In silico investigation and targeting of amyloid β oligomers of different size
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PAPERDieter Willbold et al.Competitively selected protein ligands pay their increase in specificity by a decrease in affinity
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Structure and dynamics of Aβ-fibril models used as targets to investigate the effect of putative inhibitors at
different stages of Aβ−related disease
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In silico investigation and targeting of amyloid β
oligomers of different size
Ida Autiero,a Michele Savianob* and Emma Langellaa*
*Correspondence to: Michele Saviano, National Research Council, Institute of
Crystallography, 70126 Bari, Italy. E-mail: [email protected]. Emma Langella,
National Research Council, Institute of Biostructures and Bioimaging, 80138 Naples,
Italy. E-mail: [email protected]
a National Research Council, Institute of Biostructures and Bioimaging, 80138 Naples,
Italy
b National Research Council, Institute of Crystallography, 70126 Bari, Italy
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ABSTRACT
Aggregation of Amyloid β (Aβ) peptide into fibrils has been implicated in the
pathogenesis of Alzheimer's disease (AD). As a result, in recent years, substantial
efforts have been expended in the study of the mechanism of aggregation of the Aβ
peptide as well as of its inhibition by potential drug molecules. In this context, we have
built a model of the Aβ (17-42) deca-oligomer using the solid-state NMR (ssNMR)
structure of the Aβ (17-42) penta-oligomer as a reference. Both the penta- and deca-
oligomer systems have been studied by all-atom molecular dynamics (MD) simulations
and used as target systems for the investigation of the mechanism of action of a
trehalose-derived Aβ aggregation inhibitor. In the deca-oligomer all the main structural
features of the putative fibrillar state are retained. Moreover, the simulations reveal a
remarkable gain in stability as the oligomer grows. MD studies of the inhibitor in
complex with the penta- and deca-oligomers indicate a significant destabilization of
the structure beyond the hampering of the addition of successive Aβ peptides at the
ends of the fibril due to the presence of the inhibitor molecule. Our work provides an
easy and effective approach which could be useful for the in silico development of
potential drug molecules acting at different stages of the progression of Aβ–related
disease.
INTRODUCTION
Alzheimer's disease (AD) is currently one of the most common and devastating forms
of dementia correlated with β-amyloid peptides (Aβ) accumulation in human brain
tissue (1-3). These peptides are proteolytic byproducts of the Aβ protein precursor and
are most commonly composed of 40 (Aβ1-40) and 42 (Aβ1-42) amino acids (4-11). Aβ
peptides easily aggregate to form fibrils (12-14) which finally accumulate into plaques.
Important insights into the structural characteristics of (Aβ1-40) as well as Aβ(1–42)
fibrils have been determined, establishing that amyloid fibrils show a cross-β structure
(9) that contains parallel, in-register β-sheets (15-16). The Aβ(1–42) fragment is the
dominant Aβ species in the amyloid plaques of AD patients, and, compared with Aβ(1–
40), its neurological toxicity is stronger (17-20).
Preventing the deposition of Aβ plaques in brain tissue remains a viable approach to
treating this disorder. Thus, it is of fundamental importance to elucidate the
mechanism of nucleation of Aβ fibrils and increase the ability of small ligands to
interfere with plaque formation at the molecular level. However, recently, increasing
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evidence suggests that small soluble oligomers other than fibrils may be the primary
cause of synaptic dysfunction in AD (21,22). Thus, much effort has been invested in
studying the composition as well as the stability of the possible oligomeric states and
in the understanding of the amyloid fibril growth process and its modulation by
putative drug molecules through either experimental or computational studies (23-43).
Important explanations have derived from the solid state NMR structure of the
pentameric Aβ(17-42) oligomer as determined by Lhurs et al (16), which evince the
key roles behind the quaternary structure of the amyloid oligomers, although little is
still known about the structural features of the growing fibrils.
In this context, we modeled a decameric structure of the Aβ fibril composed of 10
peptides layers representing a successive step in the process of fibril growth compared
to the experimentally available structure of the Aβ(17-42) penta-oligomer (16). Here
we report the results of the pentameric as well as decameric system, subjected to a
full atomistic molecular dynamics simulation of 100 ns, alone and in complex with an
aggregate inhibitor proposed by De Bona et al. (44) to investigate if our models could
represent target systems for the design of new inhibitor compounds. Our work could
be useful for the development of new drugs able to act not only on the first phases of
the Aβ-correlated diseases, but also able to target the successive state of grown fibril.
METHODS
The solid state NMR structure obtained by Lührs et al (pdb entry 2BEG) has been used
for the pentameric system. The model of the decameric oligomer was built using two
consecutive modules of the pentameric structure. The two oligomeric systems were
subjected to 100ns molecular dynamics (MD) simulations with explicit waters.
MD simulations were performed and analysed using the GROMACS package program
and GROMOS43a1 force field (45-47). The Aβ oligomer and each Aβ-inhibitor complex
were solvated in a cubic box of simple point charge (SPC) water with at least 11 Å
distance to the border adding counter-ions to neutralize the system. Periodic boundary
conditions were employed and the LINCS algorithm (48) was used to constrain all bond
lengths. Simulations were run under NPT conditions, using Berendsen's coupling
algorithm (49) to retain the temperature and pressure constant (300 K with a P = 1
bar). Electrostatic interactions were handled by means of the particle mesh Ewald
method (PME) (50) whereas for the Lennard-Jones potential a non-bonded cutoff of 1.4
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nm was used. The systems were then gradually heated up to 300 K in a five-step
process, from 50K to 300 K, and then simulated under standard NPT conditions for 100
ns without restraints.
The CT ligand was built using the Insight BUILDER module (51) with the covalent
valence force field (CVFF), then minimized using a conjugate gradient algorithm (52).
The conformational space was sampled through simulated annealing with distance-
dependent dielectrics of 80, in order to mimic the aqueous environment. The ligand
energy was first minimized using the steepest-descent algorithm until the maximum
derivative was less than 0.001 kcal/A. Structures were thus heated in 1000 fs up to
1000 K for 1000 fs and 200 structures were chosen on the basis of energy and
geometric criteria. Then the CT best conformation was docked on both the systems
under investigation following the complementarity between the peptidic LPFFD
scaffold and the homologous sequence of Aβ(17-21) and leaving the sugar without
structural restraints. Subsequently, the CT ligand was parametrized using the PRODRG
server. Partial charges for the sugar portion were adjusted taking into account those
reported in reference (53). Finally, the obtained complexes were subjected to MD
simulations following the above described protocol, and subsequently both MD
ensembles have been clustered, following the algorithm described by Dura et al. (54)
with a cut-off of 0.2 nm. For the simulated complexes, the representative models of
the most populated clusters have been subjected to the MMPBSA (molecular
mechanics (MM) Poisson Boltzmann/Generalized Born surface area MM-GBSA) analysis
to obtain the relative binding free energy, using MMPBSA.py program of the AmberTool
suite. (55-56).
RESULTS AND DISCUSSION
Starting from the solid-state NMR structure of Aβ(17-42) as determined by Luhrs at al.
(16), which is formed by 5 peptide layers (or chains) in parallel in register β-sheets
packing and which is considered the repeat unit of the mature fibril, we created a
model of decameric oligomer of Aβ(17-42) amyloid (Fig 1). Following Luhr's
nomenclature, B1 refers to the residues from 18 to 26, B2 to those from 31 to 42, and
U-turn those from 27 to 30, where the turn region connects the two β-strands B1 and
B2 (Fig 1).
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The analysis of the root mean square (RMS) deviation (RMSD) computed for the
pentameric as well as for the decameric system during the whole simulations reveals
that the pentameric system is less stable with respect to the decameric one (Fig 2). In
greater detail, the extreme chains are less stable in terms of secondary structure,
RMSD and RMS fluctuation (RMSF) for both systems studied as shown in Figure 3. The
closeness of each layer was monitored by measuring the distance between the center
of mass (COM) of the F19 phenyl ring of each layer and the successive one. During the
simulation, the penta-oligomer displays a comparable trend to those shown by the
deca-oligomer. Indeed, in both systems only the last chain, chain 5 and chain 10
respectively, shows an increase of the distance from the previous chain, suggesting a
detachment from the rest of the system (Fig 4).
The pentameric NMR structure (16) is principally taken into its characteristic
arrangement by important hydrophobic interactions between B1 and B2, (mainly
between the residues F19 and G38, as well as A21 and V36) and by a fundamental salt
bridge involving D23 and K28 which connects the two strands B1 and B2. These key
interactions are kept into the same layer, as intra-layer contacts, and between
adjacent layers as inter-layer contacts. In order to evaluate the structural and dynamic
features of the studied systems, these key interactions have been analyzed over the
entire course of the simulations. The stabilizing hydrophobic intra-layer contacts F19-
G38 and A21-V36 are substantially retained in both simulated systems, apart from a
sporadic loss of the A21-V36 interaction in the decamer (Supplementary Figure
S1). In contrast, the inter-layer contacts are continually lost between the last two
chains in the pentamer in a more significant way then in the decamer (Fig 5). This
fact is mirrored by the decrease of the hydrophobic contact surface between the last
two chains of the pentameric system during the simulation, as shown Figure 6. The
inter-layer D23-K28 salt bridge is often lost between the last two chains in a
comparable way for the pentameric and the decameric systems (Supplementary
Figure S2). Thus, our simulations reveal that the smaller oligomer maintains the
intra-layer interactions but shows higher vulnerability for the inter-layer contacts.
These data suggest a modest detachment of each layer from the previous one, most
pronounced in the last chain, which is attenuated with oligomer growth as suggested
by the simulation of the decameric system. It is worth noting that the higher structural
stability of the decameric system with respect to the pentamer as suggested by the
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analysis of our results is in agreement with previous structural studies focusing on the
stability differences between Aβ(1-42) oligomers of different size (23, 34-37, 57).
It should be noted, that our model of deca-oligomer gives represents a step forward in
the process of fibril growth, along the direction of the fibril axis (longitudinal direction
of fibril growth). In recent years, by means of MD simulations, other models of
amyloid protofibrils have been studied, which mainly focused on the fibril growth by
lateral association (direction perpendicular to the fibril axis), evaluating different
possible association interfaces (58, 35-37). Even though a direct comparison with our
results is difficult due to the significantly different systems topologies, there is a
substantial agreement in predicting the higher instability of fibril ends and a key role
of the D23-K28 salt bridge as well as of hydrophobic interactions in stabilizing the
overall structure. Though our MD analysis provides insights into the structural stability
and conformational dynamics of Aβ (17-42) oligomeric models, we cannot make any
hypothesis on the mechanism of amyloid fibril elongation and further investigations
would be needed as reported in previous studies (40, 60-61).
Finally we evaluated the effect of an aggregate inhibitor on the two oligomeric
systems. To this end, an inhibitor, CT, proposed by De Bona et al. (44) has been
chosen, this is a trehalose derivative of the well known Soto’s peptide (LPFFD) (62).
This peptide retains high affinity toward the self-complementary LVFFA region of Aβ(17-
21) and was thought to block elongation by binding to the ends of the growing fibril.
So, the initial complex of inhibitor-amyloid oligomer was built following the original
idea of Soto and coworkers stated above by manually docking the peptide portion of
CT ligand to the 17-21 region of the first chain of the Aβ oligomers in a self
complementary manner, leaving the sugar portion free (Fig 7). The resulting
complexes of CT inhibitor with both the penta- and deca-oligomers were subjected to
100ns MD simulations without any positional restraint in order to avoid bias, allowing
the ligand to freely move and eventually go away from the system. Indeed, the ligand
significantly moves during the simulations, but it never detaches from the oligomers
neither from the starting binding site (Supplementary Figure S3).
The secondary structure of both systems is not affected in a very significant way by
the presence of the inhibitor, however, there is a not negligible increase of the
residues in coil structure simultaneously with a decrease of the residues in β-sheet and
bend structure, most pronounced for the penta-oligomeric system (Table 1). Moreover,
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the stability of the global structure is differently influenced by CT ligand binding: i) the
RMSD value over the evolution of the simulations increases due to the presence of the
ligand in both systems. Nonetheless, for the decameric system the RMSD gap is
constant and of only about 0.1 nm, while for the pentamer this growth becomes
significant at the end of the simulation, reaching a value of 0.5 nm, thus suggesting a
most important destabilization in the latter case (Fig 8). ii) The RMSF value in the
decameric system grows only for the chain interacting with the ligand, whereas all the
chains composing the pentameric oligomer show an increase in fluctuations when the
system interacts with the ligand, in a relevant and more remarkable manner for the
first chain (Fig 9). Therefore, our results underline a most pronounced destabilizing
effect due to the interaction with the inhibitor in the case of the pentameric oligomer.
In order to gain insights into the energetics of the two complexes, we have performed
binding free energy calculations using the MMPBSA method (55). The computed
energies for ligand binding to the penta- and the deca-oligomers are -16.6 kcal/mol
and -13.6 kcal/mol, respectively. These data clearly indicate that the ligand binding to
the fibril edge is energetically favorite. Although it cannot be excluded that other CT
binding sites along Aβ fibril exist, it should be noted that the binding to the amyloid
fibril edge is emerged as an important player into inhibition, also in recent MD studies
of two nonsteroidal anti-inflammatory drugs as well as of Congo red (41-43). In these
regards, a more comprehensive analysis of the inhibitor-oligomer interactions at the
atomic level is needed.
Table 1: Percentage of the residue showing the Coil, B-Sheet and Bend Secondary Structures during the last 50 ns of Molecular Dynamics simulations.
Secondary Structure
Pentamer
Pentamer-CT
Decamer
Decamer-CT
Coil (%) 26.7 28.1 20.0 21.0
B-Sheet (%) 63.1 62.9 71.7 70.6
Bend (%) 8.4 7.8 7.3 7.2
CONCLUSIONS
We have built a model of the deca-oligomer Aβ(17-42) which represents a step forward
in the process of fibril growth compared to the experimentally available structure of
the penta-oligomer (16). The structure and dynamics of both the penta- and the deca-
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oligomers of Aβ alone and in complex with an agglomerate inhibitor (44) have been
studied with MD simulations. Our simulations reveal that in the deca-oligomer all the
structural elements are well retained; moreover it is more stable compared to the
pentameric system in agreement with previous studies (23, 34, 35). Interestingly, MD
studies of the interaction between the inhibitor and the two systems indicate that the
inhibitor acts not only by hampering the addition of successive layers at the ends of
the oligomers but also by affecting the structure and stability of the oligomers. It is
worthy of note that the strategy we employed in our study could be fruitfully applied
to build models of the elongated Aβ fibril in order to study the effect of putative
inhibitors at different stages of Aβ−related disease.
ACKNOWLEDGEMENTS
The authors would like to give their special thanks to Dr. Giuseppe Pappalardo for his
help, support, interest and valuable hints. The technical assistance of Mr. Luca de Luca
and Mr. Giovanni Filograsso are gratefully acknowledged. This work was supported by
the M.I.U.R, Ministero dell'Istruzione, dell'Università e della Ricerca (FIRB-MERIT
RBNE08HWLZ_002).
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FIGURE CAPTIONS
Figure 1: Structural details of the pentameric and decameric oligomer systems. A)
Top-view of the Aβ(17-42) pentamer (16). Upper panel Labels used to indicate
secondary structure elements (B1, B2) and connecting regions (U-turn) are shown.
Residues belonging to the different secondary structure regions are displayed in sticks
of different color. Lower panel Pairs of residues involved in fibril stabilizing interactions
are displayed in sticks of different color. B) Side-view of the pentameric (top) and
decameric (bottom) Aβ oligomers colored by chain.
Figure 2: Root mean square deviation (RMSD) of the Cα carbon atoms positions in the
pentameric (black line) and decameric (red line) systems as a function of time.
Figure 3: Single chain RMS deviation and RMS fluctuation for the pentameric (A,C)
and decameric (B, D) systems.
Figure 4: Interchain distance between the centers of mass (COM) of the F19 phenyl
rings as a function of time for the penta- and deca-oligomer (top and bottom,
respectively).
Figure 5: F19-G38 and A21-V36 inter-layer Cα distances as a function of time for the
pentamer (A and C) and decamer (B and D), respectively.
Figure 6: Hydrophobic interacting area among the chains composing the penta- and
deca-oligomeric systems (top and bottom, respectively).
Figure 7: Top view of the binding mode of CT with the Aβ first layer. Oligomer residues
are depicted in blue, CT peptidic and sugar portions are in red and yellow, respectively.
Figure 8: Root mean-square deviation of the Cα carbon atom positions in the
pentameric (black line) and decameric (red line) complexes as a function of time.
Figure 9: Single chain RMSF for the pentameric (top) and decameric (bottom)
complexes.
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Figure 1.
Figure 2.
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Figure 3.
Figure 4.
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Figure 5.
Figure 6.
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Figure 7.
Figure 8.
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Figure 9.
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