Transcript Spatial and temporal scales in computational modeling F. Müller-Plathe, ChemPhysChem, 3, 754, 2002. Scale of problem dictates modeling choice S.

Spatial and temporal
scales in computational
modeling
F. Müller-Plathe, ChemPhysChem, 3, 754,
2002.
Scale of problem dictates
modeling choice
S. O. Nielsen et. al., J. Phys.: Condensed Matter 16, R481 (2004)
Computational geomechanics
Prof. Andrade, Dept of Civil and Environmental Engineering, Northwestern University
Motivation: would like to study self-assembly
The self-assembly of biomolecular building blocks plays an increasingly
important role in the discovery of new materials and scaffolds, with a
wide range of applications in nanotechnology and medical technologies
such as regenerative medicine and drug delivery systems.
S. Vauthey, S. Santoso, H. Gong, N. Watson, & S. Zhang. PNAS, 99 5355 (2002)
Computational biophysics
http://www.ks.uiuc.edu/Research/BAR-domain/
We have developed and tested models describing
interactions of amphiphysin BAR domain (from
Drosophila), with a lipid bilayer membrane, at four
scales: atomic level, residue-based coarse graining
(RBCG) level with ~10 atoms represented by a CG bead
and single-residue resolution, shape-based coarse
graining (SBCG) level with ~150 atoms per CG bead and
a group of beads per protein, and a mesoscopic
continuum level with the membrane and proteins
represented through an elastic membrane model. Each
description level is parameterized based on the more
detailed description of simple systems.
BUT this is not always
appropriate: sometimes
we need to model some
aspects at one level of
detail and other aspects
at another level.
Architecture and mechanism of the lightharvesting apparatus of purple bacteria
Schematic representation of the photosynthetic apparatus in the cell membrane
of purple bacteria.
Architecture and mechanism of the lightharvesting apparatus of purple bacteria
Energy levels of the electronic excitations in the PSU
of BChl a containing purple bacteria. The diagram
illustrates a funneling of excitation energy towards
the photosynthetic RC.
Arrangement of
pigment–protein
complexes in the
modeled bacterial
photosynthetic unit
(PSU) of Rb.
sphaeroides.
LHII structure
LHII
structure
Need one simulation which uses multiple
methods simultaneously on different parts of
the system
All the problems
are here
Beta-lactamase enzymes
Purple spheres are zinc ions
First we will discuss the hierarchical
approach, then the simultaneous approach
Peptide Nanotube
Antimicrobials
•
•
•
•
•
•
How long are the nanotubes and
how is their length distribution
controlled by the membrane
environment?
Where does tube elongation take
place?
What factors control aggregation
on top of or in the membrane?
How much control can be
exerted by choosing the amino
acid composition and/or by
choosing a mixture of subunits
(e.g. capping units)?
How does all this relate to the
carpet vs. barrel-stave modes?
What is the carpet mechanism
really?
M. R. Ghadiri, Nature 412, 452 (2001)
Single
Barrel-stave
Carpet
Synthetic antimicrobials
aryl amide oligomers
a
b
Angew. Chem. Int. Ed., 43, 1158 (2004)
d
Coarse Grain Model: Mapping of DMPC
Tail
Endings
Preserve molecular shape
J. C. Shelley et. al., J. Phys. Chem. B 105, 4464 (2001)
Force field uses some implicit pmf interactions
and is fit from exp. and atomistic simulation data.
Spontaneous insertion of
peptide into membrane
• Very efficient: takes
about a week on a
standard Intel
workstation.
• Matched length
• Starting geometry
occurs regardless of
initial orientation in water
• Simulations also
performed with
uncapped peptides.
80 ns of the total simulation shown
How stable is the
transmembrane orientation?
Spontaneous insertion happens with the help of chaperone lipids.
J. A. Killian has showed that TM peptides increase rate of flip-flop.
C. F. Lopez, S. O. Nielsen, et. al., PNAS 101, 4431 (2004)
This process can be quantified by computing the free energy of insertion.
SDS Solubilization of Single-Wall
Carbon Nanotubes in Water
C. Mioskowski, Science 300, 775 (2003)
M. F. Islam et. al., Nano Lett. 3, 269 (2003)
Smalley – Science 297, 593 (2002)
Islam -- Would explain difference
between SDS and NaDDBS
JACS 126, 9902 (2004): SANS data
JACS 126 9902 (2004)
RCP interacting with carbon nanotubes
Snapshots of C12E5 Self-Assembly on
Graphite Surface
t=0ns
t=0.64ns
t=3.3ns
d=5.0 nm
t=3.75ns
t=4.3ns
t=6.0ns
Multi-scale simulations
Coarse grain
Atomistic
Wholesale mapping
Mixed CG/AA
representation
On-the-fly mapping
Automated CG force
field construction
Can switch back and forth repeatedly
and refine the coarse grain potentials by
force matching or other algorithms.
Multiscale “dual-resolution” simulations
Liquid methane
Idea: rotate frozen structures
T
M
T
M
structures from when
the molecule crossed
the AA to CG boundary
T
Liquid dodecane
M
T=
M
M=
Minimize an energy function
C
H
H
C
H
H
H
C
H
C
H
H
• interactions are only between atoms belonging to different coarse
grained units
–
–
–
–
Bonds
Bends
Torsions, 1-4
Non-bonded (intermolecular and within the same long-chain molecule)