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Transcript
Computersimulation of reality
real world
experiment
experimental
data
classification
abstraction
simplification
approximation
generalisation
model
of the world
comparing
is
testing
computational
methods
Three important turns in science:
Thales 600 B.C.
Galileo 1500 A.D. model
design experiment
mimic reality
Rahman 1980 A.D. model
on a computer
predictions
observe
observe
model
model
observe
model
Computersimulation of biomolecular systems
1) Why
2) How
do we simulate ?
3) What
4) And the future …
Computersimulation of biomolecular systems
1) Why
do we simulate ?
2) How
3) What
4) And the future …
For which problems are simulations useful ?
Simulation can replace or complement the experiment:
1. Experiment is impossible
Inside of stars
Weather forecast
2. Experiment is too dangerous
Flight simulation
Explosion simulation
3. Experiment is expensive
High pressure simulation
Windchannel simulation
4. Experiment is blind
Some properties cannot be
observed on very short timescales and very small spacescales
For which problems are simulations useful ?
Simulations can complement the experiment:
 Simulation explains experiments
Properties of water
Folding of protein molecules
knowledge
new ideas
 Simulation suggests
new experiments
less experiments
better chance of success
Design of drugs
enzymes
The world of molecular simulation and experiment
experiment
Resolution*
simulation
(restricted)
(unrestricted)
size :
1023 molecules
1
time :
1
10-15 seconds
second
molecule
*: Single molecules / 10-15 seconds possible
(but not both in the liquid phase)
Typical space / time scales
size :
10-3 meter
10-9 meter
time :
103 seconds
10-6 seconds
Simulation and experiment are complementing methods
to study different aspects of nature
Computersimulation of biomolecular systems
1) Why
2) How
do we simulate ?
3) What
4) And the future …
Definition of a model for molecular simulation
Every molecule consists of atoms that are very strongly bound to each other
Degrees of freedom:
atoms are the
elementary particles
Forces or
interactions
between atoms
Boundary conditions
MOLECULAR
MODEL
Force Field =
physico-chemical
knowledge
Methods to generate
configurations of
atoms: Newton
system
temperature
pressure
Choose relevant degrees of freedom: elementary particles
...
...
=
Particles:
atomic nuclei
+ electrons
all atoms
all atoms
(excluding solvent)
monomers
classical
mechanics
classical
mechanics
classical
mechanics
Force Field
(atomistic)
Force Field
(including solvent)
Force Field
(statistic)
Description:
quantummechanics
Interactions:
electrostatics
Broader applicability
Less model parameters
Physical parameters
More expensive
Restricted applicability
More model parameters
Empirical parameters
Less expensive
Definition of a model for molecular simulation
Every molecule consists of atoms that are very strongly attached
Degrees of freedom:
atoms are the
elementary particles
Forces or
interactions
between atoms
Boundary conditions
MOLECULAR
MODEL
Force Field =
physico-chemical
knowledge
Methods to generate
configurations of
atoms: Newton
system
temperature
pressure
Interactions in atomic simulaties : Force Field
physico-chemical knowledge
non-bonded
interactions
bonded
interactions
Bond stretching
Angle bending
Rotation around
bond
Planar
atomgroups
+
-
-
Electrostatic
interactions
van der Waals
interactions
Definition of a model for molecular simulation
Every molecule consists of atoms that are very strongly attached
Degrees of freedom:
atoms are the
elementary particles
Forces or
interactions
between atoms
Boundary conditions
MOLECULAR
MODEL
Force Field =
physico-chemical
knowledge
Methods to generate
configurations of
atoms: Newton
system
temperature
pressure
Classical dynamics
Situation at time t
Force is determined by relative positions
acceleration = force / mass
 velocity = acceleration ×  t
 position = velocity ×  t
position
velocity
force
Situation at time t+t
Sir Isaac Newton
1642 -1727
Determinism …
Generating configurations in atomic
simulations: molecular dynamics
... comparable to shooting a movie
of a molecular system...
Time t
velocities
positions
forces
Time (t+t)
new velocities
new positions
t  10-15 seconds
Definition of a model for molecular simulation
Every molecule consists of atoms that are very strongly attached
Degrees of freedom:
atoms are the
elementary particles
Forces or
interactions
between atoms
Boundary conditions
MOLECULAR
MODEL
Force Field =
physico-chemical
knowledge
Methods to generate
configurations of
atoms: Newton
system
temperature
pressure
Boundary conditions in atomic simulations
Vacuum
• Surface effects (surface tension)
• No dielectric screening
Droplets
• Still surface effects
• Only partial dielectric screening
• Evaporation of the solvent
Periodic: rectangular system is surrounded by copies of itself
Advantage:
• No surface effects
Disadvantage:
• Artificial periodicity
• High effective concentration
Probably still the best approach…
Computersimulation of biomolecular systems
1) Why
2) How
3) What
in my research group
Methods
Applications
do we simulate ?
4) And the future…
What do biochemists or molecular biologists
want to know of molecules?
1. stable structures
 energetically favourable structures
binding equilibrium
between two small
organic molecules
2. Relation between structure and function water transport in the
 enzymes
binding cavity of a
protein (FABP)
3. Motions en mechanisms
prediction of the three protein folding
dimensional structure or
the folding of proteins
(polypeptides)
4. Design of new compounds
binding strength of
 design of drugs
hormone replacing
molecules to the
estrogenreceptor
Applications of molecular dynamics simulation:
Example 1
Structural interpretation of
thermodynamic properties:
Binding equilibrium between two small
organic molecules
Binding equilibrium
Hydrogen bonds
Complex :
Cyclohexanediamine
NH2
NH2
?
Cyclopentanediol
H
H
N
-
HO
H
+
O
H
HO
N
H
H
+
Many different bindingmodes
O
-
Average binding strength (free enthalpy) :
Experimental
Benzene
CCl4
Gb [kJ/mol]
-9.3
-11.5
MD simulation
-10.4
Diol + Diamine + 252 CCl4 Molecules
2.1 – 2.2.10-9 seconds
Complex
formed
Formation
of the
complex
(camera focuses on the diamine)
Diol + Diamine + 252 CCl4 Molecules
3.2 – 4.0.10-9 seconds
Hydrogen bonds
ON
NO
…molecules
and a nanosecond
later …
the
are free again…
Results of the simulation (over 10-7 sec) :
 Experimentally hardly (or not) possible !
Occurrence of different binding modes :
NH2
HO
NH2
HO
NH2
HO
NH2
HO
NH2
HO
NH2
HO
54%
21%
7%
4%
NH2
HO
NH2
HO
NH2
HO
NH2
HO
NH2
8%
HO
NH2
3%
HO
Life time :
• Average life time of the complex: 2.10-10 sec (max. 3.10-9 sec)
• Average life time of a hydrogen bond: 5 .10-12 sec
What do biochemists or molecular biologists
want to know of molecules?
1. stable structures
 energetically favourable structures
binding equilibrium
between two small
organic molecules
2. Relation between structure and function water transport in the
 enzymes
binding cavity of a
protein (FABP)
3. Motions en mechanisms
prediction of the three protein folding
dimensional structure or
the folding of proteins
(polypeptides)
4. Design of new compounds
binding strength of
 design of drugs
hormone replacing
molecules to the
estrogenreceptor
Biomolecules
Boundaries:
membranes consist
of lipids with pores
of proteins
Hereditary information
in the nucleus: DNA
Carbohydrates:
storage of energy
and molecular
stamps
Proteins:
e.g. haemoglobin
for oxygen transport
Applications of molecular dynamics simulation:
Example 2
The watertransport in the binding cavity of a protein (FABP)
• Important to understand
enzymatic reactions:
the dynamics of the
binding cavity
• Simulation allows one to
follow the movements of
individual molecules
What do biochemists or molecular biologists
want to know of molecules?
1. stable structures
 energetically favourable structures
binding equilibrium
between two small
organic molecules
2. Relation between structure and function water transport in the
 enzymes
binding cavity of a
protein (FABP)
3. Motions en mechanisms
prediction of the three protein folding
dimensional structure or
the folding of proteins
(polypeptides)
4. Design of new compounds
binding strength of
 design of drugs
hormone replacing
molecules to the
estrogenreceptor
Applications of molecular dynamics simulation:
Example 3
Protein folding the challenge
Proteins consist of chains of amino acids (primary structure)
20 kinds
In an organism proteins only
function if they have been
correctly folded threedimensionally. (secondary and
tertiary structure)
• What is the relation between amino acid sequence and folded
spatial structure?
• How does the folding process take place?
Foldingsimulation
• Proteins are too large systems
to simulate the slow folding
process.
• Smaller model compounds can
be correctly folded on the
computer.
 Information about folding
mechanisms and the unfolded
state:
surprise
all different?
how different?
321  1010 possibilities!!
RMSD [nm]
Unfolded
structures
0.4
0.3
0.2
0.1
0
0
50
100
t [ns]
Folded
structures
all the same
150
200
Surprising result after simulations
of many polypeptides
The number of relevant unfolded structures is much and much smaller
than the number of possible unfolded structures
number of
possible
relevant (observed)
structures
structures
number of
amino acids in
the protein
Folding time
(exp/sim) in
seconds
peptide
10
10-8
320  109
103
protein
100
10-2
3200  1090
109
Assuming that the number of relevant unfolded structures is proportional to the
folding time, only 109 protein structures need to be simulated instead of 1090
structures.
 Folding mechanism is simpler than generally expected:
searching through only 109 structures
 Protein folding on a computer is possible before 2010
For which problems are simulations useful ?
Simulations can complement the experiment:
 Simulation explains experiments
Properties of water
Folding of protein molecules
knowledge
new ideas
 Simulation suggests
new experiments
less experiments
better chance of success
Design of drugs
enzymes
What do biochemists or molecular biologists
want to know of molecules?
1. stable structures
 energetically favourable structures
binding equilibrium
between two small
organic molecules
2. Relation between structure and function water transport in the
 enzymes
binding cavity of a
protein (FABP)
3. Motions en mechanisms
prediction of the three protein folding
dimensional structure or
the folding of proteins
(polypeptides)
4. Design of new compounds
binding strength of
 design of drugs
hormone replacing
molecules to the
estrogenreceptor
Applications of molecular dynamics simulations:
Example 4
Design of drugs
testing compounds with the computer
Enzymes work according to
the “lock and key”-principle
the “key hole”: the
active site in the
protein
containing a
“fitting key”: the
active site with an
active molecule
the active and a
new molecule (to
be tested)
superimposed
a “new key”?:
The active site with
the molecule to be
tested
Polychlorinated biphenyls
Unphysical reference state
16 hydroxylated PCB’s
Cl
HO
Cl
HO
HO
Cl
HO
Cl
Cl
Cl
Cl
HO
HO
Cl
Cl
Cl
Cl
HO
Cl
Cl
Cl
HO
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
HO
Cl
Cl
Cl
Cl
Cl
HO
Cl
HO
Cl
HO
Cl
Cl
Cl
HO
Cl
Cl
HO
Cl
Cl
HO
Cl
Cl
Cl
Cl
Cl
Cl
Cl
Cl
HO
Cl
Cl
Cl
Binding to the estrogen receptor
16 hydroxylated PCB’s:
10 < kBT  2.5 kJ mol-1
13 < 1 kcal mol-1
Average deviation: 2.5 kJ mol-1
Variation exp. values: 4.2 kJ mol-1
Computersimulation of biomolecular systems
1) Why
2) How
3) What
4) And the future …
History:
classical molecular dynamics simulations
of biomolecular systems
Year
molecular system: type, size
length of the simulation
in seconds
1957
first molecular dynamics simulation (hard discs, two dimensions)
1964
atomic liquid (argon)
1971
molecular liquid (water)
5 .10-12
1976
protein (no solvent)
2 .10-11
1983
protein in water
2 .10-11
1989
protein-DNA complex in water
10-10
1997
polypeptide folding in solvent
10-7
2001
micelle formation
10-7
200x
folding of a small protein
10-3
10-11
And the future ...
Computer speed increases with a
factor 10 about every 5½ year!
Standard classical simulations :
2001
Biomolecules in water (~104 atomen)
10-8 sec
2029
Biomolecules in water
10-3 sec
2034
E-coli bacteria (~1011 atoms)
10-9 sec
2056
Mammalian cell (~1015 atoms)
10-9 sec
2080
Biomolecules in water
106 sec
2172
Human body (~1027 atoms)
But :
Protein folding sooner?
1 sec
• Upper limit to computer speed ?
• Accuracy of classical models and force fields ?
• Better approximations and simplifications
As fast as nature !
Computersimulation of reality
real world
experiment
classification
abstraction
simplification
approximation
generalisation
model
of the world
experimental
data
comparing
is
testing
computational
methods
predictions
Acknowledgements
Gruppe informatikgestützte Chemie (igc)
http://www.igc.ethz.ch
Dirk Bakowies (Germany)
Alice Glättli (Switzerland)
Riccardo Baron (Italy)
David Kony (France)
Indira Chandrasekhar (India)
Chris Oostenbrink (Holland)
Markus Christen (Switzerland)
Daniel Trzesniak (Brasil)
Peter Gee (England)
Alex de Vries (Holland)
Daan Geerke (Holland)
Haibo Yu (China)
Daniela Kalbermatter (Switzerland)