Chem. 860 Molecular Simulations with Biophysical

Applications

Qiang CuiDepartment of Chemistry and Theoretical Chemistry Institute

University of Wisconsin, MadisonSpring, 2009

TopicsBasic 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

(Bio)molecular Simulations

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)

Use physical based techniques to numerically simulate the behavior of molecular systems

Unique power of simulations

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

Observe - analyze (model building) - design

Example 1. Water channel

de Groot, Grubmuller, Science, 294, 2353 (2001); E. Tajkhorshid et al. Science, 296, 525 (2002)

“State-of-the-art” all-atom simulation: 100,000 atoms; ~100 ns

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Example 1.2 K+ channel

Berneche et al. Roux, Nature, 414, 73 (2001); 431, 830 (2004)

Example 1.3 Real-Time-dependence

Barrier (re)crossing Hammes-Schiffer @ 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)

Example 2.2 Solvent effect on protein-ligand dynamics

Loring et al. J. Phys. Chem. B 105, 4068 (2001)

Example 2.3 Diffuse IR band and proton storage site in bRExample 2.3 Diffuse IR band and proton storage site in bR

Gerwert et al. Nature, 439, 109 (2006) QC et al. PNAS, 105, 19672 (2008)

XH+

bRbR

Ex 3. Rational Design of proteins and ligands

ab initio design of a Novel fold

Kuhlman et al., Baker, Science, 302, 1364 (2003)

Incorporate catalytic function into proteinsDwyer et al., Hellinga,

Science, 304, 1967 (2004)

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)

LimitationsPotential 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)

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

LimitationsPotential 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)

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

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