Chem' 860 Molecular Simulations with Biophysical Applications

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Chem. 860 Molecular Simulations with Biophysical
Applications

• Qiang Cui
• Department of Chemistry and
• Theoretical Chemistry Institute
• University of Wisconsin, Madison
• Spring, 2009

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(No Transcript)
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Topics

• Basic ideas of biomolecular simulations
• Empirical Force Fields
• Equilibrium simulations Basic Molecular Dynamics
  and (some) Monte Carlo
• Non-equilibrium (time-dependent) properties
• Some specialized techniques (Car-Parrinello
  QM/MM, Transition path sampling...)
• Current challenges (Multi-scale simulations)
• Goal learn how to design and carry out proper
  simulations for biophysical applications

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(Bio)molecular Simulations
Use physical based techniques to numerically
simulate the behavior of molecular systems

• Evaluate analytic theories (solvation, rate,
  spectroscopy)
• Help better interpret complex experimental data
  in structural and dynamical terms (spectra,
  diffraction, NMR)
• In the absence of direct experimental data,
  observe the behavior of the system for
  mechanistic investigations or predictions
• Equilibrium properties (thermodynamics, average
  structure and fluctuation)
• Time-dependent properties (chemical reactions,
  conformational transitions/folding, diffusion)

Karplus, Petsko, Nature, 347, 631 (1991)
Karplus, McCammon, Nat. Struct. Biol. 9, 646
(2002)
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Unique power of simulations
Observe - analyze (model building) - design

• High spatial and temporal resolution
• Facilitate analysis of important factors for
  mechanistic investigations - easy to turn on and
  off specific contribution
• High-throughput rational design of new ligands,
  biomolecules or (e.g., mutation) experiments
• Obtain insights into processes difficult (or
  devastating) to do experimentally (Nuclear
  meltdown, galaxy collision)
• Ultimately stimulate new experiments

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Example 1. Water channel
State-of-the-art all-atom simulation 100,000
atoms 100 ns
de Groot, Grubmuller, Science, 294, 2353 (2001)
E. Tajkhorshid et al. Science, 296, 525 (2002)
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Example 1.2 K channel
Berneche et al. Roux, Nature, 414, 73 (2001)
431, 830 (2004)
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Example 1.3 Real-Time-dependence
Barrier (re)crossing
Hammes-Schiffer _at_ PSU
Benkovic, Hammes-Schiffer, Science, 301, 1196
(2003)
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Example 2. Solvent effect on protein dynamics
Vitkup, Ringe, Petsko, Karplus, Nat. Struct.
Biol. 7, 34 (2000)
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Example 2.2 Solvent effect on protein-ligand
dynamics
Loring et al. J. Phys. Chem. B 105, 4068 (2001)
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Example 2.3 Diffuse IR band and proton storage
site in bR
bR
XH
Gerwert et al. Nature, 439, 109 (2006) QC et al.
PNAS, 105, 19672 (2008)
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Ex 3. Rational Design of proteins and ligands
ab initio design of a Novel fold
Incorporate catalytic function into proteins
Kuhlman et al., Baker, Science, 302, 1364 (2003)
Dwyer et al., Hellinga, Science, 304, 1967 (2004)
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Basic elements

• Potential Function (force field) how
  atoms in biomolecules ( ) interact with each
  other and how biomolecules interact with the
  environment ( ).
• Equilibrium statistical mechanics
• Non-equilibrium statistical mechanics (MD only)

Molecular Dynamics (MD)
Monte Carlo (stochastic)
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Limitations

• Potential Energy Function (force field QM level)
• Limited conformational/chemical (e.g., titration)
  sampling (requires smart techniques!)
• System finite size (depending on the range of
  interaction)

"when one microsecond is a long time"
Y. Duan, P. A. Kollman, Science, 282, 740 (1998)
1µs RMSD 3 Å
Bottom line Design proper simulation for your
question!
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Limitations

• Potential Energy Function (force field QM level)
• Limited conformational/chemical (e.g., titration)
  sampling (requires smart techniques!)
• System finite size (depending on the range of
  interaction)

Coarse-grained models
http//md.chem.rug.nl/marrink/MOV/index.html
Bottom line Design proper simulation for your
question!