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Biochimica et Biophysica Acta 1834 (2013) 24–33
Contents lists available at SciVerse ScienceDirect
Biochimica et Biophysica Acta
journal homepage: www.elsevier.com/locate/bbapap
The effect of fulvic acid on pre‐ and postaggregation state of Aβ17–42: Molecular
dynamics simulation studies
Sharad Verma a, Amit Singh b, Abha Mishra a,⁎
a
b
School of Biochemical Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi-221005, India
Department of Pharmacology, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
a r t i c l e
i n f o
Article history:
Received 27 May 2012
Received in revised form 25 July 2012
Accepted 20 August 2012
Available online 25 August 2012
Keywords:
Alzheimer's disease
Amyloid beta peptides
Fulvic acid
Molecular dynamics simulation
a b s t r a c t
Alzheimer's disease (AD), a neurodegenerative disorder, is directly related to the aggregation of Aβ peptides.
These peptides can self-assemble from monomers to higher oligomeric or fibrillar structures in a highly ordered and efficient manner. This self-assembly process is accompanied by a structural transition of the aggregated proteins from their normal fold into a predominantly β-sheet secondary structure. 14 ns molecular
dynamics simulation revealed that fulvic acid interrupted the dimer formation of Aβ17–42 peptide while in
its absence Aβ17–42 dimer formation occurred at ~ 12 ns. Additionally, fulvic acid disrupted the preformed
Aβ17–42 trimer in a very short time interval (12 ns). These results may provide an insight in the drug design
against Aβ17–42 peptide aggregation using fulvic acid as lead molecule against Aβ17–42 mediated cytotoxicity
and neurodegeneration.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
Alzheimer's disease (AD), a neurodegenerative disorder, is characterized by the presence of intra- and extra-cellular abnormal protein
aggregates known as neurofibrillary tangles and amyloid plaques,
respectively [1,2]. It has been established that β-amyloid polypeptide
(Aβ) is critically involved in the progression of AD [3–8]. These structures self-assemble from monomers to higher oligomeric or fibrillar
structures by a structural transition from their normal fold into a predominantly β-sheet secondary structure in a highly organized and
efficient manner. Apart from fiber formation, lower assemblies of Aβ
peptides were also found to cause neurodegenerative effects. Aβ
dimers have been reported as synaptotoxins [9]. Accumulating
evidences indicated a potential role of the early soluble oligomeric
species of Aβ, rather than mature fibrillar species, in the pathogenesis
of AD [10–14]. The fact that accumulation of Aβ monomers is not associated with any significant toxic effect is also noteworthy [15]. Aromatic residues of Aβ have been well known to play a central role in
the formation and stabilization of polymeric structures [16–19] as
evidenced by several structural [20,21] and molecular dynamics simulation studies [22–25]. Several polyphenols and other small aromatic
molecules and small aromatic peptides were shown to inhibit the aggregation of several amyloidogenic peptides [26–30]. Recently,
Cornejo et al. showed that the aggregation process of tau protein,
forming paired helical filaments (PHFs) in vitro, is inhibited by fulvic
acid and thereby affecting the length of fibrils and their morphology
[31].
⁎ Corresponding author. Tel.: +91 5422307070.
E-mail address: [email protected] (A. Mishra).
1570-9639/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.bbapap.2012.08.016
To get insight on the molecular effect of fulvic acid on Aβ peptide
aggregation we performed molecular dynamics simulations of Aβ
peptide with fulvic acid to elucidate the possible contribution of fulvic
acid in the inhibition of Aβ fibril aggregation.
2. Computational method
2.1. Strategy 1: analysis of the effect of fulvic acid on the Aβ dimer formation
The first phase of the study was mainly concentrated on the inhibition of Aβ dimer formation which is an initiating event for the formation of large assemblies (oligomers and fibrils) along with causing
synaptotoxicity. An initial coordinate of the Aβ17–42 peptide was taken
from PDB ID: 2BEG, obtained from RCSB protein data bank, derived
from quenched hydrogen/deuterium-exchange NMR [32]. Residues 1–
16 were omitted due to disorder and unavailability of crystal
structure [33–37]. To elucidate the effect of fulvic acid on dimer formation, two Aβ peptides were generated using model l of the PDB
co-ordinate file. Initially the model 1 contained five peptides (A to E)
from which B, C and E were removed (Fig. 1). The resulting PDB file
contained peptide A and D which was used to perform docking with
fulvic acid. The structures of fulvic acid were generated from smile
strings obtained from PubChem compound (http://pubchem.ncbi.nlm.
nih.gov/summary/summary.cgi?cid=5359407) followed by energy
minimization. Hydrogen atoms were added to protein crystal structures
using the Autodock program while all nonpolar hydrogen atoms were
merged. Five bonds were made “active” or rotatable for the fulvic acid.
Lamarckian genetic algorithm was used as a search parameter which
is based on adaptive local search. Short range van der Waals and
electrostatic interactions, hydrogen bonding, and entropy losses were
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Fig. 1. Diagrammatic presentation of peptide structure model generation for strategies 1 and 2.
included for energy based Autodock scoring function [38]. The
Lamarckian GA parameters used in the study were: numbers of
run, 30; population size, 150; maximum number of evaluations;
25,000,000, number of generation; 27,000, rate of gene mutation; 0.02
and rate of cross over; 0.8. Blind docking was carried out using grid
size 126, 126 and 126 along the X, Y and Z axes with 0.375 Å spacing.
RMS cluster tolerance was set to 2.0 Å. Docking was performed which
includes a flexible ligand and a rigid receptor [39]. All the protein and
ligand structural images were generated using PYMOL [40]. MD simulation of the complex (peptide A, peptide D and fulvic acid) was carried
out with the GROMACS4.5.4 package using the GROMOS96 43a1 force
field [41,42]. The lowest binding energy (most negative) docking
conformation generated by Autodock was taken as the initial conformation for MD simulation. The topology parameters of proteins were created by using the Gromacs program. The topology parameters of fulvic
acid were built by the Dundee PRODRG server [43]. The complex was
immersed in a cubic box of simple point charge (SPC) water molecules
[44]. The solvated system (two Aβ peptides, fulvic acid and water) was
neutralized by adding 3 Na ions. To release conflicting contacts, energy
minimization was performed using the steepest descent method of
10,000 steps followed by the conjugate gradient method for 10,000
steps. Afterward, the position-restrained dynamics simulation of the
system was carried out at 300 K for 200 ps. Finally, the full system
was subjected to MD production run at 300 K temperature and 1 bar
pressure for 14,000 ps. We also performed the MD simulation of
peptides A and D without fulvic acid for comparative study using the
same method as mentioned above.
2.2. Strategy 2: analysis of the effect of fulvic acid on the intact Aβ trimer
To elucidate the effect of fulvic acid on preformed assembly of Aβ
peptides, we used an intact trimer of Aβ which was formed by using
model l of PDB co-ordinate file (PDB ID: 2BEG). Co-ordinates of
peptides D and E were removed from the model 1 (Fig. 1). The rest
of the steps were same as mentioned above in strategy 1. The solvated
system (Aβ trimer, fulvic acid and water) was neutralized by adding 4
Na ions. The full system was subjected to MD production run at 300 K
temperature and 1 bar pressure for 12,000 ps after energy minimization and position-restrained dynamics simulation.
3. Results and discussion
3.1. Strategy 1: effect of fulvic acid on the Aβ dimer formation
Fulvic acid was bound to peptide A and formed H-bonds with Phe
19, Ala 21, Gly 37, and Val 39. The groups involved in H-bonding were
carboxylate, hydroxyl (hydrogen donor), and hydroxyl group oxygen
(hydrogen acceptor) of fulvic acid and peptide bonds of the backbone.
Apart from H-bonding, π–π interaction was also found between aromatic rings of fulvic acid and Phe 19 (Fig. 2). The complex obtained
using Autodock was used for carrying out MD simulation. The time
dependent behavior of MD trajectories for peptide-fulvic acid was analyzed including root mean square deviation (RMSD) for all backbone
atoms, short range (SR) Coulombic interaction energy and van der
Waals interaction energy. Fig. 3A showed that the RMSD trajectory
of backbone atoms was always less than 3.5 nm for the entire simulation. There was an initial steep rise in the RMSD for the first, ~ 2000 ps
and subsequently a fluctuating profile was observed for the backbone
of Aβ peptides. The sudden increase in the RMSD value was found to
be associated with the interaction of peptides which was confirmed
by the snapshots (Fig. 4) (described later) recorded at different time
intervals of the simulation. RMSD trajectory of fulvic acid showed a
profile below 0.16 nm with high fluctuation (Fig. 3B). Analysis of
fulvic acid RMSD indicated that fulvic acid showed change in the position during MD simulation which was confirmed by the analysis of
snapshots (Fig. 4). 14 ns molecular dynamics simulation revealed
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Fig. 2. Fulvic acid docked to peptide A and the interaction with peptide A residues.
that fulvic acid interrupted the dimer formation of Aβ17–42 peptide
while in its absence Aβ17–42 formed a dimer at ~ 12 ns (Figs. 4 and 5).
To explore the interaction between fulvic acid and Aβ peptides, we
calculated the energy contributions of short range van der Waals and
electrostatic energies. The van der Waals and short-range electrostatic
energies between peptides and the fulvic acid during the simulation
have been shown in Fig. 6A and B, respectively. As indicated in Fig. 6A,
the average van der Waals energy between fulvic acid and Aβ peptides
during the simulation was approximately −97.19 kJ/mol. However, the
average short-range (SR) electrostatic energy between the fulvic acid
and Aβ peptides was found to be approximately −62.89 kJ/mol
(Fig. 6B). The van der Waals energy remained more or less constant but
the SR electrostatic energies decreased (less negative) by ~90 kJ/mol
after ~5000 ps. Thus it can be concluded that the van der Waals energy
plays a more important role in the peptides and the fulvic acid interaction
than the SR electrostatic interaction. The number of H-bonds (cut off
0.35 nm) which were formed during MD simulation between fulvic
acid and peptides was found with a long range profile from 0 to 7 with
an average value of 1.36 (Fig. 6C). However, a significant decrease was
observed after ~5000 ps which were in accordance with lowering in
the SR electrostatic energies.
Classical nucleation theory has been used several times to explain
amyloid phenomena as the kinetics of fibril formation which usually
takes place with a nucleation-dependent polymerization mechanism
[45–49]. It was noteworthy that the hydrogen bond network is insignificant in β-sheet enthalpic cooperativity [50], while the association
Fig. 3. (A) RMSD profile of Aβ peptides, and (B) RMSD profile of fulvic acid.
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Fig. 4. Conformations of peptide A (red), peptide D (cyan) and fulvic acid (green) during the 14 ns MD simulation. (For interpretation of the references to color in this figure legend,
the reader is referred to the web version of this article.)
enthalpies arise predominately contributed by hydrophobic interactions
to play an important role in aggregate formation [51]. Solid-state NMR
studies showed that, in Aβ10–35 and Aβ1–40 fibrils, peptides exist in parallel β sheets [52,53]. In contrast, antiparallel organization is found for the
smaller fragments Aβ34–42 [54] and Aβ16–22 [55]. The solid state NMR
measurements revealed the antiparallel organization of amyloid fibrils
formed by the fragment N-acetyl-Lys-Leu-Val-Phe-Phe-Ala-Glu-NH2
(Aβ16–22) [55]. It was reported that if peptides contained the crucial central hydrophobic cluster (CHC; residues 17–21, LVFFA) then they can be
polymerized to higher assemblies [56]. The conformations of Aβ16–22
peptides, in a monomeric form, partition into two distinct sets of structures. The first consists of random coil conformations and the second is
best described by extended β strand-like conformations. Recently, by
monitoring secondary structure changes by circular dichroism, Teplow
Fig. 5. Dimer formation during MD simulation in the absence of fulvic acid.
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Fig. 6. Profile of (A) van der Waals (vdw) interaction energy, (B) Coulombic interaction energy, between fulvic acid and Aβ peptides, and (C) H-bonding profile of fulvic acid and Aβ
peptides during the 14 ns MD simulation.
and coworkers [57] showed that, at the first stages of assembly of
amyloids, the Aβ1–40 and Aβ1–42 peptides adopted helical conformations. These findings suggest that α-helical conformations may be
“on-pathway” intermediates to fibrillization. Other experimental observations and MD simulation studies suggested that, at least in Aβ
peptides, multiple routes governed amyloid fibril formation with obligatory α-helical intermediates [58].
14 ns simulation revealed that fulvic acid disrupt the β sheet dimer
aggregation and hence the productive polymerization of Aβ peptides.
Study of snapshots recorded at different time intervals revealed that
fulvic acid even interrupted the proper interaction between peptides
(Fig. 4). The snapshots revealed consequences of association and dissociation of Aβ peptides. Such type of fragile interaction, surely, does not
end in the formation of a proper β sheet dimer which is energetically
feasible for further elongation into an oligomer and a fibril. Hard and
Lenden have described the various schemes for the prevention of
assembly of Aβ peptides. The two of the schemes described in the
study were (1) sequestering of partially folded monomeric peptide
and (2) stabilization/promotion of off-pathway [59]. The binding of
fulvic acid to Aβ peptides partially covers both schemes as evidenced
by MD simulation. The dissociation of two Aβ peptides revealed the stabilization of partially folded monomeric peptide thus hampering the
association of peptides. Most of the interactions were polar contacts
or H-bonds between the interface residues of two peptides without
proper orientation. The switch of binding from peptide A to peptide D
revealed low affinity of binding for fulvic acid, since there was no
defined binding pocket to facilitate the binding of ligand. Moreover,
Meng et al. described that the affinity of ligand for peptide and the
antiaggregation property has no co-relation [60].
These evidences, collectively, suggest the plausible involvement of
fulvic acid in the inhibition of peptide aggregation in cytotoxic form.
3.2. Strategy 2: effect of fulvic acid on the intact Aβ trimer
Fig. 7A showed that the RMSD trajectory of trimer backbone atoms
was always less than 4.0 nm for the entire simulation. Very high rise in
the RMSD was observed after ~7000 ps and subsequently a fluctuating
profile was observed for the peptide trimer backbone. The sudden
increase in the RMSD value was found to be associated with the separation of monomeric peptide which was confirmed by the snapshots
(described later) recorded at different time intervals of the simulation.
RMSD trajectory of fulvic acid showed a profile below 0.15 nm with
high fluctuation (Fig. 7B). Analysis of fulvic acid RMSD indicated a stable
interaction with peptide A during MD simulation, which was also
confirmed by the analysis of snapshots (Fig. 9). The van der Waals and
short-range electrostatic energies between peptides and the fulvic acid
and those between fulvic acid and the solvent during the simulation
are shown in Fig. 8A and B, respectively. As indicated in Fig. 8A, the average van der Waals interaction energy between fulvic acid and peptides
during the simulation was found to be −98.24 kJ/mol. The average
short-range electrostatic energy between the fulvic acid and peptides
was found to be −88.22 kJ/mol (Fig. 8B). However, both van der
Waals energy and SR electrostatic energies showed a constant profile
during simulation but it was found that van der Waals energy played
important role a bit more in the peptides and fulvic acid interactions
than in the SR electrostatic interaction. A number of H-bonds (cut off
0.35 nm) which formed during MD simulation between fulvic acid and
peptides were in a long range profile from 0 to 4 with an average value
of 1.08 (Fig. 8C). 12 ns simulation of Aβ trimer with fulvic acid revealed
that binding of fulvic acid lead to the dissociation of trimer, also 10 ns
snapshot clearly showed the separation of peptide C. 12 ns final snapshot showed separation of AB and dimer formation by two separated
peptides (B and C) (Fig. 9). This was quite obvious in this case because
a single fulvic acid molecule may inhibit only the interaction with
bound peptide A. Convertino et al. studied the antiaggregation effect of
9,10-anthraquinone (AQ) on the trimer of Aβ1–40 and showed that AQ
disrupts the trimer in long time simulation (~865.56 ns) [61]. As
compared to AQ, fulvic acid had shown remarkable antiaggregation potential in a short time scale (12 ns). In the present case fulvic acid was
found to act as a β-sheet breaker according to previously characterized
strategies [59]. The importance of aromatic rings of peptide residues in
amyloidogenesis is well established [62]. Previous studies revealed that
the tetrapeptide KFFE was able to form amyloid-like fibrils [63]. The central hydrophobic cluster of amyloid-β (residues 17–21 LVFFA) has been
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Fig. 7. RMSD profile of (A) Aβ trimer, and (B) fulvic acid.
particularly implicated in amyloid fibril formation [63]. Other findings
revealed that Phe 19 was particularly important for forming fibrils
[64,65]. The structure of the fibrils formed from the central region of
amyloid-β (residues 11–25) showed intersheet stacking of phenylalanine
rings [66]. Makin et al. show β-sheet stabilization associated by means of
a phenylalanine zipper [20]. The β-stacking has a critical role in energetic
contribution [67], which may further drive the self-assembly process
[20].
To elucidate which residue of peptide A was involved in a stable
interaction with fulvic acid which further lead to the separation of peptides, 2D plots of interaction was generated using Discovery studio 3.1
[68]. Leu 17 and Phe 19 showed stable π–π interaction with fulvic acid
aromatic rings (Fig. 7). Apart from these interactions, Val 36 and Gly
37 also contributed to the stability of the complex by forming a
H-bond with fulvic acid (Fig. 10). It was found that the π–π interaction
with Phe 19 and Leu 17 broke the interchain π–π interaction and subsequently the phenylalanine zipper.
In the recent past cytotoxicity associated with many amyloid
disorders were initially assumed to be due to fibrils and fibril plaques
that are abundant in diseased tissues [69,70]. However, numerous recent reports have focused on soluble pre-fibrillar oligomers as the primary cytotoxic species [71–74]. Despite the significant evidences
which support the pre-fibrillar oligomeric species as cytotoxic agents,
several examples of cytotoxicity associated with fibrils still persist
Fig. 8. Profile of (A) van der Waals (vdw) interaction energy, (B) Coulombic interaction energy, between fulvic acid and Aβ peptides, and (C) H-bonding profile of fulvic acid and Aβ
peptides during the 12 ns MD simulation.
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Fig. 9. Representation of the antiaggregation effect of fulvic acid on Aβ trimer during the 12 ns MD simulation.
[75–77]. This raises the possibility that the determinants of cytotoxicity may not always be associated with the same type of species, and
for some amyloidogenic proteins, fibrils themselves or fibrilassociated species may possess cytotoxic potential [78]. Recent studies have shown that Aβ fibrils interacting with sphingolipids, gangliosides, or cholesterol, are associated with amyloid plaques in vivo
[79] and result in the release of cytotoxic species [80], on the other
hand the assembly process of islet amyloid polypeptide (also known
as amylin) fibrils on lipid membranes results in liposome disruption,
which suggest fibril-associated toxicity during the fibril growth process [81]. These studies suggest that fibrils should perhaps not be
discarded as the inert products of amyloid assembly but might provide a further source of toxicity, directly by interacting with membranes and indirectly by acting as a source of cytotoxic species [82].
Fig. 10. 2D plots of the interaction between fulvic acid and Aβ peptides at different time intervals during the 12 ns MD simulation.
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Fig. 11. (A) Representation of the separation of peptides A and B and the formation of peptide BC dimer with a time difference of 0.0003 ns, (B) helicity of Aβ residues during the
12 ns MD simulation, and (C) interaction between fulvic acid and Aβ peptides during the separation of peptides A and B and the formation of peptide BC dimer with a time difference of 0.0003 ns.
Holmes et al. in a clinical study revealed that plaque removal is not sufficient enough to prevent progressive neurodegeneration [83] which
again raised the same question regarding the role of fibrils or aggregates
of these fibrils i.e. senile plaques. This clinical study supports the
pre-fibrillar oligomers as the primary cytotoxic species hence the antiaggregation agents might play a significant role in the prevention of
neurodegeneration. Thus the present study may provide an insight on
the drug design against Aβ17–42 peptide aggregation using fulvic acid
as the lead structure for recovery from amyloid peptide aggregation
associated cytotoxicity and neurodegeneration.
Apart from these antiaggregation effects of fulvic acid, an investigation was also made on the role of α-helix formation in the
β-sheet dimer of peptides B and C. The formation of α-helix is designated as the obligatory step of on-pathway aggregation [53]. The
snapshots between the separation of peptide AB dimer and formation
of peptide BC dimer at a very short time interval (0.0003 ns) was
recorded and analyzed and, surprisingly, no α-helix or helical structure was found present (Fig. 11A). For confirmation, again the helicity
of residues during simulation using GROMACS program g_helix was
calculated. Helicity for all residues was found zero as shown in
Fig. 11B. These results were further confirmed by using g_rama of
GROMACS for the time interval 0.0003 ns. The phi and psi value of
residues obtained by g_rama populated in the Ramachandran plot
which revealed that most of the residues were in the region belonging to the β-sheet or the nearby region (Fig. 12). From these results
Fig. 12. Phi and psi values for the time interval of 0.0003 ns of Aβ peptide residues
populated in the Ramachandran plot.
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it might be concluded that the β-sheet structure of peptide B facilitates the dimer formation with peptide C and by passed the helix formation. Probably, β-sheet structure of peptide B made the process
energetically favorable to form properly oriented assembly.
4. Conclusion
Molecular dynamic simulation studies revealed that fulvic acid interrupts the dimer formation of Aβ17–42 peptide. Furthermore, fulvic
acid disrupts the preformed Aβ17–42 trimer in a very short time interval
(12 ns). Phe 19 and Leu 17 were found as main residues involved in stable interaction with fulvic acid. These results support the previous studies conducted in this regard and provide an insight in the drug design
against Aβ17–42 peptide aggregation using fulvic acid as the lead molecule for recovery from amyloid cytotoxicity and neurodegeneration.
Acknowledgement
One of the authors (Sharad Verma) is thankful to the Council of
Scientific and Industrial Research (CSIR), India for providing the Senior
Research Fellowship.
References
[1] D.J. Selkoe, The molecular pathology of Alzheimer's disease, Neuron 6 (1991)
487–498.
[2] R. Terry, Neuropathological changes in Alzheimer disease, Prog. Brain Res. 101
(1994) 383–390.
[3] J. Hardy, D. Allsop, Amyloid deposition as the central event in the aetiology of
Alzheimer's disease, Trends Pharmacol. 12 (1991) 383–388.
[4] D. Mann, Cerebral amyloidosis aging and Alzheimer's disease; a contribution
from studies on Down's syndrome, Neurobiol. Aging 10 (1989) 397–399.
[5] D. Price, R. Tanzi, D. Borchelt, S. Sisodia, Alzheimer's disease: genetic studies and
transgenic models, Annu. Rev. Genet. 32 (1998) 461–493.
[6] F. Van Leuven, Single and multiple transgenic mice as models for Alzheimer's
disease, Prog. Neurobiol. 61 (2000) 305–312.
[7] P. Fraser, D. Yang, G. Yu, L. Levesque, M. Nishimura, S. Arawaka, L.C. Serpell, E. Rogaeva,
P. St George-Hyslop, Presenilin structure, function and role in Alzheimer disease,
Biochem. Biophys. Acta 1502 (2000) 1–15.
[8] J.P. Cleary, D.M. Walsh, J.J. Hofmeister, G.M. Shankar, M.A. Kuskowski, D.J. Selkoe,
K.H. Ashe, Natural oligomers of the amyloid-b protein specifically disrupt cognitive function, Nat. Neurosci. 1 (2005) 79–84.
[9] G.M. Shankar, S. Li, T.H. Mehta, A. Garcia-Munoz, N.E. Shepardson, I. Smith, F.M. Brett,
M.A. Farrell, M.J. Rowan, C.A. Lemere, C.M. Regan, D.M. Walsh, B.L. Sabatini,
D.J. Selkoe, Amyloid-β protein dimers isolated directly from Alzheimer's
brains impair synaptic plasticity and memory, Nat. Med. 14 (2008) 837–842.
[10] M.D. Kirkitadze, G. Bitan, D.B. Teplow, Paradigm shifts in Alzheimer's disease and
other neurodegenerative disorders: the emerging role of oligomeric assemblies,
J. Neurosci. Res. 69 (2002) 567–577.
[11] H.A. Lashuel, D. Hartley, B.M. Petre, T. Walz, P.T.J. Lansbury, Neurodegenerative
disease: amyloid pores from pathogenic mutations, Nature 418 (2002) 291.
[12] R. Kayed, E. Head, J.I. Thompson, T.M. McIntire, S.C. Milton, C.W. Cotman, C.G. Glabe,
Common structure of soluble amyloid oligomers implies common mechanism of
pathogenesis, Science 300 (2003) 486–489.
[13] E. Gazit, The role of prefibrillar assemblies in the pathogenesis of amyloid diseases,
Drugs Future 29 (2004) 613–619.
[14] S. Barghorn, V. Nimmrich, A. Striebinger, C. Krantz, P. Keller, B. Janson, M. Bahr,
Martin Schmidt, R.S. Bitner, J. Harlan, E. Barlow, U. Ebert, Heinz Hillen, Globular
amyloid beta-peptide oligomer—a homogenous and stable neuropathological
protein in Alzheimer's disease, J. Neurochem. 3 (2005) 834–847.
[15] D.L. Brody, S. Magnoni, K.E. Schwetye, M.L. Spinner, T.J. Esparza, N. Stocchetti,
G.J. Zipfel, D.M. Holtzman, Amyloid-b dynamics correlate with neurological
status in the injured human brain, Science 321 (2008) 1221–1224.
[16] R. Azriel, E. Gazit, Analysis of the minimal amyloid-forming fragment of the islet amyloid polypeptide. An experimental support for the key role of the phenylalanine
residue in amyloid formation, J. Biol. Chem. 276 (2001) 34156–34161.
[17] E. Gazit, A possible role for p-stacking in self-assembly of amyloid fibrils, FASEB J.
16 (2002) 77–83.
[18] E. Gazit, Global analysis of tandem aromatic octapeptide repeats: the significance
of aromatic-glycine motif, Bioinformatics 18 (2003) 880–883.
[19] M. Reches, E. Gazit, Casting metal nanowires within discrete self assembled peptide
nanotubes, Science 300 (2003) 625–627.
[20] O.S. Makin, E. Atkins, P. Sikorski, J. Johansson, L.C.M. Serpell, Molecular basis for
amyloid fibril formation and stability, Proc. Natl. Acad. Sci. 102 (2005) 315–320.
[21] H. Inouye, D. Sharma, W.J. Goux, D.A. Kirschner, Structure of core domain of
fibril-forming PHF/Tau fragments, Biophys. J. 90 (2006) 1774–1789.
[22] G. Colombo, I. Daidone, E. Gazit, A. Amadei, A. Di Nola, Molecular dynamic simulation of the aggregation of the core-recognition of the islet amyloid polypeptide
in explicit water, Protection 59 (2005) 519–527.
[23] C. Wu, H.X. Lei, Y. Duan, The role of Phe in the formation of well-ordered oligomers of amyloidogenic hexapeptide (NFGAIL) observed in molecular dynamic
simulation with explicit solvent, Biophys. J. 88 (2005) 2897–2906.
[24] G.G. Tartaglia, A. Cavalli, R. Pellarin, A. Caflisch, The role of aromaticity, exposed
surfaces and dipole moment in determining protein aggregation rates, Prot. Sci.
13 (2004) 1939–1941.
[25] D. Zanuy, Y. Porat, E. Gazit, R. Nussinov, Peptide sequence and amyloid formation:
molecular simulation and experimental study of a human islet amyloid polypeptide fragment and its analogs, Structures 12 (2004) 439–455.
[26] Y. Porat, A. Abramowitz, E. Gazit, Inhibition of amyloid fibril formation by polyphenols:
structural similarity and aromatic interactions as a common, Chem. Biol. Drug Des. 67
(2006) 27–37.
[27] S. Bastianetto, S. Krantic, R. Quirion, Polyphenols as potential inhibitors of amyloid aggregation and toxicity: possible significance to Alzheimer's disease, Mini
Rev. Med. Chem. 5 (2008) 429–435.
[28] C. Rivie`re, T. Richard, L. Quentin, S. Krisa, J.M. Me´rillon, J.P. Monti, Inhibitory
activity of stilbenes on Alzheimer's b-amyloid fibrils in vitro, Bioorg. Med. Chem.
15 (2007) 1160–1167.
[29] A. Frydman-Marom, M. Rechter, I. Shefler, Y. Bram, D.E. Shalev, E. Gazit, Cognitiveperformance recovery of Alzheimer's disease model mice by modulation of early
soluble amyloidal assemblies, Angew. Chem. Int. Ed. 48 (2009) 1981–1986.
[30] R. Scherzer-Attali, R. Pellarin, M. Convertino, A. Frydman-Marom, N. Egoz-Matia,
S. Peled, M. Levy-Sakin, D.E. Shalev, A. Caflisch, E. Gazit, D. Segal, Complete phenotypic recovery of an Alzheimer's disease model by a quinone-tryptophan hybrid
aggregation inhibitor, PLoS One 5 (2010) e11101.
[31] A. Cornejo, J.M. Jiménez, L. Caballero, F. Melo, R.B. Maccioni, Fulvic acid inhibits
aggregation and promotes disassembly of tau fibrils associated with Alzheimer's
disease, J. Alzheimers Dis. 27 (2011) 143–153.
[32] T. Lu¨ hrs, C. Ritter, M. Adrian, D. Riek-Loher, B. Bohrmann, H. Dobeli, D. Schubert,
R. Riek, 3D structure of Alzheimer's amyloid-β(1–42) fibrils, PNAS 102 (2005)
17342–17347.
[33] X. Yu, J. Zheng, Polymorphic structures of Alzheimer's b-amyloid globulomers,
PLoS One 6 (2011) e20575.
[34] J. Zhao, Q. Wang, G. Liang, J. Zheng, Molecular dynamics simulations of low-ordered
Alzheimer β-amyloid oligomers from dimer to hexamer on self-assembled monolayers, Langmuir 27 (2011) 14876–14887.
[35] N. Blinov, L. Dorosh, D. Wishart, A. Kovalenko, Association thermodynamics and
conformational stability of b-sheet amyloid b(17–42) oligomers: effects of E22Q
(Dutch) mutation and charge neutralization, Biophys. J. 98 (2010) 282–296.
[36] J. Zheng, H. Jang, B. Ma, R. Nussinov, Annular structures as intermediates in fibril
formation of Alzheimer Aβ17–42, J. Phys. Chem. B 112 (2008) 6856–6865.
[37] H. Jang, F.T. Arce, S. Ramachandran, R. Capone, R. Azimovac, B.L. Kaganc, R. Nussinov,
R. Lal, Truncated β-amyloid peptide channels provide an alternative mechanism for
Alzheimer's disease and down syndrome, PNAS 107 (2010) 6538–6543.
[38] G.M. Morris, D.S. Goodsell, R.S. Halliday, R. Huey, W.E. Hart, R.K. Belew, A.J. Olson,
Automated docking using a Lamarckian genetic algorithm and empirical binding
free energy function, J. Comput. Chem. 19 (1998) 1639–1662.
[39] S. Verma, A. Singh, A. Mishra, Taxifolin acts as type I inhibitor for VEGFR-2 kinase:
stability evaluation by molecular dynamic simulation, J. Appl. Pharmacol. Sci. 2
(2012) 41–46.
[40] W.L. DeLano, The PyMOL molecular graphics system, DeLano Scientific LLC, San
Carlos, CA, USA, 2004 (http://www.pymol.org).
[41] H.J.C. Berendsen, D. Van der Spoel, R. Van Drunen, GROMACS—a message passing parallel molecular dynamics implementation, Phys. Commun. 91 (1995)
43–56.
[42] E. Lindah, B. Hess, D. Van der Spoel, Gromacs 3.0: a package for molecular simulation and trajectory analysis, J. Mol. Model. 7 (2001) 306–317.
[43] A.W. Schuttelkopf, D.M.F. van Aalten, PRODRG: a tool for high-throughput crystallography of protein–ligand complexes, Acta Crystallogr. 60 (2004) 1355–1363.
[44] W.F. Van Gunsteren, S.R. Billeter, A.A. Eising, P.H. Hunenberger, P.K.H.C. Kruger,
A.E. Mark, W.R.P. Scott, I.G. Tironi, Biomolecular Simulation: the GROMOS96
Manual and User Guide, Vdf Hochschulverlag AG, Zurich, 1996.
[45] A.R. Hurshman, J.T. White, E.T. Powers, J.W. Kelly, Transthyretin aggregation
under partially denaturing conditions is a downhill polymerization, Biochemistry
43 (2004) 7365–7381.
[46] F. Massi, J.E. Straub, Energy landscape theory for Alzheimer's amyloid betapeptide fibril elongation, Proteins Struct. Funct. Genet. 42 (2001) 217–229.
[47] D. Thirumalai, D.K. Klimov, R.I. Dima, Emerging ideas on the molecular basis of
protein and peptide aggregation, Curr. Opin. Struct. Biol. 13 (2003) 146–159.
[48] G. Tiana, F. Simona, R.A. Brogliaa, G. Colombo, Thermodynamics of beta-amyloid
fibril formation, J. Chem. Phys. 120 (2004) 8307–8317.
[49] E.T. Powers, D.L. Powers, The kinetics of nucleated polymerizations at high
concentrations: amyloid fibril formation near and above the “supercritical
concentration”, Biophys. J. 91 (2006) 122–132.
[50] Y.L. Zhao, Y.D. Wu, A theoretical study of beta-sheet models: is the formation of
hydrogen bond networks cooperative, J. Am. Chem. Soc. 124 (2002) 1570–1571.
[51] R.D. Hills, C.L. Brooks, Hydrophobic cooperativity as a mechanism for amyloid
nucleation, J. Mol. Biol. 368 (2007) 894–901.
[52] T.S. Burkoth, T.L.S. Benzinger, V. Urban, D.M. Morgan, D.M. Gregory, P. Thiyagarajan,
R.E. Botto, S.C. Meredith, D.G. Lynn, Structure of the β-Amyloid (10–35) fibril, J. Am.
Chem. Soc. 122 (2000) 7883–7889.
[53] O.N. Antzutkin, J.J. Balbach, R.D. Leapman, N.W. Rizzo, J. Reed, R. Tycko, Multiple quantum solid-state NMR indicates a parallel, not antiparallel, organization of β-sheets in
Alzheimer's β-amyloid fibrils, Proc. Natl. Acad. Sci. 97 (2000) 13045–13050.
[54] P.T. Lansbury, P.R. Costa, J.M. Griffiths, E.J. Simon, M. Auger, K.J. Halverson, D.A. Kocisko,
Z.S. Hendsch, T.T. Ashburn, R.G. Spencer, Structural model for the betaamyloid fibril
Author's personal copy
S. Verma et al. / Biochimica et Biophysica Acta 1834 (2013) 24–33
[55]
[56]
[57]
[58]
[59]
[60]
[61]
[62]
[63]
[64]
[65]
[66]
[67]
[68]
[69]
[70]
[71]
based on interstrand alignment of an antiparallel sheet comprising a C-terminal
peptide, Nat. Struct. Biol. 2 (1995) 990–998.
J.J. Balbach, Y. Ishii, O.N. Antzutkin, R.D. Leapman, N.W. Rizzo, F. Dyda, J. Reed, R. Tycko,
Amyloid fibril formation by Aβ16–22, a seven-residue fragment of the Alzheimer's
β-amyloid peptide, and structural characterization by solid state NMR, Biochemistry
39 (2000) 13748–13759.
D.G. Lynn, S.C. Meredith, Review: model peptides and the physicochemical
approach to β-amyloids, J. Struct. Biol. 130 (2000) 153–173.
M.D. Kirkitadze, M.M. Condron, D.B. Teplow, Identification and characterization of
key kinetic intermediates in amyloid β-protein fibrillogenesis, J. Mol. Biol. 312
(2001) 1103–1119.
D.K. Klimov, D. Thirumalai, Dissecting the assembly of Aβ16–22 amyloid peptide in
to antiparallel β sheets, Structures 11 (2003) 295–307.
T. Härd, C. Lendel, Inhibition of amyloid formation, J. Mol. Biol. 421 (2012)
441–465.
X. Meng, L.A. Munishkina, A.L. Fink, V.N. Uversky, Molecular mechanisms underlying the flavonoid-induced inhibition of α-synuclein fibrillation, Biochemistry
48 (2009) 8206–8224.
M. Cavertino, R. Pellarin, M. Catto, A. Carotti, A. Caflisch, 9,10-anthraquinone hinders
β-aggregation: how does a small molecule interfere with Aβ-peptide amyloid fibrillation, Prot. Sci. 18 (2009) 792–800.
E. Gazit, A possible role of π-stacking in the self-assembly of amyloid fibrils,
FASEB J. 1 (2002) 77–83.
L. Tjernberg, W. Hosia, N. Bark, J. Thyberg, J. Johansson, Charge attraction and beta
propensity are necessary for amyloid fibril formation from tetrapeptide, J. Biol.
Chem. 277 (2002) 43243–43246.
W.P. Esler, E.R. Stimson, J.R. Ghilardi, Y.A. Lu, A.M. Felix, H.V. Vinters, P.W. Mantyh,
J.P. Lee, J.E. Maggio, Point substitution in the central hydrophobic cluster of a
human beta-amyloid congener disrupts peptide folding and abolishes plaque
competence, Biochemistry 35 (1996) 13914–13921.
C. Wurth, N.K. Guimard, M.H. Hecht, Mutations that reduce aggregation of the
Alzheimer's Abeta42 peptide: an unbiased search for the sequence determinants
of Abeta amyloidogenesis, J. Mol. Biol. 319 (2002) 1279–1290.
P. Sikorski, E.D.T. Atkins, L.C. Serpell, Structure and texture of fibrous crystals formed
by Alzheimer's Aβ (11–25) peptide fragment, Structures 11 (2003) 915–926.
C.A. Hunter, Aromatic–aromatic interactions: electrostatic or charge transfer?
Angew. Chem. Int. Ed. 32 (1993) 1584–1586.
Accelrys Software Inc., Discovery Studio Modeling Environment, Release 3.1,
Accelrys Software Inc., San Diego, 2011.
A. Campbell, Beta-amyloid: friend or foe, Med. Hypotheses 56 (2001) 388–391.
H.G. Lee, G. Casadesus, X. Zhu, J.A. Joseph, G. Perry, M.A. Smith, Perspectives on
the amyloid-beta cascade hypothesis, J. Alzheimers Dis. 6 (2004) 137–145.
R. Kayed, E. Head, J.L. Thompson, T.M. McIntire, S.C. Milton, C.W. Cotman, C.G. Glabe,
Common structure of soluble amyloid oligomers implies common mechanism of
pathogenesis, Science 300 (2003) 486–489.
33
[72] N. Reixach, S. Deechongkit, X. Jiang, J.W. Kelly, J.N. Buxbaum, Tissue damage in
the amyloidoses: transthyretin monomers and nonnative oligomers are the
major cytotoxic species in tissue culture, Proc. Natl. Acad. Sci. 101 (2004)
2817–2822.
[73] S. Lesne´, M.T. Koh, L. Kotilinek, R. Kayed, C.G. Glabe, A. Yang, M. Gallagher, K.H.
Ashe, A specific amyloid-beta protein assembly in the brain impairs memory,
Nature 440 (2006) 352–357.
[74] G.M. Shankar, S. Li, T.H. Mehta, A. Garcia-Munoz, N.E. Shepardson, I. Smith, F.M.
Brett, M.A. Farrell, M.J. Rowan, C.A. Lemere, C.M. Regan, D.M. Walsh, B.L.
Sabatini, D.J. Selkoe, Amyloid-beta protein dimers isolated directly from
Alzheimer's brains impair synaptic plasticity and memory, Nat. Med. 14
(2008) 837–842.
[75] A.L. Gharibyan, V. Zamotin, K. Yanamandra, O.S. Moskaleva, B.A. Margulis,
I.A. Kostanyan, L.A. Morozova-Roche, Lysozyme amyloid oligomers and
fibrils induce cellular death via different apoptotic/necrotic pathways,
J. Mol. Biol. 365 (2007) 1337–1349.
[76] M. Meyer-Luehmann, T.L. Spires-Jones, C. Prada, M. Garcia-Alloza, A. de Calignon,
A. Rozkalne, J. Koenigsknecht-Talboo, D.M. Holtzman, B.J. Bacskai, B.T. Hyman,
Rapid appearance and local toxicity of amyloid-beta plaques in a mouse model
of Alzheimer's disease, Nature 451 (2008) 720–724.
[77] L. Pieri, M. Bucciantini, D. Nosi, L. Formigli, J. Savistchenko, R. Melki, M. Stefani,
The yeast prion Ure2p native-like assemblies are toxic to mammalian cells
regardless of their aggregation state, J. Biol. Chem. 281 (2006) 15337–15344.
[78] A.K. Paravastu, I. Qahwash, R.D. Leapman, S.C. Meredith, R. Tycko, Seeded growth
of beta-amyloid fibrils from Alzheimer's brain-derived fibrils produces a distinct
fibril structure, Proc. Natl. Acad. Sci. 106 (2009) 7443–7448.
[79] S. Devanathan, Z. Salamon, G. Lindblom, G. Gro¨bner, G. Tollin, Effects of
sphingomyelin, cholesterol and zinc ions on the binding, insertion and aggregation of the amyloid Abeta(1–40) peptide in solid-supported lipid bilayers, FEBS
J. 273 (2006) 1389–1402.
[80] I.C. Martins, I. Kuperstein, H. Wilkinson, E. Maes, M. Vanbrabant, W. Jonckheere,
P. Van Gelder, D. Hartmann, R. D'Hooge, B. De Strooper, J. Schymkowitz, F. Rousseau,
Lipids revert inert Abeta amyloid fibrils to neurotoxic protofibrils that affect learning
in mice, EMBO J. 27 (2008) 224–233.
[81] M.F. Engel, L. Khemte´mourian, C.C. Kleijer, H.J. Meeldijk, J. Jacobs, A.J. Verkleij, B. de
Kruijff, J.A. Killian, J.W. Ho¨ppener, Membrane damage by human islet amyloid polypeptide through fibril growth at the membrane, Proc. Natl. Acad. Sci. 105 (2008)
6033–6038.
[82] W. Xue, A.L. Hellewell, W.S. Gosal, S.W. Homans, E.W. Hewitt, S.E. Radford,
Fibril fragmentation enhances amyloid cytotoxicity, J. Biol. Chem. 284
(2009) 34272–34282.
[83] C. Holmes, D. Boche, D. Wilkinson, G. Yadegarfar, V. Hopkins, A. Bayer, R.W. Jones, R.
Bullock, S. Love, J.W. Neal, E. Zotova, J.A.R. Nicoll, Long-term effects of Aβ42
immunisation in Alzheimer's disease: follow-up of a randomised, placebo-controlled
phase I trial, Lancet 372 (2008) 216–223.