embio meeting vienna, 2006
DESCRIPTION
EMBIO Meeting Vienna, 2006. Heidelberg Group IWR, Computational Molecular Biophysics, University of Heidelberg Kei Moritsugu. MD simulation analysis of interprotein vibrations and boson peak Kinetic characterization of temperature-dependent protein internal - PowerPoint PPT PresentationTRANSCRIPT
22/5/2006 EMBIO Meeting 1
EMBIO Meeting Vienna, 2006
Heidelberg GroupIWR, Computational Molecular Biophysics, University of Heidelberg
Kei Moritsugu MD simulation analysis of interprotein vibrations and boson peak Kinetic characterization of temperature-dependent protein internal motion by essential dynamics Langevin model of protein dynamics
Langevin Model of Protein Dynamics
EMBIO Meeting
Vienna, May 22, 2006
IWR, University of HeidelbergKei Moritsugu and Jeremy C. Smith
- Introduction Dynamical model for understanding protein dynamics Langevin equation
- Direct application of Langevin dynamics:
Velocity autocorrelation function model
- Extension of the Langevin model:
Coordinate autocorrelation function model
22/5/2006 EMBIO Meeting 3
Physical interest: multi-body (> ~1000 atoms)
inhomogeneous system
Why Protein Dynamics?
Anharmonic motion on rough potential energy surface
Understand a “molecular machine”from physical point of view
Biological/chemical interest: expression and regulation of function mediated by anharmonic protein dynamics
conformationaltransition
22/5/2006 EMBIO Meeting 4
Protein Dynamics: How to Analyze?
Molecular Dynamics Simulation
Neutron Scattering Experiment- low resolution- large, complex system with surrounding environments
Dynamical Model
Data Analysis
Simplification- harmonic approximation- two-state jump model
- Langevin model
….- atomic motions with fs-ns timescales- limited time < s, system size < ~100 Å
Settles et.al., Faraday Discussion 193, 269 (1996)
Model Parameters
Protein Dynamics
22/5/2006 EMBIO Meeting 5
Dynamical Model
Langevin Equation2
2
)( )
(ij j ii
ji j
jiijF
d Vm q q
dtq R t
q
q
1
( ) 0
(0) ( ) 2 ( )
i
i j ij
R t
R R t t
Random forceFriction
PES roughness = Friction curvature = Frequency
,
1( ) ( )
2( ) i j
i jijV FV V q q q 0q
Harmonic Approximation of Potential Energy
22/5/2006 EMBIO Meeting 6
Mode Analysis Simplifying Protein Dynamics
Normal Mode/Principal Component
Apply Dynamical Model for Each Mode
collective motion high frequency vibration
1 1 1( ; , )x f t 2 2 2( ; , )x f t 3 3 3( ; , )x f t 4 4 4( ; , )x f t
22/5/2006 EMBIO Meeting 7
Calculations of Langevin ParametersMD Simulations Normal Mode Analysis
2
(0) ( )exp( / 2)(cos sin )
2n n
n nnn
nnnn
v v tt t t
v
2 2 / 4nn n n
120 K in vacuum
300 K in solution ( )
( )i
i
r t
r t
( )
( )
n in ii
n in ii
x t u r
v t u r
2FU U
Temperature dependence
Solvent effects
Velocity Autocorrelation Function (VACF) Model
n , nn
by each normal mode, n
Langevin Parameters
22/5/2006 EMBIO Meeting 8
Computations 1
Molecular Dynamics Simulations
Normal Mode Analysis
myoglobin (1A6G, 2512 atoms, 153 residues) equilibrium conditions at 120K and 300K 1-ns MD simulation with CHARMM vacuum: microcanonical MD solution: rectangular box with 3090 TIP3P waters, NPT, PME
vacuum force field minimization of 1-ns average structure in vacuum calculate the Hessian matrix and its diagonalization
independent atomic motion,
with vibrational frequency, n
1, 2, ,( , , )Tn n n N nu u u u
22/5/2006 EMBIO Meeting 9
Langevin Friction
in water > in vacuum 300K > 120 K
300K water300K vacuum 120K water120K vacuum
22/5/2006 EMBIO Meeting 10
Langevin Frequency
(anharmonicity) < 0 : low >high 300 K > 120 K
vacuum NMA
NMA
water vacuum
NMA
(solvation) > 0 : low >high 300 K = 120 K
22/5/2006 EMBIO Meeting 11
Potential Energy Surface via Langevin Model
NMAvacuumsolution
: roughness (anharmonicity) < 0
intra-protein interaction solvation: collisions with waters suppress protein vibrations
increase of : increased roughness (solvation) > 0, independent of T
Normal Mode Water MDVacuum MD
22/5/2006 EMBIO Meeting 12
Dynamic Structure Factors1
( , ) ( , ) e2
i tS F t dt
q q
(0) ( )2,
1
( , ) i i
Ni i t
MD inc ii
F t b e e
q r q rq
MD Trajectory
Langevin Model3 6
2 ( ) 2, 2
1 1
( , ) exp | [1 ( )]N N
iBL inc i n n
i n i n
k TF t b t
m
q | q u
/ 2
2
(0) ( )( ) (cos sin )
2nnn n t nn
n n nnn
x x tt e t t
x
Langevin Model + Diffusion
(q, ) (q, ) (q, )corr L DF t F t F t2(q, ) exp( )DF t Dq t
120K water120K vacuum 300K water300K vacuum
q = 2Å-1
22/5/2006 EMBIO Meeting 13
Conclusion 1
Langevin model via VACF Protein vibrational dynamics
Friction: anharmonicity low > high high T > low T increase via solvation Frequency shift: (anharmonicity) < 0 (solvation) > 0
Svib(q,)
22/5/2006 EMBIO Meeting 14
Modified Model for Diffusion
Extended Langevin model1) CACF model2) Add diffusional contribution
vibration
t
x(t)
v(t)
diffusionPCA mode 1 PCA mode 100PCA mode 1 PCA mode 100300K
water
22/5/2006 EMBIO Meeting 15
Probabilistic Vibration/Diffusion Model
20
0
exp( / 2)(co(0) ( )
1s1 exp(
))
2(sin )v
v v vv
t tx x t t
txt
diffusion0
Langevin vibration
,v v
Coordinate Autocorrelation Function (CACF) Model
2 2 / 4v v v
PCA mode 1 PCA mode 100
MDmodel
MDmodel
22/5/2006 EMBIO Meeting 16
Computations 2
Molecular Dynamics Simulations
myoglobin (1A6G, 2512 atoms, 153 residues) in solution: rectangular box with 3090 TIP3P waters equilibrium conditions under NPT ensemble T = 120, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 280, 300 K 1-ns MD simulation with CHARMM PME
Principal Component Analysis
Fitting: Calculation of model parameters
variance-covariance matrix: ij i jC x xindependent atomic motion,
with square fluctuation, n
1, 2, ,( , , )Tn n n N nu u u u
MD trajectories (0) ( )n n MDx x t
least square fit to model functiont = 0 ~ 5, 10, 20 ps
diagonalization
22/5/2006 EMBIO Meeting 17
Mean Square Fluctuations: Decomposition
85% 85%
85% 85%
2 2
1 1
2 2
1 1
(1 )
N N
n n nvib vibn n
N N
n n ndiff diffn n
x x
x x
n: eigenvalue of PCA: model parameter
22/5/2006 EMBIO Meeting 18
300
1
/ 300nn
300
,1
/ 300v v nn
Temperature Dependence: Dynamical Transition
0.375v v
Vibrational FrictionVibrational Frequency Ratio of Vibration
22/5/2006 EMBIO Meeting 19
Height of Vibrational Potential Wells via Model
230 K250 K280 K300 K
E
v
2
vibx 2 2
2
( ) / 2
/ 2
v v vib
v
E x
for < 1
22/5/2006 EMBIO Meeting 20
Diffusion Constant via Model
E ,v v
k Kramers Rate Theory
2 2/ 4 / 2exp[ ]
2v v vk E
2
vibx
MDKramers theory
2 2
vibD ka k x : diffusion on 1D lattice
a a a
kkk
v
~ ~
22/5/2006 EMBIO Meeting 21
S(q,w)
MDCACF modelVACF model
q = 2Å-1
300 K in water
22/5/2006 EMBIO Meeting 22
Conclusion 2
Langevin-vibration&diffusion model via CACF Protein dynamics
Simulation-based probabilistic description
Vibration: linear scheme with T v
Diffusion: nonlinear scheme with T , v ,
Diffusion constant via the present model using Kramers theory
2
vibx
2
diffx
S(q,)
22/5/2006 EMBIO Meeting 23
Acknowledgement
Thanks for your attention!
Vandana Kurkal-Siebert
Fellowship by JSPS