Download NMR studies of the amyloid β -peptide

NMR studies of the
amyloid β-peptide
Jens Danielsson
Stockholm University
© Jens Danielsson, Stockholm 2007
ISBN (91-7155-349-5 pp 1-86)
Printed in Sweden by Printers name, Stockholm 2007
Distributor: Department of Biochemistry and Biophysics
Dedicated to my Family
List of Papers
I.
Jens Danielsson, Jüri Jarvet, Peter Damberg and Astrid Gräslund, “Translational diffusion measured by PFG-NMR on full
length and fragments of the Alzheimer Aβ(1-40) peptide. Determination of hydrodynamic radii of random coil peptides of
varying length”, Magn Res Chem., 2002; 40:S89-S97
II.
Jüri Jarvet, Peter Damberg, Jens Danielsson, Ingrid Johansson, Göran Eriksson and Astrid Gräslund, “A left-handed 31
helical conformation in the Alzheimer Aβ(12-28) peptide”,
FEBS letters , 2003, 555(2), 371-374
III.
Jens Danielsson, Jüri Jarvet, Peter Damberg, and Astrid
Gräslund, “Two-Site Binding of β-Cyclodextrin to the Alzheimer Aβ(1-40) Peptide Measured with Combined PFGNMR Diffusion and Induced Chemical Shifts”, Biochemistry,
2004, 43, 6261-6269
IV.
Jens Danielsson, Jüri Jarvet, Peter Damberg and Astrid Gräslund, “The Alzheimer β-peptide shows temperaturedependent transitions between left-handed 31-helix, β-strand
and random coil secondary structures”, FEBS J., 2005, 272,
3938-3949.
V.
Jens Danielsson, August Andersson, Jüri Jarvet and Astrid
Gräslund. “15N-relaxation study of the Alzheimer β-peptide:
structural propensities and persistence length”, 2006, Magn
Res Chem. 2006, 44, S114-S121
VI.
Jens Danielsson, Roberta Pierattelli, Lucia Banci and Astrid
Gräslund, “High Resolution NMR Studies of the Zinc Binding Site of the Alzheimer’s Aβ-peptide”, 2006, FEBS J., doi:
10.1111/j.1742-4658.2006.05563.x
VII.
Jüri Jarvet, Jens Danielsson, Peter Damberg, Marta
Oleszczuk and Astrid Gräslund, “Structure and positioning of
the Alzheimer Aβ(1-40) peptide in SDS micelles using NMR
and paramagnetic probes.”, Manuscript in preparation
VIII.
Martin Dahlberg, Jens Danielsson, Astrid Gräslund and Atto
Laksonen, “Structure of the Amyloid β-peptide Fragment 1-9,
A combined molecular dynamics and NMR study”, Manuscript in preparation
Paper I and V is reproduced by permission of John Wiley & Sons Limited.
Paper II, IV and VI is reprinted by permission of Federation of the European Biochemical Societies
Paper III is reproduced with permission from American Chemical Society
Papers not included in this thesis
Amina S. Woods, Rafal Kaminski, Murat Oz, Yun Wang, Kurt Hauser,
Robin Goody,Hay-Yan J. Wang, Shelley N. Jackson, Peter Zeitz, Karla P.
Zeitz, Dorota Zolkowska, Raf Schepers, Michael Nold, Jens Danielson,
Astrid Gräslund, Vladana Vukojevic, Georgy Bakalkin, Allan Basbaum and
Toni Shippenberg, “Decoy Peptides that Bind Dynorphin Noncovalently
Prevent NMDA Receptor-Mediated Neurotoxicity”, 2006, J. Proteome Res.
3, 478-484.
August Andersson, Henrik Biverståhl, Jon Nordin, Jens Danielsson, Emma
Lindahl, Lena Mäler, “The membrane-induced structure of melittin is correlated with the fluidity of the lipids”, 2006, Biochim Biophys Acta,
doi:10.1016/j.bbamem.2006.07.009.
August Andersson, Jens Danielsson, Astrid Gräslund and Lena Mäler, “Kinetic models for peptide-induced membrane leakage in vesicles and cells”,
Submitted Manuscript
Contents
Introduction ...................................................................................................11
Biological background ...................................................................................13
Misfolding diseases.....................................................................................................13
Alzheimer’s disease is related to the amyloid β-peptide ..............................................15
Amyloid precursor protein ...........................................................................................15
Proteolytic degradation of APP and the formation of soluble Aβ .................................17
Oligomerization of the Aβ-peptide and neurotoxic mechanisms ..................................19
Fibrilization and structure of amyloid fibrils..................................................................21
Metal interaction of the soluble Aβ-peptide .................................................................22
The soluble Aβ-peptide’s membrane interactions........................................................23
Ligand binding to Aβ, and other strategies to prevent Aβ-toxicity ................................25
Theory of hydrodynamic dimensions and structural conversions of peptides
......................................................................................................................28
Dimensions of polymers and polypeptides ..................................................................28
Translational Diffusion of peptides ..............................................................................31
Structural transitions ...................................................................................................32
Spectroscopic methods.................................................................................35
NMR............................................................................................................................37
J-couplings and the structural interpretation thereof....................................................37
Nuclear spin relaxation and dynamics.........................................................................38
Linebroadening in NMR ..............................................................................................39
Diffusion measurements with NMR .............................................................................42
Circular Dichroism and secondary structure of peptides .............................................45
Estimation of secondary structure fraction with CD .....................................................46
Fluorescence spectroscopy.........................................................................................47
Results and discussion .................................................................................50
The soluble Aβ occurs as a mainly unfolded monomer ...............................................51
The monomeric Aβ has some residual structural propensities ....................................53
The Aβ peptide shows a temperature dependent structural behavior..........................55
The structural propensities of Aβ corresponds to structure both in membrane mimicking
media and in fibrils ......................................................................................................58
Metals such as copper and zinc interact with and alter the aggregation properties of Aβ
....................................................................................................................................62
Aβ binding of β-cyclodextrin involves aromatic residues and reduces aggregation .....65
Outlook ..........................................................................................................68
Sammanfattning på svenska.........................................................................70
Acknowledgements .......................................................................................72
References ....................................................................................................74
Abbreviations
β-cd
Aβ
AD
AFM
ALS
APP
CD
COSY
CSA
CSF
FTIR
HSQC
NMR
NOE
PFG-NMR
PII
TFE
ThT
TMS
β-cyclodextrin
Amyloid β peptide
Alzheimer’s disease
Atomic force microscopy
Amyotrophic lateral sclerosis
Amyloid Precursor Protein
Circular dichroism
Correlation spectroscopy
Chemical shift anisotropy
Cerebrospinal fluid
Fourier transformed infrared spectroscopy
Heteronuclear single quantum coherence
Nuclear magnetic resonance
Nuclear Overhauser effect
Pulsed field gradient NMR (see above)
Polyproline type II
Trifluoroethanol
Thioflavin T
Transmembrane segment
10
Introduction
Life is a delicate matter; the molecular machinery has to be tuned to function
in an extremely complex environment. The central dogma of biochemistry
describes the storage (DNA) and flow (RNA) of genetic information and the
transcription of the information into functional molecular units, proteins. In
order for life to be maintained, all three parts of the central dogma must
work, and the direct functional work is, with certain exceptions, done by the
proteins. Proteins are polypeptide chains constructed from a pool of twenty
different amino acids, each of which has its own specific characteristic properties. The function of a protein is closely related to the three dimensional
structure. This relationship may look different for different proteins; a protein may adopt its structure directly after the production and after that have a
rather rigid structure. Other proteins are unstructured, partly or totally, and a
well defined structure is induced when the protein exhibits its function. Yet
another possibility is the protein structure has to change for the protein to
function, maybe due to binding to a target.
The three dimensional structure of a protein is determined by the primary
structure, the amino acid sequence of the polypeptide chain. The relationship
between the primary structure and the secondary and tertiary structure is not
straightforward, and the relationship between sequence and structure is not
entirely understood. The folding process of the protein is quite fast, milliseconds to seconds and occurs spontaneously, at least for small and medium
size soluble proteins. Protein folding is a cooperative process where locally
folded regions fold together and stabilize the overall structure. This, in turn,
implies that the folding energy landscape is not flat, but can rather be seen as
a rough funnel with the native structure having the lowest energy and one or
more transition states manifested as local minima in the wall of the funnel.
This very complicated process is performed in a “biomolecular soup”
with proteins, RNA, DNA and membrane lipids (and much more) as ingredients. The polypeptide concentration in the cell is typically 10-20 mg/ml
which is very high. In order to make this complex machinery work, an intricate control system has evolved with chaperon proteins that keep the unfolded proteins from aggregation during the folding process and with degradation systems in the cases when folding fails.
In some cases when proteins are not folded correctly, either the protein is
not folded at all or folded in a way that inhibits the normal function of the
protein. In some cases the new structure, or lack of structure gives the pro11
tein a new, possibly pathogenic function. One could also imagine this as an
evolutionary process where the new fold somehow is favored while the old
one is not. In the case of prion diseases the misfolded protein induces misfolding of other proteins of the same kind. Considering the complexity of
folding it is surprising that diseases arising from misfolded proteins are not
more common than they are. Nevertheless misfolding diseases are an important field in medicine and pathophysiology and also in biophysics. Understanding the events that lead to misfolding of a protein may lead to the understanding of the mechanisms of normal protein folding. In addition,
knowledge about the molecular mechanisms underlying any disease provides
a possibility to design prevention or a cure for that specific disease. Important misfolding diseases are e.g. type II diabetes, Parkinson disease and Alzheimer’s disease.
This thesis is about the peptide which, misfolded and oligomerized, is believed to be the molecular basis of Alzheimer’s disease. I have made biophysical studies of this peptide in order to better understand the misfolding
and aggregation process of this peptide. The peptide is called the amyloid β
peptide and is the cleavage product of a ubiquitous membrane bound protein
called amyloid precursor protein or APP.
There is no established unambiguous definition of a peptide, but usually a
polypeptide chain with less than about 50 amino acids is considered a peptide. Peptides may or may not have a well defined structure, but short polypeptides usually have a high order of flexibility and no ordered structure.
Unstructured peptides and proteins or protein domains play an important part
in biology. One way to understand the underlying mechanisms for misfolding, and consequently also folding, is to understand the physical interactions
stabilizing and inducing structure, either the native or the misfolded.
12
Biological background
“Digerdöden drabbar alla, även den som inte vill”
Anonymous graffiti
This thesis concerns biophysical studies of Alzheimer’s amyloid β-peptide
(Aβ) in order to elucidate the molecular properties of the peptide that cause
it to form oligomers, aggregate into insoluble aggregates, form fibrils rich in
cross β secondary structure and finally accumulate in the brain and form
amyloid plaques. The Aβ-peptide arises as a cleavage product of a precursor
protein that is anchored to the neuronal cell membrane. In the membrane
bound state the peptide is assumed to be in an α-helical structure, but upon
cleavage the peptide leaves the membrane and goes into solution. The neurotoxic effect of Aβ seems to be linked to the presence of soluble aggregates of
the peptide and not directly to fibrils and plaques (Hsia et al., 1999; Lue et
al., 1999; McLean et al., 1999; Wang et al., 1999; Klein et al., 2001).
Upon aggregation and oligomerization and upon membrane interaction
the peptide undergoes a conformational change towards a β-rich structure
which builds up the fibrils that are the typical histopathological landmark of
Alzheimer’s disease. The life of the Aβ-peptide thus involves a change in the
secondary structure from the generic α-helical structure to the pathological β
sheet structure, with an important mainly unstructured solvent intermediate.
This means that Alzheimer’s disease may be classified as a protein misfolding disease. In this section, the life of the Aβ-peptide will be discussed, from
the membrane bound APP-form to the final aggregated state of the peptide.
Misfolding diseases
The molecular basis of misfolding diseases that are associated with fibrillar
amyloid aggregates is not yet fully understood. The family of these diseases
may be divided into two major groups, one which concerns neurological
13
degeneration and one that does not. The neurodegenerative misfolding diseases, in turn, consist of a wide variety of syndromes, including well-known
diseases as Alzheimer’s disease, amyotrophic lateral sclerosis (ALS), Huntington’s and Parkinson’s diseases. These diseases are so called neurodegenerative amyloid-related disorders (Chiti and Dobson, 2006). Among the nonneurodegenerative diseases one may mention the systemic amyloidosis and
the more localized type II diabetes.
The prion diseases are other important examples, causing spongiform
neuropathies. Among the most well known prion diseases are CreutzfeldtJacobs disease, bovine spongiform encephalopathy (mad cow disease) and
scrapie. The macroscopic appearance of the tissues affected by these misfolding disorders is similar. The term spongiform gives a hint of the appearance of the amyloid affected tissues: The accumulation of amyloid in some
cases kills the surrounding cells and thus creates “holes” in the tissue. This
makes the tissue appear as a sponge. These features were described already
in the 17th century as waxy liver and spongy spleens. In the mid 19th century, staining experiments showed that affected tissue stained similar to cellulose, and the scientist Rudolph Virchow drew the conclusion that the causing substance was cellulose and named it amyloid from Latin amylum and
Greek amylon for cellulose (Sipe and Cohen, 2000) .
The stained structures, i.e. the amyloid plaques, are aggregates of fibrils
composed of one or more types of molecules, specific to the disease. In some
cases the amyloid deposition in the tissues can be huge, up to kilograms, as
in systemic amyloidosis (Bucciantini et al., 2002). In other cases as in neurodegenerative amyloid diseases the pathological impact has a much earlier
onset and the depositions are microscopic even when the disease has caused
the death of the patient. The fibrils are long and thin, 60-130Å, and are composed of otherwise soluble proteins (Sipe and Cohen, 2000; Ghiso and
Frangione, 2002).
Independent of the molecular origin of the fibrils they have some common properties, e.g. amyloid fibrils consist of aggregates of molecules in βsheet conformation, regardless of the native peptide structure (Ghiso and
Frangione, 2002; Murphy, 2002; Dobson, 2003). The cell dysfunction or
death caused by the amyloid depositions may have different origins. The
deposition itself can mechanically disturb its surroundings or the prefibrillar
aggregates can be toxic or in other ways disturb or inhibit normal cell functions (Selkoe, 2003; Quist et al., 2005; Chiti and Dobson, 2006).
14
Alzheimer’s disease is related to the amyloid β-peptide
One of the most important of the misfolding diseases is Alzheimer’s disease
(AD), where the amyloid deposition is in the brain and causes severe dementia and eventually death. This disease affects approximately 10 % of all humans at 65 years of age and every second of all those who have reached 85
years (Gaggelli et al., 2006).
AD is named after the psychiatrist and neuro-pathologist Alois Alzheimer. He described the histological features of AD in a famous paper 1907
called “Über eine eigenartige Erkrankung der Hirnrinde” (About a peculiar
disease of the brain cortex) (Alzheimer, 1907).
Alzheimer’s disease shows accumulation of amyloid both intra- and extra-cellularly. Intracellularly the tau-protein forms amyloid fibrils and extracellularly the fibrils are formed mainly by the amyloid β-peptide (Hardy
and Selkoe, 2002; Selkoe, 2003) These extracellular depositions are called
neuritic (or senile) plaques. Deposition of tau-protein alone gives a dementia
other than AD, and this is called fronto-temporal dementia, while deposition
of Aβ alone induces tau-deposition and results in AD (Evin and Weidemann,
2002; Hardy and Selkoe, 2002).
Aβ is a 39-42 residue peptide, most commonly 40 or 42 residues, that is
cleaved from a transmembrane protein, the amyloid precursor protein (APP).
In vivo, the Aβ concentration is nanomolar. In vitro the cleaved Aβ occurs a
monomer at low concentrations, ≤ 30 µM, and at physiological pH and room
temperature. Mainly, the Aβ-peptide is in random coil conformation at these
conditions and there is no significant difference in structure between the 40
and 42 residue long fragments (Riek et al., 2001). However, the 42 residue
fragment Aβ(1-42) is more prone to assemble into fibrils already at low concentrations (Harper and Lansbury, 1997). Other fragments of the Aβ-peptide
also form fibrils, and the central hydrophobic cluster Aβ(16-22) is the shortest among the fibril-forming fragments (Balbach et al., 2000).
Amyloid precursor protein
The Aβ-peptide is an enzymatic cleavage product of the amyloid precursor
protein (APP), a ubiquitous protein found in different tissues, but exists in
higher concentrations in the brain. APP, discovered as late as 1987, is a
transmembrane protein that is anchored to the neuron cell membrane with
one transmembrane segment (TMS). There are different isoforms of the protein with different sizes, ranging from 695 to 770 residues. The most abun15
dant isoform in the neuron is the 695-residue APP. The difference between
the shorter and the longer variants is a central protease inhibitor segment that
is present in the longer fragments. The longer isoforms are present in the
blood platelets and are involved in the coagulation cascade regulation. All
isoforms of APP contain the Aβ-segment (Selkoe, 1998).
D596
A638
Figure 1. Schematic picture of APP inserted into a biological membrane. The transmembrane segment is represented as a cylinder and the Aβ fragment is highlighted
in a box, with the sequence of the peptide shown. In the N-terminal extracellular part
of APP two specific binding sites for divalent metal ions are located. The proteolytic
cleavage sites are also shown.
APP has a hydrophobic segment that is assumed to be the TMS, and this
hydrophobic TMS is located in the C-terminal region of the protein ranging
from position G625 to L648 (Figure 1). The Aβ-segment ranges from residue
D596 to V636 or A638 depending on Aβ length. Thus, the Aβ-segment is partially located in the membrane. The TMS is assumed to be an α-helix, even
though no structure of the membrane bound APP in the membrane has been
reported. Several studies of the peptide in membrane mimicking systems
suggest that the Aβ-segment located in the membrane adopts an α-helical
secondary structure (Coles et al., 1998; Shao et al., 1999). This, and the fact
that the rest of the putative membrane spanning region of APP consists of
residues that are prone to adopt α-helical secondary structure suggest that the
whole TMS is helical.
The biological function of neuronal APP is not entirely known. The topology of the protein with an extracellular large part anchored to the mem16
brane with one TMS resembles that of a receptor, and APP has been suggested to be involved in G-coupled cell signalling as well as being a regulating protein of cell trafficking (Okamoto et al., 1995; Sabo et al., 2001).
APP has also been suggested to be involved in metal homeostasis of the
cell. APP has selective metal binding sites and it participates in the regulation of the copper levels and is affected by the copper level. Lowering the
copper levels down-regulates the gene expression of APP and APP gene
knockout increases copper levels (Storey and Cappai, 1999; Phinney et al.,
2003; Bellingham et al., 2004a-b; Maynard et al., 2005). Depletion of metals
in drinking water gave lower Aβ fibril formation among rabbits in vivo
(Sparks and Schreurs, 2003). In the extracellular part of APP one can find
specific binding sites for copper and zinc, close to the N-terminus of the
protein. There are also other specific binding sites on APP that bind heparin
and collagen (Frederickson et al., 2005).
Not only the membrane bound APP may exhibit specific functions but
also a soluble fragment of APP, that is the degradation product of αsecretase cleavage, is responsible for potential functions of APP. The structure of this cleaved fragment has only been reported as a course grain model
(Gralle et al., 2006). This soluble fragment is responsible for APP effects in
coagulation (Selkoe DJ, 1998). APP may have multiple functions in the
membrane-bound native state or in the soluble cleaved form. The neurotoxic
peptide fragments Aβ(1-40) and Aβ(1-42) are however the results of double
proteolytic cleavage of APP by two secretases, other than α-secretase.
Proteolytic degradation of APP and the formation of
soluble Aβ
Normal APP is anchored to the membrane with one transmembrane segment
as described above. In the normal degradation of APP two proteases are
involved, which produce three APP fragments. First, α-secretase cleaves the
protein at position 625 on the extracellular side and produces the large fragment that is suggested to have some biological function. The rest of the protein is still attached to the membrane and is cleaved by γ-secretase at position 636-638 and the two produced fragments leave the membrane. This
pathway of degradation of APP is called the non-amyloidogenic pathway
because the released fragments form neither toxic oligomers nor fibrils
(Maccioni et al., 2001; Hardy and Selkoe, 2002; Blennow et al., 2006).
The pathologic, amyloidogenic pathway also involves the γ-secretase but the
extracellular cleavage is performed by another protease, a β-secretase. The
β-secretase is a membrane bound protease enzyme and the full name is β-site
17
APP-cleaving enzyme 1 (BASE1) (Vassar et al., 1999). BASE1 cleaves the
APP at position 596 and upon subsequent cleavage by γ-secretase the 40-42
residue Aβ-peptide is the produced (Figure 1).
This sequence of events results in that the peptide is being partly inserted
into the membrane when the rest of the APP is enzymaticly removed by the
secretases. Generally the Aβ peptide is assumed to immediately leave the
membrane and go into solution, but this hypothesis has recently been challenged and the peptide has been suggested to stay in the membrane and directly exhibit its toxic effect (Marchesi, 2005). In solution the peptide appears as a monomer at sufficiently low concentrations. The cleaved Aβpeptide has the sequence:
DAEFR5HDSGY10EVHHQ15KLVFF20AEDVG25SNKGA30IIGLM35VGGVV40IA
The peptide has some amphipathic properties with a hydrophobic C-terminal
region and a hydrophilic N-terminal region. This is a property that the Aβpeptide shares with other amyloidogenic peptides and proteins such as those
derived from Huntingtin and the 106-126 fragment of the prion peptide. The
much longer amyloidogenic protein α-synuclein shows a similar pattern, but
this protein has periodic alternating regions of hydrophobic and hydrophilic
regions (Murphy, 2002; Chiti and Dobson, 2006).
Escaping the membrane involves a structural transition of the Aβ-peptide
from the membrane-bound α-helical secondary structure to the mainly unstructured solution state peptide. Solution state studies of Aβ reveal that
there are some non-random regions of the peptide, in the central parts, but
that no well-defined secondary structure is present in aqueous solution (Riek
et al., 2001). Molecular dynamics simulations of the Aβ(1-42) peptide
showed that also the N-terminal region exhibited some order (Flöck et al.,
2006). MD studies of the monomeric soluble Aβ-peptide have mainly concerned the α-helix to β-sheet structural conformational transition and the
peptide was forced into a helical conformation as an initial condition
(Borreguero et al., 2005; Xu et al., 2005).
The physiological concentration of Aβ in the cerebrospinal fluid (CSF) is
nanomolar, as in plasma. This is much below the critical concentration for
spontaneous aggregation to initiate (Harper and Lansbury, 1997). The critical concentrations for aggregation of Aβ(1-40) and Aβ(1-42) differ. The
concentration is slightly higher for Aβ(1-40), meaning that monomeric
Aβ(1-40) is more stable than the longer fragment. This implies that in order
to aggregate, Aβ has to be enriched in specific regions in the brain to a concentration above the critical concentration. This can be achieved in different
ways, where one is obtained by binding of Aβ to a membrane which would
increase the effective concentration (Terzi et al., 1997).
After escaping the membrane the Aβ-peptide is removed from the tissue
by peptide degradation, performed by the enzymes neprilysin and endo18
thelin-converting enzyme. A flux of Aβ across the blood-brain barrier is also
present, assisted by co-proteins (Carson and Turner, 2002; Tanzi et al.,
2004). An imbalance between production and removal of the peptide increases the amount of peptide available for toxic action.
Oligomerization of the Aβ-peptide and neurotoxic
mechanisms
Despite the fact that there is strong evidence to support the hypothesis that
Aβ is responsible for the dementia of AD (Chen et al., 2000; Janus et al.,
2000; Selkoe and Podlisny, 2002; Westerman et al., 2002), the soluble
monomeric form of Aβ does not seem to exhibit any direct neurotoxicity.
The concentration of free monomeric Aβ does not directly relate to the severity of the memory impairment (Lesné et al., 2006), but soluble oligomeric
forms of Aβ seem to exhibit that correlation (Hartley et al., 1999; Hsia et al.,
1999; Ward et al., 2000; Klein et al., 2001). The discovery of the soluble
oligomers and the correlation between their presence and dementia have led
to an amyloid cascade hypothesis that describes the cause of AD on a molecular level (Figure 2) (Hardy and Selkoe, 2002),.
Figure 2. Two pathways for aggregation of the amyloid β peptide. In the case of
protofibril formation and subsequent assembly into fibrils the peptide is caught into
the stable fibrils and may be kept from toxic effects. The neurotoxic effect brought
about by Aβ may be caused by a dodecamer (n = 12) of the peptide.
The Aβ-peptide first undergoes oligomerization and then further aggregation into protofibrils and fibrils. The oligomers are soluble and are suggested
to play an important role in the pathogenic cascade of AD by being toxic to
neurons (Bucciantini et al., 2002; Gong et al., 2003; Dobson, 2004). The
19
oligomers share their topological features with the oligomers of other amyloidogenic peptides. This suggests that there is a common cell-toxic mechanism exhibited by these peptides (Kayed et al., 2003).
The structure of the rather newly discovered oligomeric species is not
known in detail. Recently a specific Aβ oligomer has been suggested to have
specific toxic effects on neurons. This is a dodecamer that binds specifically
to the dendritic processes of the neuron and blocks the membrane
potentiation (Barghorn et al., 2005; Muresan and Muresan, 2006). This dodecamer also impairs memory function in mice, the memory impairment is
directly linked to the prescence of dodecameric Aβ (Lesné et al., 2006). In
molecular terms the oligomer can be characterized as a micelle of Aβpeptides with the hydrophobic C-terminus buried in the micellar center and a
critical micelle concentration of 17.6 µM (Kayed et al., 2003; Sabaté and
Estelrich, 2005). The peptides in the oligomer are mainly unstructured (Chiti
and Dobson, 2006).
The oligomeric Aβ may aggregate further and build up protofibrils and
fibrils. However, the oligomers are not necessary for fibril formation and
oligomerization and fibrillation are suggested to be different pathways in Aβ
metabolism (Figure 2) (Bitan et al., 2003; Barghorn et al., 2005; Chen and
Glabe, 2006). Formation of protofibrils and fibrils may be a protective event
in order to lower the oligomeric concentration (Carrotta et al., 2005).
The mechanism by which the Aβ oligomer exhibits neurotoxicity is not
clear, but production of reactive oxygen species has been suggested. Another
suggested mechanism is that the oligomers change cell membrane function
and thereby disturb calcium homeostasis and/or membrane dynamic properties. Yet another mechanism suggested is alteration of metal homeostasis
(Bush et al., 2003b; Walsh and Selkoe, 2004). A common feature for all
these proposed mechanisms is that they lead to destruction of synapses and
consequently cell death. The basic requisite for Aβ to become toxic is the
structural conversion from the non-toxic soluble form to the toxic oligomeric
form. The toxicity is induced by a misfolding event (Chiti and Dobson,
2006).
The oligomerization may expose certain reactive residues of the peptide
and the number of reactive residues should increase upon aggregation into
the dodecamer. More and more evidence suggests that the oligomeric forms
of the peptide alter the membrane integrity of the cell. In vitro selective
cation channels are formed by Aβ-peptide. This is also supported by the fact
that Aβ changes the Ca2+ homeostasis giving rise to increased intracellular
Ca2+ -levels. These channels do not show a single morphology, but an AFM
study suggests that the channels have well-defined structures and similar
topology as seen in channels formed by other amyloidogenic peptides
(Arispe et al., 1993; Lin et al., 2001; Quist et al., 2005).
At this stage in the life of Aβ several structural transitions have occured,
from the membrane-anchored APP-bound largely α-helical peptide to the
20
soluble non-toxic monomeric peptide and further on to the oligomeric toxic
state of the peptide. This is however not all, since the peptide can undergo
yet another transition and accumulate to fibrils with a very well-defined
structure.
Fibrilization and structure of amyloid fibrils
The assembly of Aβ peptides into fibrils may occur either on the so called
activated monomer (Taylor et al., 2003) to fibril-end basis or by assembling
of oligomers, involving a bead on a string model. The kinetics of fibrilization of supersaturated Aβ includes a lag phase where the monomeric peptide
is in fast exchange with oligomeric species. After some time a seed is
formed, a nucleus of aggregated peptides in fibril formation, and this seed
promotes rapid aggregation of peptides into the fibrillar structure. The time
gap before the seed is formed and rapid aggregation begins is called the lag
time and is very dependent on sample conditions and may range from minutes to days (Murphy, 2002; Sabaté and Estelrich, 2005). When the aggregation process is initiated it is a single non-cooperative process (Carrotta et al.,
2005). The aggregated Aβ, earlier assumed to be a toxic species, has been
suggested to be a protective escape route for the peptide. The peptide is kept
out of the equilibrium between monomers and toxic oligomers (Carrotta et
al., 2005; Barnham et al., 2006).
In the aggregated form Aβ forms amyloid fibrils, a structure that shows
features that are similar for all amyloidogenic proteins and peptides. The
general topological properties of the fibrils are those of an elongated fiber,
up to a µm long and approximately 20 nm in diameter. The fibril consists of
two filaments, twisted around each other in a left-handed helix (Sachse et al.,
2006).
On a molecular level the structure of Aβ in the fibrils has recently been
reported using solid state NMR, site-specific mutagenesis and X-ray diffraction. In the fibrils Aβ adopts a β-sheet secondary conformation. The Nterminus of the peptide is mainly unstructured and there are two β segments
in the central region and the C-terminal regions. The residues that constitute
the β-segments are 17-24/25 and 31-40 and these segments are separated by
a turn (Figure 4). The segments are kept together by hydrophobic interactions and the peptide is hydrogen-bonded to the adjacent peptide along the
fibril axis (Shivaprasad and Wetzel, 2004, 2006; Lührs et al., 2005; Nelson
et al., 2005; Chimon and Ishii, 2005; Sachse et al., 2006; Petkova et al.,
2006).
21
Figure 3. The molecular arrangement in Aβ fibrils. Each monomer has two regions
with β sheets that are held together by hydrophobic interactions. The monomers are
kept together by hydrogen bonds between the molecules. The hydrogen bonds are
here represented by thick black lines.
The fibril is most likely the final stage of the Aβ-peptide and in this superstructure the peptide adopts a β-strand secondary structure. Thus, in its
life-span Aβ undergoes three structural transition where the transition from
mainly unordered monomeric peptide to the fibril-bound cross-β structure is
the final one. This structural transition seems to remove the peptide from the
toxic pool and fix it in an immobile state.
Metal interaction of the soluble Aβ-peptide
An increased copper, iron and zinc concentration has been found in the
brains of Alzheimer’s disease patients, enriched in the core of the amyloid
plaques but also generally in the cortical tissue (mainly zinc) (Lovell et al.,
1998; Religa et al., 2006). As described above, APP has specific metal binding sites for copper and zinc and is believed to participate in the regulation
of metal homeostasis. The soluble monomeric Aβ-peptide also binds metals,
mainly copper and zinc at specific binding site(s). These site(s) is/are not
identical with the binding sites of APP which are located in the extracellular
domain of APP. Binding of metal to the peptide alters the solubility properties of the peptide in a non-trivial manner.
High concentrations of copper and zinc induce aggregation of Aβ, and
high concentration in this case corresponds to a metal:peptide ratio >1 (Bush
et al., 1994b; Brown et al., 1997; Huang et al., 1997; Raman et al., 2005).
The aggregate formed is suggested to be amorphous and unspecific and it
does not contain any well-defined structure. High metal concentrations may
therefore prevent the formation of the cross-β rich fibrils discussed above
(Brown et al., 1997; Yoshiike et al., 2001; House et al., 2004; Raman et al.,
22
2005). The metal induced aggregation of Aβ has been suggested to be the
result of intermolecular His-His bridging after which an amorphous aggregation occurs (Smith et al., 2006; Stellato et al., 2006; Syme and Viles, 2006).
Low concentrations of copper and zinc, on the other hand, reduce aggregation of Aβ and help in keeping it as a soluble monomer. Metal interaction
is also able to destabilize Aβ oligomers and shift the monomer-oligomer
equilibrium towards monomers (Cardoso et al., 2005; Garai et al., 2006).
The normal zinc and copper concentrations in the cerebrospinal fluid (CSF)
are 3 µM and 1 µM respectively, but during synaptic transmission the concentration of Zn2+ locally increases up to 0.3 mM (Molina et al., 1998; Bush,
2003a). In the normal case (when the Aβ concentration in CSF is ~ nM) the
low metal concentration in the CSF helps to keep the peptide monomeric and
soluble but an altered metal homeostasis may, directly or indirectly, induce
toxic oligomers.
Metal ions like copper and zinc bind with high affinity and specificity to
the monomeric Aβ. The binding sites for copper and zinc have been shown
to be located in the N-terminal part of the peptide and for copper the coordination has been suggested to be planar. Increasing evidence show that the
three histidines, His6, 13 and 14 are involved as ligands. The fourth ligand
has been suggested to be Tyr10 but N-terminal mutations and acetylation
suggest that the N-terminal amide nitrogen acts as the fourth ligand
(Kowalik-Jankowska et al., 2003; Syme et al., 2004; Karr et al., 2005;
Tickler et al., 2005). Also in the case of zinc the histidines have been shown
to be necessary for high affinity binding to Aβ (Liu et al., 1999; Miura et al.,
2000; Curtain et al., 2001; Syme and Viles, 2006). In the case of the Nterminal fragment Aβ(1-28) and Aβ(1-16) site specific mutations where one
or two of the ligands were replaced by alanines show that His13 and His 14
are absolutely crucial for zinc binding while His6 increases the affinity significantly, in (Yang et al., 2000; Kowalik-Jankowska et al., 2003).
The identity of the fourth ligand, in addition to the three histidines, necessary for zinc coordination has been under some debate, and experiments
have provided contradictory results. In most studies mainly shorter fragments of Aβ have been used. In some of these studies Tyr10 has been suggested to be a ligand, but also Glu11, Arg5 or the N-terminus (Zirah et al.,
2004, 2006; Mekmouche et al., 2005; Syme and Viles, 2006). When the full
length peptide was used to study metal binding the results suggest that the Nterminus is the fourth ligand (Hou and Zagorski, 2006).
The soluble Aβ-peptide’s membrane interactions
As described earlier Aβ is produced by the cleavage of APP inside the membrane and thus the peptide is initially located in the membrane. Immediately
23
after cleavage the peptide leaves the membrane and ends up in monomeric,
oligomeric and subsequently aggregated amyloid forms. The most likely
toxic entity is the oligomeric form of the peptide but the exact toxic mechanism is still not entirely understood.
The toxic mechanism of the oligomers is thought to be either a direct or
indirect mechanism, mediated through oxidative stress or by inducing inflammatory processes. More and more evidence also suggests that the oligomeric forms of the peptide alter the membrane integrity of the cell. In
vitro, selective cation channels are formed by the Aβ-peptide This is also
supported by the fact that Aβ changes the Ca2+ homeostasis with increased
intracellular Ca2+-levels (Arispe et al., 1993; Lin et al., 2001). These channels do not show a single morphology, but an AFM study suggests the channels to have a well-defined structure and consist of 4-6 peptides. The pore
structures are not known in detail, but similarities with β-barrel pore forming
toxins has led to the suggestion that the peptide, which is prone to form β
structures, forms β-barrel pores (Lin et al., 2001; Lashuel et al., 2002).
Aβ induces leakage of sodium, potassium and calcium into lipid vesicles,
but only in vesicles with negatively (partially or completely) charged
headgroups (Kourie et al., 2001; Alarcón et al., 2006). The peptide does not
insert itself into neutral membranes and this is suggested to explain the lack
of peptide-induced influx of ions. In negatively charged model membranes
the peptide both inserts into the membrane and induces leakage (Bokvist et
al., 2004). Interestingly, in the presence of metal ions (copper and zinc) the
peptide, when interacting with the negatively charged vesicle, exhibits a
structural transition from a dominating β structure to a high α-helical content. This suggests that, in presence of copper and zinc the oligomeric aggregate in the membrane is formed by a small number of transmembrane helices, and this may build up the channel, disrupting the membrane integrity. A
particular property of the Aβ channel is that zinc inhibits the channel permeability, suggesting that zinc either blocks the channel or alters the channels
properties, such as structure, in such way that ion leakage stops (Arispe et
al., 1996).
The metal binding site of Aβ is not located in the assumed membrane
spanning region but still seems to influence the membrane interaction of the
peptide. The shorter fragment Aβ(1-28) and the reversed sequence Aβ(40-1)
neither insert into the vesicles, nor cause any leakage (Curtain et al., 2001,
2003; Alarcón et al., 2006). The hydrophobic region in the shorter fragment
Aβ(1-28) is too short to penetrate the membrane. The hydrophobic region in
the membrane corresponds to 20-23 amino acids in a α-helical conformation.
It should be pointed out that the putative membrane spanning residues, in the
Aβ peptide, are not the same residues that form the transmembrane segment
of APP.
The structure of the membrane bound Aβ has been studied in various
membrane mimicking media, such as SDS micelles or TFE/water mixtures.
24
The results reveal two regions that adopt α-helices, i.e. the C-terminal region
including residues 29-36/38 and a central region including residues 15/1624. These regions could correspond to the transmembrane segment of the
membrane bound soluble Aβ. The α-helical regions are separated by a kink
corresponding to residues 25-29 (Coles et al., 1998; Watson et al., 1998;
Shao et al., 1999; Crescenzi et al., 2002; Lau et al., 2003).
Ligand binding to Aβ, and other strategies to prevent
Aβ-toxicity
The pathology of AD includes a series of stages starting with increased levels of soluble Aβ, possibly due to mutations in APP close to the cleavage
sites of the proteases or a decreased clearance of produced Aβ. Following
the increased level of Aβ-peptide, oligomerization occurs and oligomeric
and protofibrilic forms of the peptide appear. The oligomers/protofibrils then
either induce inflammatory processes in microglia and astrocytes or cause
direct synaptic and neuritic injuries. Membrane integrity changes may cause
changed ionic homeostasis, and thus oxidative stress and injury. This causes
widespread neuritic death and consequently dementia and death (Ghiso and
Frangione, 2002; Hardy and Selkoe, 2002; Chiti and Dobson, 2006).
Several families of strategies to prevent AD can be identified (Hardy and
Selkoe, 2002; Dobson, 2004). First, the action of the proteases could be inhibited or altered, which thereby lowers the level of Aβ-peptide. Inhibition
of γ- or β-secretase would stop Aβ production totally. However, this strategy
would also inhibit other, potentially important functions of the secretases
(Masters et al., 2006). Related to this approach is the administration of a
molecule that targets APP and inhibits the proteolytic effects of the proteases
(Espeseth et al., 2005). Second, the oligomerization of the peptide could be a
target for inhibition as well as the degradation of already formed oligomers.
This may be done by changing the properties of the monomer to inhibit the
aggregation process or by immuno-neutralization of soluble Aβ-oligomers
(Klein et al., 2001; Brendza et al., 2005; Garai et al., 2006; Ali et al., 2006).
Third, the inflammatory process induced in the disease can be a target for
treatment. Another strategy is chelation of metal ions such as Cu2+ and Zn2+,
by chelators such as Clioquinol. This is closely connected to the strategy that
targets oligomerization of the peptide (Raman et al., 2005; White et al.,
2006). In addition to these strategies selective Aβ-channel blocking and addition of membrane stabilizing agents could be ways to in prevent the toxic
events of AD (Kagan, 2005).
25
One of the treatment/prevention strategies presented above is very suitable for studies with biophysical methods; namely ligand binding to the peptide. The ligand should be constructed such that the properties of the complex differ from those of the Aβ-peptide alone, and thus the ligand prevents
the toxic effects. Ligands are also a good strategy because it may be possible
to administer them orally. A number of different ligands have been proposed. Some have an aggregation reducing effect and these ligands may also
reduce toxicity. Among other substances, nicotine is reported to bind to and
inhibit aggregation of the Aβ-peptide. The interaction is suggested to be
non-specific and involves the N-terminal histidines, either direct or indirect
by a chelating effect and thus inhibit normal metal interactions with the His
residues (Salomon et al., 1996; Dickerson and Janda, 2003; Moore et al.,
2004). As described above, metal binding to the Aβ-peptide alters the aggregation properties of the peptide. Curcumin from the Turmeric root has also
been shown to interact with Aβ and reduce peptide aggregation. The interaction seems also to destabilize formed fibrils, possible by pushing the equilibrium in the monomer-oligomer-fibril system towards the monomeric form
(Ono et al., 2004).
Another strategy is to use peptide ligands to induce peptide-peptide interactions. Several short peptides interact specifically with the soluble Aβpeptide and particularly sequences of the peptide itself have been studied
(Santhoshkumar and Sharma, 2004; Schwarzman et al., 2005). Different
fragments of the peptide, mainly including the hydrophobic central sequence
16-21, reduce fibril formation and neurotoxicity (Tjernberg et al., 1996;
Hetényi et al., 2002; Matsunaga et al., 2004).
The cyclic oligosaccharide, β-cyclodextrin, interacts with the Aβ-peptide
and the interaction is suggested to be between the inside of the cyclodextrin
ring and Phe19 or Phe20 (Qin et al., 2002). The inhibition of aggregation has
been determined with scintillation proximity assay to a 50 % inhibition by a
5 mM concentration of β-cyclodextrin and the interaction inhibits the formation of the soluble oligomers (Yu et al., 2002). Mass spectroscopy has shown
that the stoichiometry of the Aβ-peptide and β-cyclodextrin is one-to-one
(Camilleri et al., 1994).
Cyclodextrins form a family of cyclic oligosaccharides that are e.g. used
in pharmaceutical preparations when slow release of a drug is of interest.
The cyclodextrins are torus-shaped rings built up by different numbers of
glucose residues. There are three major types of cyclodextrins, the α-, β- and
γ-cyclodextrins, in which the rings consist of six, seven and eight glucopyranose units, respectively. The cyclodextrins have different characteristics due to differences in size, e.g. the solubility. The cyclodextrin molecules are amphiphilic molecules. The cavity of the torus is hydrophobic
while the rest is hydrophilic, making the cavities favourable places for
26
Figure 4. The structure of β-cyclodextrin. Light regions represent hydrophilic regions and dark regions represent hydrophobic regions. The two pictures reflect the
two different sides of the oligosaccharide.
hydrophobic interactions (Figure 4). The differences in size of the hydrophobic cavity in the different cyclodextrins give possibilities of specificity in
interaction (Szejtli, 1998; Aachmann, 2003).
The main interaction with amino acid residues seems to be between the
aromatic rings of phenylalanines and the hydrophobic cavity of cyclodextrin.
The dissociation constant of a single phenylalanine amino acid and the different cyclodextrins is 23 mM, 56 mM and 7 mM for the α, β, and γ- cyclodextrin, respectively (Matsuyama et al., 1987; Castronouvo et al., 1995;
Aachmann, 2001). In this case, with phenylalanine alone, the interaction is
strongest with the cyclodextrin with the largest hydrophopic cavity and generally the interactions involving cyclodextrins are one-to-one (Szejtli, 1998).
However, there is no direct correlation between cavity size and affinity for
phenylalanine.
27
Theory of hydrodynamic dimensions and
structural conversions of peptides
“Whenever a theory appears to you as the only possible one,
take this as a sign that you have neither understood the theory
nor the problem which it was intended to solve”
Karl Popper
In addition to structural and dynamic properties of a peptide/protein it is
important to characterize the hydrodynamic properties, such as hydrodynamic radius and diffusion coefficient that are related to structural and dynamic properties. Stoke-Einstein’s equation relates the diffusion coefficient
to the hydrodynamic radius, RH. RH may provide information on the folding
and structural state as well as interaction with other molecules or selfaggregation (Cameron and Fielding, 2001; Dehner and Kessler, 2005). The
dynamic hydration of a peptide or protein is also reflected in the hydrodynamic radius (Halle and Davidovic, 2003). In this section the framework for
the studies of RH presented in this thesis are outlined. Some polypeptide theory used to describe general peptides, such as Aβ is discussed.
The Aβ peptide has some structural propensities that include undergoing a
structural transition when raising the temperature. Studying the thermodynamics of this structural transition provides information on the stability and
energetics of the structure. The method used to calculate enthalpies and cooperativity of the transition is also outlined in this section.
Dimensions of polymers and polypeptides
A polypeptide chain can in its simplest form be approximated with a random
walk with stepsize l0. The radius of gyration for this simple model is given
by:
2
| Rg |
28
1
=
N
∑
i
 i
j
rj −
∑
 j =1 N + 1
N +1− j 
rj 
∑
j =i +1 N + 1

N
2
(1)
Here N is the number of residues, ri is the vector pointing at residue i and < >
represents the average. In this model the radius of gyration is the average
distance of a residue to the center of mass.
In a simple random walk model the typical extension of a random walk
with N steps and step size l0 is given by:
| R |2 =
N
∑ li ⋅ l j = ∑ | li |2 = Nl 02
i, j
(2)
i
This gives the end-to-end distance, which is directly proportional to the radius of gyration. Thus, the radius of gyration increases with the square root
of the number of segments in a freely jointed chain. For such a freely jointed
chain with no interactions between the segments the characteristic length, the
step size, is equal to the length of the segment. For a random walk with constrained angles the step size is bigger than the length of the segment but the
overall scaling is the same, if the number of steps (segments) is large
enough. This simple model of a polypeptide chain as a random walk is unfortunately not very consistent with reality. First, all directions are not
equally probable between subsequent segments. Second, a true polypeptide
chain must be self-avoiding. It is not possible for two segments to exist at the
same place at the same time.
A model with segments of finite volume with a repulsive interaction between the segment and the rest of the chain was proposed by Flory and de
Gennes (Flory, 1988). A simple argument where the free energy, F, of a
chain with N segments is evaluated below. Assume that the radius of the
volume occupied of the chain is R. The concentration of segments is then:
c = k1
N
R3
(3)
Where k1 is a proportionality constant. The repulsive interaction between the
segments will give an interaction energy that is proportional to the number
of pairs of segments and thus to the square of the concentration, and proportional to the volume.
The entropy, S, for a freely jointed chain is:
S = −k B
3R 2
2 Nl 02
(4)
29
The free energy is given by F = E-TS, where E is the energy, and using equations 3 and 4 an expression for the energy is obtained:
N2
3R 2
F = k 2 3 + k BT
R
2 Nl 02
(5)
The radius that minimizes the free energy in equation 5 gives:
R 5 = k2
l 02
N3
k BT
R = const ⋅ N
3
5
(6)
This result is remarkably close to experimental data despite the simplicity
and many approximations in the model (Flory, 1988).
A more rigorous treatment of the free energy gives a more complex expression. If only the terms depending on R are kept it is:
F
1
ε
N 2 3 R2 v2 N 3
R
= (1 −
)v d +
+
− 2 ln
2
6
k BT 2
vk B T R
2 Nl 0
6 R
l0
(7)
In equation 7 three new parameters are introduced: d is the dimensionality, v
is the volume of one segment in the chain and ε describes the monomermonomer interaction, and is an attractive interaction if it is positive and a
repulsive when it is negative.
When introducing the parameter δ = 1-ε / (vkBT), we see from examining
equation 7 that there are three possibilities, δ > 0, δ = 0 and δ < 0.
When for δ > 0 differentiation of equation 7 gives the radius of gyration
which scales with N as:
3
R ∝ N 2+ d
(8)
For the 3D case this is very close to experimental and simulation data and
exactly as predicted by the simple approach above. This is called the Flory
scaling and the chain is said to be in a swollen state (de Gennes, 1979).
A special case is obtained when δ = 0, the so called θ-point. Here the radius scales as the random walk of the freely jointed chain, R ∝ N½. In this
case the interactions between the monomers are equal to the interactions
between the solvent and the segments.
30
In both of the above described cases the scaling depends on N if δ is small
but positive. For short chains where N < 1 / δ 2 the random walk scaling
dominates, and for longer chains the Flory scaling is valid. For δ < 0 the
chain tends to collapse and the radius scales as R ∝ N1/3.
One can conclude that the radius of gyration and thus the hydrodynamic
radius is related to the number of segments in the chain by a simple scaling
law (Brochard and de Gennes, 1977; Fitzkee and Rose, 2004; Kohn et al.,
2004):
R ∝ Nν
(9)
All these expressions are derived and valid for long chains, such as polypeptides. But equation 9 is of course valid for all types of macromolecules.
Light scattering experiments on highly denaturated proteins and peptides
shows a scaling factor of ν = 0.598 and Monte Carlo simulations yield the
same result (Miller and Goebel, 1968; Lifshitz et al., 1978; Fitzkee and
Rose, 2004; Kohn et al., 2004).
Translational Diffusion of peptides
The radius of gyration is related to the hydrodynamic radius, and is directly
proportional, Rg = dRH. Where d is a proportionality factor. The upper limit
of the proportionality factor, d = 0.775, is valid for spherical non-interacting
particles. For polypeptides this value is always lower. However, the scaling
is the same for the end-to-end distance, the radius of gyration and hydrodynamic radius.
One method to measure the hydrodynamic radius is to measure the translational diffusion coefficient. Translational diffusion is caused by the random collisions with solvent molecules; this causes gain of momentum for the
diffusing agent and thus random movement. The random movement is called
Brownian motion and may occur in any number of spatial dimensions. The
hydrodynamic dimension of the polypeptide chain reflects directly in the
translational diffusion coefficient, Dt, through Stokes-Einsteins equation:
Dt =
k BT
6πη RH
(10)
Here Boltzmann’s constant kB is introduced, T is the absolute temperature
and η is the dynamic viscosity. The hydrodynamic radii of peptides and proteins can be determined via the measurements of their diffusion coefficients
(Miller and Goebel, 1968; Lifshitz et al., 1978; Fitzkee and Rose, 2004;
31
Kohn et al., 2004). The hydrodynamic properties yield information on the
conformational state of the polypeptide, and if the chain follows the expected Flory scaling or not. If peptides or proteins of various sizes have hydrodynamic radii that scales with 1/3 one can draw the conclusion that they
are in a folded state (Wilkins et al., 1999). Most reports on determining the
hydrodynamic radii have been using small angle scattering or through the
diffusion coefficient measured by dynamic light scattering.
The hydrodynamic radius of a peptide chain is, as shown above, dependent on the number of segments in the chain. It is also valid that a general
volume can be written in terms of the hydrodynamic radius:
V = ΘRHϑ
(11)
Where Θ is a proportionality constant. For a sphere it is 4π/3 and ϑ is a general exponent with the value 3 in the spherical case. The mass is related to
the volume through the density and thus the diffusion coefficient via the
hydrodynamic radius can be related to the mass of the peptide and the scaling behaviour of the peptide can be studied.
So far the diffusion is assumed to occur in an infinite dilute solution with
no or very small interactions between the diffusing agents. In solutions with
high concentrations the diffusion is not entirely free and is affected by obstruction. The concentration dependence of the measured diffusion Dt is
approximately given by:
Dobs = D0 (1-3.2λΦ)
(12)
Here D0 is the diffusion coefficient at infinite dilution, λ is a shape and interaction dependent parameter (λ = 1 for a hard, non-interacting sphere) and Φ
is the dry volume fraction (Tokuyama and Oppenheim, 1994)
Structural transitions
Structural transitions in peptides and proteins can occur on different levels,
on the tertiary structure level or the secondary structure level. For peptides
the structural transitions mainly occur on the secondary structure level. In
peptides an important structural state is the left-handed 31-helix, also called
polyproline type II helical structure (PII) or the 32-helix. It has been discovered that PII is an important secondary structure in seemingly unstructured
peptides, such as Aβ in solution. Not only the polyproline peptides adopt this
32
structure but many other peptides (Wilkins et al., 1999). Structural transitions can be induced by adding energy that exceeds the energy that stabilizes
the structure. A typical example is adding heat to an α-helix until the stabilizing hydrogen bonds break and a transition towards random coil occurs.
The structural transitions can be modelled using statistical physics. PII helices do not have any inter-residue hydrogen bonds so a slightly modified
Zimm-Bragg analyzis can be used (Zimm and Bragg, 1959). The modification is simply that the requirement to have at least three successive segments
in helix conformation is removed and that only the first segment is assumed
to be in a random coil conformation.
Assuming that a two state transition is studied, and every amino acid residue can adopt either PII-helix or random coil, then the partition function for
a molecule is given by the sum of all possible states. All states are however
not equally possible so a statistical weight is used. Each state’s statistical
weight is the product of statistical weight factors from the different combinatorial possibilities. The model is presented in more detail in paper IV and by
Zimm and Bragg (Zimm and Bragg, 1959).
Performing the calculations results in a surprisingly simple expression for
the partition function, Q, and the fraction of residues in PII structural state,
θ, can be calculated from Q.
  Nγ

 Nγ
γ −1  N
γ −1  N
λ0 ( λ0 − s ) +  1 + 1
 λ1 ( s − λ0 ) 
s   0 + 0
λ1 − s 
λ0 λ0 − s 
s (γ 0 − γ 1 )
 λ1
−
θ = 
N
N
( N − 1)( λ0 ( λ0 − s ) + λ1 ( s − λ1 ))
( N − 1)( λ0 − λ1 )
λ0,1 =
γ 0,1 =
{
1
1+ s ±
2
∂λ0,1
(1 + s )2 + 4σs
}
(13)
∂s
The parameters s and σ can be interpreted in physical terms. s can be thought
of as a equilibrium constant for the PII-helix to coil transition and thus related to the enthalpy change of the system due to conversion of one segment
from unordered to PII-helix. The relation is the well-known thermodynamic
relation:
d ln s ∆H
=
dT
RT 2
(14)
The parameter σ can be interpreted as the cooperativity of the conversion, a
value close to one for low or no cooperativity and a low value for high cooperativity. The temperature dependence of the transition can be studied and if
the populations of the structural entities can be determined the parameters s
33
and σ can be determined from equation 13. s should be approximately linear
close to the transition temperature Tm.
s =1−
∆H
(T − Tm )
RTm2
(15)
At s = 1 the two states are equally populated and σ determines the slope of
the transition.
The outcome of this is that by measuring the PII-helical fraction at different temperatures, preferably close to the transition temperature, it is possible
to calculate the enthalpy change of the system due the structural transition,
the transition temperature and the cooperativity. This of course holds for all
similar structural transitions, not only the PII-helix to random coil transition.
34
Spectroscopic methods
“It is a mistake to think you can solve any major problems
just with potatoes”
Douglas Adams
Different dynamical features occur on different time-scales. Time-scales in
biomolecules can be defined in terms of correlation times, τc. Mathematically the correlation time is defined by the correlation function. It is the characteristic time of the exponential decay of the time correlation function:
C (t ) = C (0)e
−
t
τc
(16)
For the peptide studied in this thesis, the Alzheimer’s amyloid β-peptide,
several time scales are of interest in characterizing the peptide’s properties.
Local motions and vibrations of bonds occur on a femto- to picoseconds
timescale. This ultra fast time scale is also that for the change in electronic
configuration when a molecule is excited by the absorption of light, as seen
in absorption- or CD-spectroscopy.
Molecular rotation is a slower process but still very fast. A typical rotational correlation time for a peptide is on the order of a few nanoseconds.
For the Aβ-peptide the rotational correlation time can be calculated from the
hydrodynamic radius.
τrot =
4πRH3η
3kBT
(17)
The symbols were defined in the previous chapter. Assuming the hydrodynamic radius of Aβ to be 17Å and the temperature to be room temperature (T
= 298K) in aqueous solution the rotational correlation time, τrot, of Aβ is 4.3
ns. A few nanoseconds are also the typical lifetime of the excited state of a
fluorescent molecule.
Translational diffusion has no obvious correlation time but the expected
time for the molecule to diffuse one molecular radius is for an Aβ-peptide 3
ns and thus occurs roughly on a similar time-scale as rotation.
Structural transitions and folding of proteins occur on longer time scales
where induction of secondary structure occurs on pico- to microseconds and
35
folding and induction of tertiary structure occur on micro- to seconds. The
Aβ-peptide does not have any well defined structure, but has some secondary structure propensities. On the other hand, the Aβ-peptide undergoes
other structural transitions. One important feature is the oligomerization of
Figure 5. Time-scales for proteins and NMR spectroscopy
the peptide into soluble toxic oligomers as described above and the subsequent formation of fibrils and amyloid plaques.
The formation of soluble oligomers occurs on a much longer timescale
and is seen after minutes to hours (Barghorn et al., 2005). Fibril formation is
an even slower process and there is a lag time between the occurrence of a
supersaturated monomer solution and fibril formation. This lag time is concentration dependent but at physiological concentrations of Aβ the fibril
formation occurs on a time-scale of hours to days (Harper and Lansbury,
1997).
Thus, the biomolecular processes that define the properties of Aβ occur
on a wide variety of time-scales. These processes are however not independent: the sub-molecular and molecular properties that occur on a very fast
timescale underlie the macroscopic properties and pathogenic effects that
occur on a much slower time-scale.
Many of these processes are within reach of spectroscopic methods (Figure 5), as already mentioned above. NMR relaxation reflects both the very
fast internal motion of the molecule, less than ns, and slow internal motions
in micro- to milliseconds. NMR relaxation also carries information on molecular rotation (nanosecond time scale) (Ishima and Torchia, 2000). The
chemical shift in NMR can reflect very slow processes on second and longer
time scales as well as fast processes on the µs time-scale. Measuring translational diffusion with NMR does not reflect the time-scale of the correlation
time of diffusion presented above, but instead reflects the timescale of diffusion time studied, typically 100 ms. The different time-scales within reach
for NMR is one of the major advantages of this spectroscopic method.
36
NMR
Nuclear magnetic resonance (NMR) is the main spectroscopic method used
in the present thesis. NMR is a widely used spectroscopic method today and
for purposes ranging from geological measurements via medical imaging to
biomolecular dynamics. NMR has a long history and already 1936 Görter
described an apparatus that, in theory, could detect the magnetic resonance
of protons (Görter, 1936). In 1946 two groups independent of each other
performed both solid-state and liquid-state NMR experiments (Bloch et al.,
1946a-b; Purcell et al., 1946). Already early in NMR history biological studies were performed: as early as in 1954 DNA was studied and 1957 a 40
MHz 1H-spectrum of ribonuclease was obtained (Jacobson et al., 1954;
Saunders et al., 1957). Today the magnetic fields are significantly higher and
800-900 MHz magnets are not uncommon. The methods used to study biological molecules have an increasing complexity and have developed from
continuous wave 1D methods to Fourier transformed pulsed heteronuclear
multidimensional experiments.
One important application of biological NMR is structure determination,
but also dynamical properties, such as local mobility and hydrodynamics are
within reach of NMR. In this thesis NMR has been used mainly to investigate dynamic properties of the Aβ-peptide using diffusion measurements,
relaxation measurements but also to investigate ligand interactions with induced chemical shift changes and line-broadening. Some structural properties of the peptide are also studied using measurements of J-coupling. For an
introduction in NMR theory and basic principles of NMR spectroscopy I
recommend the NMR textbook by Malcolm Levitt (Levitt, 2001).
J-couplings and the structural interpretation thereof
J-couplings, or indirect couplings, arise through the coupling of two
neighboring spins through covalent bonds. The indirect spin-spin coupling
give rises to a splitting of the signal due to polarization of the spins and altered orbital motion of the valence electrons. It is almost exactly the same
possibility for each spin to find its neighbor in an α or a β-state and therefore
there will be a splitting in two peaks of equal intensity for each spin, in a two
spin system. For larger spin systems the splitting gets more complicated and
follows the statistics of a Pascal triangle. The splitting is typically 1-200 Hz.
37
The J-coupling is most often measurable up to 3-bonds separation, and is not
dependent on the magnetic field.
The 3-bond, 3J, couplings carry information on the structure of the molecule and are dependent on the dihedral angle between the spins. This relation
can be parametrised and this was done by Karplus (Karplus, 1959, 1963)
using the empirical relation J = A + Bcosφ +Ccos2φ. Here A, B and C are
constants that are dependent on the molecular system and φ is the dihedral
angle. For example the J-coupling between the amide proton and the αproton is dependent on the φ - angle and thus carries information on the secondary structure in the backbone.
The J-coupling can be measured directly from a 1D NMR spectrum if the
studied peak is well resolved. If there is overlap in peaks 2D or 3D-spectra
are necessary. Typically a COSY experiment yields the J-couplings in a protein.
Different secondary structures show different J-couplings because the dihedral φ-angle differs between different structures. However, as seen in the
Karplus equation, the relation between J and φ is not one-to-one, and the
interpretation of J-coupling data should be done with care.
Nuclear spin relaxation and dynamics
In order to obtain an NMR signal the spins have to be disturbed relative to
the thermal equilibrium state and the magnetic moments have to precess
coherently. The loss of coherence and the process of returning the magnetization to thermal equilibrium are termed relaxation and carry information on
molecular dynamics and motion on a fast time-scale. This time scale is in the
nano- to pico-second range and involves local motion as well as molecular
tumbling.
Relaxation of spins in a simple spin ½ system is caused by the stochastic
fluctuating magnetic field that is created by dipole-dipole couplings and
chemical shielding anisotropy (CSA) in a tumbling molecular system. The
stochastic fluctuations in the magnetic field can be represented as a random
perturbation term in the Hamiltonian of the system and can induce a spin
flip, from β to α-state. Using this formalism relaxation can be described in
terms of the spectral density function of the molecule (Wangsness and
Bloch, 1953; Redfield, 1957, 1965).
Relaxation of the spin from a perturbed state back towards thermal equilibrium is called longitudinal relaxation because it involves the reconstitution
of the macroscopic magnetization vector along the magnetic field-direction.
This relaxation occurs with a characteristic time constant called T1 or the
reciprocal rate R1. Loss of coherence of the precessing spins leads to loss of
38
the detectable NMR signal, and this has another characteristic time constant
called the tranverse relaxation time T2.
A third relaxation phenomenon is the steady state Nuclear Overhauser Effect, NOE, that is due to dipolar-dipolar cross-correlation relaxation. This
phenomenon is possible in a system with two dipole-dipole coupled spins.
One way to measure the NOE effect, is to apply a radio frequency field to
one of the coupled spins that equalizes the populations, i.e. removes the difference in number of spins in the α- and β-state for that spin. This is called
saturation. In the saturated system cross-relaxation rates cause an increase in
the population difference in the other of the coupled spins. This effect is
dependent on the rotational correlation time of the molecule studied and thus
reflects both dynamic and structural properties of the molecule. (For a more
complete description of relaxation phenomena in NMR, the text book of
Kowalewski and Mäler is recommended (Kowalewski and Mäler, 2006)).
Longitudinal relaxation and NOE are both caused by spin flip between αand β-state. NOE actually involves two simultaneous spin flips. These relaxation parameters are mainly dependent on fast dynamics of the molecule.
Transverse relaxation on the other hand is due to loss of spin coherence and
also contains information on the molecular motion on a slower timescale. All
three relaxation parameters can, as mentioned above, be described in terms
of linear combinations of the spectral density function of the system studied
and the magnetic field strength. The spectral density function is the Fourier
transform of the correlation function of the perturbing magnetic field caused
by the dipole-dipole-couplings and molecular tumbling. The dipole-dipole is
just one of many possible interactions responsible for relaxation of spin = ½
systems. Relaxation through the chemical shift anisotropy interaction should
also be considered.
To obtain dynamical parameters, relaxation data can be used to map the
correlation function of the spectral density function and thereby obtain rotational correlation times both for local reorientation of the spin-spin vector
and reorientation of the molecule studied. This approach is usually called the
model-free approach and a generalized order parameter is obtained
(Wennerström et al., 1974; Lipari and Szabo, 1982). The generalized order
parameter reflects the local rigidity.
Linebroadening in NMR
Linebroadening of the NMR signal may be caused by a variety of mechanisms, mainly related to T2 relaxation. The NMR signal is represented as the
Fourier transform of the induced sinusoidal signal. The loss of coherence of
the individual spins reduces the magnitude of the signal and thus the sinu39
soidal signal decays exponentially with the characteristic time T2 as described above. In the simplest case, a single spin, the obtained timedependent signal is:
−
M xy = M eq e
t
T2
sin ωt
(18)
Here Meq is the magnetization at thermal equilibrium and ω is the larmor
frequency. In a system of i spins the obtained signal is given by a sum of
damped sinusoidal functions:
M xy = ∑ M e
i
eq
−
t
T2i
sin ωi t
(19)
i
The Fourier transform of the function described by equations 18 and 19 is a
Lorenzian function in the frequency domain. The Fourier transform is a linear operation, and thus, a sum of signals yields a sum of Lorenzians. The
frequency function is dependent on the Larmor frequency, ω0, and the relaxation rate R2=1/T2:
S (ω ) =
R2
R + (ω − ω0 ) 2
2
2
(20)
This is a function with a maximum at the Larmor frequency and a linewidth, in Hertz, that is R2/π. Thus the line-width of the signal in the Fourier
transformed NMR spectrum is directly proportional to the relaxation rate. A
high relaxation rate corresponds to broad lines. This is ultimately a consequence of Heisenberg’s uncertainty principle, where ∆E∆t ≥ ħ/2 → ∆ν∆t ≥
1/4π, thus a relaxation time of 10 ms corresponds to an 8 Hz wide line which
is a broad line in NMR.
This means that factors that influence the relaxation rate of a resonance
are reflected in the line width of the signal. Typically this could be due to
changed conformation of the molecule, oligomerization or ligand binding. If
the relaxation rate is high enough the signal can be broadened beyond detection. Another important relaxation mechanism is through the presence of
paramagnetic species. If the studied molecule has unpaired electrons or if a
paramagnetic agent is added to the sample an increased relaxation rate will
be observed.
Paramagnetic relaxation is due to dipole-dipole couplings between the
unpaired electron spin and the nuclear spin. The dipole-dipole-couplings are
of course strongly distance dependent and decreases with the 6th power of
the distance. The relaxation enhancement of the paramagnetic agent causes
the NMR signal to broaden significantly if it is close enough. This can be
used both to study interactions between paramagnetic molecules and dia40
magnetic ones, and to refine structures by either using intrinsic paramagnetic
centres or by introducing paramagnetic markers (Figure 6).
Figure 6. Different strategies in using paramagnetic probes. Attaching a paramagnetic probe to the molecule (left) or addition of a probe into the solution. The distance dependence of the PRE then helps to refine structure of the protein or peptide.
If the NMR signal disappears totally the spin is very close to the paramagnetic probe, but if the signal remains the change in relaxation rate can be
used to measure the distance to the paramagnetic site (Bertini and Luchinat,
1996; Jacob et al., 1999).
Another property that may affect the NMR linewidth appearance is
chemical exchange between states that exhibit different chemical shifts. The
different states may be related to different conformations, bound and free
states or different oligomeric states. Consider two states A and B, with their
respective chemical shifts, δA and δB in Hertz [Hz]. If the exchange is slow
on the NMR time scale there will be two lines in the spectra with intensities
corresponding to the respective populations of states A and B. Slow exchange on the NMR time scale corresponds to an exchange rate, k, that is
orders of magnitude smaller than the difference in chemical shift, k << ∆δAB,
(Figure 7). On the other hand, in the case of fast exchange, k >> ∆δAB, the
two peaks will collapse into one, this peak will be centered at the frequency
that corresponds to the weighted mean of the chemical shifts of state A and
B. The weight is the equilibrium concentrations of state A and B:
δ obs =
δ A + Kδ B
1+ K
(21)
Here K is the equilibrium constant. If the chemical shifts of state A and B
are known, chemical shift studies may provide information on exchange
rates and equilibrium constants of the system. In the intermediate exchange
rate region, where k ≈ ∆δAB, the lineshapes are somewhat distorted and close
41
Figure 7. NMR line shapes for two spins in chemical exchange at different exchange
rates.
to the transition point, k = ∆δAB, the lines are significantly broadened and
often not visible in the NMR spectra (Figure 7).
To be able to resolve spectra that exhibit intermediate exchange the system may be studied at a different static magnetic field strength, or at a different temperature in order to change the chemical exchange rate or the NMR
chemical shift time scale (Millet et al., 2000).
Diffusion measurements with NMR
Relaxation measurements yield information on local motion and molecular reorientation. Hydrodynamics reflects another scale of dynamics and may
be characterized by its diffusion coefficient as described above. The translational diffusion coefficient, Dt, can be obtained from NMR experiments by
the use of gradient fields in addition to the strong static magnetic field
(Hahn, 1950; Carr and Purcell, 1954; Stejskal and Tanner, 1965). Dt is calculated from the mean square displacement of spins during a diffusion time
and thus reflects both an ensemble and a time average and cannot be used to
study diffusion on fast timescales nor on too slow timescales. In this section
the basics of Pulsed Field Gradient (PFG)-NMR diffusion is described.
PFG-NMR is easiest described by representing the net number of spins in
the α state as a magnetization vector M. However, the net magnetization
does not produce any signal. An NMR signal is proportional to the magnetization vector along an orientation perpendicular to the field, B0. This mag42
netization rotates with the Larmor frequency, induces an alternating current
if the magnetization precesses in a coil.
The magnetization in the xy-plane after a 90°-pulse has a phase shift after
a time τ according to the precession. If all spins experience the same magnetic field the phase shift for spins with different location in the sample will
be the same φ(τ) = γB0τ. If a field gradient along the z-axis over the sample,
g(t,z), is added to B0, the field experienced by the spin will depend on the
localization along the z-axis. The phase shift for a spin is then given by:
τ
φ (t ) = γB0τ + γ ∫ g ⋅ z (t )dt
(22)
0
A gradient pulse with length τ induces a z-dependent phase shift that reduces
the signal. A second gradient with reversed sign can rephase the signal, assuming that they are at the same z-coordinate as they were at the first pulse.
This is called a gradient echo. Small static inhomogenities in the magnetic
field that cause dephasing and consequently line broadening can be rephased
by a spin-echo where the spin precession direction is changed with a 180°pulse and the precession times in both directions are equal, thus causing the
total phase shift to be zero.
Figure 8. The NMR spin echo pulse sequence with gradient pulses. The first gradient pulse dephases the signal and the second gradient pulse rephases them again. If
the spins undergo Brownian motion during the delay ∆ the rephasing will be incomplete and this causes a signal attenuation
The basic experiment for measuring diffusion by NMR is a spin-echo experiment with gradient pulses, where the spins undergo Brownian motion
between the de- and refocusing gradients. The spin-echo experiment is initiated with a 90°-pulse followed by a delay τ. During this delay a gradient
pulse with length δ and strength g is applied. A 180°-pulse is applied followed by a delay τ and an identical gradient pulse, figure 8. Small static
43
ln
S (2τ )
δ
= −γ 2 g 2 Dδ 2 (∆ − )
S0
3
inhomogenities are refocused by the spin-echo. The gradient echo is fully
effective only if the spins do not move in the time that separates the gradient
pulses. In the presence of diffusion the refocusing will not be complete and
the signal will be attenuated. Equation 23 give the signal attenuation known
as the Stejskal-Tanner equation (Stejskal and Tanner, 1965; Price, 1997):
ln
δ
S (2τ )
= −γ 2 g 2 Dδ 2 (∆ − )
S0
3
(23)
Measuring the signal intensity at different gradient strengths or different
diffusion times makes it possible to calculate the diffusion coefficient (Figure 9).
Figure 9. The signal attenuation due to incomplete rephasing of water proton spins
that undergo Brownian motion (A). In B the attenuation is fitted to Stejskal-Tanners
equation, equation 23.
Measurements of accurate diffusion coefficients require temperature timestability and constant gradients over the whole sample. The diffusion coefficient is highly temperature dependent in both the Boltzmann factor and the
viscosity. Also temperature gradients over the sample cause convection and
a flow term has to be added to equation 23. This can be compensated for by
special pulse sequences (Momot and Kuchel, 2004); however, a homogenous
temperature is preferable.
A constant field gradient over the sample is necessary, otherwise equation
23 will have a space dependent gradient term i.e. g(z). Measuring the diffusion coefficient using non-constant gradients gives an attenuation that deviates from the Stejskal-Tanner equation. This non-linearity of the gradient
field can be dealt with using either a distribution function of gradient
strengths (Damberg et al., 2001) or by replacing the slope in equation 23
with a power series (Nilsson and Morris, 2006). Then equation 23 can be
used to measure the diffusion coefficient with high accuracy for any given
substance with a measurable NMR signal.
44
Circular Dichroism and secondary structure of
peptides
CD (circular dichroism) is a low resolution spectroscopic technique from
which structural information can be obtained. The phenomenon of chiroptical activity has a long history and was observed already in the early 19th
century. In 1951 the structural motifs of biomolecules were proposed and the
correlation of secondary structure and chiroptical activity was proposed just
a couple of years later (Pauling et al., 1951; Yang and Foster, 1954). Nowadays CD is a standard tool for estimating secondary structure content and to
follow structural transitions.
In circular dichroism (CD) one takes advantage of the chirality of a molecule and the helicity of photons. The photon, is a massless boson with spin
one. These massless bosons have two possible spin projections, -1 and +1,
and these projections corresponds to left and right circular polarized light.
Ordinary linearly polarized light is one-to-one superposition of -1 and +1
spin photons.
Biological molecules such as peptides and proteins have chiral properties
and thus absorb circularly polarized light differently, dependent on if the
light is left- or right-handed polarized. The difference results in elliptic polarized light, and the ratio of the two semiaxises is called the ellipticity, θ
(Figure 10).
Figure 10. The CD signal arises from that left and right circularly polarized light
being absorbed differently. This gives elliptic polarized light and the ratio between
the semiaxises is the ellipticity. If the absorption of the circularly polarized light also
introduces a phase shift, α in the figure, the elliptic polarized light is tilted with an
angle θ. This is called the ORD (optical rotatory dispersion)
This ellipticity is related to the difference in absorption of left- and righthanded circularly polarized light AL and AR according to:
45
θ=
2.303⋅( AL − AR )⋅180
4π
(24)
The ellipticity is usually normalised so that it is written in terms of molar
ellipticity [degrees per mole residue and length2].
Different secondary structures have different chiroptical activity that
gives characteristic CD spectra. Peptides and proteins that have well defined
structures such as α-helices and β-sheets, are easy to recognize in CD spectra.
Estimation of secondary structure fraction with CD
The Aβ peptide has mainly disordered or random coil properties. Disordered
peptides have some characteristics in their CD spectra (Woody, 1992). A
true random coil spectrum shows no positive bands and has a distinct negative band at 195 nm. A left-handed 31-helix (PII-helix) has a positive band at
225 nm and a negative band close to 200 nm (Woody, 1992; Shi et al.,
2002). The positive band close to 225 nm is at 229 nm in a pure polyproline
chain and is shifted towards shorter wavelengths when other residues are
involved. This band corresponds to an n-π* transition (Ma et al., 1999).
Using these characteristics the fraction of PII-helix in a peptide can be estimated from CD spectra. An empirical relation bteween the intensity at the
obseved band at 225 nm and the amount of PII structure (assuming random
coil to be the only other structure present) has been derived (Rucker et al.,
2003):
PII pop =
[θ ]max + 6100
13700
(25)
Where [θ]max is the maximum CD signal at the local maximum close to 225
nm. This approximation is rather crude and gives only an estimate of the
population. It is valid only if a two-state system is considered, such as a system with PII and random coil contributions.
The α-helix CD-spectrum shows two minima at 222 nm and 208 nm and
one maximum at 190 nm. This spectra is the superposition of several exciton
contributions: the 222 nm minimum is mainly due to the nπ* excitation,
while the 208 nm minimum and the maximum mainly arise from the ππ*
excitation. Estimation of α-helical content is possible in analogy with the PII
case, usually from the ellipticity at 208 nm (Greenfield and Fasman, 1969).
46
β-sheets show two different classes of CD-spectra, depending on if it is a
parallel or anti-parallel structure. Both show one clear negative and one positive band where the negative band corresponds to nπ* excitation and the
positive ππ* excitation. The parallel β-sheet CD spectrum is red-shifted
relative to that of the anti-parallel β-sheet.
Fluorescence spectroscopy
In fluorescence, the spontaneous emission of light due to de-excitation of a
singlet state to the ground state of the molecule is studied. In the work presented in this thesis fluorescence has been used to study metal interaction
with Aβ.
When a molecule interacts with a photon the molecule may change its
electronic configuration to an excited state, Si, from the ground state Sa. Si is
a singlet state and from this state the molecule can deexcite via different
processes. Sa may convert into a triplet state and subsequent phosphorescence or the molecule can relax back to Sa under photon emission, fluorescence. The excited singlet state can also relax due to collisions with the solvent and by dissipation into vibrational states. Another important mechanism
is quenching where the molecule collides with solute molecules that are capable of quenching the excited Si state, see figure 11. The fraction of excited
singlets that deexcite through fluorescence is called the quantum yield.
In polypeptides the aromatic side chains of tryptophan, phenylalanine and
tyrosine are intrinsic fluorophores. The Aβ-peptide contains three phenylalanine residues and one tyrosine but the phenylalanine quantum yield is only
20% of the quantum yield of tyrosine (Chen, 1967). Thus, tyrosine fluorescence is the choice when intrinsic Aβ fluorescence is to be measured.
As mentioned above an excited molecule in state Si may deexcite nonradiatively due to collision with quenchers. One type of quenching mole-
47
Figure 11. Energy diagram of a fluorescent molecule. After excitation the electron is
in an excited state S1 and from S1 a spontaneous emission may occur back to
ground state by emitting a photon. The fluorophore may also transfer into a triplet
state with a substantially longer lifetime. The emission of light when relaxing from a
triplet state to a ground state is called phosphorescence.
cules are the paramagnetic molecules. One of the most effective of these is
molecular oxygen that quenches most fluorophores, but also copper ions
give rise to a high degree of quenching. The mechanism of copper quenching
is suggested to be that the paramagnetic molecule induces a triplet state of
the flourophore which is not fluorescent. If the quenching is to be effective
the quencher has to collide with the fluorophore while it is in the Si state,
during the fluorescence lifetime,τ. Thus, the quenching rate is diffusion limited. Consider the paramagnetic copper ion as a quencher and the tyrosine of
Aβ as the fluorophore. The collision rate constant per molar is given by the
solution of the Smoluchowski equation (Ware, 1962; Lakowicz and Weber,
1973):
(26)
k = 4πN * D + D r + r ⋅ P (Q )
A
(
Aβ
Cu
)(
Aβ
Cu
)
where N*A is the number of molecules per millimole, D is the diffusion coefficient of Aβ and Cu respectively and r is the radii of the contributing molecules. The diffusion coefficient of the copper ion in water solution is 7.2⋅10-6
cm2/s and of Aβ is 1.5 ⋅10-6 cm2/s, and their radii is 1.5 Å and 17 Å. P(Q) is
the probability that a collision leads to quenching of tyrosine fluorescence.
Assuming that all collisions will lead to quenching, P(Q) ≈ 1 (which is unreasonable since only collision with the tyrosine residue leads to quenching).
This gives a collision rate k = 1010 s-1M-1. Tyrosine has a fluorescence lifetime, τ ≈ 3.3⋅10-9 s (Ferreira et al., 1994) If the quenching concentration is
millimolar to molar the collision rate is 107-1010 and the probability that a
copper ion collides during the lifetime of the fluorophor is significant. This
48
means that at millimolar to molar concentrations of copper direct diffusioncontrolled quenching is possible but at submillimolar concentrations specific
binding of the quenching copper close to or at the fluorescent tyrosine is
required.
49
Results and discussion
“There is a theory which states that if ever for any reason
anyone discovers what exactly the Universe is for and why it
is here it will instantly disappear and be replaced by something even more bizarre and inexplicable”
Douglas Adams
It is a challenging task to characterize the biophysical properties of intrinsically unstructured proteins and peptides. However, this task has attracted
increasing interest in the recent years, because local residual structure may
be important in determining the folding (and thus the misfolding) properties
of peptides (Wirmer et al., 2006). In a true random coil structure no residual
local structure and no preferred global structural propensity is present. In
such case no specific parameters would be measurable along the peptide
chain; all measurable properties would be coupled only to the specific details
of each amino acid residue. However, for a number of intrinsically unfolded
peptides, such as α-synuclein and tau, local residual structures have been
found and their structure deviate significantly from the so called true random
coil (Smet et al., 2004; Mukrasch et al., 2005; Bernadó et al., 2005; Lippens
et al., 2006). Also the amyloid β peptide has been shown to have some residual structure that deviates from random coil (Riek et al., 2001).
Studies of unfolded peptides can include the studies of local dynamics
and local residual structure, as well as the properties of domains of the peptide and the global molecular dimensions of the peptide. These different
properties can be measured using a variety of different spectroscopic methods described earlier in this text. The local residual structure and dynamics
may be measured using NMR relaxation and chemical shifts. The global
structural propensities and the molecular dimensions are readily measured
using low resolution methods such as CD or fluorescence and also by PFGNMR diffusion measurements.
50
The soluble Aβ occurs as a mainly unfolded monomer
After degradation of the membrane-bound APP the Aβ peptide is released
into solution. In vitro, the peptide exists as a soluble entity until it aggregates
into soluble oligomers (the toxic species?) and finally into insoluble fibrils
and amyloid. The global molecular dimension of the peptide is directly reflected in the hydrodynamic properties.
The expected scaling of the hydrodynamic radius for a long polypeptide is
ν = 3/5, in agreement with the self-avoiding random coil in the swollen state.
This means that the diffusion coefficient of sufficiently long peptides scales
with -ν. Peptides belonging to the same structural family should scale in the
same way and measurement for fragments of a peptide with different lengths
gives information on whether there are structural changes or aggregation
processes that are chain-length dependent. Fragments that differ in the aggregation or structural state would fall outside the scaling law.
In Paper I the diffusion coefficients of fragments as well as the full
length Aβ-peptide were measured using the NMR diffusometry described
above. All measurements were performed at physiological pH and room
temperature (25 °C) and in H2O/D2O or pure D2O. Viscosity effects arising
from the heavy water were accounted for using a linear dependence on the
fraction D2O used. The validity of this approximation was tested by measurements of a molecule with a known diffusion coefficient at different
H2O/D2O ratios, assuming that the overall structure of that molecule did not
change when changing the heavy water content.
In the diffusion measurements non-constant gradient profiles were accounted for with the method developed by Damberg et al (Damberg et al.,
2001). The studied fragments ranged from the hydrophobic central pentamer
Aβ(16-20) up to the full-length Aβ peptide. The fragment variant Aβ(1228)G19G20 was included since it is known not to aggregate and could therefore serve as a control.
The measured diffusion coefficients were fitted to a simple scaling law
for the diffusion coefficient:
DT = ξ1M −ξ 2
(27)
Data for all fragments fitted well to equation 27 and no systematic deviation
was noticed. Thus we could conclude that all peptides exhibit the same aggregation state, and in this case they are monomeric. If any of the fragments
would exist as a dimer the diffusion constant would deviate from eq. 27 with
a factor of 1/2ξ2. No points deviate by more than 0.02 << 1/2ξ2, when using
the evaluated parameters: ξ1 = 6.06 10-9 m2 s-1 and ξ2 = 0.44. Equation 27 is
a scaling law for the diffusion coefficient, which may easily be changed to a
51
relation between the hydrodynamic radius and the mass using Stoke’sEinstein’s equation.
The hydrodynamic radii of single amino acids and small di- and tripeptides as well as denatured proteins, up to a molecular mass of 12 kDa
were compared to the results obtained in Paper I. All these additional data
fit well to a simple power law, RH = 0.27M0.50 Å, over all peptide sizes, from
70 Da to 12kDa. Using literature data obtained from native folded proteins
Figure 12. Hydrodynamic radius versus the molecular mass of Aβ and literature
values for small di- and tripeptides and large denatured proteins. In A the scaling
law is fitted to Aβ results only and here ν = 0.44. In B the scaling law is fitted to the
shorter Aβ fragments and the di- and tripeptides, here the fitted parameter ν = 0.50.
Using only the longer fragments of Aβ and the denatured proteins as in C, ν = 0.57,
close to the expected Flory-scaling.
(Wilkins et al., 1999) an exponent of 0.30 was obtained, in good agreement
with a spherical model.
The results are however not in agreement with the predicted Flory scaling
of ν = 3/5 for an excluded volume chain but rather in agreement with a chain
in θ-solvent, ν = 1/2. The chain interactions with itself are equal to the interactions with the solvent. Other studies of unfolded proteins and peptides
using X-ray scattering, coil libraries or PFG-NMR diffusion to measure the
radius of gyration give the predicted value of the exponent, close to 0.6, but
these measurements were performed in high concentrations of denaturant,
which may give a different interaction pattern with the solvent (Wilkins et
al., 1999; Kohn et al., 2004; Fitzkee and Rose, 2004).
The theoretical scaling laws are calculated to be valid for long polypeptide chains. Using only the mono-, di- and tripeptides hydrodynamic radii
from the literature (Longsworth, 1953) and the penta-, hexa- and septameric
fragment’s hydrodynamic radii presented in Paper I a scaling of ν = 0.50 is
obtained. Using data from the the longer fragments together with the long
peptide chain diffusion constants published by Wilkins et al. (Wilkins et al.,
1999) yields a scaling closer to the theoretically expected value, ν = 0.57.
52
This suggests that including too short fragments may bias the calculation of
the scaling of the hydrodynamic radius (Figure 12). Using only the fragments from the Aβ peptide studied here a scaling of ν = 0.44 is found and
this deviates both from the θ-solvent (ν = 0.5) and from the Flory scaling (ν
= 0.6). A scaling below 0.5 suggests a more compact overall structure and
this may be interpreted in terms of some residual structure in the peptide
which reflects in the hydrodynamic scaling. Only the data for really short
fragments scale as true random coil structures in a θ-solvent.
We conclude that the Alzheimer Aβ-peptide is in monomeric form at low
concentrations and physiological pH. The peptide chain behaves as more
compact than a Gaussian chain in a θ-solvent and this is in agreement with a
residual secondary structure propensity along the peptide chain.
The monomeric Aβ has some residual structural
propensities
In solution the monomeric Aβ peptide secondary structure is not entirely
random, as shown earlier by Riek et al. (Riek et al., 2001) and also suggested by the hydrodynamic studies in Paper I. Structural studies were performed on the fragment Aβ(12-28), a plaque competent fragment with
higher solubility than the full length peptide, in paper II. CD data and high
resolution NMR experiments reveal that Aβ(12-28) at low temperature has a
high propensity to adopt a left-handed 31-helix, (polyproline type II helix
(PII helix) or 32-helix).
The amyloid Aβ-peptide as well as a number of other peptides partly
adopt PII-helix, and this holds not only for proline-rich chains (Rucker and
Creamer, 2002; Ding et al., 2003; Eker et al., 2004a, c).
The PII-helix is defined by its dihedral backbone angles, [φ, ψ] = [-75°,
145°]. In this helix a full turn is completed by only three residues. There are
no interresidual hydrogen bonds that stabilise the structure or any salt
bridges (Whittington SJ and Creamer TP, 2003). The stabilisation is instead
proposed to be mediated by backbone-solvent interactions. This is supported
by the fact that heavy water, D2O, stabilises the PII-helix in favour of normal
water. This could mean that the hydrogen bonds between solvent water
molecules and the backbone are stronger with D2O, making the structure
more stable than in H2O (Shi et al., 2002; Schweitzer-Stenner et al., 2004;
Chellgren and Creamer, 2004). The high resolution NMR studies of Aβ(1228) in Paper II showed large variations in amide proton exchange times
which suggest that some of the amides are more protected than others. However, the experimental amide proton exchange rates of most residues in
53
Aβ(12-28) are close to the theoretical values for unstructured peptides, and
this suggests that no stable hydrogen bonds involving the amide protons are
present in this structure.
The amount of PII-helix is strongly temperature dependent with a higher
population of the PII-state at low temperatures. This temperature dependence
is shown for the shorter fragment studied in Paper II and is further studied
for the full length peptide in Paper IV and discussed below.
The backbone φ,ψ-angles for the PII-helix in a Ramachandran plot is very
close to those of a β-strand, so the geometric differences between β-strand
and PII-helix are small. By various methods, e.g. FTIR and Raman spectroscopy, the propensity for different amino acids to adopt PII-helix structure
has been estimated. Using these estimations for the Aβ-peptide reveals that
the N-terminal half of the peptide seems to have a higher propensity for
forming PII helix than the C-terminal part. In total, about 42% of the residues in Aβ have a high PII propensity and all these are found between residues 1 and 28 (Eker et al., 2004b). In paper IV the PII-helix content of the
full length peptide is studied and at low temperature the amount of 31-helix
corresponds well with the predicted values. The fraction PII-helix calculated
from CD data using equation 25 described earlier in this text, is 45% compared to the predicted 42%. Shorter fragments of the Aβ-peptide also show
CD spectra that well correspond to the predicted fraction of PII-helix. This
suggests that the propensity to adopt PII-helix may be an intrinsic amino
acid residue property rather than a polypeptide chain property.
To further elucidate what regions in the peptide that adopt PII-helices 1HNMR studies were performed. In Paper II NMR spectra show higher amide
proton dispersion at low temperatures corresponding to a higher degree of
general order in the structure. Measurements of the 3JHNHα-couplings suggest
that the N-terminal part of the peptide adopts a PII-helix while some of the
central residues, corresponding to the central hydrophobic cluster, mainly
adopt a β-strand conformation, as discussed further in Paper IV. 15Nrelaxation measurements, presented in Paper V, reveal that there are two
regions with dynamics that differ from the rest of the peptide. Relaxation
data, i.e. R1 and R2 rates were used to calculate effective local correlation
times for each residue that reflect the local mobility. The effective correlation time in these two regions was found to be shorter than the average
value, suggesting an increased mobility in these regions. The mobile regions
may correspond to highly unordered segments surrounded by regions with
higher propensities to adopt an extended structure. Secondary chemical
shifts together with results from Paper II and IV suggest that the ordered
regions mainly consist of PII-helix and β-strand. All these data taken together suggest a model consisting of six regions with different structural
propensities. The peptide has two regions with high propensity to adopt PIIhelix, corresponding to residues 1-4 and 11-15 separated by a flexible region
and two regions with a high β-strand propensity, residues 16-24 and 31-40.
54
Also these two structured regions are separated by a flexible region (25-30).
The highest fraction of structure propensities is seen at low temperature indicating that at higher temperatures the thermal motions reach an amplitude
that shadows the structural propensities.
The Aβ peptide shows a temperature dependent
structural behavior
In Paper II it is shown that the amount of PII-helix structure in the
Aβ(12-28) fragment is highly temperature dependent, in agreement with the
expected behaviour (Shi et al., 2002). At low temperature, 3 °C, the fraction
of PII-helix was estimated, using equation 25, to be 54%. Raising the temperature decreases the fraction of PII-helix and at 60°C the fraction of PIIhelix has decreased to 25%.
The temperature dependence of the full length peptide as well as some
shorter fragments thereof was studied in Paper IV. CD spectra show a clear
PII-helix spectrum at low temperature. This holds especially true for the Nterminal fragments of the peptide. For the outermost N-terminal fragment
Aβ(1-9) the fraction of PII-helix at 0°C was determined to be almost 60%.
Increasing the temperature reduces the amount of PII-helix, and this structural transition was modelled using a Zimm-Bragg analysis. This approach
makes it possible to calculate both a transition temperature, the enthalpy
change corresponding to the structural transition and the cooperativity from
PII-helix population data.
The melting temperature, or the transition temperature, Ttrans, corresponds
to the temperature when 50% of the peptide has a PII-helical secondary
structure content. For the full length peptide Ttrans is 263K and for the shorter
fragments Ttrans is higher, indicating that shorter fragments have PII-helices
that are more stable. Introducing more flexibility to the chain also seems to
affect the stability of the PII-helix. This was tested by studies of a variant Aβ
peptide. The variant peptide fragment Aβ(12-28)G19G20, where the bulky
phenylalanines are replaced by glycines, shows a less stable PII-helix secondary structure and the Ttrans is reduced from 283 to 267K compared to what is
seen for the native form of Aβ(12-28). This may suggest that the side chains
of the amino acids play a role in the stabilization of the extended PII-helix.
The large side chains are kept apart, for steric reasons, and this favours an
extended conformation.
The transition from PII to random coil has been studied for short model
peptides and show non-cooperative transitions for peptides with length N =
1-3 (Ma and Wang, 2003; Chen et al., 2004). In the Aβ case the shortest
55
fragment in our studies, the N-terminal Aβ(1-9), shows no cooperativity in
the transition from PII-helix to random coil. The analysis assumes a twostate model where each residue can adopt one of two conformations, helical
or random. The longer peptide fragments and the full length peptide exhibit
some cooperativity in the structural transition. This cooperativity is however
not high and the full length peptide has a cooperativity of 0.14 (a cooperativity of 1 corresponds to no cooperativity) which is low compared to a typical
value of 0.0002 for the highly cooperative transition from α-helix to coil
exhibited by long chains. In the case of the α-helix to coil transition the cooperativity arises from the i,i+4 hydrogen bonds that stabilize the structure,
but no stabilizing hydrogen bonds are present in the 31-helix. So, from where
does the cooperativity arise? One hypothesis is that the weak cooperativity
lies in bulky side chain interactions, in line with the argument outlined
above. Another hypothesis is that the PII-helix forms a groove along the
backbone, in which water may coordinate and form hydrogen bonding networks that are energetically favourable. These hypotheses are just, hypotheses and the question has to be studied further.
The thermodynamics of the PII-helix-to-coil transition was studied by CD
spectroscopy. The CD spectra of the different fragments of Aβ show an approximate two-state transition with an isoelliptic point at 200-210 nm. A
closer look at this isoelliptic point reveals that the point is more of a region
suggesting that there might be more than two conformational states contributing to the spectrum. Also, the fragment Aβ(25-35) shows a different behaviour from that of the N-terminal fragments and the full length peptide:
already at low concentrations this fragment adopts a thermally stable parallel
β-sheet conformation. These two deviations from a simple two state model
suggested that more information could be extracted by more high resolution
methods. The enthalpy change in the PII to random coil transition has been
studied for short model peptides and the results show very different values
but are suggested to be in the order of -10 kJ mole-1 residue-1(Ma and Wang,
2003; Chen, 2004). However, for the full length Aβ the enthalpy change of
the transition was estimated to ∆H = -6.8 ± 1.3 kJ mole-1 residue-1 in agreement with the enthalpy change of the shorter model peptides.
In order to study this structural transition in more detail NMR experiments were performed on two fragments of Aβ, Aβ(1-9) and Aβ(12-28) in
Paper IV. These fragments were chosen because the N-terminal fragment
has a high PII-helix propensity and the central fragment includes the important hydrophobic stretch. The changes in 3JHNHα couplings upon increasing
the temperature indicated that the transition is in fact a three-state event: at
low temperatures there is a high PII-helix propensity and a temperature increase is accompanied by a higher β-strand propensity of the peptide. Increasing the temperature further induces a change in 3JHNHα couplings that
corresponds to a transition towards random coil values. This may be ex-
56
plained by an increase in thermal motions that mask the structural propensities, as described above.
The results may have implications for peptide aggregation. At low temperature the peptide is more soluble than at higher concentration. The reason
may be that the peptide is less prone to adopt a β-strand conformation at low
temperatures, and therefor the correct contact points between peptides are
not as easily found.
The temperature-induced structural changes of the peptide are also reflected in the hydrodynamic radius. Translational diffusion measurements by
PFG-NMR experiments were performed on the same fragment as the 3JHNHα
couplings and are discussed in Paper II and IV. In Paper II we found that
the hydrodynamic radius of Aβ(12-28) is smaller at low temperature than at
room temperature. The RH at 1 °C was 96% of the RH at 25 °C. In Paper IV
we studied this phenomenon further and the same pattern was observed for
Aβ(12-28) which at low temperature has a RH that is 96% of the room temperature value. A series of experiments were performed at increasing temperatures. These experiments show that the hydrodynamic radius follows the
same pattern as the 3JHNHα couplings. A three-state transition was found with
an initially increasing RH to a maximum value at a certain temperature, and
increasing the temperature further was found to reduce the RH again. This
pattern was explained from a Monte Carlo calculation showing that the βstrand conformation is more extended and rigid than the PII-helix which is
reflected in RH. However, the fraction of residues in PII-helix was never
greater than 60% for the N-terminal fragment (1-9) and less than 55% in the
central fragment (12-28). This suggests that there may be additional explanations to this behavior of the hydrodynamic radius.
To study the structure transitions further, in silico studies were performed
on Aβ(1-9), as discussed in Paper VIII. The shorter fragment was selected
for multiple reasons: the change in hydrodynamic radius was most significant for this peptide, the population of PII-helix was high in this fragment
and finally the size of the peptide is very suitable for MD simulations.
The simulations show that at low temperatures there is a high propensity
for PII-helix along the peptide chain, involving all residues, and with a total
fraction of more than 50%. The high population of PII-helix is obtained
when single residue dihedral angles are determined. When only structures
with a persistence length longer than 2 residues are taken into account almost no PII-helix secondary structure is present in the peptide. This is in
agreement with the idea that PII-helix notion is an intrinsic amino acid residue property and the that PII-helix does not need to be looked upon as an
overall conformation (Makowska et al., 2006).
The radius of gyration for Aβ(1-9) was calculated from the structures obtained from the MD simulation described in Paper VIII, and was calculated
as the mass weighted mean distance to the centre of mass. The hydrodynamic radius can then easily be calculated from Rg using the relation
57
Rg = 0.775 RH. Interestingly the simulated data mimics the experimental data
quite well, in terms of the general behaviour of the peptide’s RH. At low
temperature the ensemble average has a RH that is approximately 6.6 Å, increasing to 7 Å at room temperature and decreasing to 6.4 Å at high temperature. However, in the in silico case, this behaviour is not due to the βstrand being more extended than the PII-helix but because there are two
structural conformations of Aβ(1-9), at low temperatures. This gives a bimodal distribution of Rg as shown in Figure 1 in Paper VIII, where the
population with the smaller radius corresponds to a hairpin-like structure and
the population with a larger radius corresponds to an extended conformation.
A similar hairpin structure has been shown in simulations of Aβ(12-28) and
in experiments at low pH (Abe et al., 2002; Baumketner and Shea, 2006).
The hairpin in the Aβ(1-9) is formed by a turn in the region comprising residues 4-6 which corresponds well to the high mobility region suggested from
our relaxation measurements and described above. This may explain the
three state behaviour of the hydrodynamic radius. However, the 3JHNHαcouplings show the same pattern and these results are not directly explained
by the presence of a hairpin conformation population.
Using the MD simulations in Paper VIII we also studied the stabilizing
factors for the PII-helix. No direct correlation between the average number
of hydrogen bonds from solvent water to backbone and PII-helix population
of each residue could be observed. However, the total number of water hydrogen bonded to the peptide backbone decreased significantly with raising
the temperature. This may suggest that interactions between solvent water
and peptide backbone are indeed involved in the stabilization of the PIIhelix.
The structural propensities of Aβ corresponds to
structure both in membrane mimicking media and in
fibrils
The solution structure propensity model described above and shown in figure 6 in Paper V does not represent a well defined secondary, or even less
any tertiary, structure but merely represents residual local structural propensities. The structure propensities may however be important for peptide function and malfunction. Unstructured proteins and peptides are very common
and these often undergo structural transitions into well defined secondary
structures when binding to a specific site where the peptide exhibits its biological function (Bernadó et al., 2005). Other peptides, such as Aβ, exhibit
its amyloidogenic and probably also its toxic function when having a more
58
well defined structure than in aqueous solution. The residual structural propensities of the inactive peptide seem to reflect the structure in the folded
active peptide in many cases (Smith et al., 1996; Mohana-Borges et al.,
2004).
The structural model described in Paper V has four regions with some residual secondary structure propensity, two β-regions and two PII-helix regions, separated by two mobile regions. The structure of Aβ in fibrils has
been investigated by solid-state NMR, H/D exchange experiments and selective double Cysteine mutated Aβ. These studies have shown that two βstrands are formed and separated by a turn involving residues 26-30. The βstrands range from 17-25 and 31-40 and are aligned in an anti parallel orientation with respect to each other. The strands are held together by hydrophobic interactions and in this conformation the peptides are stacked upon each
other in a parallel orientation and are stabilized by intermolecular hydrogen
bonds (Shivaprasad and Wetzel, 2004, 2006; Lührs et al., 2005; Sachse et
al., 2006; Petkova et al., 2006). There is a remarkably good agreement between the solid state model and the structural propensities observed by us in
terms of localization of the β-regions as well as the turn-region predicted
from relaxation data. The β-strand structural propensities may contribute to
the aggregation and amyloidogenic properties of Aβ. The structure, if any, of
the N-terminal region 1-15 is not known.
Membrane mimicking media, such as SDS, induce structure of the Aβpeptide. The induced structure is mainly composed of two α-helices. The
helices are located in segments 16-24 and 29-38 and separated by a turn or
kink. These segments are again in agreement with the regions that have βstrand propensity in the soluble monomer. These regions seem to be more
prone to interact intra- or inter-molecularly than with solvent water.
To obtain further information on the Aβ peptide interaction with SDS micelles paramagnetic agents were used to determine the location of the peptide in the micelle. In Paper VII, the SDS-peptide interaction was studied.
To study the size of the aggregate compared to the SDS micelle alone translation diffusion measurements were performed. The results showed that,
when measuring SDS diffusion it is of great importance to correct the observed SDS diffusion for obstruction effects and for the contribution from
the free, non-micelle bound SDS molecules. The hydrodynamic radius of the
SDS micelle alone was determined to be 22 Å.
When adding peptides to the micelles, the diffusion coefficient will be influenced by several effects of unknown relative magnitudes, like a change in
shape and in dynamics, so the exact hydrodynamic radius of a diffusing peptide-SDS micelle aggregate cannot be predicted with any precision.
If these effects are assumed to be small and neglected, we can estimate
the change in hydrodynamic radius of the peptide-micelle complexes from
the diffusion coefficients. The diffusion coefficient of the fragment Aβ(1228) bound to SDS micelles and the diffusion coefficient of SDS micelles
59
alone are the same. This unchanged diffusion behavior suggests that the peptide-micelle aggregate has the same size as the micelle. Also for Aβ(1-40)
the peptide-micelle aggregate shows roughly the same hydrodynamic dimensions as the micelle alone. This suggests that the peptide is in a compact
structure induced by the surrounding SDS molecules.
Our NMR-studies showed that Aβ in a SDS membrane mimicking environment adopts a mainly α-helical structure, and the two helical regions
involve residues 16-24 and 29 -38, in good agreement with earlier studies on
this system (Coles et al., 1998; Watson et al., 1998; Shao et al., 1999;
Crescenzi et al., 2002; Lau et al., 2003). The position of Aβ in the membrane has been under some debate. Crescenzi et al suggested that the second,
C-terminal helix is inserted into the membrane and the N-terminal helix is
positioned on the surface of the membrane (Crescenzi et al., 2002). Addition
of the paramagnetic ion manganese, Mn2+, was used by us to investigate the
positioning of the peptide in the micelle. The results, discussed in depth in
Paper VII, show directly that the C-terminal helix is protected from the
manganese and covered by SDS molecules. The line broadening induced by
the increased relaxation rate on the central helix is periodic. This periodicity
is consistent with a helix located on the surface of the micelle and consequently some of the residues are protected while some are not.
Figure 13. Relative hydrophobicity of the Aβ fragment and the surrounding residues
in APP. This shows clearly that the C-terminus of Ab is hydrophobic and indicates a
central hydrophobic stretch. The suggested transmembrane segment is highlighted as
a box and the cleavage sites for the proteolytic secretases are also indicated.
60
The combined results from the structural studies, the paramagnetic relaxation enhancement and the hydrodynamic data suggest a model for Aβ-SDS
interaction described in Paper VII. This model is in agreement with the
model suggested by Crescenzi et al. The studies of Aβ in a membrane mimicking environment do not necessarily reflect the structure and positioning of
Aβ in the membrane directly after degradation by γ-secretase. When studying the sequence of APP and the hydrophobicity of the residues, a membrane
spanning region is suggested from residue 30 to 52 in Aβ nomenclature, see
figure 13. In addition to this, membrane-release studies, where APP fragments of different lengths are inserted into a membrane and the fraction of
released peptide is determined, show that the Aβ peptide (1-40 and 1-42) is
rapidly released from the membrane, while longer segments of the transmembrane APP have a larger fraction that remains inserted in the membrane
(Unpublished data, personal communication with Nilsson IM). The Nterminal helix may be located at the surface of the membrane.
The structural and positioning studies of Aβ in micelles provides information on membrane interaction of the soluble, released Aβ, that has been suggested to form channels in biological membranes. It is debated whether the
monomeric peptide inserts into membrane, if monomeric peptides aggregate
on the membrane surface and then compromise the membrane integrity, or if
Aβ oligomers bind to and induce ionic leakage (Bokvist et al., 2004; Kakio
et al., 2004; Demuro et al., 2005). The architecture of these channels is not
known but Arispe et al. suggested a structure where the C-terminal helix is
buried in the membrane and the N-terminal helix is located close to the
membrane surface (Arispe, 2004).Using our results a similar model may be
constructed, just using the intrinsic properties of the different helices, one
hydrophobic and one amphipathic. This model is sketched out above in figure 14.
Figure 14. Hypothetical Aβ pore architectures. The peptide may form pores by assembling into a barrel (A) formed by β-sheets. Alternatively the peptide-membrane
interaction induces the formation of α-helices and the helical peptides then assemble
into pores (B). The second model is in agreement with an amphipatic α-helix as
found in our SDS-experiments.
61
Metals such as copper and zinc interact with and alter
the aggregation properties of Aβ
Metal binding to Aβ is suggested to be involved in the pathogenesis of Alzheimer’s disease. Both APP and Aβ are suggested to participate in the normal metal homeostasis system, as described in the text above. Copper and
zinc interaction with Aβ peptide induces peptide aggregation if the metal
concentration is high enough, >1:1 metal:peptide ratio and higher (Bush et
al., 1994a; Huang et al., 1997; Raman et al., 2005). The formed aggregate is
suggested to be amorphous, and thus high concentrations of copper and zinc
prevent fibril formation by formation of non-fibril aggregates (Brown et al.,
1997; Yoshiike et al., 2001; House et al., 2004; Raman et al., 2005). On the
other hand, binding of low concentrations of copper or zinc ions to the full
length peptide Aβ(1-40), at less than 1:5 metal:peptide ratio, reduces the Aβ
oligomeric stability and prevents aggregation, whether amorphous or fibril
forming (Cardoso et al., 2005; Garai et al., 2006)
Figure 15. Aβ peptide aggregation measured using ThT fluorescence in the absence
and presence of zinc and copper ions. In the absence of metal ions (open circles) the
aggregation starts after a lagtime and is, when initiated, very fast. In the presence of
1:1 copper (open squares) the lagtime is somewhat prolonged and the aggregation
rate is significantly slower. In the presence of zinc ions the lagtime is significantly
shorter than in the apo-form of the peptide. The amount of fibrils formed differs
between the samples, suggesting that metals reduce fibril formation, either by keeping the peptide in solution or by amorphous aggregation.
62
The soluble monomeric peptide has a high affinity copper binding site in
the N-terminus. The metal ion is suggested to coordinate in a planar configuration with the three histidines (6, 13 and 14) and the N-terminus or tyrosine
10 as ligands. N-terminal deletions alter the binding affinity, suggesting that
Tyr10 is not involved in the copper binding. The peptide also has a zinc
binding site involving the three histidines. The fourth ligand for zinc binding
has recently been suggested to be Tyr10, Arg5, Glu11 or the N-terminus
(Mekmouche et al., 2005; Zirah et al., 2006). Binding of a metal to the Nterminal part of Aβ highly affects the aggregation properties of the peptide,
even though the regions that are involved in structure conversion upon aggregation are located in the central and C-terminal regions.
The formation of fibrils, rich in cross-β-structure, can be followed by ThT
fluorescence, which is strongly enhanced upon binding to amyloid fibrils and
provides a tool to study the kinetics of fibril formation. Aβ alone, at subcritical concentrations shows a lag time followed by fast aggregation. In the
presence of copper and zinc the lag time is significantly prolonged which
may be due to the destabilization of oligomers brought about by metal ions
(Figure 15) (Garai et al., 2006). Another feature shown in figure 15 is that
the final concentration of fibrils is significantly reduced in the presence of
zinc and copper. This may be due to increased amorphous aggregation induced by the metals.
In Paper VI 1H-13C and 1H-15N correlation NMR spectroscopy is used to
study zinc binding to Aβ(1-40) at physiological pH. Metal binding induces a
structural change in the peptide which is in intermediate exchange between
the apo and the holoform on the NMR time scale. This causes line broadening of the resonances affected by the binding. 1H-13C-HSQC gives more
details than the 1H-15N-HSQC and shows that zinc binding involves the three
histidines, 6, 13 and 14, and the N-terminal aspartic acid residue as ligands.
The tyrosine has been suggested to be one of the ligands in metal coordination but 1H-13C-HSQC of the aromatics shows that the tyrosine aromatic ring
is unaffected by zinc while the imidazole rings of all histidines are strongly
affected.
15
N-relaxation studies reveal that metal binding induces increased order in
the N-terminus, suggesting that the peptide folds around the ion. However,
the high exchange rate and the low dissociation constant suggest that the
folded structure is somewhat unspecific and flexible. It has been suggested
that metal binding may produce stable peptide dimers or oligomers by HisHis bridging. The translational diffusion measurements presented in Paper
VI suggest that no such dimers are present, at least not in a population detectable by NMR under the conditions studied. Formation of dimers or oligomers may induce rapid aggregation leading to very large aggregates with
line widths beyond the detection limits.
The binding of zinc to Aβ is very specific in terms of a binding site. In
order to determine the affinity of metal to Aβ intrinsic Tyr 10 fluorescence
63
was studied. The affinity for copper was determined by studying the paramagnettic copper induced fluorescence quenching. Zinc on the other hand is
diamagnetic and consequently does not cause fluorescence quenching. To
measure the zinc affinity we took advantage of the observation that copper
and zinc seem to compete for the same binding site. Measuring copper
quenching in the presence of increasing concentrations of zinc makes it possible to indirectly calculate zinc affinity. Using this protocol the dissociation
constants of copper and zinc binding to Aβ were determined and were found
to be in the low micromolar range, with a somewhat stronger affinity for
copper than for zinc. Kd for copper in phosphate buffer at pH 7.2 is 0.4 µM
and for zinc 1.1 µM.
The data obtained from the high resolution NMR experiments lead to a
model for zinc binding. This is sketched in figure 6 in Paper VI. No high
resolution structure could be determined, due to intermediate exchange on
the NMR time scale between the apo- and holoforms. Low peptide concentration as well as induced aggregation also makes it difficult to perform the
experiments necessary for a reliable structure determination.
The N-terminal region of the Aβ peptide, with no metal bound to the peptide, has a high propensity for an extended PII-helix conformation, as
pointed out above. The extended conformation, together with the presence of
charged residues in the N-terminus, is proposed to help to keep the peptide
soluble and protected from amorphous aggregation (Syme et al., 2002;
Jarvet et al., 2003; Eker et al., 2004c). The concentration dependent metal
effects on Aβ aggregation described above may be understood in the
following simple model: Metal ions at high concentrations saturate the
binding site(s) of Aβ and lower the electrostatic repulsion between the
overall negatively charged Aβ peptides (net charge nominally -3 at pH 7).
This effect dominates at high metal ion concentrations and explains the
higher aggregation propensity under these conditions. Binding at a second
binding site may be crucial. Assuming a second binding site that involves the
charged residues Glu 22 and Asp 23, metal binding reduces intermolecular
electrostatic repulsion, and this may facilitate interactions between the
hydrophobic stretches of the peptide. This, in turn, may promote
hydrophobic clustering and aggregation. The structure induction brought
about by metal-induced folding of the N-terminus counteracts aggregation.
This effect, masked at high metal ion concentrations, should dominate at low
metal ion concentrations, thereby explaining the decreased aggregation
propensity under these conditions. The extended conformation of the Nterminal region in the metal-free form of the peptide may facilitate fibril
formation after peptide aggregation. In the metal-bound peptide, on the other
hand, the folded N-terminus could interfere with fibril formation and this
would explain the reduced fibril formation of metal-bound aggregated
peptides.
64
The toxic oligomers formed by Aβ are destabilized by metal binding
(Garai et al., 2006). This may be explained by a model where the oligomers
are micelle-like structures, which have been suggested by, among others,
Sabaté et al. (Kayed et al., 2003; Sabaté and Estelrich, 2005). The formation
of micelles requires amphipathic properties of the molecule, and this is the
case of Aβ, as seen in figure 13. The micelle formation is also dependent on
a peptide conformation that allows the hydrophobic regions to cluster in the
centre of the micelle and with the hydrophilic tail pointing outward. Upon
metal binding the conformational change of the hydrophilic tail may make
the micelle state less energetically favourable.
Aβ binding of β-cyclodextrin involves aromatic
residues and reduces aggregation
As pointed out above metals like copper and zinc reduce Aβ aggregation at
low ionic concentrations due to induced structure and electrostatic effects in
the N-terminal part of the peptide. This is somewhat surprising, since the
metals induce structural and dynamic changes in the 1-15 region and this
fragment of the peptide is known not to be amyloidogenic. The central hydrophobic region, residues 17-21, seems to be important for aggregation and
the formation of cross-β rich fibrils. Binding of a ligand to this region should
influence the aggregation behavior of Aβ. The Alzheimer peptide has been
shown to interact with cyclodextrin, and the interaction reduces fibril formation at high concentrations of the cyclic oligosaccharide β-cyclodextrin (βcd). In Paper III the peptide-β-cd interaction was studied using NMR. Both
the full-length peptide and shorter fragments were studied at room temperature and physiological pH.
Upon interaction, both the size and the shape of the interacting agents
change and thus their hydrodynamic properties change. From diffusion data
the dissociation constant, Kd, may be determined. The diffusion coefficient,
Dobs, was determined over a range of total ligand ([L]0) or peptide ([H]0)
concentrations. The obtained data was fitted to the following one-to-one
binding equation:
 [L ] + [H ] + K
 [L] + [H ]0 + K d
0
d
D obs = D free + (D complex − D free ) 0
−  0

2[L ]0
2[L ]0


2

[H ]0
 −
[L ]0





(28)
A two-parameter fit with respect to Dcomplex and Kd using a range of at least
three β-cd concentrations gives the desired parameter values. The diffusion
constant of the free peptide (Dfree) has to be determined. In addition, the in-
65
duced chemical shift changes were used to determine the binding site and to
determine Kd, using diffusion data and chemical shift changes combined.
The interaction has earlier been suggested to occur between the aromatic
residues and the hydrophobic interior of β-cd. The Aβ peptide has four putative aromatic binding sites, Phe4, Tyr10, Phe19 and Phe20. The results of
our study show that if the phenylalanines at positions 19 and 20 in the fragment Aβ(12-28) are replaced with glycines, thus removing all aromatic side
chains, no interaction occurs. This shows that the phenylalanines are necessary for β-cd -peptide interaction. For the central fragment Aβ(12-28) where
the phenylalanines are present, interaction occurs and Kd = 3.8 mM. Induced
chemical shift changes suggested that the interaction mainly involves
phenylalanine 19. This binding is not strong, but it is in agreement with the
fibril reducing activity of β-cd determined earlier. In the earlier study a 50%
reduction of fibrils was seen at 5 mM cyclodextrin concentration (Yu, 2002).
When determining Kd of the full-length peptide cyclodextrin interaction,
the combined results from induced chemical shift changes and diffusion data
were consistent with a two-site binding involving Phe19 and Tyr10 with a
total apparent dissociation constant
of Kd = 4 mM. YThe individual Kd for the
F
two sites was determined to be Kd = 4.7 mM and Kd = 6.6 mM, respectively,
if the sites are assumed to be independent. The outermost N-terminal aromatic amino acid phenylalanine 4 did not seem to bind β-cyclodextrin with
any measurable affinity. This was tested by showing that the fragment Aβ(19) does not bind β-cyclodextrin.
In the diffusion measurements, increasing amounts of β-cyclodextrin
were added to the solution, introducing possible obstruction effects and/or
viscosity changes which consequently bias the determination of the diffusion
coefficient. This obstruction effect was studied in Paper III and it turned out
that the effect is linear with β-cd concentration. This effect has been accounted for in all experiments in our study.
Other types of cyclodextrins were studied as well and showed no binding.
This may be because the hydrophobic pocket of β-cyclodextrin has optimal
dimensions for interaction with the aromatic side chains. The γ- and αcyclodextrins have too large or too small cavities for interaction to occur.
The binding of a single phenylalanine to β-cyclodextrin has been determined earlier by isothermal titration calorimetry and a dissociation constant
of approximately 55 mM has been found (Aachmann, 2001). This was confirmed in our study using NMR diffusometry. The interaction of diphenylalanine was substantially stronger, Kd = 10 mM. Thus the interaction
between the Aβ-peptide and cyclodextrin is stronger than the interaction
between the aromatic ring alone and the β-cd, suggesting that the local environment of the aromatic residue contributes to the interaction. This is also
supported by the fact that we could not detect interaction with the N-terminal
phenylalanine at all. The aromatic Phe4 is surrounded by hydrophilic
charged residues while the phelylalanines at positions 19 and 20 are part of
66
the central hydrophobic cluster, and thus are located in a more hydrophobic
environment (figure 16).
Figure 16. Location of the aromatic putative binding sites for β-cd and the relative
hydrophobicity at the sites. The sites where we found binding in Tyr 10 and Phe 19
and/or 20 and they are all located in a somewhat hydrophobic environment while
Phe 4 is surrounded by hydrophilic residues, and this may explain the weaker interaction of β-cd with Phe 4.
Aβ binding of β-cd reduces stability and inhibits the formation of Aβ oligomers, just as metal binding does (Yu et al., 2002). The change in aggregation properties brought about by metal interaction is caused by changes in
the N-terminal region but in the case of β-cd it might be due to the interaction with the phenylalanines in the hydrophobic central stretch. The inhibition by β-cd probably arises because β-cd covers the hydrophobic region and
the hydrophilic side of β-cd readily interacts with the solvent water. Also,
the β-cd bound in the hydrophobic region would sterically hinder peptide
micelle formation.
The study presented in Paper III also shows that PFG-NMR diffusion
measurements is a powerful tool for measuring weak interactions, even when
the peptide and ligand have sizes of the same order. The combined use of
diffusion results and induced chemical shift changes gave a high resolution
picture of β-cd binding to Aβ.
67
Outlook
In general terms, the aim of the different studies included in this thesis
has been to characterize structural and dynamic properties of the Aβ peptide
that may have an impact on the molecular pathogenesis of AD. Even though
not any of the studies or the sum of all studies provided any complete picture
of the molecular mechanisms of peptide oligomerization and aggregation,
new insights may be drawn from them, in the context of results from other
laboratories.
Looking into the future, there are three areas that I would find very interesting to investigate further. First, the toxic mechanism of Aβ must be studied further. The biophysical properties, such as structure and dynamics, of
the Aβ-oligomer should be characterized. One major problem in such studies
is the low concentration of Aβ that can be used to produce stable Aβ oligomers. Second, it is important to further characterize the membrane interactions. Is it the oligomer that interacts with the membrane and induces membrane leakage, or does the monomer binds to the membrane and then assemble into a membrane penetrating oligomer? How is the SDS-bound structure
related to the peptide structure in a more realistic membrane mimicking environment, such as vesicles, consisting of a true lipid bilayer? And how is
that structure related to the reported channel properties of Aβ? Peptide interactions with a fast tumbling bicelle (mixed micelle) may better than micelles
resemble the bilayer nature of a cell membrane. At the same time this membrane model system may provide possibilities to determine structure and
dynamics of the membrane bound peptide using NMR.
The peptide, upon membrane interaction, has been suggested to form
cation-specific channels; these may be studied by vesicle leakage experiments. Using leakage data the kinetics of both the leakage and membrane
binding and peptide assembly may be estimated. Both these topics, the oligomers and the membrane interaction should be combined with further investigations of the metal interactions of Aβ. How is the membrane interaction affected if the peptide is in an apo- or holoform? It has been shown that
the induced structures when the peptide binds to a membrane differ in the
presence or absence of metals. However, metals have also been shown to
reduce oligomeric stability. The mechanism behind this would be of great
importance to know in detail, because it would provide information on the
oligomer stabilizing parameters. The structure of Aβ inserted in the mem68
brane as a part of APP may be studied if a longer fragment is synthesized,
including the whole trans membrane segment, i.e. Aβ(10-55).
Finally it would be very interesting to study other, similar unstructured,
amyloid forming peptides to see if they also show some residual secondary
structure propensities that are reflected in the function and malfunction of
the peptides. Huntingtin, for example, shows a similar hydrophobicity profile as Aβ (Burke, 2003), and also the hydrophilic region in huntingtin has
some extended properties, very similar to Aβ.
69
Sammanfattning på svenska
Den här avhandlingen handlar om den amyloida β peptiden (Aβ), en peptid
som återfinns i de proteinansamlingar, amyloida plack, som finns i
hjärnbarken på patienter som har Alzheimers sjukdom. Aβ är en del av ett
större, membranbundet, protein som kallas Alzheimers prekursor protein
(APP), och i APP är Aβ den del av proteinet som förankrar proteinet i
cellmembranet. APP bryts ner av enzymer och om en kombinerad
degradering katalyserad av proteinet av β- och γ-sekretas sker så skapas Aβ.
Efter degraderingen lämnar Aβ cellmembranet och är initialt en mestadels
ostrukturerad monomer (peptiderna förekommer en och en), men aggregerar
sedan och bildar giftiga oligomerer (aggregat av ett fåtal peptider). Sedemera
aggregerar peptiderna till olösliga fibriller och plack. Sammansättnigen av
Aβ till oligomerer och fibriller innebär en förändring av dess struktur, och
den här avhandlingen handlar om den monomera peptidens strukturella och
dynamiska egenskaper.
Vi har utfört diffusionsmätningar på Aβ, både hela peptiden och delar av
den, och detta gjordes för att utröna om peptiden företrädesvis är monomer
eller om den klumpar ihop sig parvis eller i oligomerer. Resultaten av dessa
mätningar visar att peptiden är monomer vid låga koncentrationer, neutralt
pH och rumstemperatur. Resultaten visar också att Aβ har hydrodynamiska
egenskaper som indikerar att peptiden har en tendens till struktur, att
peptiden inte beter sig som en helt ostrukturerad kedja av aminosyror.
Genom att använda NMR, kärnspinnresonansspektroskopi, och CD,
cirkulär dikroism, kunde vi studera denna tendens till struktur hos Aβpeptiden. Det visar sig att peptiden kan delas upp i 6 delar med olika typer
av strukturpropensitet. I ena halvan av peptiden, den så kallade N-terminala
delen har Aβ en tendens att anta en strukturtyp som kallas vänstervriden 31helix, eller polyprolinlik helix typ II (PII). Det finns två sådana segment i de
första 15-16 aminosyrorna och de är separerade av ett segment som är
ostrukturerat och som har en hög rörlighet. I den andra delen av peptiden, i
den C-terminala delen, har peptiden en tendens att anta en annan typ av
struktur, så kallad β-flak struktur. Också i det här fallet är det två regioner
som har denna egenskap och dessa är separerade av ett segment med hög
rörlighet. Segmenten som har en tendens att anta en β-flakstruktur hos den
monomera Aβ peptiden motsvarar direkt den β-flakstruktur som man kan
finna hos Aβ i de olösliga fibrillerna, det är samma segment som antar β-flak
i de peptider som bygger upp fibrillerna.
70
Oligomerer av Aβ peptiden är troligen det som orsakar nervcellsdöden i
Alzheimers sjukdom. Hur detta sker är inte klarlagt men mycket tyder på att
Aβ binder till cellmembran och skapar hål i membranet och därigenom
förstör cellmembranets barriärfunktion. För att studera hur Aβ peptiden
interagerar med cellmembran genomförde vi studier av peptiden i SDS
lösning. SDS är en detergent som bildar miceller, små sfäriska aggregat av
SDS-molekyler och dess vattenavstötande del påminner om den
vattenavstötande delen av ett cellmembran. I SDS-lösning antar Aβ en tredje
typ av struktur, en så kallad α-helix, detta sker i samma segment där den
antar β-flak i fibriller och i lösning. Det verkar som om dessa segment har
en hög propensitet att anta en struktur. Våra resultat visade att peptiden
binder till en micell och den ena α-helixen är begravd i micellen medan den
andra ligger på ytan. Dessa resultat ledde till en hypotetisk struktur på en
membranpor bildad av Aβ peptider.
Både Aβ och APP binder metalljoner såsom koppar och zink. När Aβ
binder metalljoner så ändras lösligheten hos peptiden drastiskt på ett
tämligen komplext sätt. Vid låga metallkoncentrationer motverkar
metalljonerna aggregation och bildning av giftiga oligomerer men vid höga
metalljonskoncentrationer så induceras aggregation i stället. Vi använde
NMR och fluorescens för att studera hur Aβ binder tvåvärda zink- och
kopparjoner. Vi kunde visa att Aβ binder zink med tre histidiner, i
positionerna 6, 13 och 14 och den yttersta aminosyran aspartat. Sålunda
viker sig peptiden runt zinkjonen och den N-terminala delen av peptiden får
en ändrad struktur. Denna nya struktur motverkar troligen aggregation. Vi
såg också tecken på ett andra bindningsställe, lokaliserat i den centrala delen
av peptiden. När metalljonen binder till det andra stället minskar troligen
lösligheten med aggregation av peptiden som följd.
En annan ligand som påverkar lösligheten för Aβ är sockret βcyklodextrin (β-cd), en ringformad molekyl bestående av sju ihopbundna
glukosmolekyler. Denna molekyl har visat sig kunnat minska fibrillbildning
och också oligomerisering av Aβ. Vi använde NMR för att karakterisera hur
Aβ och β-cd interagerar. Vi kunde visa att β-cd binder till två ställen på Aβ,
dels till den centrala delen av peptiden och dels till aminosyraresten tyrosin
på position 10. Den binder tämligen svagt och bindningskonstanten
bestämdes med hjälp av diffusionsmätningar.
Den monomera Aβ peptiden är sålunda inte helt ostrukturerad utan har
tendenser att anta strukturer och dessa strukturtendenser överensstämmer väl
med de strukturer peptiden antar i aggregerat tillstånd och som bunden till
SDS-miceller. De egenskaper som gör att peptiden formar fibriller är alltså
mätbara redan hos den lösliga monomera peptiden. Den monomera
strukturen kan vara avgörande för peptidens aggregationsegenskaper och då
peptiden interagerar med en ligand som påverkar strukturen eller dess
vattenavstötande egenskaper inverkar direkt på aggregationen av peptiden.
71
Acknowledgements
The work on which this thesis is based in not one mans work and I have a
number of persons to pay my gratitude to. In an acknowledgement section
such as this it is impossible to cover all persons that, direct or indirect, has
contributed to my years at the university resulting in this thesis. However,
there are some people that I wish to mention in particular.
Astrid Gräslund, som först och främst vågade ge mig chansen till
forskarutbildningen. Sedan dess har du inspirerat, och handlett mig på ett
fantastiskt sätt. Du har också visat ett nästan oändligt tålamod med mina
brister. Ditt sätt att leda institutionen skapar en atmosfär av frihet och
kreativitet, där varje medarbetare och student förväntas ta ett eget ansvar,
och det är mycket inspirerande.
Jüri Jarvet, som har lärt mig det jag kan om NMR och även andra typer
av spektroskopi. Du har tålmodigt lyssnat på idéer och frågor, dumma som
mindre dumma och tagit dem alla på allvar. I nästan alla projekt har vi
samarbetat och samarbetet har alltid varit givande och lärorikt.
Lena Mäler, som alltid har kloka råd och insiktfulla åsikter om
vetenskapligt arbete i allmänhet och om NMR i synnerhet.
Roberta Pierattelli and Lucia Banci, who teached me a lot about NMR
spectroscopy and analysis of NMR data. You also gave me an insight into
the world of paramagnetic and protonless NMR. Further, I am grateful that
you made my stay at CERM in Firenze such a great time.
August Andersson, för stimulerande och givande diskussioner och
debatter. Du ser alltid på ett problem från ett annat håll, så att det öppnas nya
vägar till lösningar. Det har varit ett nöje att komma till kontoret varje dag.
Martin Dahlberg, för att du gett mig insikter i simuleringarnas värld och
för din seriösa inställning.
Vladana Vukojevic and Georgy Bakalkin, for inspiring and interesting
cooperation on the dynorphin project.
Torbjörn Astlind, för att alla spektrometrar och datorer fungerar på
avdelningen. Jag upphör aldrig att imponeras av dina kunskaper.
Haidi Astlind, för att du alltid får det administrativa att flyta smidigt, och
att du aldrig tröttnar på att hjälpa och svara på frågor.
Britt-Marie Olsson, för att laboratorierna fungerar och kemikalier och
peptider inköps. Att du dessutom alltid sprider ett gott humör gör det roligare
på institutionen.
72
Peter Damberg, för dina kloka råd och dina kritiska kommentarer, och
för att du delar med dig av dina kunskaper.
Jag vill också tacka övriga medförfattare, Göran Eriksson, Henrik
Biverståhl, Jon Nordin, Ingrid Johansson, Marta Oleszczuk, Kamila
Oglecka and Emma Lindahl. Henrik och Jon vill jag dessutom tillsammans
med Evangelos Papadopoulos tacka för trevligt kontorssällskap.
And for great football discussions, indoor football games and glorious
Friday port wine I wish to thank Vasco Castro and Loïc Hugonin. For interesting discussions and help I like to mention Jesper Lind, Elsa BárányWallje, Joshua Hicks and Alex Peralvarez. I would also like to thank all
people, present and former, at Biophysics for creating a great environment at
the department.
Peter Brzezinski, för att du varit min bi-handledare under dessa år och att
du tagit dig tid till detta.
Jonas Danielsson, att ha sin lillebror som vetenskaplig förebild och
inspirationskälla är en ynnest. Att vi dessutom har delat intresset för
Hammarby, både fotboll, handboll och bandy, gör det inte sämre.
Slutligen vill jag nämna min familj, min närmsta likväl som min utökade,
som stöttat mig genom alla dessa år. Mina barn, Axel, Alva och Ellen som
hela tiden gör livet lätt att leva. Min mor och Torvald som varit där liksom
mina systrar. Och Sara för att du står ut med mig, för att du inspirerar mig
och för att du finns.
73
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