Why Does Polyglutamine Aggregate?
Insights from studies of monomers
Xiaoling Wang, Andreas Vitalis, Scott Crick, Rohit Pappu
Biomedical Engineering & Center for Computational Biology,
Washington University in St.Louis
pappu@biomed.wustl.edu
http://lima.wustl.edu
Expanded CAG Repeat Diseases and Proteins
DISEASE
GENE
PRODUCT
NORMAL CAG
MUTANT CAG
REPEAT RANGE
REPEAT RANGE
Huntington’s
huntingtin
6 - 39
36-200
DRPLA
atrophin 1
3 – 35
SBMA
49-88
androgen rec.
9 – 33
SCA1
38- 65
ataxin -1
6 – 44
SCA2
39-83
ataxin -2
13 –33
SCA3/MJD
32- 200
ataxin -3
3 – 40
SCA6
54-89
CACNA1A
4 – 19
SCA7
20-33
ataxin - 7
4 – 35
SCA17
37-306
TBP
24–44
46 -63
Bates, et al., Eds. (2002) Huntington's Disease, Oxford University Press
Basic physics of aggregation
n: denotes the number of peptide molecules in the system (concentration)
N: Length of each peptide molecule in the system
GM : Free energy of soluble monomer
GA : Free energy of aggregate
GA  GM 

 

A
 M
n
Aggregation is spontaneous if:
  0
Work done to grow a cluster
n*
W  n   n  Gex  n 
Gex  n   Cluster excess or interfacial free energy
For n  n*, W  n  1  W  n   0
For n  n*, W  n  1  W  n   0
1.
2.
3.
4.
In vitro aggregation studies of synthetic polyglutamine peptides
Evidence for nucleation-dependent polymerization
Rates of elongation versus concentration are fit to a pre-equilibrium model
And fits to the model suggests that n*=1 for Q28, Q36, Q47
See Chen, Ferrone, Wetzel, PNAS, 2002
UV-CD data: Q5(-), D2Q15K2(-.-), Q28(…), Q45(---);
Chen et al. JMB, 311, 173 (2001)
1. No major difference between different chain lengths
2. CD spectra for polyglutamine resemble those of denatured proteins
For given N, there is a concentration (n) for which
∆ < 0. Why?


Hypothesis: Water is a poor solvent for polyglutamine:

Chain flexibility and attractions overwhelm chain-solvent
interactions

Polymers form internally solvated collapsed globules

Rg and other properties scale with chain length as N0.34

Most chains aggregate and fall out of solution
CD data and heuristics counter our hypothesis:

For denatured proteins, Rg~ N0.59 - polymers in good solvents

Polyglutamine is polar – suggests that water is a good solvent

Requires new physics to explain polyglutamine aggregation
Let’s test our hypothesis
MRMD – the “algorithm”
1. Using a series of “short” simulations, estimate the time
scale  over which :

Autocorrelation of “soft” modes decay

There are recurrent transitions between compact and
swollen conformations
2. Use the estimate for , the time scale for each
“elementary simulation” is tS~10

60-100 independent simulations, each of “length” ts
3. Pool data from all simulations and construct
conformational distributions using bootstrap methods
Simulation engine
 Forcefield: OPLSAA for peptides and TIP4P for water
 Constant pressure (P), constant temperature (T): NPT
 T = 298K, P = 1atm
 Thermostat and barostat: Berendsen weak coupling
 Long-range interactions: Twin range spherical cutoffs
 Periodic boundary conditions in boxes that contain > 4000 water
molecules
 Peptides: ace-(Gln)N-nme, N=5,15,20,…
 Cumulative simulation times > 5s
 We have an internal control – the excluded volume (EV) limit – to
quantify conformational equilibria in good solvents
Top row in water, bottom row in EV limit
Q5
In water
EV Limit
Q15
Q20
Scaling of internal distances is consistent with
behavior of chain in a poor solvent
Q5
Q15
Data for polyglutamine in EV limit
Data for polyglutamine in water
Q20
Can we test our “prediction”? Yes
 Using Fluorescence Correlation Spectroscopy (FCS)
 Peptides studied: -Gly-(Gln)N-Cys*-Lys2

* indicates fluorescent label, which is Alexa488
 Solution conditions:

PBS: pH 7.3, 8.0g NaCl, 0.2g KCl, 1.15g Di-sodium
orthophosphate, 0.2g Potassium di-hydrogen
orthophosphate, dissolved in pure H2O

Approximately one molecule in beam volume
 Is diffusion time, D N0.33 or is ln(D )  0.33ln(N)?
Evidence for poor solvent scaling
Polyglutamine: Compact albeit disordered
Observation of disorder is consistent with CD data
Quantifying topology
What is the length scale over which spatial correlations decay?
Compute <cos(θij)> as a function of |j-i|
Ni
residue i
C i
θ
C i+1
C j
Nn
C j+1
residue j
Up-down topology for collapsed polyglutamine
Q15
Q20
Hydrogen bonding patterns
Why collapse and what does it mean?
1. Summary – The ensemble for polyglutamine in water:

Is disordered albeit collapsed

Has a preferred up-down average topology

With a strong propensity for forming beta turns

And little to no long-range backbone hydrogen bonds
2. What drives collapse in water: Generic backbone?
3. Is there anything special about polyglutamine?
4. What does all this mean for nucleation of aggregation?
Distributions for polyglycine
Water
8M Urea
EV Limit
Mimics of polypeptide backbones prefer to be collapsed in water,
which appears to be a universal poor solvent for polypeptides
Polyglutamine is a chain of two types of amides: secondary and primary
Primary and secondary amides
Propanamide (PPA)
N-methylformamide (NMF)
Amides in water
 Pure (primary or secondary) Amides in water:
 N =nW + nA
 NPT Simulations with varying nA implies varying A
 T=300K, P = 1atm
 OPLSAA forcefield for amides, TIP4P for H2O
 nA = 16, 32, 64, etc. for 1, 2, 3, … molal solutions;
 nW = 800
 Amide (ternary) mixtures: Primary and secondary amides
 N = nW + nP + nS
 Keep nW and nP fixed and vary nS or nW and nS fixed, vary nP
 Will show data for nP = nS = 32
Pair correlations
1. NMF prefers water-separated contacts over hydrogen bonded contacts
2. PPA prefers hydrogen bonded contacts over water-separated contacts
3. PPA donor - NMF acceptor hydrogen bonds are preferred in mixtures
Cluster statistics
Typical large cluster in PPA:NMF mixtures
Consistent with data of Eberhardt and Raines, JACS, 1994
In polyglutamine, sidechains “solvate” the
backbone in compact geometries
Q20: Rg=8.86Å,  =0.096
Q20: Rg=8.11Å,  =0.13
Q20: Rg=8.49Å, =0.16
Hypothesis – part I: Why is aggregation
spontaneous?
 For a system of peptides of length N:
 There is a finite concentration (n) for which ∆ < 0
 ∆ < 0 if:
 Aggregated state of intermolecular solvation via
glutamine sidechains is preferred to the
disordered state of intramolecular solvation
whereby sidechains solvate their own backbones
 It is our hypothesis that:
 Peptide concentration at which ∆ becomes negative
will decrease “rapidly” with increasing chain length
Hypothesis – part II: Nucleation
 Ensemble of nucleus is species of highest free energy for monomer
 Nucleation must involve the following penalties:

DESOLVATION: Replace favorable sidechain-backbone
contacts and residual water-backbone contacts with
unfavorable backbone-backbone contacts
ENTROPIC BOTTLENECK: Replace disordered ensemble
with ordered nucleus
 Conformations in the nucleus ensemble?
1. β-helix-like (see work of Dokholyan group, PLoS, 2005)

2.
-pleated sheet (see work of Daggett group, PNAS, 2005)
3.
Antiparallel β-sheet (see fiber diffraction data)
Thanks to…
THE LAB






Xiaoling Wang
Andreas Vitalis
Scott Crick
Hoang Tran
Alan Chen
Matthew Wyczalkowski
Collaborations
 Ron Wetzel – UTK
 Murali Jayaraman – UTK
 Carl Frieden – WUSTL
Ongoing work…
1. Monomer distributions for N > 25
2. Free energies of nucleating intramolecular beta sheets
3. Influence of sequence context: In vivo, its not just a
polyglutamine
4. Quantitative characterization of oligomer landscape
5. Generalizations to aggregation of other intrinsically
disordered proteins rich in polar amino acids
6. Experiments: New FCS methods to study oligomers
and nucleation kinetics