 0.017 | 1.53 ± 0.006 | 181.06 ± 3.78 | 182.2 ± 4.4 | 51.0 ± 4.2 | 245.9 ± 6.6 | |
| trajectory 4 (1 μs) | 0.63 ± 0.009 | 1.49 ± 0.005 | 180.46 ± 3.24 | 178.4 ± 5.4 | 49.3 ± 3.9 | 243.8 ± 6.9 | |
| oxidized Aβ9–40-Met35ox | trajectory 1 (300 ns) | 0.71 ± 0.021 | 1.55 ± 0.009 | 197.29 ± 2.93 | 166.9 ± 5.3 | 38.3 ± 3.3 | 224.5 ± 6.1 |
| trajectory 2 (300 ns) | 0.65 ± 0.012 | 1.56 ± 0.006 | 193.72 ± 3.28 | 161.8 ± 4.1 | 37.1 ± 3.8 | 223.7 ± 6.4 | |
| trajectory 3 (300 ns) | 0.74 ± 0.019 | 1.52 ± 0.008 | 199.20 ± 3.95 | 162.0 ± 4.7 | 40.3 ± 5.0 | 214.0 ± 7.3 | |
| trajectory 4 (1 μs) | 0.84 ± 0.0070 | 1.51 ± 0.007 | 197.57 ± 2.96 | 160.4 ± 4.3 | 48.1 ± 4.0 | 223.6 ± 6.6 | |
The Rg of the native and oxidized protofibrils over the 300 ns and 1 μs trajectories are shown in Figure 4C and D, respectively, and summarized in Table 1. Rg values are calculated from the mass-weighted spatial distribution of the atoms in the protofibril and can be interpreted as a measure of the structural compactness of the protofibril. Both native and oxidized protofibrils exhibited similar Rg values of around 1.52 during the 300 ns trajectories. After 400 ns of simulation however, Rg values for the oxidized protofibril were slightly higher than those of the native protofibril (Figure 4D), implying that Met35 oxidation slightly decreased the compactness of the protofibril.
SASA is another important property that gives information about the overall protein conformation in an aqueous environment. Proteins are composed of hydrophobic and hydrophilic residues and tend to adopt structures that minimize the exposure of hydrophobic residues to the aqueous solvent. Increases in SASA from a stable state can indicate protein instability, such as unfolding that exposes hydrophobic residues to the solvent, which can lead to further undesirable changes such as irreversible aggregation.78 Substitution of amino acids, whether mutational or chemical, can also disturb the native conformation of a protein and result in partial unfolding, which leads to increases in SASA.
In this study, SASA values for the protofibrils were computed. As shown in Figure 5A,B and Table 1, SASA values of the oxidized protofibril were larger than those of the native protofibril; the average SASA values computed from the last 50 ns of the 1 μs simulations for the native and oxidized Aβ protofibrils were 180.46 ± 3.24 and 197.57 ± 2.96 nm2, respectively. Met35 oxidation thus caused about 17 nm2 or 10% increase of protofibril SASA. To assess the effect of oxidation on solvent exposure of the Met35 residue, SASA values of the Met35 or Met35ox residues for all simulation trajectories were also calculated (Figure 5C,D). As shown, Met35ox, located in the core of the protofibril, showed higher (by about 4 nm2) SASA values compared to Met35 in the native protofibril. Oxidation of Met to methionine sulfoxide increases the hydrophilicity of the residue, and even though Met is deeply buried in the hydrophobic core of the protofibril, its solvent exposure increased. However, the ∼4 nm2 increase in Met35 SASA only partially contributes to the overall ∼17 nm2 increase in protofibril SASA, indicating that oxidation of the Met35 at the core of the protofibril might have caused global conformational changes to the protofibril such that the oxidized structure is in a more solvent exposed state.
Figure 5.

Solvent-accessible surface area (SASA) values of the native (black) and oxidized (red) protofibrils calculated from 300 ns (A) and 1 μs (B) simulation trajectories. SASA values of the Met35 (black) or Met35ox (red) residue in native and oxidized Aβ protofibrils calculated from 300 ns (C) and 1 μs (D) simulations.
To evaluate the local dynamics and flexibility of each residue of the Aβ chains, the RMSF values of the backbone of Aβ in the top hexamer (chains A to F) and bottom hexamer (chains G to L) for native and oxidized protofibrils after 1 μs of simulation were calculated and are plotted in Figure 6. RMSF plots of the 300 ns simulations are shown in Figure S4 of the Supporting Information. As expected, terminal chains A and F of the top hexamer and chains G and L of the bottom hexamer showed higher fluctuations with higher RMSF values than the interior chains (Figure 6A,C). Moreover, in the oxidized protofibril, 8 out of 12 chains (chains A, E, F, G, I, J, K, and L) showed statistically significant higher RMSF values compared to the native protofibril (p < 0.05). Some of these chains are terminal chains, and some are in the interior of the protofibril. As such, our results show that Met35 oxidation caused increased chain flexibilities throughout the protofibril.
Figure 6.

RMSF plots of different Aβ chains belonging to the top hexamer (chains A to F: A and B) and bottom hexamer (chains G to L: C and D) of the native (A and C) and oxidized (B and D) protofibrils after 1 μs of simulation.
Taken together, our analyses of the global conformational characteristics of a native Aβ40-Met35 and an oxidized Aβ40-Met35ox protofibrils indicate that Met35 oxidation has a destabilizing effect on the highly ordered protofibril structure, wherein the Aβ40-Met35ox protofibril showed higher values of RMSD, SASA, and RMSF compared to those of the Aβ40-Met35 protofibril. Rg values were minimally affected. Both protofibrils deviated from the initial energy-minimized structures wherein twisting and misalignment of the β-strands were observed during simulations.
Methionine–Methionine Distances in the Protofibril Core
The hydrophobic interactions of Met35 residues from the two opposing hexamers facilitate the favorable interaction of the two hexamers in the native protofibril (Figure 1). This parallel transversal combination of the two hexamers around the longitudinal axis of the protofibril is a common feature of various polymorphisms identified in the Aβ fibril architecture79 and serves to shield hydrophobic residues at the C-termini of the Aβ peptides. Theoretical and experimental works have shown that residues Ile31, Met35, and Val39 are involved in the hydrophobic interface of both Aβ40 and Aβ42 fibrils.77,80−83
Because of the important role Met35 plays in stabilizing the fibril structure, we analyzed the packing of the Met35 residues in the protofibril core by measuring the distances between Met35 and Met35 residues in the native protofibril and between Met35ox and Met35ox residues in the oxidized protofibrils; results from the 1 μs simulations are summarized in Figure 7. The same plots for the 300 ns simulations are shown in Figure S5 of the Supporting Information. As shown in Figure 7, except for the end chains A and G, all other Met35–Met35 pairs equilibrated to 0.8 to 1 nm distances in the native protofibril. The end chains A and G showed greater Met35–Met35 distances of around 1.8 nm during most of the simulation and dropped to around 1 nm after 800 ns of simulation. This greater fluctuation is consistent with higher RMSF values observed for the two chains (Figure 6A,C). Met35ox–Met35ox distances in oxidized fibrils in general showed more fluctuations during the simulations. In particular, interior chain pairs, C and I, D and J, and E and K, showed statistically significant higher Met35ox–Met35ox distances than Met35–Met35 distances in the native protofibril (p < 0.05), while the end chain pairs (A and G, F, and L) and the near end-chain pair (B and H) did not show significant differences in Met-Met distances.
Figure 7.

Distances between Met35 and Met35 (black) and between Met35ox and Met35ox (red) residues of six opposing Aβ chain pairs (A and G, B and H, C and I, D and J, E and K, and F and L) in the protofibrils for the 1 μs simulation.
The trends in methionine–methionine distances suggest that the oxidation of the most buried methionine residues of the central chains away from protofibril ends had the biggest impact in disrupting the fibril structure. This finding also suggests that the increase in SASA of the protofibril with oxidation (Figure 5) can be due to increased solvent exposure of the interior Met35 residues upon oxidation.
Intra- and Inter-Peptide Salt Bridge Distances in Protofibrils
The Asp23–Lys29 (D23–K28) salt bridge that forms near the turn region of the Aβ peptide plays an important role in stabilizing the U-shaped β-strand-turn-β-strand motif of the peptide and prevents large backbone motion. We performed an analysis of the D23–K28 salt bridge distances in the native and oxidized protofibrils to assess if Met35 oxidation adversely affected the stability of the intra-peptide salt bridges. D23–K28 distances for each Aβ chain for the 1 μs simulations are shown in Figure S6. Comparisons between salt bridge distances of the native protofibril and oxidized fibrils did not show a consistent trend. Distances are comparable for chains E, G, H, I, and L. They are larger in the oxidized protofibril than the native protofibril for chains J and K but smaller for chains A, C, and D. Thus overall, Met35 oxidation did not have a consistent effect on intra-molecular salt bridge distances, and these salt bridges appear to be relatively unaffected by Met35 oxidation.
We also analyzed the inter-peptide D23–K28 salt bridges formed by adjacent Aβ peptides for the 1 μs simulation (Figure S7). These salt bridges also stabilize the peptides’ U-shape conformation and contributes to the rigidity of the Aβ protofibril. As shown in Figure S7, no consistent trend emerged. Some inter-chain salt bridge distances were decreased by Met35 oxidation (chains C and D, G and H, and D and K), some remained unchanged (chains B and C, D and K, I and J) and, in one neighboring pair, increased (chains J and K). Overall, our analysis of intra- and inter-salt bridge distances thus showed that oxidation did not have a significantly destabilizing effect on the turn region of the Aβ peptides’ U-shape motif, nor did it destabilize the stacking of peptides in the protofibril axial direction in each of the hexamers.
Hydrogen Bonds in Protofibrils
Experimental and theoretical investigations have shown that the extended β-sheet conformation of the Aβ protofibril and fibril is stabilized by a network of H-bonds, both intra- and inter-peptides.82,84 The U-shape motif of each Aβ peptide in the protofibril is stabilized by H-bonds that form between the two β-strands. The peptides then stack axially via hydrogen bonds to form the extended inter-peptide β-sheet structure of the fibrils and protofibrils, with the hydrophilic surface composed of N-terminal amino acids facing the solvent and the hydrophobic surface composed of C-terminal amino acids facing the interior of the fibril and protofibril core.85−87 To study the effect of Met35 oxidation on the H-bond network of the protofibril, we calculated the total number of H-bonds (Figure 8 and Table 1) as well as the inter- and intra-chain H-bonds (Figures S8 and S9) of the native and oxidized protofibrils as a reduction in the number of H-bonds that destabilize β-sheets, which can lead to the destabilization of the Aβ protofibril structure.
Figure 8.

The total number of hydrogen bonds in the native protofibril (black) and the Met35-oxidized protofibrils (red) for the 300 ns (A) and 1 μs (B) simulations.
As shown in Figure 8 and Table 1, the oxidized protofibril has a lower total number of H-bonds compared to the native protofibril. The difference is clear in the longer 1 μs simulations where the native protofibril has an average of 244 H-bonds compared to an average of 223 H-bonds in the oxidized protofibril over the last 50 ns of the simulations (Table 1). Oxidation of the Met35 residues in the core of the protofibril thus caused about a 10% reduction in the H-bond network in the whole protofibril.
To gain more insights into the type of H-bonds that were lost due to Met35 oxidation, we analyzed the number of intra- and inter-H-bonds (Figures S8 and S9 and Table 1). As shown, the number of inter-chain H-bonds of the oxidized protofibril is lower compared to that of the native protofibril while the numbers of intra-chain H-bonds between the oxidized and native protofibrils were comparable. Thus, H-bonds lost due to Met35 oxidation were primarily inter-chain H-bonds. In addition, we have also performed contact map analysis. As shown in Figure S11, the oxidized fibrils (Figure S11B, D) showed modest increases in pairwise distances compared to the native, unoxidized protofibril, which point to a less well-packed structure.
Secondary Structures of Aβ Protofibrils
The Aβ protofibril adopts a highly ordered conformation wherein the peptides primarily form β-sheets. A secondary structural analysis thus gives us insights into the effect of Met35 oxidation on the structural stability of the protofibril. We employed the DSSP method76 to map the secondary structures of both native and oxidized protofibrils for the simulations (Figure 9A,B). Secondary structure plots were also constructed from the analysis (Figure 9C,D and Figure S10), and results are summarized in Table S1.
Figure 9.
Secondary structure analysis of native and oxidized Aβ protofibrils for the 1 μs simulations. DSSP mapping of native (A) and oxidized (B) Aβ protofibrils show the secondary structures adopted by each amino acid of the 12 Aβ peptides that form the protofibril. Secondary structure plots of native (C) and oxidized (D) Aβ protofibrils show the number of amino acids that adopt each of the secondary structural elements.
As shown in Figure 9A, the predominate secondary structures in the native protofibril were β-sheets (red) and coils (white), followed by turns (yellow) and bends (green). In the oxidized protofibril, the level of β-sheets was reduced, accompanied by a notable increase in the level of coils (Figure 9B). These changes are more easily visualized in plots of secondary structures of the native (Figure 9C) and oxidized (Figure 9D) protofibrils and by the averaged percentages of the secondary structures from the last 50 ns of trajectories (Table S1). As the other secondary structures remained largely at the same low levels in the oxidized fibrils, the photo-oxidation of Met35 appeared to mainly have a disruptive effect on some β-sheets in the protofibril and did not cause the significant formation of other, ordered secondary structures such as α-helices.
Discussion
Photosensitizer-induced oxidation of Aβ aggregates is being explored as a promising therapeutic strategy for the targeted degradation and clearance of the aggregates. Photo-oxidized fibrils exhibit lower toxicity in vitro, and importantly, photo-oxidation has been reported to reduce brain Aβ aggregate levels and extend the longevity of AD animal models.30,40,41 We have shown in a recent in vitro study that a fibril-selective photosensitizer caused clumps of Aβ40 fibrils to dissociate and fragment into smaller fibrils with light irradiation.45 Moreover, the oxidized fibrils retained a significant amount of β-sheet structures of the native fibrils and the ability to seed the aggregation of Aβ monomers. This partial fibril destabilization may be advantageous since more complete degradation of amyloid fibrils can potentially result in oligomers that are more toxic compared to fibrillar Aβ conformers.88,89 In order to better understand photo-sensitized fibril degradation and clearance and further develop PDT to treat AD, a detailed understanding of the effect of photo-oxidation on fibril structure and stability is needed.
In this study, we performed all-atom MD simulations to investigate the effect of Met35 oxidation on the structural dynamics and stability of an Aβ9–40 protofibril. Simulation snapshots show that the oxidized protofibril retained its aggregated structure (Figure 1). Twisting of Aβ chains along the protofibril axis and some loss of β-sheet contacts were observed in both native and oxidized protofibrils. However, chain twisting was observed more frequently and at a higher degree in the oxidized protofibril compared to the native protofibril. β-Sheet loss is also more apparent in the oxidized protofibril. Analyses of the global conformational states of the native and oxidized protofibrils indicate that Met35 oxidation has a destabilizing effect on the highly ordered and compact protofibril structure. Compared to the native protofibril, the oxidized protofibril showed increased backbone Cα-RMSD and SASA. In addition, 8 out of 12 chains of the oxidized protofibril showed higher residue RMSF values compared to the native protofibril, indicating that many residues in the oxidized protofibril exhibit higher flexibility.
Further analysis of the specific interactions that stabilize the extended-β-sheet protofibril conformation shows that although the oxidized protofibril contains fewer inter-chain H-bonds and β-sheets, the intra-chain salt bridges and intra-chain H-bonds that stabilize the U shape of each peptide and the inter-chain salt bridges stabilize the stacking of the peptides in each of the hexamers were largely unperturbed. Met35 photo-oxidation thus did not exhibit a significant destabilizing effect in the U shape of the peptides or the stacking of the peptides in the hexamers. It did, however, disrupt the hydrophobic interactions between the two hexamers as the Met35ox–Met35ox distances are larger for the interior, most hydrophobic, chains compared to Met35–Met35 distances. This finding is also consistent with increases in SASA values of the oxidized protofibril.
The MD simulation results from this study thus indicate that the oxidation of Met35 caused partial destabilization to the overall conformation of the protofibril. Specifically, Met35 oxidation that resulted in the addition of a hydrophilic oxygen disrupted the hydrophobic interface that stabilizes the stacking of the two hexamers. The oxidized protofibril is more solvent exposed and has more backbone flexibility but retained the underlying U-shaped structure of each peptide. Although more twisting of the peptides along the protofibril axis was observed, the stacking of the peptides in the hexamers remained with Met35 oxidation. Our simulation results are consistent with experimental observations that photo-oxidation of Aβ40 fibril results in the dis-agglomeration and fragmentation of Aβ fibrils but did not cause complete disruption of the fibrillar morphology or β-sheets.45 We note, however, that photosensitized oxidation also leads to the oxygenation of two histidine residues (His13 and His14) and their effects are not included in this computational study. The addition of hydrophilic oxygens to the imidazole ring of histidine can also disrupt their hydrophobic interactions and contribute to fibril destabilization. Also, the 2LMN dodecamer structure lacks eight N-terminal residues. In a first resolved fibril structure that contains the N-terminal residues, Söldner and coworkers found in an MD study that these residues had a clear stabilizing effect where Arg5, Asp7, and Ser8 formed interfilament contacts that stabilized a threefold symmetric fibril structure derived from patients.90 Future studies that include oxidized His residues and full-length peptides will further resolve the effects of photo-oxidation on fibril stability. To capture possible large-range structural changes, longer simulation times, perhaps coupled with course-graining or enhanced sampling methods, can also be performed in the future.
The partial destabilization of preformed Aβ fibrils observed in our photo-oxidation study differs from that where Aβ fibrils were oxidized by chemical oxidants (e.g., oxidation of Aβ1–42 fibrils by H2O2 that caused remodeling of the fibrillar morphology to irregularly shaped rope-like structures and globules91) or where Aβ fibrils are destabilized by the binding of ligands (e.g., caffeine, brazilin, a resveratrol derivative, and wine-related polyphenols that completely disaggregated pre-formed Aβ fibrils into disordered monomers in vitro92−94). Consistent with experimental results, MD simulation of the binding of caffeine to an Aβ17–42 pentamer showed destabilization of the pentamer conformation and loss of H-bonds and β-sheet structures as well as salt bridges.57 A recent MD simulation study examined the effects of oxidation of five different residues (Met35, Phe19, Ph20, Lys16, Lys28) on the stability of an Aβ11–42 pentamer via umbrella sampling.56 This particular oxidation pattern was experimentally achieved by a pulsed radio-frequency cold atmospheric plasma jet that caused the complete disintegration of Aβ1–42 fibrils.56 The high level of oxidation was found in the simulation study to disrupt salt bridges and cause significant disturbance to the pentamer structure.56 This simulation study also showed that a low and moderate degree of oxidation (one (Met35) or three (Met35, Phe19, and Phe20) oxidized amino acids) had insignificant impact on the pentamer conformation and did not disrupt salt bridges, which is consistent with our findings in this study.
Conclusions
We studied the effects of Met35 oxidation on the conformation and stability of a Aβ9–40 protofibril, employing all-atom MD simulations for up to 1 μs. The results demonstrate that the oxidation of Met35 caused some destabilization to the overall conformation of the β-sheet-rich protofibril, as evidenced in increases in RMSD, SASA, and RMSF values. The oxidized protofibril is thus more solvent exposed and has more backbone flexibility, which may be contributed by the destabilization of the hydrophobic interface that stabilize the stacking of two hexamers in the protofibril as evidenced by increased methionine–methionine distances in the oxidized protofibril. However, Met35 oxidation did not significantly perturb the intra- and inter-chain salt bridges that stabilize the U-shaped conformation adopted by each chain or the stacking of the peptides that form each of the hexamers. These simulation results are consistent with experimental findings that photo-oxidation caused partial destabilization of Aβ40 fibrils and did not completely disrupt the conformation and underlying secondary structures of the Aβ aggregate. This is in contrast with oxidation caused by chemical oxidants or strong oxidizing sources such as cold atmospheric plasma. This computational study thus provides molecular level insights into the partial perturbations of Aβ40 aggregates by photosensitizer-induced oxidation. Combined with in vivo studies that demonstrated the efficacy of PDT in lowering aggregate levels and reducing neurotoxicity of Aβ aggregates in AD animal models, this investigation contributes to our future development of photo-active platforms for treating protein misfolding diseases such as AD.
Acknowledgments
The Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant ACI-1053575, was used for performing simulations.
Glossary
Abbreviations
- Aβ
amyloid β
- AD
Alzheimer’s disease
- MD
molecular dynamics
- PDT
photodynamic therapy
- ROS
reactive oxygen species
- NMR
nuclear magnetic resonance
- His
histidine
- Tyr
tyrosine
- Met
methionine
- PDB
Protein Data Bank
- NVT
isothermal ensemble
- NPT
isobaric ensemble
- LINCS
A Linear Constraint Solver for Molecular Simulations
- PME
particle mesh Ewald
- RMSD
root mean square deviation
- RMSF
root mean square fluctuation
- Rg
radius of gyration
- SASA
solvent-accessible surface area
- DSSP
Dictionary of Secondary Structure of Protein
- XSEDE
Extreme Science and Engineering Discovery Environment
Supporting Information Available
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.2c07468.
(Table S1) Secondary structures (% residues), with associated standard deviations, for the native and oxidized Aβ protofibrils obtained from the last 50 ns (2500 frames) of trajectories; (Figure S1) snapshots of native and oxidized Aβ protofibrils from three 300 ns simulation trajectories; (Figure S2) principal component analysis (PCA) results obtained for the native and oxidized Aβ protofibrils from the last 50 ns (2500 frames) of the three 300 ns simulations; (Figure S3) principal component analysis (PCA) results obtained for the native and oxidized Aβ protofibrils from the last 50 ns (2500 frames) of the 1 μs simulations; (Figure S4) RMSF plots of different Aβ chains of the protofibrils; (Figure S5) distances between Met35 and Met35 and between Met35ox and Met35ox residues of six opposing Aβ chain pairs in the protofibrils; (Figure S6) profiles of the intra-chain Asp23–Lys28 (D23–K28) salt bridge distances of Aβ chain in the native and oxidized protofibrils for the 1 μs simulations; (Figure S7) distances of inter-peptide salt bridges formed by Asp23 and Lys28 (D23-K28) on adjacent Aβ peptides for native and oxidized protofibrils for the 1 μs simulations; (Figure S8) total number of inter-chain hydrogen bonds in the native protofibril and the Met35 oxidized protofibrils. Figure S9. The number of intra-chain hydrogen bonds in the native protofibril and the Met35-oxidized protofibrils; (Figure S10) secondary structure plots of native and oxidized Aβ protofibrils for the three 300 ns simulations; (Figure S11) matrix of smallest distance between each pair of amino acids in native (A and C) and Met35 oxidized (C and D) protofibrils over the 1 μs for the last 50 ns of simulations (PDF)
Author Contributions
F.M., T.D.M., and E.Y.C designed the research; F.M. performed research and analyzed results; F.M and E.Y.C wrote the paper.
This research was funded by the National Science Foundation (NSF) Awards 1605225 and 1207362, and the National Institute of Health (NIH) Award 1R21NS111267-01 to E.Y.C. We would also like to acknowledge generous gifts from the Huning family and others from the State of New Mexico.
The authors declare no competing financial interest.
Supplementary Material
References
- O’Brien R. J.; Wong P. C. Amyloid Precursor Protein Processing and Alzheimer’s Disease. Annu. Rev. Neurosci. 2011, 34, 185–204. 10.1146/annurev-neuro-061010-113613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Murphy M. P.; Levine H. Alzheimer’s Disease and the Beta-Amyloid Peptide. J. Alzheimer’s Dis. 2010, 19, 311–323. 10.3233/JAD-2010-1221. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lesné S.; Koh M. T.; Kotilinek L.; Kayed R.; Glabe C. G.; Yang A.; Gallagher M.; Ashe K. H. A Specific Amyloid-Beta Protein Assembly in the Brain Impairs Memory. Nature 2006, 440, 352–357. 10.1038/nature04533. [DOI] [PubMed] [Google Scholar]
- Hardy J.; Selkoe D. J. The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics. Science 2002, 297, 353–356. 10.1126/science.1072994. [DOI] [PubMed] [Google Scholar]
- Karran E.; Mercken M.; De Strooper B. The Amyloid Cascade Hypothesis for Alzheimer’s Disease: An Appraisal for the Development of Therapeutics. Nat. Rev. Drug. Discovery 2011, 10, 698–712. 10.1038/nrd3505. [DOI] [PubMed] [Google Scholar]
- Kayed R.; Head E.; Thompson J. L.; Mcintire T. M.; Milton S. C.; Cotman C. W.; Glabel C. G. Common Structure of Soluble Amyloid Oligomers Implies Common Mechanism of Pathogenesis. Science 2003, 300, 486–489. 10.1126/science.1079469. [DOI] [PubMed] [Google Scholar]
- Reitz C. Alzheimer’s Disease and the Amyloid Cascade Hypothesis: A Critical Review. Int. J. Alzheimers Dis. 2012, 2012, 1. 10.1155/2012/369808. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bloom G. S. Amyloid-β and Tau: The Trigger and Bullet in Alzheimer Disease Pathogenesis. JAMA Neurol. 2014, 71, 505–508. 10.1001/jamaneurol.2013.5847. [DOI] [PubMed] [Google Scholar]
- Sheng M.; Sabatini B. L.; Südhof T. C. Synapses and Alzheimer’s Disease. Cold Spring Harbor Perspect. Biol. 2012, 4, 1–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Parihar M. S.; Brewer G. J. Amyloid-β as a Modulator of Synaptic Plasticity. J. Alzheimer’s Dis. 2010, 22, 741–763. 10.3233/JAD-2010-101020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sachse C.; Fändrich M.; Grigorieff N. Paired β-Sheet Structure of an Aβ(1-40) Amyloid Fibril Revealed by Electron Microscopy. Proc. Natl. Acad. Sci. 2008, 105, 7462–7466. 10.1073/pnas.0712290105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chen G. F.; Xu T. H.; Yan Y.; Zhou Y. R.; Jiang Y.; Melcher K.; Xu H. E. Amyloid Beta: Structure, Biology and Structure-Based Therapeutic Development. Acta Pharmacol. Sin. 2017, 38, 1205–1235. 10.1038/aps.2017.28. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Meyer-Luehmann M.; Spires-Jones T. L.; Prada C.; Garcia-Alloza M.; De Calignon A.; Rozkalne A.; Koenigsknecht-Talboo J.; Holtzman D. M.; Bacskai B. J.; Hyman B. T. Rapid Appearance and Local Toxicity of Amyloid-β Plaques in a Mouse Model of Alzheimer’s Disease. Nature 2008, 451, 720–724. 10.1038/nature06616. [DOI] [PMC free article] [PubMed] [Google Scholar]
- He Z.; Guo J. L.; McBride J. D.; Narasimhan S.; Kim H.; Changolkar L.; Zhang B.; Gathagan R. J.; Yue C.; Dengler C.; Stieber A.; Nitla M.; Coulter D. A.; Abel T.; Brunden K. R.; Trojanowski J. Q.; Lee V. M. Y. Amyloid-β Plaques Enhance Alzheimer’s Brain Tau-Seeded Pathologies by Facilitating Neuritic Plaque Tau Aggregation. Nat. Med. 2018, 24, 29–38. 10.1038/nm.4443. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cushman M.; Johnson B. S.; King O. D.; Gitler A. D.; Shorter J. Prion-like Disorders: Blurring the Divide between Transmissibility and Infectivity. J. Cell Sci. 2010, 123, 1191–1201. 10.1242/jcs.051672. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Guo J. L.; Lee V. M. Y. Cell-to-Cell Transmission of Pathogenic Proteins in Neurodegenerative Diseases. Nat. Med. 2014, 20, 130–138. 10.1038/nm.3457. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kfoury N.; Holmes B. B.; Jiang H.; Holtzman D. M.; Diamond M. I. Trans-Cellular Propagation of Tau Aggregation by Fibrillar Species. J. Biol. Chem. 2012, 287, 19440–19451. 10.1074/jbc.M112.346072. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Taniguchi A.; Sasaki D.; Shiohara A.; Iwatsubo T.; Tomita T.; Sohma Y.; Kanai M. Attenuation of the Aggregation and Neurotoxicity of Amyloid-b Peptides by Catalytic Photooxygenation. Angew. Chem., Int. Ed. 2014, 53, 1382–1385. 10.1002/anie.201308001. [DOI] [PubMed] [Google Scholar]
- Li C.; Wang J.; Liu L. Alzheimer’s Therapeutic Strategy: Photoactive Platforms for Suppressing the Aggregation of Amyloid β Protein. Front. Chem. 2020, 8, 509. 10.3389/fchem.2020.00509. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Xu Y.; Xiao L. Efficient Suppression of Amyloid-β Peptide Aggregation and Cytotoxicity with Photosensitive Polymer Nanodots. J. Mater. Chem. B 2020, 8, 5776–5782. 10.1039/D0TB00302F. [DOI] [PubMed] [Google Scholar]
- Yang Y.; Tu J.; Yang D.; Raymond J. L.; Roy R. A.; Zhang D. Photo- and Sono-Dynamic Therapy: A Review of Mechanisms and Considerations for Pharmacological Agents Used in Therapy Incorporating Light and Sound. Curr. Pharm. Des. 2019, 25, 401–412. 10.2174/1381612825666190123114107. [DOI] [PubMed] [Google Scholar]
- Da Silva L. P.; Magalhães C. M.; Núñez-Montenegro A.; Ferreira P. J. O.; Duarte D.; Rodríguez-Borges J. E.; Vale N.; Esteves Da Silva J. C. G. Study of the Combination of Self-Activating Photodynamic Therapy and Chemotherapy for Cancer Treatment. Biomolecules 2019, 9, 384. 10.3390/biom9080384. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kessel D. Photodynamic Therapy: From the Beginning. Photodiagn. Photodyn. Ther. 2004, 1, 3–7. 10.1016/S1572-1000(04)00003-1. [DOI] [PubMed] [Google Scholar]
- Van Straten D.; Mashayekhi V.; de Bruijn H. S.; Oliveira S.; Robinson D. J. Oncologic Photodynamic Therapy: Basic Principles, Current Clinical Status and Future Directions. Cancers 2017, 9, 19. 10.3390/cancers9020019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Redza-Dutordoir M.; Averill-Bates D. A. Activation of Apoptosis Signalling Pathways by Reactive Oxygen Species. Biochim. Biophys. Acta, Mol. Cell Res. 2016, 1863, 2977–2992. 10.1016/j.bbamcr.2016.09.012. [DOI] [PubMed] [Google Scholar]
- Plaetzer K.; Kiesslich T.; Oberdanner C.; Krammer B. Apoptosis Following Photodynamic Tumor Therapy: Induction, Mechanisms and Detection. Curr. Pharm. Des. 2005, 11, 1151–1165. 10.2174/1381612053507648. [DOI] [PubMed] [Google Scholar]
- Lemasters J. J. Dying a Thousand Deaths: Redundant Pathways from Different Organelles to Apoptosis and Necrosis. Gastroenterology 2005, 129, 351–360. 10.1053/j.gastro.2005.06.006. [DOI] [PubMed] [Google Scholar]
- Sohma Y.; Sawazaki T.; Kanai M. Organic & Biomolecular Chemistry Chemical Catalyst-Promoted Photooxygenation of Amyloid Proteins. Org. Biomol. Chem. 2021, 19, 10017–10029. 10.1039/D1OB01677F. [DOI] [PubMed] [Google Scholar]
- Lee B. I.; Chung Y. J.; Park C. B. Photosensitizing Materials and Platforms for Light-Triggered Modulation of Alzheimer’s β-Amyloid Self-Assembly. Biomaterials 2019, 190-191, 121–132. 10.1016/J.BIOMATERIALS.2018.10.043. [DOI] [PubMed] [Google Scholar]
- Yu D.; Guan Y.; Bai F.; Du Z.; Gao N.; Ren J.; Qu X. Metal–Organic Frameworks Harness Cu Chelating and Photooxidation Against Amyloid β Aggregation in Vivo. Chem. – Eur. J. 2019, 25, 3489–3495. 10.1002/chem.201805835. [DOI] [PubMed] [Google Scholar]
- Li M.; Xu C.; Ren J.; Wang E.; Qu X. Photodegradation of β-Sheet Amyloid Fibrils Associated with Alzheimer’s Disease by Using Polyoxometalates as Photocatalysts. Chem. Commun. 2013, 49, 11394–11396. 10.1039/c3cc46772d. [DOI] [PubMed] [Google Scholar]
- Yue X.; Mei Y.; Zhang Y.; Tong Z.; Cui D.; Yang J.; Wang A.; Wang R.; Fei X.; Ai L.; et al. New Insight into Alzheimer’s Disease: Light Reverses Aβ-Obstructed Interstitial Fluid Flow and Ameliorates Memory Decline in APP/PS1 Mice. Alzheimer’s Dementia: Transl. Res. Clin. Interv. 2019, 5, 671–684. 10.1016/j.trci.2019.09.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Tardivo J. P.; Del Giglio A.; De Oliveira C. S.; Gabrielli D. S.; Junqueira H. C.; Tada D. B.; Severino D.; De Fátima Turchiello R.; Baptista M. S. Methylene Blue in Photodynamic Therapy: From Basic Mechanisms to Clinical Applications. Photodiagn. Photodyn. Ther. 2005, 24, 175–191. 10.1016/S1572-1000(05)00097-9. [DOI] [PubMed] [Google Scholar]
- Lee B. I.; Lee S.; Suh Y. S.; Lee J. S.; Kim A. K.; Kwon O. Y.; Yu K.; Park C. B. Photoexcited Porphyrins as a Strong Suppressor of β-Amyloid Aggregation and Synaptic Toxicity. Angew. Chem., Int. Ed. 2015, 127, 11634–11638. 10.1002/anie.201504310. [DOI] [PubMed] [Google Scholar]
- Mangione M. R.; Palumbo Piccionello A.; Marino C.; Ortore M. G.; Picone P.; Vilasi S.; Di Carlo M.; Buscemi S.; Bulone D.; San Biagio P. L. Photo-Inhibition of Aβ Fibrillation Mediated by a Newly Designed Fluorinated Oxadiazole. RSC Adv. 2015, 5, 16540–16548. 10.1039/C4RA13556C. [DOI] [Google Scholar]
- Lee J. S.; Lee B. I.; Park C. B. Photo-Induced Inhibition of Alzheimer’s β-Amyloid Aggregation Invitro by Rose Bengal. Biomaterials 2015, 38, 43–49. 10.1016/j.biomaterials.2014.10.058. [DOI] [PubMed] [Google Scholar]
- Kim K.; Lee S. H.; Choi D. S.; Park C. B. Alzheimer’s Disease: Photoactive Bismuth Vanadate Structure for Light-Triggered Dissociation of Alzheimer’s β-Amyloid Aggregates. Adv. Funct. Mater. 2018, 28, 1870298 10.1002/adfm.201870298. [DOI] [Google Scholar]
- Lee B. I.; Suh Y. S.; Chung Y. J.; Yu K.; Park C. B. Shedding Light on Alzheimer’s β-Amyloidosis: Photosensitized Methylene Blue Inhibits Self-Assembly of β-Amyloid Peptides and Disintegrates Their Aggregates. Sci. Rep. 2017, 7, 7523. 10.1038/s41598-017-07581-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Taniguchi A.; Shimizu Y.; Oisaki K.; Sohma Y.; Kanai M. Switchable Photooxygenation Catalysts That Sense Higher-Order Amyloid Structures. Nat. Chem. 2016, 8, 974–982. 10.1038/nchem.2550. [DOI] [PubMed] [Google Scholar]
- Nagashima N.; Ozawa S.; Furuta M.; Oi M.; Hori Y.; Tomita T.; Sohma Y.; Kanai M. Catalytic Photooxygenation Degrades Brain Aβ in Vivo. Sci. Adv. 2021, 7, eabc9750 10.1126/sciadv.abc9750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Du Z.; Gao N.; Wang X.; Ren J.; Qu X. Near-Infrared Switchable Fullerene-Based Synergy Therapy for Alzheimer’s Disease. Small 2018, 14, 1801852 10.1002/smll.201801852. [DOI] [PubMed] [Google Scholar]
- Dos Santos A. F.; De Almeida D. R. Q.; Terra L. F.; Baptista M. S.; Labriola L. Photodynamic Therapy in Cancer Treatment - an Update Review. J. Cancer Metastasis Treat. 2019, 2019, 25. 10.20517/2394-4722.2018.83. [DOI] [Google Scholar]
- Dolmans D. E. J. G. J.; Fukumura D.; Jain R. K. Photodynamic Therapy for Cancer. Nat. Rev. Cancer 2003, 3, 380–387. 10.1038/nrc1071. [DOI] [PubMed] [Google Scholar]
- Ni J.; Taniguchi A.; Ozawa S.; Hori Y.; Kuninobu Y.; Saito T.; Saido T. C.; Tomita T.; Sohma Y.; Kanai M. Near-Infrared Photoactivatable Oxygenation Catalysts of Amyloid Peptide. Chem 2018, 4, 807–820. 10.1016/j.chempr.2018.02.008. [DOI] [Google Scholar]
- Fanni A. M.; Okoye D.; Monge F. A.; Hammond J.; Maghsoodi F.; Martin T. D.; Brinkley G.; Phipps M. L.; Evans D. G.; Martinez J. S.; Whitten D. G.; Chi E. Y. Controlled and Selective Photo-Oxidation of Amyloid-β Fibrils by Oligomeric p -Phenylene Ethynylenes. ACS Appl. Mater. Interfaces 2022, 14, 14871–14886. 10.1021/acsami.1c22869. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Monge F.; Fanni A.; Jiang S.; Whitten D. G.; Bhaskar K.; Chi E. Y. Luminescent Molecular Sensors for the Selective Detection of Neurodegenerative Disease Protein Pathology in CSF. Biophys. J. 2019, 116, 146a–147a. 10.1016/j.bpj.2018.11.814. [DOI] [Google Scholar]
- Donabedian P. L.; Pham T. K.; Whitten D. G.; Chi E. Y. Oligo(p-Phenylene Ethynylene) Electrolytes: A Novel Molecular Scaffold for Optical Tracking of Amyloids. ACS. Chem. Neurosci. 2015, 6, 1526–1535. 10.1021/acschemneuro.5b00086. [DOI] [PubMed] [Google Scholar]
- Ahn M.; Lee B. I.; Chia S.; Habchi J.; Kumita J. R.; Vendruscolo M.; Dobson C. M.; Park C. B. Chemical and Mechanistic Analysis of Photodynamic Inhibition of Alzheimer’s β-Amyloid Aggregation. Chem. Commun. 2019, 55, 1152–1155. 10.1039/C8CC09288E. [DOI] [PubMed] [Google Scholar]
- Hou L.; Shao H.; Zhang Y.; Li H.; Menon N. K.; Neuhaus E. B.; Brewer J. M.; Byeon I. J. L.; Ray D. G.; Vitek M. P.; Iwashita T.; Makula R. A.; Przybyla A. B.; Zagorski M. G. Solution NMR Studies of the Aβ(1-40) and Aβ(1-42) Peptides Establish That the Met35 Oxidation State Affects the Mechanism of Amyloid Formation. J. Am. Chem. Soc. 2004, 126, 1992–2005. 10.1021/ja036813f. [DOI] [PubMed] [Google Scholar]
- Watson A. A.; Fairlie D. P.; Craik D. J. Solution Structure of Methionine-Oxidized Amyloid β-Peptide (1-40). Does Oxidation Affect Conformational Switching?. Biochemistry 1998, 37, 12700–12706. 10.1021/bi9810757. [DOI] [PubMed] [Google Scholar]
- Palmblad M.; Westlind-Danielsson A.; Bergquist J. Oxidation of Methionine 35 Attenuates Formation of Amyloid β-Peptide 1-40 Oligomers. J. Biol. Chem. 2002, 277, 19506–19510. 10.1074/jbc.M112218200. [DOI] [PubMed] [Google Scholar]
- Friedemann M.; Helk E.; Tiiman A.; Zovo K.; Palumaa P.; Tõugu V. Effect of Methionine-35 Oxidation on the Aggregation of Amyloid-β Peptide. Biochem. Biophys. Rep. 2015, 3, 94–99. 10.1016/j.bbrep.2015.07.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bitan G.; Tarus B.; Vollers S. S.; Lashuel H. A.; Condron M. M.; Straub J. E.; Teplow D. B. A Molecular Switch in Amyloid Assembly: Met35 and Amyloid β-Protein Oligomerization. J. Am. Chem. Soc. 2003, 125, 15359–15365. 10.1021/ja0349296. [DOI] [PubMed] [Google Scholar]
- Brown A. M.; Lemkul J. A.; Schaum N.; Bevan D. R. Simulations of Monomeric Amyloid β-Peptide (1-40) with Varying Solution Conditions and Oxidation State of Met35: Implications for Aggregation. Arch. Biochem. Biophys. 2014, 545, 44–52. 10.1016/j.abb.2014.01.002. [DOI] [PubMed] [Google Scholar]
- Bayliss D. L.; Walsh J. L.; Shama G.; Iza F.; Kong M. G. Reduction and Degradation of Amyloid Aggregates by a Pulsed Radio-Frequency Cold Atmospheric Plasma Jet. New J. Phys. 2009, 11, 115024 10.1088/1367-2630/11/11/115024. [DOI] [Google Scholar]
- Razzokov J.; Yusupov M.; Bogaerts A. Oxidation Destabilizes Toxic Amyloid Beta Peptide Aggregation. Sci. Rep. 2019, 9, 5476. 10.1038/s41598-019-41931-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gupta S.; Dasmahapatra A. K. Caffeine Destabilizes Preformed Aβ Protofilaments: Insights from All Atom Molecular Dynamics Simulations. Phys. Chem. Chem. Phys. 2019, 21, 22067–22080. 10.1039/C9CP04162A. [DOI] [PubMed] [Google Scholar]
- Nie R. Z.; Cai S.; Yu B.; Fan W. Y.; Li H. H.; Tang S. W.; Huo Y. Q. Molecular Insights into the Very Early Steps of Aβ1-42 Pentameric Protofibril Disassembly by PGG: A Molecular Dynamics Simulation Study. J. Mol. Liq. 2022, 361, 119638 10.1016/j.molliq.2022.119638. [DOI] [Google Scholar]
- Singh K.; Kaur A.; Goyal D.; Goyal B. Mechanistic Insights into the Mitigation of Aβ Aggregation and Protofibril Destabilization by a D-Enantiomeric Decapeptide Rk10. Phys. Chem. Chem. Phys. 2022, 24, 21975–21994. 10.1039/D2CP02601E. [DOI] [PubMed] [Google Scholar]
- Gao D.; Wan J.; Zou Y.; Gong Y.; Dong X.; Xu Z.; Tang J.; Wei G.; Zhang Q. The Destructive Mechanism of Aβ1–42 Protofibrils by Norepinephrine Revealed via Molecular Dynamics Simulations. Phys. Chem. Chem. Phys. 2022, 24, 19827–19836. 10.1039/D2CP01754G. [DOI] [PubMed] [Google Scholar]
- Wang Q.; Wang Y.; Lu H. P. Revealing the Secondary Structural Changes of Amyloid β Peptide by Probing the Spectral Fingerprint Characters. J. Raman. Spectrosc. 2013, 44, 670–674. 10.1002/jrs.4253. [DOI] [Google Scholar]
- Simmons L. K.; May P. C.; Tomaselli K. J.; Rydel R. E.; Fuson K. S.; Brigham E. F.; Wright S.; Lieberburg I.; Becker G. W.; Brems D. N. Secondary Structure of Amyloid β Peptide Correlates with Neurotoxic Activity in Vitro. Mol. Pharmacol. 1994, 45, 373–379. [PubMed] [Google Scholar]
- Bitan G.; Vollers S. S.; Teplow D. B. Elucidation of Primary Structure Elements Controlling Early Amyloid β-Protein Oligomerization. J. Biol. Chem. 2003, 278, 34882–34889. 10.1074/jbc.M300825200. [DOI] [PubMed] [Google Scholar]
- Bitan G.; Kirkitadze M. D.; Lomakin A.; Vollers S. S.; Benedek G. B.; Teplow D. B. Amyloid β-Protein (Aβ) Assembly: Aβ40 and Aβ42 Oligomerize through Distinct Pathways. Proc. Natl. Acad Sci. 2003, 100, 330–335. 10.1073/pnas.222681699. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Paravastu A. K.; Leapman R. D.; Yau W.-M.; Tycko R. Molecular Structural Basis for Polymorphism in Alzheimer’s β-Amyloid Fibrils. Proc. Natl. Acad. Sci. 2008, 105, 18349–18354. 10.1073/pnas.0806270105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zoete V.; Cuendet M. A.; Grosdidier A.; Michielin O. SwissParam: A Fast Force Field Generation Tool for Small Organic Molecules. J. Comput. Chem. 2011, 32, 2359–2368. 10.1002/jcc.21816. [DOI] [PubMed] [Google Scholar]
- Abraham M. J.; Murtola T.; Schulz R.; Páll S.; Smith J. C.; Hess B.; Lindah E. Gromacs: High Performance Molecular Simulations through Multi-Level Parallelism from Laptops to Supercomputers. SoftwareX 2015, 1-2, 19–25. 10.1016/j.softx.2015.06.001. [DOI] [Google Scholar]
- Best R. B.; Zhu X.; Shim J.; Lopes P. E. M.; Mittal J.; Feig M.; MacKerell A. D. Jr. Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone φ, ψ and Side-Chain Χ1 and Χ2 Dihedral Angles. J. Chem. Theory Comput. 2012, 8, 3257–3273. 10.1021/ct300400x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Huang J.; Rauscher S.; Nawrocki G.; Ran T.; Feig M.; de Groot B. L.; Grubmüller H.; MacKerell A. D. Jr. CHARMM36m: An Improved Force Field for Folded and Intrinsically Disordered Proteins. Nat. Methods 2017, 14, 71–73. 10.1038/nmeth.4067. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hess B.; Bekker H.; Berendsen H. J. C.; Fraaije J. G. E. M.. LINCS: A Linear Constraint Solver for Molecular Simulations. J. Comput. Chem. 1997, 1463, . [DOI] [Google Scholar]
- Darden T.; York D.; Pedersen L. Particle Mesh Ewald: An N·log(N) Method for Ewald Sums in Large Systems. J. Chem. Phys. 1993, 98, 10089–10092. 10.1063/1.464397. [DOI] [Google Scholar]
- 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. J. Chem. Phys. 1984, 81, 3684–3690. 10.1063/1.448118. [DOI] [Google Scholar]
- Nosé S.; Klein M. L. Constant Pressure Molecular Dynamics for Molecular Systems. Mol. Phys. 1983, 50, 1055–1076. 10.1080/00268978300102851. [DOI] [Google Scholar]
- Pettersen E. F.; Goddard T. D.; Huang C. C.; Couch G. S.; Greenblatt D. M.; Meng E. C.; Ferrin T. E. UCSF Chimera - A Visualization System for Exploratory Research and Analysis. J. Comput. Chem. 2004, 25, 1605–1612. 10.1002/jcc.20084. [DOI] [PubMed] [Google Scholar]
- Towns J.; Cockerill T.; Dahan M.; Foster I.; Gaither K.; Grimshaw A.; Hazlewood V.; Lathrop S.; Lifka D.; Peterson G. D.; Roskies R.; Scott J. R.; Wilkens-Diehr N. XSEDE: Accelerating Scientific Discovery. Comput. Sci. Eng. 2014, 16, 62–74. 10.1109/MCSE.2014.80. [DOI] [Google Scholar]
- Kabsch W.; Sander C. Dictionary of Protein Secondary Structure: Pattern Recognition of Hydrogen-bonded and Geometrical Features. Biopolymers 1983, 22, 2577–2637. 10.1002/bip.360221211. [DOI] [PubMed] [Google Scholar]
- Berhanu W. M.; Hansmann U. H. E. Structure and Dynamics of Amyloid-β Segmental Polymorphisms. PLoS One 2012, 7, e41479 10.1371/journal.pone.0041479. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kendrick B. S.; Carpenter J. F.; Cleland J. L.; Randolph T. W. A Transient Expansion of the Native State Precedes Aggregation of Recombinant Human Interferon-γ. Proc. Natl. Acad. Sci. 1998, 95, 14142–14146. 10.1073/pnas.95.24.14142. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Stroud J. C.; Liu C.; Teng P. K.; Eisenberg D. Toxic Fibrillar Oligomers of Amyloid-β Have Cross-β Structure. Proc. Natl. Acad. Sci. 2012, 109, 7717–7722. 10.1073/pnas.1203193109. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kahler A.; Sticht H.; Horn A. H. C. Conformational Stability of Fibrillar Amyloid-Beta Oligomers via Protofilament Pair Formation - A Systematic Computational Study. PLoS One 2013, 8, e70521 10.1371/journal.pone.0070521. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sato T.; Kienlen-Campard P.; Ahmed M.; Liu W.; Li H.; Elliott J. I.; Aimoto S.; Constantinescu S. N.; Octave J.-N.; Smith S. O. Inhibitors of Amyloid Toxicity Based on Beta-Sheet Packing of Abeta40 and Abeta42. Biochemistry 2006, 45, 5503–5516. 10.1021/bi052485f. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zheng J.; Jang H.; Ma B.; Tsai C. J.; Nussinov R. Modeling the Alzheimer Aβ17-42 Fibril Architecture: Tight Intermolecular Sheet-Sheet Association and Intramolecular Hydrated Cavities. Biophys. J. 2007, 93, 3046–3057. 10.1529/biophysj.107.110700. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Liu F. F.; Liu Z.; Bai S.; Dong X. Y.; Suna Y. Exploring the Inter-Molecular Interactions in Amyloid-β Protofibril with Molecular Dynamics Simulations and Molecular Mechanics Poisson-Boltzmann Surface Area Free Energy Calculations. J. Chem. Phys. 2012, 136, 04B610. [DOI] [PubMed] [Google Scholar]
- Sunde M.; Serpell L. C.; Bartlam M.; Fraser P. E.; Pepys M. B.; Blake C. C. F. Common Core Structure of Amyloid Fibrils by Synchrotron X-Ray Diffraction. J. Mol. Biol. 1997, 273, 729–739. 10.1006/jmbi.1997.1348. [DOI] [PubMed] [Google Scholar]
- Brogi S.; Butini S.; Maramai S.; Colombo R.; Verga L.; Lanni C.; De Lorenzi E.; Lamponi S.; Andreassi M.; Bartolini M.; et al. Disease-Modifying Anti-Alzheimer’s Drugs: Inhibitors of Human Cholinesterases Interfering with β-Amyloid Aggregation. CNS. Neurosci. Ther. 2014, 20, 624–632. 10.1111/cns.12290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Boyle A. L.; Woolfson D. N. De Novo Designed Peptides for Biological Applications. Chem. Soc. Rev. 2011, 40, 4295–4306. 10.1039/c0cs00152j. [DOI] [PubMed] [Google Scholar]
- Ranganathan S.; Gribskov M.; Nakai K.; Schönbach C.. Encyclopedia of Bioinformatics and Computational Biology: ABC of bioinformatic, Academic Press: Elsevier, 2018; pp. 661–676. [Google Scholar]
- Thapa A.; Jett S. D.; Chi E. Y. Curcumin Attenuates Amyloid-β Aggregate Toxicity and Modulates Amyloid-β Aggregation Pathway. ACS Chem. Neurosci. 2016, 7, 56–68. 10.1021/acschemneuro.5b00214. [DOI] [PubMed] [Google Scholar]
- Reiss A. B.; Arain H. A.; Stecker M. M.; Siegart N. M.; Kasselman L. J. Amyloid Toxicity in Alzheimer’s Disease. Rev. Neurosci. 2018, 29, 6130–6627. 10.1515/revneuro-2017-0063. [DOI] [PubMed] [Google Scholar]
- Söldner C. A.; Sticht H.; Horn A. H. C. Role of the N-Terminus for the Stability of an Amyloid-β Fibril with Three-Fold Symmetry. PLoS One 2017, 12, e0186347 10.1371/journal.pone.0186347. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hou L.; Lee H. G.; Han F.; Tedesco J. M.; Perry G.; Smith M. A.; Zagorski M. G. Modification of Amyloid-Β1-42 Fibril Structure by Methionine-35 Oxidation. J. Alzheimer’s Dis. 2013, 37, 9–18. 10.3233/JAD-122389. [DOI] [PubMed] [Google Scholar]
- Mao F.; Yan J.; Li J.; Jia X.; Miao H.; Sun Y.; Huang L.; Li X. New Multi-Target-Directed Small Molecules against Alzheimer’s Disease: A Combination of Resveratrol and Clioquinol. Org. Biomol. Chem. 2014, 12, 5936–5944. 10.1039/C4OB00998C. [DOI] [PubMed] [Google Scholar]
- Du W. J.; Guo J. J.; Gao M. T.; Hu S. Q.; Dong X. Y.; Han Y. F.; Liu F. F.; Jiang S.; Sun Y. Brazilin Inhibits Amyloid β-Protein Fibrillogenesis, Remodels Amyloid Fibrils and Reduces Amyloid Cytotoxicity. Sci. Rep. 2015, 5, 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ono K.; Yoshiike Y.; Takashima A.; Hasegawa K.; Naiki H.; Yamada M. Potent Anti-Amyloidogenic and Fibril-Destabilizing Effects of Polyphenols in Vitro: Implications for the Prevention and Therapeutics of Alzheimer’s Disease. J. Neurochem. 2003, 87, 172–181. 10.1046/j.1471-4159.2003.01976.x. [DOI] [PubMed] [Google Scholar]
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