Structural Interconversion in Alzheimer's Amyloid-Î²(16â35) - American

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Structural Interconversion in Alzheimer’s Amyloid-#(16-35) Peptide in an Aqueous Solution Nelson Alves, and Rafael B. Frigori J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.7b12528 • Publication Date (Web): 19 Jan 2018 Downloaded from http://pubs.acs.org on January 20, 2018

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The Journal of Physical Chemistry

Structural Interconversion in Alzheimer’s Amyloid-β(16-35) Peptide in an Aqueous Solution Nelson A. Alves∗,† and Rafael B. Frigori∗,‡ †Departamento de Física, FFCLRP, Universidade de São Paulo, Avenida Bandeirantes, 3900. Ribeirão Preto 14040-901, SP, Brazil. ‡Universidade Tecnológica Federal do Paraná, Rua Cristo Rei 19, Toledo 85902-490, PR, Brazil E-mail: [email protected]; [email protected]

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Abstract Structural properties of Aβ(16-35) fragment are investigated as a model for the amyloidβ peptide excluding its coil-inducing terminals. Our Replica-Exchange Molecular Dynamics simulations using all-atoms and explicit aqueous solvation widely reduce any structural bias. The principal folding pathway shows direct conversion of coil to β-sheet, without the long proposed helix intermediates. Our PCA analysis indicates that the fragment is also intrinsically disordered, as the full amyloid-β peptide. Thus, the observed folding mechanism lacks freeenergy barriers and any peaks in the thermal capacity.

INTRODUCTION Under suitable physiological conditions many polypeptide chains have been observed to misfold, and then form deposits of aggregated amyloids. The phenomena involves the early emergence of protofibrils that subsequently produce insoluble fibrillar structures, strongly associated to important neurodegenerative proteinopathies, such as Alzheimer (AD) and Parkinson (PD). 1 Therefore, understanding the conformational evolution experienced by those proteins is crucial to unveil the molecular mechanisms triggering fibrillization, as in the amyloid-β (Aβ), typical of AD settings. 2 Strikingly enough, most of proteins involved in neurodegenerative disorders may be characterized by the occurrence of unstructured regions. These so-called intrinsically disordered proteins (IDP) present ensembles with extended/collapsed disordered folds, molten globules or semiordered folds. 3–5 Such low-level of well structured folds indicates that IDP interconvert among transiently ordered (metastable) structural states at a faster rate than the unfolding time-scale transitions of ordered proteins. 6 From a thermodynamical perspective, this indicates the absence of free-energy barriers of folding, 7 which facilitates molecular excursions into biologically deleterious configurations. Considering the Aβ peptides, it has been experimentally observed by spectroscopic techniques such as circular dichroism and solution NMR the presence of α-helical structures during the transient step from Aβ monomers towards the fibril formation. 8–11 Thus, a pathway from a random coil 2


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to β-sheet in Aβ monomers is likely to be mediated by the formation of those transitory α-helices. It has been speculated that this conformational transition is a prerequisite to form an ensemble of monomeric species that self-assembly into soluble oligomers, which after a lag time give rise to β-sheet-rich amyloid structures. 2,9 However, NMR studies of Aβ(1-40) and Aβ(10-35)-NH2 in water do not show α-helical or β-sheet conformations but mostly coil structures, 12 contrary to the results presented in, 10 where it is emphasized that helix formation is a key step for fibrillogenesis. As a matter of fact, the collected experimental results provide evidence that α-helix is strongly solvent and pH dependent. The environmental role has also been corroborated computationally. For instance, in 13 a replica-exchange molecular dynamics (REMD) was carried out with the Charmm22 force field and Born implicit solvation for Aβ(1-28) and Aβ(10-42) fragments. It was observed a remarkable pH dependence on helix propensities of some residues. In particular, despite of the well known weakness of implicit solvation when dealing to salt bridge formation, it was confirmed the destabilization of helices by such interaction between residues E22 and K28. Besides that, the appearing of a β-turn in the central loop marked by residues 24-26 is facilitated as pH is raised from 2 to 4. Notably, at pH 6 those peptides show the lowest helix propensity but present high exposition to the solvent, so being able to form β-sheet elements. Another study of conformational changes on fragment Aβ(10-35) was performed by REMD with all-atom OPLS force field but using explicit TIP3P water model. 14 The analysis at 280 K produced configurational prevalences as random coil conformations (58%), β-turns (8%), bends (31%), and a minor percentage of helices and β-strands (3%). Furthermore, the most frequent longrange contacts defined for distances larger than 3 residues was the salt bridge between residues D23 and K28, followed by the salt bridge involving the residues E22 and K28. The importance of the residues E22 and K28 in enhancing fibril rate formation has been highlighted with the congener Aβ(1-40)[D23-K28] model, which restricts its side chains by a lactam bridge. 15 Experimental results showed that this peptide folds 1000 times faster than its wild type Aβ(1-40). In the same vein, the lactam congener Aβ(10-35)-lactam[D23-K28] and

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Aβ(10-35)[D23-K28] with its side chains constrained harmonically, were investigated using CHARMM22 and the TIP3P model for water at 300 K. 16 OPLS force field was also used to study the Aβ(1035)-lactam[D23-K28] model. It resulted that the E22-K28 salt bridge is unstable, once charged residues in D23-K28 remain solvated. Thus, such faster aggregation rates are mostly induced by entropic restrictions present in the monomer due to the constraints on the salt bridge, which enhances the formation of the bend motif. Furthermore, it was stablished in 17 the key role of the water molecules in solvating charges and therefore, enabling hydrogen bond formation. As a consequence, it prevents formation of the D23-K28 salt bridge in the Aβ(10-35) monomer, which results in large structural fluctuations. Nonetheless, proteins generally present considerable helical content, but the stability of those α-helices seems to depend also on the length of such domains. 18 In particular, the PDB structure of Aβ(1-42) shows two helical regions along residues 8-25 and 28-38, connected by a β-turn, while this helical element is restricted to residues 14-24 and 32-35 in Aβ(1-40). Given that full Aβ peptides quickly aggregate in vitro, it might be more convenient to analyze less aggregation-prone fragments as Aβ(16-35) to study the formation of helix and β-sheet and its interconversion. This peptide fragment still contains the main features of full Aβ peptides, namely the central hydrophobic cluster comprised by residues 17-21, the 25-29 segment around which the turn-like motif is observed in fibrils, and part of the second hydrophobic segment with residues 30-35. Although the Aβ(16-35) fragment has not been the focus of any comprehensive experimental study, a coarse-grained REMD simulation 19 using OPEP potential has gathered thermodynamic and structural information about its folding and homodimerization. This fragment presented a melting temperature Tm at 304 K, with the highest β-sheet content at 293 K. But even below Tm the monomers have not shown a remarkable prevalence of any particular secondary structures. More specifically, at 293 K it was found very small percentage of β-sheet (8%), and α-helix (0.4%) structures, while turns (58%) and coils (27%) correspond to the most frequent conformations. The α-helices were identified in the region E22-N27. Interestingly, the simulation found a decreasing

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frequency of salt bridge contacts above Tm . In the present study we explore the temporal persistence of α-helices without the influence of the unstructured peptidic region at the N-terminal characterized mainly by the first 10 or 13 residues, which enforces coil-like structures. To this end, we performed large-scale REMD simulations of the Aβ(16-35) fragment with Charmm22* force field and explicit TIP4P/Ew solvation. Thus, we intended to avoid not only most systematics related to eventual over-simplified molecular modeling, but also algorithmic issues as energetic entrappings. As a result, helix-like structures although representing a small percentage of all secondary structures, increase slightly with temperature. Notwithstanding, despite β-sheet elements increase for temperatures up to 296K, their formation is not related to a secondary structure conversion of helix into β-sheet. Since in this protein model there is no decrease in the helix formation either along the MD trajectories or as a function of the temperature, the most probable structural transition happening among secondary elements is random coil to β-sheet. Those conclusions also follow from the analysis of the conformational persistence as a function of the temperature, including how it changes specific residue propensities in forming structural regions. A PCA study corroborates our findings concerning molecular stability, so establishing a scenario mostly dominated by fast structural interconversions. An structural analysis is also carried out concerning the formation of hydrogen-bonds and salt bridges in forming a stable turn involving residues 24-27.

MATERIAL AND METHODS All-atom model and TIP4P/Ew solvation We performed MD simulations with the GROMACS 5.1.4 software using REMD algorithm, once generalized ensemble techniques are known to better sample the free-energy landscape of Aβ fragments. 14,20 The peptide was described by the all-atom Charmm22* force field and solvated with explicit water molecules described by the TIP4P/Ew model. The motivation for choosing such solvent model is twofolded, as discussed below.

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In the one hand, it has been generally believed that a good solvent model for water should at least provide a robust description of that phase diagram, where fixed-points play a central experimentally verifiable role related to the solvation thermodynamic stability. In this vein, a comprehensive study by Vega et al. 21 have demonstrated that modern water models as SPC/E, TIP4P and TIP4P/Ew overestimate the experimental density of ice phases by just a few percent. However, while TIP3P, SPC/E and TIP4P respectively deviated by 80 K, 58 K and 40 K from the experimental melting temperature, the optimized TIP4P/Ew solvation considerably decreases that discrepancy up to 28 K. On the other hand, the aforesaid physical results imply on biological effects clearly observed even at physiological temperatures. For instance, it was verified in recent exhaustive simulations across different force fields and solvation models that intrinsically disordered proteins, as Aβ 22 and Amylin, 23 are better described by the Charmm22* force field when associated to TIP4P/Ew solvation. So far, such approach would improve physical results even when compared to state-ofthe-art implicit solvation models. 24 MD simulations As usual, the simulations were conducted using periodic boundary conditions in a dodecahedron box with border 1 nm and integration time step of 2 fs. The neighbor lists for the nonbonded interactions were updated every 30 fs during the simulation. The Lincs algorithm was used to constrain all bond lengths in the peptide. We employed the cutoff scheme with 1 nm for both electrostatic and van der Waals terms and the Particle Mesh Ewald method was used to treat the long-range electrostatic interactions. The temperature was maintained by coupling temperature to a bath using the modified Berendsen thermostat (V-rescale), while the pressure was kept with the Parrinello-Rahman algorithm with time constant τP = 2 at 1 bar. Figure 1 shows our starting conformation for MD simulations. It corresponds to the fragment 16-35 extracted from the Aβ(1-40) peptide with PDB code 1AML, which already contains an helical element. We highlight the hydrophobic core in green, and depict the residues D23 and K28 usually forming a salt bridge. After the energy-minimization with the steepest descent method, 6


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Figure 1: (Color online) Initial conformation for all replicas where it is drawn in dark green the hydrophobic segments L17-A21, and A30-M35. Lateral chains of D23 and K28 that usually form a salt bridge are also depicted. each replica of the neutral system was thermally equilibrated. We choose a set of 32 replicas whose temperatures are almost equally spaced, and it covers the physiologically functional range of Aβ’s from 239 K to 343 K. Furthermore, this set of temperatures produced a sequence of enthalpy histograms with substantial overlap in the energies between consecutive temperatures. The resulting statistics for data analysis was obtained from REMD simulations in the NPT ensemble during 500 ns for each replica, the first 50 ns on each time-series were discarded to ensure thermal equilibrium. Analyzes were performed with packages embedded in GROMACS 5.1.4 and using in-house Python scripts for running MDTraj. 25 The secondary structure content was identified along the MD trajectories by the DSSP program. 26

RESULTS AND DISCUSSION Secondary structure contents of Aβ(16-35) Our temperature-dependent structural analysis is summarized in Figure 2, whose panels show that coil structures are the most predominant elements in this simulation. Also bends and turns display considerable occupancy and slight temperature dependence. While helical elements as well as β-sheets appear in a very small percentage, it is noteworthy the small increase of 3- and αhelical elements as a function of temperature, and the decrease of β-sheet elements for temperatures higher than 296 K.

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To verify the propensity of each residue in forming secondary structure elements, we display in Figure 3 the residue-based distribution as a function of the residue index. The 3- and α-helices occur mainly in two regions, approximately described by the residue numbers 17-22 and 24-28. It worths to note that helices are also prevalent in the region 17-22 of Aβ(1-29) and Aβ(10-42). 13 Nevertheless, a second region 29-35 prone to show helical elements in Aβ(10-42) is shifted in our model to residues 24-28. Additionally, the occurrence of β-sheet elements is favored in the vicinity of the residues 18-20 and 29-33. The regions where helix and β-sheet occur in our simulation correspond to the hydrophobic cluster, but the observed percentage of these secondary structure elements is very low. 60 Coil

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Figure 2: (Color online) Percentage of all secondary structure elements identified by DSSP algorithm as a function of temperature. We also included the rare event 5-helix (π-helix) (green color).

Turns occur mainly around the residues 17-22 and 24-27, with probabilities in the range [0.2 - 0.6], while the coil structures are the major secondary elements. Therefore, the model produces conformations mainly classified as random coils, bends and turns showing slight dependence on the temperature. The principal structural interconversion pathway is found by seeking regions with high probability to form helix and β-sheet elements. Thus, we find the emergence of β-sheet along residues 29-33, which surprisingly is not a consequence of decreasing the helical elements. Actually, we 8


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Figure 3: (Color online) Secondary structure profiles for fragment 16-35 of the Aβ protein. The residues participants in each motif are depicted at 239 K, 265 K, 296 K and 339 K. Left panel: 3-helix, α-helix and random coil motifs. Right panel: β-bridges, β-sheets, bends, and turns. observe a significant decrease in the probability of forming random coils in that region as the temperature increases. Therefore, this model arguably presents a direct coil to β-sheet conversion, although this conversion produces a very small percentage of β-sheet structures, about 2.5% of all secondary structure content. In order to have a further dynamic understanding on the formation of these secondary elements, we display their temporal evolution in Figures 4 and 5, respectively for temperatures 239 K and 296 K. We restricted the composition of conformations to helical and β-sheet elements in those figures. Colors identify α-helix (black line), 3-helix (blue line), and β-sheet (red line). It is observed that β-sheet configuration appears only after the first 200 ns and 100 ns, respectively for the trajectories obtained at 239 K and 296 K. Then, it could be presumed that for longer simulations the content of β-sheet elements would be enhanced compared to helical segments, specially as the temperature increases. However, Figure 2 shows an opposite trend to the formation of β-sheets. To explain this peculiar trend of β-sheets, we present data panels in Figures 6 and 7, respectively for α-helix and β-sheet, obtained at 239 K, 296 K, and 339 K. Those figures compare how frequent are the α-helices (Figure 6) and β-sheets (Figure 7) elements along the time series. In contrast to α-helical elements, which tends to be more populated over the time series as the temperature increases, we note that the initial formation of β-sheet elements occur latter in time as compared to

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the formation of α-helical elements. The occurrence of β-sheet elements seem to start earlier and becomes more frequent as the temperature approaches 296 K, leading to the percentage in Figure 2. Therefore, the protein fragment clearly does not drive the formation of β-sheet elements at the expenses of α-helices. As a consequence, the expected α to β conformational transition is not observed. Actually, we did not observe any two-state like thermodynamic transition. This is corroborated by our calculation of thermal capacity CP , whose peaks were absent in the studied temperature range. In fact, the CP curve increases monotonically as the temperature decreases, and so it is likely that a maximum in CP may only occur in the glass phase. This contrasts to the result of a maximum in CP around 300 K presented in 19 for Aβ(16-35) modeled with a coarse-grained force field and GB implicit solvation.

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Figure 4: (Color online) Time-dependent formation of α-helix (black line), 3-helix (blue line), and β-sheet (red line) observed at every 0.2 ns at 239 K. Residues 16–35 were shifted to the range [1,20].

Principal Component Analysis A principal component analysis (PCA) was carried out to identify ensembles of similar structures along the MD trajectories. Results are seen in Figures (8) and (9), respectively obtained at 239 K and 296 K, which illustrate the structural clusterings projected onto a two-dimensional 10


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Figure 5: (Color online) Time-dependent formation of α-helix (black line), 3-helix (blue line), and β-sheet (red line) observed at every 0.2 ns at 296 K. Residues 16–35 were shifted to the range [1,20].

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Figure 6: (Color online) α-helix content at 239 K, 296 K, and 339 K, as a function of time with measurements at every 10 ps.

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Figure 7: (Color online) β-sheet content at 239 K, 296 K, and 339 K, as a function of time with measurements at every 10 ps. space. This evinced that conformations with structural similarities cannot be grouped into few and well separated clusters. Thus, the lack of dominant clusters demonstrates that a dynamic interconversion among secondary elements is happening along the trajectories. Representative conforma-

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tions labeled (I–IV) are associated to regions with lower free-energy, as measured by -log(counts) in kB T units. In particular, the typical conformations displayed in both figures mostly present random coils and turns, with minor content of 3- and α-helices. However, it is noteworthy that Figure (9) exhibits a small cluster (region I) whose conformations also contain β-sheet elements. In general, it is not observed high-density clusters, so corroborating further the low structural stability of such conformations.

Figure 8: (Color online) PCA component analysis from measurements obtained every 10 ps at 239 K. Right panel shows the representative structures for free-energy basins defined as -log(counts) in kB T units.

Figure 9: (Color online) PCA component analysis from measurements obtained every 10 ps at 296 K. Right panel shows the representative structures for free-energy basins defined as -log(counts) in kB T units. 12


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Hydrogen Bond and Salt Bridge Analysis To investigate the main interactions that keep turn-like and helical structures, we performed a structural analysis on all pairs of atoms that may form hydrogen bond (HB). This interaction is formed mainly in the short 3-helices. We considered that HB are formed according to the criteria dist(H...Acceptor) < 2.5 Å and angle > 1200 . The trajectory analysis at 239 K showed that HB is mostly formed between D23–S26 (42%), N27–A30 (29%), and I31–L34 (27%). Still significant is the formation of HB between S26–L28 (14%). The percentage means how often a contact accomplishes with the above criteria. Most of interactions are in the 24-27 region of the turn-like motif, which overlaps with the one related to helical motif. At the intermediate temperature 296 K, we observe the following probabilities for HB forming: N27–A30 (32%), D23–S26 (27%), I31– L34 (27%), and N27–I31 (13%). As aforesaid, the persistent HB contacts reveal that the structural motifs are weakly dependent on the temperature. Salt bridges, as the effective outcome from short-range hydrogen bonding and long-range Coulomb interactions, are mostly regarded to entropically stabilize unfavorable foldings. That has been particularly established by NMR studies of Aβ fibrils that the U-turn like structures are mediated by a salt bridge connecting residues D23-K28. 27,28 In our present analysis, a cutoff of 4Å between charged atoms define the formation of a salt bridge involving K28 with either E22 or D23 residues. Figure (10) displays the probabilities of forming a salt bridge as a function of temperature. It is clear that the conformations favored by salt bridges amounts to a small percentage. From a statistical perspective, the salt bridges populate the four basins of the PCA clusters (Fig. 8 and 9) with different prevalences. For instance, we defined a basin as a region inside an adimentional radius of 1.5 units around each PCA minimum. Thus, at 239 K the D23-K28 salt bridge mostly populates the region III, showing prevalences of 16.4% of all salt bridge conformations, while other regions are almost equally populated with ∼ 2%. Then, by increasing the temperature up to 296 K, we found that such salt bridge distribution shifts to the region II (3.1%), while other basins individually correspond up to ∼ 1%. Moreover, at 239 K the salt bridge E22-K28 13


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Figure 10: (Color online) Probabilities of salt bridge formation as a function of temperature. mostly populates the basin II (6.1%), while it is negligible elsewhere (∼ 0.3%). However, when the temperature is increased up to 296 K there is a shift to basins I (4.1%) and II (3.3%), while other regions are less favored (∼ 2%). Thus, salt bridge interactions are expected to rule the stabilization of the central turn involving the residues 24-27, but in our model they account only for 4% (D23-K28) and 7% (E22-K28) of all observed conformations. In fact, salt bridges were not predominant in any basin, revealing large conformational fluctuations.

CONCLUSIONS We performed an analysis of the possible helix to β-sheet conversion in a molecular model that contains the main features of the Alzheimer amyloid-β peptide, but excludes its unstructured termini. This led us to study the formation of secondary elements in Aβ’s by reducing the systematic effects induced by molecular disorder. We performed a 500 ns simulation combined with REMD technique using the accurate Charmm22* force field and TIP4P/Ew solvent to identify the dominant clusters of conformations. It was found that helix formation, including 3-helix and α-helix, continuously increases with temperature although representing a small percentage (∼ 6% at 296 K) of all secondary structures. Once there is no decreasing in the population of helix elements as random coils convert to β-sheets we exclude the presence of α-helical intermediate-states in the 14


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folding pathway of the Aβ(16-35) fragment. The PCA data analysis shows that conformations develop low stability regions as a consequence of frequent interconversion between different motifs. Such findings are corroborated from a thermodynamic perspective, given the monotonic behavior of CP as a function of the temperature, so indicating a folding mechanism lacking free-energy barriers or any peaks in the thermal capacity. Despite of many factors enhancing the formation of fibrils, it is emphasized in 16,29 that conformations in the monomeric stage with preformed salt bridges accelerate the fibril formation process, as also demonstrated by the model with a lactam bridge. Thus, this process would not require inter-peptide interactions for its fibril formation. By recalling that in fibril models with two-fold symmetry about the long fibril axis 27,28 the β-strand conformations are approximately formed in 12-24 and 30-40 regions, which are joined by a turn-like motif at residues 25-29, we argue that our model still possess the main ingredients for fibril formation, although in a very small percentage. Thus, strategies on designing aggregation inhibitors that aim to stabilize specific Aβ’s helical regions to counteract their supposed role on polymerization into toxic assemblies, 30 may not be fully appropriated.

Acknowledgement N.A.A was supported by the Brazilian agency FAPESP, process 16/04176-4. R.B.F. thanks DFFFCLRP/USP by warm hospitality during his sabbatical stay. Simulations were performed in the BlueGene/Q supercomputing facility at Rice University through USP-Rice collaboration.

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Figure 11: TOC Graphic

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Structural Interconversion in Alzheimer's Amyloid-Î²(16â35) - American

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