simulation studies of biomolecules @ soft interfaces : continuing challenge of bridging length-...
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Simulation Studies ofSimulation Studies ofBiomolecules @ Soft Interfaces :Biomolecules @ Soft Interfaces :
Continuing challenge of Continuing challenge of bridging length- & bridging length- &
time-scalestime-scales
Third Computational Chemistry Conference on “use of Third Computational Chemistry Conference on “use of computational techniques in chemistry, biology, computational techniques in chemistry, biology,
biochemistry, and materials science” biochemistry, and materials science” SURA NCSA UoK ARL www.2003SURA NCSA UoK ARL www.2003
It gives me great pleasure to talk to you today about research going on in my group at UPenn that is focused on membranes and membrane-bound species.
* DISCLAIMER - This talk contains no equations – theoreticians may find the extensive use of color images offensive
SURA-NCSA-UoK-ARL CCC2003*SURA-NCSA-UoK-ARL CCC2003*
My early computations dealt with ATOMIC systems. But, in the mid-1970’s, computers became more powerful I shifted to MOLECULAR solids & liquids.
Since the 1980’s my research has dealt with simulation algorithms and applications ranging from materials to bio-membranes.
Current interests - ab initio based (DFT) methods for chemical & enzyme reactions and coarse-grain simulations of self-assembling soft matter systems.
In the 1960’s COMPUTATION started to become respectable….
PROLOGUEPROLOGUE
Use computer to follow the motion of a Use computer to follow the motion of a system of atoms or molecules using system of atoms or molecules using principles of physics (Newton, Lagrange, principles of physics (Newton, Lagrange, Feynman) and statistical mechanics Feynman) and statistical mechanics (Onsager, Kubo, van Hove) to go from (Onsager, Kubo, van Hove) to go from trajectories to observables. trajectories to observables.
Interactions can be from empirical Interactions can be from empirical potentials or from quantum mechanics, potentials or from quantum mechanics, often via DFT - Car-Parrinello often via DFT - Car-Parrinello methodology.methodology.
MethodologyMethodology
Biomolecules @ Soft Biomolecules @ Soft InterfacesInterfaces*
Carlos Lopez, Steve Nielsen, Carlos Lopez, Steve Nielsen,
Preston Moore, Robert Doerksen,Preston Moore, Robert Doerksen,
Srinivas Goundla,Srinivas Goundla,
Rosalind Allen, Bin Chen, Rosalind Allen, Bin Chen,
John & Mee ShelleyJohn & Mee Shelley
* * Bridging from atoms to the Bridging from atoms to the mesoscalemesoscale
Infection Pathway of a Virus in a Living Infection Pathway of a Virus in a Living Cell*Cell*
Single-molecule real-time visualization of the infection pathway of single viruses in living cells, each labeled with only one fluorescent dye molecule.
Trajectories show various modes of motion of adeno-associated viruses (AAV) during their infection pathway into living HeLa cells:
(i) Consecutive virus touching at the cell surface and fast endocytosis;
(ii) Free and anomalous diffusion of the endosome and the virus in the cytoplasm and the nucleus; and
(iii) Directed motion by motor proteins in the cytoplasm and in nuclear tubular structures.
* Munich Group Science
Polymersomes (Penn Polymersomes (Penn MRSEC)*MRSEC)*
*Discher, Hammer, Bates (*Discher, Hammer, Bates (ScienceScience 1997)1997)
Nature’s Nanoworld *Nature’s Nanoworld *
*Cell membranes are complex, containing lipids, proteins, cholesterol, carbohydrates, plus actin filements, etc… Design principles for Nature’s devices, plus their self- & supramolecular assembly can yield new materials.
Membranes – A Playground for Membranes – A Playground for
Molecular Dynamics Simulation Molecular Dynamics Simulation
MANY ACHIEVEMENTSMANY ACHIEVEMENTS
MANY ACTIVE GROUPS:MANY ACTIVE GROUPS:
Schulten, Carloni, Sansom,Schulten, Carloni, Sansom,Tielman, Roux, Pastor, etc.Tielman, Roux, Pastor, etc.
M2 pentamer in a lipid bilayer at T=303K
94 DMPC lipids plus5 M2-TM peptides
Channels well-studied Schulten Roux Carloni Sansom Teilman
Ion Channel in a Lipid Bilayer Ion Channel in a Lipid Bilayer ––
n-AChR (M2-TM)n-AChR (M2-TM)
N-terminal intracellular on topN-terminal intracellular on top
Nature’s Ion ChannelsNature’s Ion Channels
Transmembrane – Assembly & Function Difficult with classical MD
Mostly pre-assembled systems Simulated structures Open/Closed?
Gramicidin (Warshel, Roux – Karplus,…) K+ (Carloni, Roux, Tielman, Sansom,…) OMP, Porins (Carloni, Sansom, Schulten,
…)
Design Principles ?Design Principles ?
Carbon Nanotube as Nanosyringe Carbon Nanotube as Nanosyringe ??
G. Hummer, J. Rasaiah, & J.P. NoworytaNature 414, 188-190 (2001)
Tube:13.4 Å long8.1 Å diameter
“We observe pulse like transmission of waterthrough the nanotube…two-state transitions betweenempty and filled states on nanosecond timescale..”
Water in a Water in a
carbon carbon nanotubenanotube
Why Coarse Grain ? *Why Coarse Grain ? *
Atomistic ModelsEmpirical potentials -
local structuresLimited system sizeLimited timescale
**One million lipids / m2
A Coarse-grain Model for Soft
Interfaces
Strategy for Simulations of Advanced MaterialsStrategy for Simulations of Advanced Materials
A Coarse-grain ModelA Coarse-grain Modelfor Soft Interfacesfor Soft Interfaces*
Carlos Lopez, Steve Nielsen, Carlos Lopez, Steve Nielsen,
Preston Moore, Robert Doerksen,Preston Moore, Robert Doerksen,
Srinivas Goundla,Srinivas Goundla,
Rosalind Allen, Bin Chen, Rosalind Allen, Bin Chen,
John & Mee ShelleyJohn & Mee Shelley
* * Bridging from atoms to the Bridging from atoms to the mesoscalemesoscale
From hundreds of From hundreds of atoms to billions - the atoms to billions - the challenge of the challenge of the mesoscalemesoscale
Coarse grain models & soft interfacesCoarse grain models & soft interfaces
Coarse Grain DMPCCoarse Grain DMPC
Choline Head Group
Phosphate Group
Glycerol Groups
Acyl Chains
Chain Ends
Self Assembly of DMPC-Self Assembly of DMPC-CGCG
NVT Ensemble:46 Å X 45 Å X 59 Å 64 DMPC,T: 30°C, 1ns (20fs/step)
MUCH faster thanMUCH faster thanatomistic modelsatomistic models
See JPC 2001See JPC 2001
Coarse Grain Membrane - ResultsCoarse Grain Membrane - Results
J Phys Chem 2001J Phys Chem 2001
DMPC-CG 1024 BilayerDMPC-CG 1024 Bilayer
NPT Ensemble Orthorhombic Cell 1024 Lipids 1 ns (20fs/step) T: 30°C, P: 1atm Equilibration
340psSnapshots of
ConfigurationsComp Phys Comm 2002Comp Phys Comm 2002
Membrane Surface DynamicsMembrane Surface Dynamics
Area: 18nm X 20nm Note Transient Holes P(Blue), N(Orange)
Water Removed for Clarity
Challenges & OpportunitiesChallenges & Opportunities
Nothing amuses more harmlessly than Nothing amuses more harmlessly than computation, and nothing is oftener computation, and nothing is oftener applicable to real business and speculative applicable to real business and speculative inquiry.inquiry.
A thousand stories which the ignorant tell and A thousand stories which the ignorant tell and believe die away at once when the computist believe die away at once when the computist takes them in his grip.takes them in his grip.
Samuel JohnsonSamuel Johnson: 1709-1784: 1709-1784
Nanosyringe - Nature’s Nanosyringe - Nature’s DesignDesign
Protein Helix BundleProtein Helix Bundle Coarse Grain TubeCoarse Grain Tube
Pore diameter sized to accommodate “water”
Hydrophobic
NanosyringeNanosyringe
CG-tube mimic of nanotube or viral channel
insertion into membrane
NPT-MD 30°C, 1atm
Transmembrane Transmembrane NanotubeNanotube
CG-tube mimic of membrane-bound
nanotube or viral channel
NPT-MD 30°C, 1atm
Hydrophobic NanotubeHydrophobic Nanotube
Tube gets blocked with lipids after 15,000 steps
First lipid inserted at 5000 steps (10 ns ?)
Tube tilts to fit bilayer
Q: How to make a nanosyringe…? A: Nature uses
hydrophilic caps
CG nanotube (nanosyringe) in CG DMPCCG nanotube (nanosyringe) in CG DMPC
Nanosyringe - Nature’s Nanosyringe - Nature’s DesignDesign
Protein Helix BundleProtein Helix Bundle Coarse Grain TubeCoarse Grain Tube
Hydro - philic
Pore diameter sized to accommodate “water”
Hydro-phobic
Insertion into MembraneInsertion into Membrane
Start outside the membrane (water not shown)
Tube inserts into the membrane, favoring hydrophobic interactions
Insertion into MembraneInsertion into Membrane
Tube drags lipids into the middle of the bilayer. Then “sees” the other side of the membrane.
Tube straightens up and then remains in this position through the run.
Nature’s DesignNature’s Design
CG tube in CG tube in DMPCDMPC:
“Water” goes through tube
NPT 30°C, 1atm
PoreationSnapshot of tube in CG Snapshot of tube in CG DMPCDMPC Two waters are present in the tube. Lipids removed from bottom leaflet to reveal the tube/lipid interface
Insertion into MembraneInsertion into Membrane
Antibacterial Peptide Molecules
Common traits of AB peptides:Common traits of AB peptides: Relatively short peptides.Relatively short peptides. Charged and hydrophobic groups segregate Charged and hydrophobic groups segregate
onto opposite sides of a structure.onto opposite sides of a structure. Believed to kill cells by disrupting Believed to kill cells by disrupting
membranes.membranes.
Q: De novo design of biomimetic antimicrobial molecules?
Anti-microbial Peptide Anti-microbial Peptide MimicsMimics
Bin Chen, Carlos Lopez,Bin Chen, Carlos Lopez,Robert Doerksen, Bill Robert Doerksen, Bill
DeGradoDeGrado
HN
O O
HN
S
R
n
Polyarylamide n = 3Polyarylamide n = 3
1
MagaininMagaininMimicMimic
de novo design and synthesis of antimicrobialsde novo design and synthesis of antimicrobials
• Gradient-corrected density Gradient-corrected density functional theory calculationsfunctional theory calculations
• Atomistic molecular dynamics and Atomistic molecular dynamics and Monte Carlo calculationsMonte Carlo calculations
• Coarse-grained molecular dynamics Coarse-grained molecular dynamics simulationssimulations
Build initial target
polymer backbones
A schematic flow-chart showing the whole design process
Search low-energy conformations,parameterize
torsion potentials
Test force fields, investigate the polymer’s conformations at vacuum
and interfaces and its hydrophobicity, select the potential target
Evaluate the polymer’s antibacterial activity and
other important properties, determine the final target
Provide microscopic-level insights on the antibacterial mechanisms and
guidelines for improving the antibacterial polymer
Density functional theory calculations
Monte Carlo andmolecular dynamics
Experimental synthesis and assay tests
molecular dynamics simulations at membrane/water interface
DeNovo Designed Anti-microbial PolymersDeNovo Designed Anti-microbial Polymers
0
10
20
30
40
50
60
70
0 60 120 180 240 300 360
X : HX : S-CH
3
E [
kJ
/mo
l]
[degree]
HN
O
X
HN
O O
HN
S
R
n
PNAS 2002PNAS 2002
Antibacterial Activity of Antibacterial Activity of PolyamidesPolyamides
H N
O O
H N
S
NH2
n
n MIC E. coliE. coli K. pneumoniaeK. pneumoniae B. subtilisB. subtilis 2 19 66 12 3 <19 N/A 19 4 7.5-15 31-50 16 6 >500 250 >500
(AB)(AB)nn
0
20
40
60
80
100
0 50 100 150 200 250 300
Le
ak
ag
e F
rac
ton
(%
)Time (s)
15 µg/mL
7.5 µg/mL
3.75 µg/mL
1.88 µg/mL
A Coarse-grain Simulation Model A Coarse-grain Simulation Model for Probing Mechanisms of for Probing Mechanisms of
Anti-bacterial ActionAnti-bacterial Action*
Srinivas Goundla, Carlos Lopez, Steve NielsenSrinivas Goundla, Carlos Lopez, Steve Nielsen
Michael L. Klein*
Center for Molecular Modeling
University of Pennsylvania
CG-AB with CG LipidCG-AB with CG Lipid
Approximation to AB: Use existing CG
types to emulate the AB molecule.
AB Dimer in CG LipidAB Dimer in CG Lipid
Peptide mimics are adsorbed
at the lipid surface.
Peptide mimics first enter bilayer and eventually settle under the head groups
AcknowledgementsAcknowledgements
Thanks to friends & Thanks to friends & collaboratorscollaborators
NPACI @ NCSA, SDSC, PSCNPACI @ NCSA, SDSC, PSC
NSFNSF NIHNIH
Many thanks Many thanks for inviting me tofor inviting me to
talk to you! talk to you!
ENDEND
Challenges & OpportunitiesChallenges & Opportunities
It will surely come to the desktop…It will surely come to the desktop…
Phenomena at longer-length and time Phenomena at longer-length and time scales will be accessible…scales will be accessible…
HPC will participate in discovery of HPC will participate in discovery of advanced materials and more…advanced materials and more…
Terascale Computing has arrivedTerascale Computing has arrived
Challenges & OpportunitiesChallenges & Opportunities
Nothing amuses more harmlessly than Nothing amuses more harmlessly than computation, and nothing is oftener computation, and nothing is oftener applicable to real business and speculative applicable to real business and speculative inquiry.inquiry.
A thousand stories which the ignorant tell and A thousand stories which the ignorant tell and believe die away at once when the computist believe die away at once when the computist takes them in his grip.takes them in his grip.
Samuel JohnsonSamuel Johnson: 1709-1784: 1709-1784