Protein Networks / Protein Complexes

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Protein Networks / Protein Complexes

• Protein networks could be defined in a number of
  ways
• - Co-regulated expression of genes/proteins
• Proteins participating in the same metabolic
  pathways
• Proteins sharing substrates
• Proteins that are co-localized
• Proteins that form permanent supracomplexes
  protein machineries
• Proteins that bind eachother transiently
• (signal transduction, bioenergetics ... )

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A biological cell a large construction site?
In a biological cell there are many tasks that
need to be executed in a timely and precise
manner.
Job office publishes lists (DNA) of people
looking for jobs (protein). Managers from the
personnel office (DNA-transcription factors)
recruit (express) proteins.
Workers (proteins) need to get to their working
places (localization). During work they get
energy from drinking beer (ATP).
All steps depend on interaction of proteins with
DNA or with other proteins!
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1 Protein-Protein Complexes
It has been realized for quite some time that
cells dont work by random diffusion of
proteins, but require a delicate structural
organization into large protein complexes.
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Examples of Stable Protein Complexes Ribosome
The ribosome is a complex subcellular particle
composed of protein and RNA. It is the site of
protein synthesis, http//www.millerandlevine.co
m/chapter/12/cryo-em.html
Model of a ribosome with a newly manufactured
protein (multicolored beads) exiting on the
right.
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Examples of Stable Protein Complexes Proteasome
The proteasome is the central enzyme of
non-lysosomal protein degradation. It is involved
in the degradation of misfolded proteins as well
as in the degradation and processing of short
lived regulatory proteins.The 20S Proteasome
degrades completely unfoleded proteins into
peptides with a narrow length distribution of 7
to 13 amino acids. http//www.biochem.mpg.de/xray
/projects/hubome/images/rpr.gif Löwe, J., Stock,
D., Jap, B., Zwickl, P., Baumeister, W. and
Huber, R. (1995). Crystal structure of the 20S
proteasome from the archaeon T. acidophilum at
3.4 Å resolution. Science 268, 533-539.
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Stable Protein Complex Nuclear Pore Complex
A three-dimensional image of the nuclear pore
complex (NPC), revealed by electron microscopy.
A-B The NPC in yeast. Figure A shows the NPC
seen from the cytoplasm while figure B displays a
side view. C-D The NPC in vertebrate (Xenopus).
http//www.nobel.se/medicine/educational/dna/a/t
ransport/ncp_em1.html Three-Dimensional
Architecture of the Isolated Yeast Nuclear Pore
Complex Functional and Evolutionary
Implications, Qing Yang, Michael P. Rout and
Christopher W. Akey. Molecular Cell, 1223-234,
1998
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Stable Protein Complex Photosynthetic Unit

• Other large complexes
• - Apoptosome
• Thermosome
• Transcriptome

Structure suggested by force field
based molecular docking. http//www.ks.uiuc.edu/R
esearch/vmd/gallery

• Other large complexes
• Apoptosome 7-fold symmetry
• Chaperone (GroEL/GroES) 7-fold symmetry
• Thermosome
• Transcriptome

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2 Protein-protein networks
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2. Yeast 2-Hybrid Screen
Data on protein-protein interactions from Yeast
2-Hybrid Screen. One role of bioinformatics is
to sort the data.
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Protein cluster in yeast
Cluster-algorithm generates one large cluster
for proteins interacting with each other based
on binding data of yeast proteins.
Schwikowski, Uetz, Fields, Nature Biotech. 18,
1257 (2001)
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Annotation of function
After functional annotation connect clusters
of interacting proteins.
Schwikowski, Uetz, Fields, Nature Biotech. 18,
1257 (2001)
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Annotation of localization
Schwikowski, Uetz, Fields, Nature Biotech. 18,
1257 (2001)
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Relation between lethality and function as
centers in protein networks

• study analyzed protein-protein interaction
  network in yeast S. cerevisae
• Yeast two-hybrid screen data identified
• 2240 direct physical interactions
• between 1870 proteins, see
• Uetz et al. (1999) und Xenarios et al. (2000).
• analyze the effects of single gene deletions for
  lethality
• in proteom data base existed 1572 entries of
  known phenotypic profiles.

Jeong, Mason, Barabási, Oltvai, Nature 411, 41
(2001)
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Protein-Protein interactions in yeast

• Cluster analysis of 2YHB data.
• Shown is largest cluster containing 78 of all
  proteins.
• The color of each node marks the phenotypic
  effect if this protein is removed from the cell
  (gene knockout).
• red - lethal
• green no effect
• orange slow growth
• gelb - unknown

Jeong, Mason, Barabási, Oltvai, Nature 411, 41
(2001)
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Relation between lethality and function as
centers in protein networks

• Likehood p(k) of finding proteins in yeast that
  interact with exactly k other proteins.
• Probability has power law dependence.
• (Similar plot for bacterium Heliobacter pylori.)
• ? network of protein-protein interactions is a
  very inhomogenous scale-free network where a few,
  highly connected, proteins play central roles of
  mediating the interactions among other, less
  strongly connected, proteins.

Jeong, Mason, Barabási, Oltvai, Nature 411, 41
(2001)
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Relation between lethality and function as
centers in protein networks

• Computational analysis of the tolerance of
  protein networks for random errors (gene
  deletions).
• Random mutations dont have an effect on the
  total topology of the network.
• When hub proteins with many interactions are
  eliminated, the diameter of the network decreases
  quickly.

The degree of proteins being essential (gene
knock-out is lethal for cell) depends on the
connectivity in the yeast protein
network. Strongly connected proteins with central
roles in the architecture of the network are 3
times as essential as proteins with few
connections.
Jeong, Mason, Barabási, Oltvai, Nature 411, 41
(2001)
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3 Identification of protein complexes
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Systematic identication of large protein complexes
Yeast 2-Hybrid-method can only identify binary
complexes. Cellzome company attach additional
protein P to particular protein Pi , P binds to
matrix of purification column. ? yields Pi and
proteins Pk bound to Pi .
Identify proteins by mass spectro- metry
(MALDI- TOF).
Gavin et al. Nature 415, 141 (2002)
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Analyis of protein complexes in yeast (S.
cerevisae)
Identify proteins by scanning yeast
protein database for protein composed of
fragments of suitable mass. Here, the
identified proteins are listed according to
their localization (a). (b) lists the number
of proteins per complex.
Gavin et al. Nature 415, 141 (2002)
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Example of particular complex
Check of the method can the same complex be
obtained for different choice of attachment
point (tag protein attached to different
coponents of complex)? Yes (see gel).
Method allows to identify components of complex,
not the binding interfaces. Better for
identification of interfaces Yeast 2-hybrid
screen (binary interactions). 3D models of
complexes are important to develop inhibitors.

• theoretical methods (docking)
• electron tomography

Gavin et al. Nature 415, 141 (2002)
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3. Netzwerk aus Proteinkomplexen
Service function of Bioinformatics catalog such
data and prepare for analysis ... allowing to
formulate new models and concepts (biology!). If
results are very important dont wait for some
biologist to interpret your data. You may want to
get the credit yourself.
Modularity Formation of separated Islands ??
Gavin et al. Nature 415, 141 (2002)
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Structural ProteomicsSali, Glaeser, Earnest,
Baumeister, Nature 422, 216 (2003)
Biological cells are not organized by undirected
diffusion of the soluble proteins! Instead many
important cellular functions are carried out by
stable or transiently formed protein complexes.
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known protein structures

PDZ Domäne CheA Aquaporin Ribosom
Large proteins are underrepresented in the PDB
data base. Based on the Cellzome results, people
estimate that each protein complex in yeast
contains 7.5 proteins.
Sali et al. Nature 422, 216 (2003)
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Single particle analysis with EM

• Complexes of 44 tripeptidyl-peptidase II
  molecules on a surface.
• The pictures in each line show different averaged
  views of complexes possessing
• the same orientation ? image analysis.
• (b) 3D-rekonstruction of the TPP II-complex at
  3.3 nm resolution.
• Different views. Note the enhanced resolution by
  combining information of
• the different views shown in (a).

Sali et al. Nature 422, 216 (2003)
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Information about macromolecular complexes
Subunit structure atomic resolution lt 3
Å Subunit shape medium resolution gt 3
Å Subunit contact Knowledge about direct
spatial contacts between subunits Subunit
proximity subunits dont need to be in direct
contact. Grey boxes indicate areas with large
experimental difficulties.

Sali et al. Nature 422, 216 (2003)
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Hybrid-methods for macromolecular complexes
Structural Bioinformatics (a) Integration of
varios protein elements into one large
complex. (b) Partial atomic model of the entire
yeast ribosome by fitting atomic models of rRNA
and proteins into a low-resolution EM map of the
80S ribosome.

Sali et al. Nature 422, 216 (2003)
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Structure of large complexes combine EM X-ray
docking of atomic X-ray structure of tubulin (3.5
Å resolution) into 8Å-EM-structure of
microtubuli.

Sali et al. Nature 422, 216 (2003)
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Situs package Automated low-resolution fitting
Situs was developed for automatic fitting of
high-resolution structures from X-ray
crystallography into low-resolution maps from
electron microscopy. http//biomachina.org see
also database for animations of EM
data http//emotion.biomachina.org/ Idea
Create low-resolution image of X-ray
structure. Determine center of mass and moments
of inertia. Model one protein by a few mass
centers. Use neuronal network to best position
nodes (mass points) into EM density map of the
molecular complex. Molecular mass represented by
nodes should maximally overlap with EM map.

Wriggers et al. J. Mol. Biol. 284, 1247 (1998)
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Discretization of proteins by few mass points

Wriggers et al. J. Mol. Biol. 284, 1247 (1998)
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Reconstruction of actin filament using Situs

Wriggers et al. J. Mol. Biol. 284, 1247 (1998)
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Reconstruction of actin filament using Situs

Wriggers et al. J. Mol. Biol. 284, 1247 (1998)
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Situs package Conformational Dynamics
In the mean time, the Situs developers have also
switched to using FFT techniques to match images
and real data.

Chacon et al. Acta Cryst D 59, 1371 (2003)
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Electron Tomography
a) The electron beam of the EM microscope is
scattered by the central object and the scattered
electrons are detected on the black plate. By
tilting the object in small steps, we collect
electrons scattered at different angles. b)
reconstruction in the computer. Back-projection
(Fourier method) of the scatter-information at
different angles. The superposition generates a
three-dimensional tomogrom.

Sali et al. Nature 422, 216 (2003)
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Identification of macromolecular complexes in
cryoelectron tomograms of phantom cells

Prepare phantom cells (ca. 400 nm diameter)
with well-defined contents Liposomes filled with
thermosomes and 20S proteasomes. Thermosome 933
kD, 16 nm diameter, 15 nm height, subunits
assemble into toroidal structure with 8-fold
symmetry. 20S proteasome 721 kD, 11.5 nm
diameter, 15 nm height, subunits assemble into
toroidal structure with 7-fold symmetry. Collect
Cryo-EM pictures of phantom cells for a tilt
series from -70º until 70º with 1.5º
increments. Aim identify and map the 2 types of
proteins in the phantom cell. This is a problem
of matching a template, ideally derived from a
high-resolution structure, to an image feature,
the target structure.
Frangakis et al., PNAS 99, 14153 (2002)
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Detection and idenfication strategy

Frangakis et al., PNAS 99, 14153 (2002)
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Search strategy

• Adjust pixel size of templates to the pixel size
  of the EM 3D reconstruction.
• The gray value of a voxel (volume element)
  containing ca. 30 atoms is obtained by summation
  of the atomic number of all atoms positioned in
  it.
• Possible search strategies
• Scan reconstructed volume by using small boxes of
  the size of the target structure (real space
  method)
• Paste template into a box of the size of the
  reconstructed volume (Fourier space method). This
  method is much more efficient.

Frangakis et al., PNAS 99, 14153 (2002)
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Correlation with Nonlinear Weighting
The correlation coefficient CC is a measure of
similarity of two features e.g. a signal x
(image) and a template r both with the same size
R. Expressed in one dimension
are the mean values of the subimage and the
template. The denominators are the variances
To derive the local-normalized cross correlation
function or, equivalently, the correlation
coefficients in a defined region R around each
voxel k, which belongs to a large volume N
(whereby N gtgt R), nonlinear filtering has to be
applied. This filtering is done in the form of
nonlinear weighting.
Frangakis et al., PNAS 99, 14153 (2002)
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Raw data

• Central x-y slices through the 3D reconstructions
  of ice-embedded phantom cells filled with
• 20S proteasomes,
• thermosomes,
• and a mixture of both particles.
• At low magnification, the macromolecules appear
  as small dots.

Frangakis et al., PNAS 99, 14153 (2002)
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Correlation coefficients

• Histogram of the correlation coefficients of the
  particles found in the proteasome-containing
  phantom cell scanned with the "correct"
  proteasome and the "false" thermosome template.
  Of the 104 detected particles, 100 were
  identified correctly. The most probable
  correlation coefficient is 0.21 for the
  proteasome template and 0.12 for the thermosome
  template.
• Histogram of the correlation coefficients of the
  particles found in the thermosome-containing
  phantom cell. Of the 88 detected particles,
  77 were identified correctly. The most probable
  correlation value is 0.21 for the thermosome
  template and 0.16 for the proteasome template.
• Detection in (a) works well, but is somehow
  problematic in (b) because (correct) thermosome
  and proteasome are not well separated.

Frangakis et al., PNAS 99, 14153 (2002)
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Reconstruction of phantom cell
Volume-rendered representation of a reconstructed
ice-embedded phantom cell containing a mixture of
thermosomes and 20S proteasomes. After applying
the template-matching algorithm, the protein
species were identified according to the maximal
correlation coefficient. The molecules are
represented by their averages thermosomes are
shown in blue, the 20S proteasomes in yellow.

The phantom cell contained a 11 ratio of both
proteins. The algorithm identifies 52 as
thermosomes and 48 as 20S proteasomes.
Frangakis et al., PNAS 99, 14153 (2002)
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Electron tomography

• Method has very high computational cost.
• Observation biological cells are not packed so
  densely as expected, allowing the
  identification of single proteins and protein
  complexes
• Problem for real cells molecular crowding.
• Potential difficulties to identify spots.
• - need to increase spatial resolution of tomograms

Frangakis et al., PNAS 99, 14153 (2002)
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Reconstruction of endoplasmatic reticulum
Picture rights shows rough endoplasmatic
reticulum (membrane network in eukaryotic cells
that generates proteins and new membranes) coated
with ribosomes. The picture is taken from an
intact cell. Membranes are shown in blue, the
ribosomes in green-yellow.

http//science.orf.at/science/news/61666 Dept. of
Structural Biology, Martinsried
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Reconstruction of actin filaments
Actin filaments are structural proteins they
form filaments which span the entire cell. They
stabilize the cellular shape, are required for
motion, and are involved in important cellular
transport processes (molecular motors like
kinesin walk along these filaments).

Shown is the cytoskeleton of Dictyostelium.
Apparently, filaments cross and bridge each other
at different angles, and are connected to the
cell membrane (right picture). Actin filaments
are shown in brown. The cell segment left has a
size of 815 x 870 x 97 nm3. Middle single actin
filaments connected at different angles. Right
actin filaments (brown) binding to the cell
membrane (blue).
http//science.orf.at/science/news/61666 Dept. of
Structural Biology, Martinsried
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Science fiction

• Reconstruct proteom of real biological cells.
• Required steps
• obtain EM maps of isolated (e.g. 6000 yeast)
  proteins
• enhance resolution of tomography
• speed up detection algorithm

http//science.orf.at/science/news/61666 Dept. of
Structural Biology, Martinsried
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Summary

• The structural characterization of large
  multi-protein complexes and the resolution of
  cellular architectures will likely be achieved by
  a combination of methods in structural biology
• X-ray crystallography and NMR for high-resolution
  structures of single proteins and pieces of
  protein complexes
• (Cryo) Electron Microscopy to determine
  medium-resolution structures of entire protein
  complexes
• Stained EM for still pictures at
  medium-resolution of cellular organells
• (Cryo) Electron Tomography to for 3-dimensional
  reconstructions of biological cells and for
  identification of the individual components.
• Mapping and idenfication steps require heavy
  computation.
• Employ protein-protein docking as a help to
  identify complexes?

Botstein Risch, Nature Gen. 33, 228 (2003)