Modeling the Structures of Proteins and Macromolecular Assemblies

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Modeling the Structures of Proteins
andMacromolecular Assemblies
Andrej Šali http//salilab.org/

• Depts. Of Biopharmaceutical Sciences and
  Pharmaceutical Chemistry
• California Institute for Quantitative Biomedical
  Research
• University of California at San Francisco

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1. Yeast and E. coli ribosomes Electron microscopy,
   comparative modeling, and structural genomics.
2. Yeast Nuclear Pore Complex Low-resolution
   modeling of large assemblies bridging the gaps
   between structural biology, proteomics, and
   system biology.
3. Comments.

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S. cerevisiae ribosome
Fitting of comparative models into 15Å cryo-
electron density map. 43 proteins could be
modeled on 20-56 seq.id. to a known
structure. The modeled fraction of the proteins
ranges from 34-99.
C. Spahn, R. Beckmann, N. Eswar, P. Penczek, A.
Sali, G. Blobel, J. Frank. Cell 107, 361-372,
2001.
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E. coli ribosome
H.Gao, J.Sengupta, M.Valle, A. Korostelev,
N.Eswar, S.Stagg, P.Van Roey, R.Agrawal,
S.Harvey, A.Sali, M.Chapman, and J.Frank. Cell,
in press.
Upon EF-G binding, the ribosome becomes less
compact. In contrast to mRNA, many protein
contacts undergo large conformational changes,
suggesting ribosomal proteins facilitate the
dynamics of translation.
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MODPIPE Large-Scale Comparative Protein
Structure Modeling
START
1
Get profile for sequence (NR)
Expand match to cover complete domains
PSI-BLAST
Scan sequence profile against representative PDB
chains
Align matched parts of sequence and structure
MODELLER
For each template structure
For each target sequence
Scan PDB chain profiles against sequence
Build model for target segment by satisfaction of
spatial restraints
Evaluate model
END
R. Sánchez A. Šali, Proc. Natl. Acad. Sci. USA
95, 13597, 1998. N. Eswar, M. Marti-Renom, M.S.
Madhusudhan, B. John, A. Fiser, R. Sánchez, F.
Melo, N. Mirkovic, A. Šali.
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http//salilab.org/modbase
Pieper et al., Nucl. Acids Res. 2002.
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Comparative modeling of the TrEMBL database
Unique sequences processed 733,239 Sequences
with fold assignments or models 415,937 (57)
4/03/02 4 weeks on 500 Pentium III CPUs
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Model Accuracy
Marti-Renom et al. Annu.Rev.Biophys.Biomol.Struct.
29, 291-325, 2000.
MEDIUM ACCURACY
LOW ACCURACY
HIGH ACCURACY
NM23 Seq id 77
CRABP Seq id 41
EDN Seq id 33
X-RAY
/ MODEL
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Future directions

• Make sure we have building blocks (structural
  genomics).
• Develop methods for simultaneous fitting of
  proteins into EM density and conformational
  modeling (induced fit, comparative modeling, ab
  initio).
• Need large computing (eg, cluster of hundreds of
  nodes with gt1GB memories).

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Modeling of the yeast nuclear pore complex by
satisfaction of spatial restraints (MODELLER)
F. Alber, T. Suprapto, J. Kipper, W. Zhang, L.
Veenhoff, S. Dokudovskaya, M. Rout, B. Chait,
A. Šali

• Rockefeller University, New York
• UCSF

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Modeling macromolecular assemblies by
satisfaction of spatial restraints

1. Representation of a system.
2. Scoring function (spatial restraints).
3. Optimization.

There is nothing but points and restraints on
them.
Sali, Ernst, Glaeser, Baumeister. From words to
literature in structural proteomics. Nature 422,
216-225, 2003.
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Modeling of NPC

• Stochiometry.
• Parse proteins into domains.
• Protein and sub-complex shapes from Stokes
  radii.
• Excluded volume of proteins.
• Symmetry of NPC (EM).
• Radial and axial localization of proteins (IEM).
• Protein-protein proximity (immuno-purification).
• Binary protein-protein contacts from overlay
  experiments.
• Modeling in the context of the nuclear envelope.
• Comparative models for some domains.
• Structural genomics of nucleoporins.

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Schematic structure of yeast NPC
C.W. Akey, M. Rout
TOP VIEW
SIDE VIEW
cytosolic side
nuclear membrane
nuclear side
half-spoke contains 30 nucleoporin proteins
(NUPs). 480 NUPs in NPC.
spoke
half-spoke
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Protein-protein contacts
For each protein pair within a half-spoke, the
upper bound on the center-center distance is the
estimated maximal complex diameter
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Successful optimization
11/18/02
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NUP84-complex
Experiment
Model
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Structural proteomics aims to characterize
structures of most macromolecular complexes, in
space and time.
On average, a domain may interact with a few
other domains. The function of a complex is
determined by its structure and dynamics. There
are too many complexes to be determined directly
by high-resolution experimental structure
determination. Thus, just like in structural
genomics, an efficient combination of experiment
and computation is required.
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Structural Proteomics versus Structural Genomics
Potential targets not clear clear Target
selection not clear clear Scope not
clear clear Structure determination hybrid X-ra
y or NMR Functional Annotation essential not a
major focus
There are additional sciences and technologies in
structural proteomics, relative to structural
genomics.
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Structural Genomics
Sali. Nat. Struct. Biol. 5, 1029, 1998. Sali et
al. Nat. Struct. Biol., 7, 986, 2000. Sali. Nat.
Struct. Biol. 7, 484, 2001. Baker Sali. Science
294, 93, 2001.
Characterize most protein sequences based on
related known structures.
There are 16,000 30 seq id families
(90) (Vitkup et al. Nat. Struct. Biol. 8, 559,
2001)
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Target selection for structural proteomics(scope)

• Comprehensive coverage.
• What targets
• Stable assemblies? Transient complexes? Pairs of
  domains?
• Can they be organized into groups?
• How many such groups are there?

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Target selection for structural proteomics?

• There are 3,000 folds containing 90 of all
  sequences.
• A target Binary domain-domain interface.
• There may be a finite number of domain-domain
  interfaces, largely defined by the domain fold
  types.
• Given pairwise interactions, a large assembly may
  be reconstructed.

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Protein and assembly structure by experiment and
computation
Sali, Ernst, Glaeser, Baumeister. From words to
literature in structural proteomics. Nature 422,
216-225, 2003.
3/25/3
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Modeling macromolecular assemblies by
satisfaction of spatial restraints

1. Representation of a system.
2. Scoring function (spatial restraints).
3. Optimization.

There is nothing but points and restraints on
them.
Sali, Ernst, Glaeser, Baumeister. From words to
literature in structural proteomics. Nature 422,
216-225, 2003.
3/25/03
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Future directions

• Development of general/flexible/hierarchical
  representation of assemblies.
• Quantifying spatial information from experiments.
  
• Optimization of structure.
• Toy models.
• Space, time.

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Role of NIH

• Structural proteomics is timely and feasible.
• Humongous integration of concepts, sciences,
  methods, tools, people.
• Thus, need research centers, but also R01
  research.
• Significant computing.
• Bridging the gaps between structural biology,
  proteomics, and system biology.

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