Transcript Folie 1

Prediction of SH3 Domain
Binding Motifs
Presented by: Siba Ismael
Supervised by: Mazen Ahmad
University of Saarland
Saarbrücken, 17.10.08
Outline

SH3 motif and proline-rich domains
- Motivation to find SH3 domains binding sites
-Why proline-rich domains?

Binding Free Energy Method: What flanking sequences govern
binding specificity

Materials and Methods; Bioinformatics

Results of Prediction

Conclusions and Outlook
Outline
2
SH3 Domains
Motivation- Assembly
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Comprise 60 residues

Play assembly and regulatory
roles.

Assembly role: example; Grb2

Cascade: Growth factor
receptor tyrosine kinase
Grb2 SOS Ras
MAPK
- Play roles in cell growth and
differentiation
Introduction- SH3 Motif and ProlineRich Domains
3
SH3 Domains
Motivation- Regulation

Regulation: example; Src
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Built-in SH2+SH3: inactivation
(autoinhibition)

Disruption: External SH2 and SH3
domains interaction
-result in kinase activation

SH3 interactions: week
- typical dissociation constant
- essential for reversible switching
mechanism.
Introduction- SH3 Motif and ProlineRich Domains
4
Repetitive Proline-Rich Sequences
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in many cases, thought to function as docking sites for signaling modules

found in the context of larger multidomain signaling proteins.
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Binding: assembly and targeting of protein complexes involved in:
- cell growth
- cytoskeletal rearrangements
- transcription
- postsynaptic signaling processes

play a regulatory role and autoinhibitory interactions
Introduction- SH3 Motif and ProlineRich Domains
5
Repetitive Proline-Rich Sequences

Why proline in interaction
modules?

Proline: unique amino acid in:
- constraints on dihedral
angles imposed by cyclic side
chain
- its resulting secondary
structural preferences
Introduction- SH3 Motif and ProlineRich Domains
6
Repetitive Proline-Rich Sequences

Why proline in interaction modules?

propensity to form a polyproline type II (PPII)
helix.
- extended left-handed helical structure with three
residues per turn.
- useful recognition motif:
- carbonyls point out from the helical axis into
solution
- restricted backbone: entropy cost of binding
reduced
- twofold rotational pseudosymmetry:
- two binding possibilities
- orientational switching
differing domain
Introduction- SH3 Motif and Prolinefunction
Rich Domains
7
Repetitive Proline-Rich Sequences

Why proline in interaction modules?

The only naturally occuring Nsubstituted amino acid:
- sequence-specific recognition
without high-affinity interaction.
- specific and low affinity interactions:
- reversibility
- intracellular signalling

Stable cis conformation
- high kinetic barrier
- rate limiting step
Introduction- SH3 Motif and ProlineRich Domains
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Proline-Rich Sequences vs. SH3 Interaction
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PxxP motif: flanked by different specificity
elements:
- K/RxxPxxP and PxxPxK/R classes of ligand
motif
- single recognition surface: two N- to Cterminal orientations ligand binding
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SH3 fold: two antiparallel β sheets at right
angles.
- in fold RT and n-Src loops: flanking specificity
pockets

Aromatic SH3 groove
of residues)
PPII helix ridges (a pair
Introduction- SH3 Motif and ProlineRich Domains
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So how to detect the binding
affinity to SH3 domains?
Computational Analysis!!!
Solvation Energy!!
„BIOPHYSICS“
10
Binding Free Energy

mechanical energy to disassemble a whole into
separate parts
scalar
bind G  3G  (4G  2G)  1G
bind G  solvG  coulG

Binding free energy cycle:
- in terms of transfer free energies
Why?
- from a homogeneous dielectric environment
(interactions: Coulomb's law)
- to an inhomogeneous dielectric environment:
differing internal and external dielectric constants.
Binding Free Energy Components
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Binding Free Energy
Solvation Energy Contribution

Solvation energy for the complex and each of its parts
Remember!! This
stands for Coulombic
 solv G  4G  2G
 solv G   solv Gcomplex   solv Gligand
  solv G protein
But how to calculate solvation energy?
Binding Free Energy Components
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Binding Free Energy
Solvation Energy Contribution

Full solvation energy cycle
- Step 1: Total Solvation
- Step 2: charging of the solute in solution
inhomogeneous
presence of mobile ions.
-Step 3: attractive solute-solvent dispersive
interaction
- Step 4: repulsive solute-solvent interaction
- Steps 5 and 6: null steps.
- but used to offset unwanted energies
charging of the solute in vacuum
homogeneous
absence of mobile ions.
Binding Free Energy Components
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Binding Free Energy
Solvation Energy Contribution
solvG   pG  nG
 pG  2G  6G
 pGBorn 
q2
(
1
80a  out

1
 in
 n G   4 G  (  3G   5 G )

 

)
4G  pV  A
3G  5G    u ( att ) ( y ) ( y )dy

APBS??
ACC??
Binding Free Energy Components
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Binding Free Energy
Including Coulombic Contribution

the sum of pairwise Coulombic interactions:
- for all atoms in the molecule
- for a particular uniform dielectric
coul G  1G   coul Gcomplex
  coul G protein   coul Gligand

Coulomb‘s Law:
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Potential Dielectric Energy:
1
q1q2
F
4 r 2
U12 
1
q1q2
4 r
Coulomb??
Binding Free Energy Components
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Binding Free Energy
Entropy

Entropy: a measure of the
unavailability of a system’s
energy to do work
- measure of the
randomness of molecules
in a system
- central to the second law
of thermodynamics
Spontaneous changes
Entropy (isolated systems)
Binding Free Energy Components
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Binding Free Energy
van der Waals

van der Waals force: attractive or
repulsive forces between molecules
and per molecule:
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not covalent bonds or electrostatic
interaction of ions, but:
- permanent dipole–permanent dipole
forces
- permanent dipole–induced dipole
forces
- instantaneous induced dipoleinduced dipole
Binding Free Energy Components
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Poisson-Boltzmann Equation
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Differential equation – describes electrostatic interactions between
molecules in ionic solutions

models implicit solvation (continuum solvation )


 (r) : the posit ion- dependentdielectric, (r) : theelectrostatic potential

 (r) : chargedensityof thesolute
f
c i : concentration of theion i at a distanceof infinit yfrom thesolute
z i : thechargeof theion, q : thechargeof a prot on,
k B : Bolt zmannconstant,T : the temperatu
re

 (r) : a factorfor theposit ion- dependentaccessibility of posit ionr
to theions in solution.
Binding Free Energy Components
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Methods
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APBS Package: Adaptive Poisson–Boltzmann Solver:
- numerical solution for the Poisson-Boltzmann
equation
- modeling biomolecular solvation
In my work:
* apbs: electrostatic potential and polar solvation
* acc: SASA calculation: „solvent accessible surface
area“
nonpolar solvation
* coulomb: coulombic interactions in vacuum
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Pdb2pqr Package: platform-independent utility
- converts protein files in PDB format to PQR format
Methods
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Methods
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PQR file: PDB file
temperature and occupancy columns;
replaced by the per-atom charge (Q) and radius (R)
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Jackal: package for protein structure modeling
scap: protein side-chain program:
 predicts side-chain conformations and side chains of a whole
protein and in
 mutates specified residues in a protein
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R language Package: Statistical Language environment
Methods
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Methods
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To predict a binding motif of length 10:
- chose the crystal structure of the peptide
APSYSPPPPP complexed with the Abl SH3
domain
- mutate it to other sequences
- T otal: 2010 -1 differentmotifs
comparewith template!!
- Reduce to 208 -1 differentmotifs
comparewith template 
all have the PxxP motif?!
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Fix P at P0 and P3
Try: predicton of 10 very good out of the 600
candidates, and 15 of the nonbinders
almost all have a PxxP domain!
Methods
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Methods

From
literature:
Binding
Free
Energy
Difference
to the
base
sequence
with the
following
mutations:
Methods
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Results
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Correlation?!
Correlation :
Correlation:
Correlation:
0.4530898
0.9534504
0.722554
Results
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Reproducibility?!
Without vdW or
entropy
correlation:
0.5435262
Why not much
good?
For both
Correlation: 0.3357690
Second compared to base
sequence
Results
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Peptide Binding-Solvation Polar
Easier barrier to break for binders
Results
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Coulombic Interactions
Mean Coulombic Energy is less for binders!
Results
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Nonpolar Solvation Contribution
Neglicted effect!
Results
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van der Waals Contribution
Major contribution to binding specificity
Results
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Entropy Contribution
Most non-Binders Lost more Entropy upon Binding than did
Binders!
Results
30
Binding Free Energy
Less Binding Free Energy for Binders!
Easier barrier to break
Results
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Separation of Binders from non-binders
Prediction
Linear Discriminant
Analysis!
Results
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From Literature
Binders
Results
Nonbinders
Sequence
Gpred
SKKEMQPTHP
19.6
ASQKMEPRAP
43.3
WELSSQPTIP
26.3
LAPASTPTSP
13.6
ASTPTSPSSP
11.4
SSPGLSPVPP
13.8
RGVLIEPVYP
38.9
DEPNLEPSWP
26.4
RLVGARPLLP
24.6
RTESEVPPRP
26.6
LASRPLPLLP
20.1
ISQRALPPLP
30.8
ITMRPLPALP
17.3
RSGRPLPPIP
32.7
KWDSLLPALP
17.4
YWDMPLPRLP
4.2
YYQRPLPPLP
9.1
YFSRALPGLP
8.8
SLWDPLPPIP
15.2
DPYDALPETP
28.6
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Results concerning Prediction!

Proline preferece in the binding motif
- Available experimental measurements at
positions P3, P0, P−3, and P−5:
- Particularly important for the peptide binding:
- conserved Pro residues at P3 and P0: strong
binding affinity (PxxP- work here)
- residues at P−3, and P−5: the binding specificity
(the other work)

Other residues, especially hydrophobic (Phe,
Leu, Met, Val, and Trp), also favored
Results
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Conclusion and Outlook!

Binding free energy:
- nice method predictiong binding preferences
- easy to deal with data

Can be used in prediction of different sets of
protein-ligand interaction prediction

High throughput results in the fields of medicine,
pharmacy, and biology
Conclusions and Outlook
35
References
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Tingjun Hou, Ken Chen, William A McLaughlin, Benzhuo Lu, and Wei Wang.
Computational Analysis and Prediction of the Binding Motif and Protein
Interacting Partners of the Abl SH3 Domain
Wikipedia
T.Geyer, Dynamic Cell Simulation
Jackal: supported by National Science Foundation and National Institute of Health;
developed in Honig Lab
Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA. APBS: Electrostatics of
nanosystems: application to microtubules and the ribosome. Proc. Natl. Acad.
Sci. USA 98, 10037-10041 2001.
Dolinsky TJ, Nielsen JE, McCammon JA, Baker NA. PDB2PQR: an automated
pipeline for the setup, execution, and analysis of Poisson-Boltzmann
electrostatics calculations. Nucleic Acids Research, 32, W665-W667 (2004).
R: Regulatory Compliance and Validation Issues A Guidance Document for the Use of
R in Regulated Clinical Trial Environments
Google Machine Search
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