Transcript No Slide Title

Biochemie IV – Struktur und Dynamik von Biomolekülen II. (Mittwochs 8-10 h, INF 230, klHS)
30.4.
7.5.
14.5.
21.5.
28.5.
4.6.
11.6.
18.6.
25.6.
2.7.
9.7.
16.7.
23.7.
Jeremy Smith: Intro to Molecular Dynamics Simulation.
Stefan Fischer: Molecular Modelling and Force Fields.
Matthias Ullmann: Current Themes in Biomolecular Simulation.
Ilme Schlichting: X-Ray Crystallography-recent advances (I).
Klaus Scheffzek: X-Ray Crystallography-recent advances (II).
Irmi Sinning: Case Study in Protein Structure.
Michael Sattler: NMR Applications in Structural Biology.
Jörg Langowski: Brownian motion basics.
Jörg Langowski: Single Molecule Spectroscopy.
Karsten Rippe: Scanning Force Microscopy.
Jörg Langowski: Single Molecule Mechanics.
Rasmus Schröder: Electron Microscopy.
Jeremy Smith: Biophysics, the Future, and a Party.
Protein
Computational
Molecular Biophysics
Universität
Heidelberg
IBM PLANS SUPERCOMPUTER
THAT WORKS AT SPEED OF
LIFE
IBM today will announce its intention to invest $100 million over
the next five years to build Blue Gene, a supercomputer that will
be 500 times faster than current supercomputing technology.
Researchers plan to use the supercomputer to simulate the
natural biological process by which amino acids fold themselves
into proteins. (New York Times 12/06/99)
Protein
Folding
Exploring the
Folding
Landscape
Uses of Molecular Dynamics Simulation:
•structure
•flexibility
•solvent effects
•chemical reactions
•ion channels
•thermodynamics (free energy changes, binding)
•spectroscopy
•NMR/crystallography
Atomic-Detail Computer Simulation
Model System
Molecular Mechanics Potential
V
 k b  b 
2
b
0
bonds


 k    
2
0

angles
N
  K 1  cosn      K    
2
n
dihedrals n 1
0
impropers
  12   6 
qq 
  4 ij  ij    ij      i j 
 r   i , j  Dr 
 rij 
i, j
 ij  
 ij 

Energy Surface 
Exploration by Simulation..
Model System
•set of atoms
•explicit/implicit solvent
•periodic boundary conditions
Potential Function
•empirical
•chemically intuitive
•quick to calculate
Tradeoff: simplicity (timescale) versus accuracy
Lysozyme in explicit water
2/8
MM Energy Function


l
r
qi
qj
Potential Function  Force
Newton’s Law:
Vi
Fi  
ri
Fi  mi ai
Taylor expansion:
Verlet’s Method
1
h
o
u
r
h
e
r
e
Statistical
Mechanics
Observable
1 hour here
Ensemble Average
MD Simulation:
Ergodic Hypothesis:
Analysis of MD
Configurations
Averages
Fluctuations
Time Correlations
Timescales.
Bond vibrations - 1 fs
Collective vibrations - 1 ps
Conformational transitions - ps or longer
Enzyme catalysis - microsecond/millisecond
Ligand Binding - micro/millisecond
Protein Folding - millisecond/second
Molecular dynamics:
Integration timestep - 1 femtosecond
Set by fastest varying force.
Accessible timescale about 10 nanoseconds.
•SOME EXAMPLES
Does CD4-binding peptide have a similar
structure in all strains of HIV-1 ?
11 Sequences
in 9 clades
•
•
•
•
•
•
•
•
•
•
•
A1
B1
C1
D2
E2
E3
F1
G2
1A0
2A3
OC4
LEU PRO CYS ARG ILE LYS GLN PHE ILE ASN MET TRP GLN GLU VAL
LEU PRO CYS ARG ILE LYS GLN ILE VAL ASN MET TRP GLN GLU VAL
ILE PRO CYS ARG ILE LYS GLN ILE ILE ASN MET TRP GLN GLU VAL
LEU PRO CYS ARG ILE LYS PRO ILE ILE ASN MET TRP GLN GLU VAL
LEU PRO CYS LYS ILE LYS GLN ILE ILE ASN MET TRP GLN GLY VAL
LEU PRO CYS LYS ILE LYS GLN ILE ILE LYS MET TRP GLN GLY VAL
LEU LEU CYS LYS ILE LYS GLN ILE VAL ASN LEU TRP GLN GLY VAL
LEU PRO CYS LYS ILE LYS GLN ILE VAL ARG MET TRP GLN ARG VAL
LEU PRO CYS LYS ILE LYS GLN ILE VAL ASN MET TRP GLN ARG VAL
LEU GLN CYS ARG ILE LYS GLN ILE VAL ASN MET TRP GLN LYS VAL
ILE PRO CYS LYS ILE LYS GLN VAL VAL ARG SER TRP ILE ARG GLY
+2
+2
+2
+2
+3
+4
+2
+5
+4
+4
+5
Molecular Dynamics
Simulation Setup
• Box dimensions: 53x40x40 Ǻ
• Explicit water molecules (TIP3P)
(~8600 atoms)
• Explicit ions
(Sodium and Chloride, 26 ions in total);
physiological salt: 0.23M
• ~240 peptide atoms
=> approx. 8900 atoms in total
• Uncharged system
• NPT ensemble: 300K, 1atm
• 5ns simulation time for each strain
=> 55ns total simulation time
Dihedral angles


Surface electrostatic properties
conserved.
Cancer Biotechnology.
Detection of Individual p53Autoantibodies in Human Sera
Rhodamine 6G
Fluorescence Quenching of Dyes
by Trytophan
Quencher
N
N
O
OH
O
MR121
Dye
N
Fluorescently labeled
Peptide
?
Analysis
r
Strategy:
Quenched
Results:
Healthy
Person
Serum
Cancer
Patient
Serum
Fluorescent
Protein Folding/Unfolding
Protein
Folding
Exploring the
Folding
Landscape
Prion diseases of animal and man
BSE
scrapie
CWD
TME
cattle
sheep
elk
mink
bovine spongiform encephalopathy
chronic wasting disease
transmissible mink encephalopathy
kuru
CJD
human
human
Creutzfeldt-Jakob disease
vCJD
GSS
FFI
human
human
human
variant CJD
Gerstmann-Sträussler-Scheinker disease
fatal familial insomnia
sporadic
genetic
infectious
Properties of the prion protein
-
The natural prion protein is encoded by a single exon as a polypeptide chain
of about 250 to 260 amino acid residues.
-
Posttranslational modification: cleavage of a 22 (N-terminal) and 23 (Cterminal) residue signal sequence => about 210 amino acid residues
-
PrP contains a single disulfide bridge.
-
PrP contains 2 glycosylation sites.
-
PrP inserts into the cellular plasma membrane through a glycosylphosphatidyl-inositol anchor at the C-terminus.
Structure of the prion protein
Superimposed PrP structures
The first image below shows the structure of part of the hamster and
mouse PrPC molecules superimposed. The close similarity in the
structures is obvious, as is the preponderance of alpha helical structure.
Location of human mutations
The picture shows the position of various mutations important for prion disease
development in humans modelled on the hamster structure PrPC.
Many of these mutations are positioned such that they could disrupt the secondary
structure of the molecule.
Mouse Prion Protein (PrPc)
NMR Structure
Structure of PrPSc
The PrPSc has a much higher
b-sheet content.
Bundeshochleistungsrechner Hitachi SR8000-F1
IBM PLANS SUPERCOMPUTER
THAT WORKS AT SPEED OF
LIFE
IBM today will announce its intention to invest $100 million over
the next five years to build Blue Gene, a supercomputer that will
be 500 times faster than current supercomputing technology.
Researchers plan to use the supercomputer to simulate the
natural biological process by which amino acids fold themselves
into proteins. (New York Times 12/06/99)
Safety in Numbers
Large-Scale Conformational Change
Structural Changes in Proteins:
The Physical Problem
ENERGY LANDSCAPE:
high-dimensional, rugged.
Need to find PATHWAY WITH
LOWEST SADDLE POINT.
Conformational
Pathways
Navigate energy landscape to find
continuous path of lowest free energy
from one end point to the other.
`
Muscle Contraction
Thin filament
Thick filament
Z disc
Sliding filaments…. of Myosin and Actin
SONJA SCHWARZL
STEFAN FISCHER
ATP Hydrolysis by Myosin
Power Stroke in Muscle
Contraction.
End ss 2003