18/03/2013 Enrico Riccardi MD in Engineering 1 - NTNUfolk.ntnu.no/thuatt/upload/seminar/Enrico Riccardi - Simulation Lab.v1.00.pdf · 12/06/2013 Enrico Riccardi Gromacs MD simulations

18/03/2013 Enrico Riccardi MD in Engineering 1

2 12/06/2013 Enrico Riccardi Gromacs MD simulations

Introduction to MD

Gromacs: (The) Molecular Dynamics (MD)

simulations package

Enrico Riccardi

Ugelstad Laboratory,

Chemical Engineering Department,

NTNU, Trondheim


Introduction into Molecular Dynamics (MD)

If we can study and understand

the behavior of the

atoms/molecules and the

underlying mechanisms,

answers to many (any?)

questions and problems could

be obtained.

Every phenomenon and every property can be traced back to atomic-scale

characteristics and processes.


Averaging Obtain static and dynamic properties

Calculate force for each particle

Solve equations of motion for ri (t),vi (t)

Molecular Dynamics (MD) is a computational technique which simulates

microscopic systems in atomistic/molecular resolution.

MD can, in principle, predict most system

properties through the knowledge of atoms

location, momentum, and atom-atom

interactions.



Computational Simulation Limits



Gromacs

GROMACS is Free Software, available under the “GNU Lesser General Public License”

http://www.gromacs.org/

Current release: GROMACS 4.6

Berendsen, et al. (1995) Comp. Phys. Comm. 91: 43-56. Lindahl, et al. (2001) J. Mol. Model. 7: 306-317. Van der Spoel, et al. (2005) J. Comput. Chem. 26: 1701-1718. Hess, et al. (2008) J. Chem. Theory Comput. 4: 435-447. Pronk, et al. (2013) Bioinformatics 29 845-854.


http://www.gromacs.org/Documentation/Installation_Instructions_4.5

Installation procedure:

http://www.gromacs.org/Downloads

Download:

http://dqfnet.ufpe.br/groups/geekstuff/wiki/2ebb2/

System requirements: Linux, Mac OS X, Windows Almost any hardware

Gromacs


Molecular Dynamics steps

2. Select a suitable force field

1. Definition of the simulation box and generation of initial configuration

5. Statistical analysis of the results

3. System setting and set up

4. Simulation RUN


MD simulation file flow chart

settings.mdp

letsgo.tpr

forcefield.top

configuration.gro

Traj.xtc







4. Simulation RUN


MD Resolution

Atomistic resolution

Each atom contributes with 3 degrees of freedom to the system

Coarse grained (CG) resolution

Atoms are grouped into “super atoms”


MD Resolution

computational effort / accuracy balance


MD Resolution

-glucose monomer

B1 ≡ C1

B4 ≡ C4

B6 ≡ C6

O

HO OH

O

HO OH

O O

HO OH

HO

HO

HO

O

Coarse Grained Examples

Dextran polymer

Polystyrene


Initial Conditions

Generate initial configuration, rinitial , (3N-dimensional) vector

Tk

vm

Tk

mvP

B

ixi

B

iix

2exp

22

1

N

i

iiB vmTNkE1

2

2

1

2

3

Equipartition principle Maxwell-Boltzmann distribution function


Rigid Walls

Stochastic Boundary

Conditions

Boundary Conditions


Periodic Boundary Conditions (PBC)

Adjacent identical system replica A particle exiting is replaced by his image entering

Boundary Conditions


settings.mdp

letsgo.tpr

forcefield.top

configuration.gro

Traj.xtc



Initial Conditions

5 C 0.000000 0.000000 0.000000 H 0.000000 0.000000 1.089000 H 1.026719 0.000000 -0.363000 H -0.513360 -0.889165 -0.363000 H -0.513360 0.889165 -0.363000

Writing a .xyz file

Define the initial structure of a molecule


Initial Conditions

Define the initial structure of a molecule

Writing a .gro file

6 1WATER OW1 1 0.126 1.624 1.679 0.1227 -0.0580 0.0434 1WATER HW2 2 0.190 1.661 1.747 0.8085 0.3191 -0.7791 1WATER HW3 3 0.177 1.568 1.613 -0.9045 -2.6469 1.3180 2WATER OW1 4 1.275 0.053 0.622 0.2519 0.3140 -0.1734 2WATER HW2 5 1.337 0.002 0.680 -1.0641 -1.1349 0.0257 2WATER HW3 6 1.326 0.120 0.568 1.9427 -0.8216 -0.0244 1.82060 1.82060 1.82060

residue number (5 positions, integer) residue name (5 characters) atom name (5 characters) atom number (5 positions, integer) position (in nm, x y z in 3 columns, each 8 positions with 3 decimal places) velocity (in nm/ps (or km/s), x y z in 3 columns, each 8 positions with 4 decimal places)


1. Initial Conditions

Visual tools:

Avogadro (freeware)

Possibility to switch between output format in a click

Optimize the initial structures

Visual consistency check

Material Studio


Initial Conditions

Reach desired system dimension by CLONING the desired molecule(s) n times:

genconf Syntax: genconf –f onemol.gro -nbox nx ny nz -rot -o manymol.gro

manymol.gro will thus contain nx*ny*nz the molecule contained in onemol.gro

A visual tool (VMD) can be used to check the results

vmd manymol.gro vmd onemol.gro


Initial Conditions

Example: Nanocomposite system







4. Simulation RUN


Polyatomic molecules are subjected to intra and inter molecular interactions. The total potential energy and force can thus be expressed as:

&

The intramolecular interactions Uintra may include

- bond stretch (Us) - bond bending (Ub)

- torsion/dihedral (Ut) - electrostatic interaction (Ue)

- van der Waals interaction

The intermolecular interactions Uinter may include

- electrostatic interaction (Ue)

- van der Waals interaction

Force Field


Bond interaction models:

Simple harmonic potential:

Constrains to freeze bond length (allow larger t):

• SHAKE algorithm

(bonded atoms are iteratively relocated to their equilibrium bond length)

• RATTLE algorithm

(bond lengths of atoms constrained by velocity alteration)

• Quaternion (solid rotation), etc.

Force Field


Torsion (four body interactions):

i

di di -1

i -1

i i -2 Bending (three body interactions):

Ethane Torsional Potential

Force Field


Non-Bonded interaction models:

− Lennard-Jones potential

: particle diameter, : potential depth

− Morse potential : equilibrium bond length : frequency parameter

Force Field


Non-Bonded interaction models:

− Coulomb interaction between point-charges:

Special treatments are thus needed that include

− direct spherical cut-off − switching functions − Ewald summation − reaction field method

qi : i atom charge

: relative permittivity

: vacuum permittivity

Force Field


settings.mdp

letsgo.tpr

forcefield.top

configuration.gro

Traj.xtc



.top file

Sample .top file #include "ffoplsaa.itp" #include "Xylene-p.itp" #include "CHCL3.itp" #include "tip3p.itp" #include "ions-NA.itp" #include “Surfactant-LIG.itp" [ system ] ; Name Complete-Mess [ molecules ] ; Compound #mols CHL 105 DRG 752 SOL 9727 NA 256 LIG 64


Tip3p.itp [ moleculetype ] ; molname nrexcl SOL [ atoms ] ; id at type res nr residu name at name cgnr charge mass 1 opls_111 1 SOL OW 1 -0.834 16.00000 2 opls_112 1 SOL HW1 1 0.417 1.00800 3 opls_112 1 SOL HW2 1 0.417 1.00800 [ bonds ] ; I j funct length force.c. 1 2 1 0.09572 502416.0 1 3 1 0.09572 502416.0 [ angles ] ; i j k funct angle force.c. 2 1 3 1 104.52 628.02

.top file


CHCL3.itp

[ moleculetype ] ; Name CHL [ atoms ] ; nr type resnr residue atom cgnr charge mass typeB chargeB massB 1 opls_135 1 CHL C 1 0.086 12.01100 2 opls_151 1 CHL CL 2 -0.030 35.45300 3 opls_151 1 CHL CL 3 -0.028 35.45300 4 opls_151 1 CHL CL 4 -0.028 35.45300 5 opls_140 1 CHL H 5 0.000 1.00800 [ bonds ] ; ai aj funct 1 2 1 ; C CL 1 3 1 ; C CL 1 4 1 ; C CL 1 5 1 ; C H [ angles ] ; ai aj ak funct 2 1 3 1 ; CL C CL 2 1 4 1 ; CL C CL 2 1 5 1 ; CL C H 3 1 4 1 ; CL C CL 3 1 5 1 ; CL C H 4 1 5 1 ; CL C H

.top file







4. Simulation RUN


settings.mdp

letsgo.tpr

forcefield.top

configuration.gro

Traj.xtc



Integration of Newton’s second law (equation of motion, EOM)

; RUN CONTROL PARAMETERS integrator = md dt = 0.001 ; time step (in ps) nsteps = 1000000 ; number of steps ; OUTPUT CONTROL OPTIONS nstxout = 5000 ; save coordinates every ps nstvout = 5000 ; save velocities every ps nstenergy = 5000 ; save energies every ps ; NEIGHBOR SEARCHING PARAMETERS nstlist = 10 pbc = xyz rlist = 1.0

Sample .mdp file

.mdp file


; OPTIONS FOR ELECTROSTATICS AND VDW coulombtype = PME ; Particle Mesh Ewald for long-range Electrostatics rcoulomb = 1.0 vdw-type = Cut-off rvdw = 1.0 ; Temperature coupling tcoupl = v-rescale ; Couple temperature to ; external heat bath according to velocity re-scale method tau_t = 0.1 ; Coupling time constant, controlling strength of coupling ref_t = 300 ; Temperature of heat bath ; Pressure coupling Pcoupl = Parrinello-Rahman Pcoupltype = Isotropic tau_p = 2.0 compressibility = 4.5e-5 ref_p = 1.0

Sample .mdp file

.mdp file


; GENERATE VELOCITIES FOR STARTUP RUN gen_vel = yes ; Assign velocities to particles by taking them randomly from a Maxwell distribution gen_temp = 300 ; Temperature to generate corresponding Maxwell distribution

Sample .mdp file

.mdp file







4. Simulation RUN


Basic principles of MD equations of motion

Integration yields the time evolution of the particle’s positions ri


settings.mdp

letsgo.tpr

forcefield.top

configuration.gro

Traj.xtc



MD simulation START!

settings.mdp

forcefield.top

configuration.gro

grompp –f setting.mdp –p forcefield.top –c configuration.gro -o letsgo.tpr

mdrun –s letsgo.tpr


Simulation Progress

- Particle trajectories


Snap Shot

VMD can be used to check simulation snapshot and trajectory

vmd snapshot.gro

trjconv -f traj.xtc -dump 10000 -o snapshot.gro


Trajectory

Movie

vmd traj.xtc







4. Simulation RUN


settings.mdp

letsgo.tpr

forcefield.top

configuration.gro

Traj.xtc



Initialization of the ri and vi

Integrate the equation of motion

Determine forces on atoms

Determination of mean values

MD

simulation

loops Ensemble

averaging

Equilibration

&

Time

averaging

Result Averaging Procedure


Kinetic energy and temperature:

Pressure:

Potential energy (U), total energy (E), enthalpy (H):

Microscopic quantities examples


Thank for your attention


Ensembles

- DPD

Newton equation of motion

At every time step the forces acting on every particle is calculated as

Pair potential

Drag force

Random force contribution

Weight function

Random fluctuating parameter with Gaussian statistics


Numerical: − dt → t: differential equations become finite difference equations of motion

− magnitude of t.

− integration algorithm

− potential model: approximation from QM or macroscopic properties fit.

− potential cutoff: if L < 2rc

Error sources

Thermodynamic:

− quantum fluctuation neglected

− finite-size effects: periodic boundary conditions (artificial order)

stochastic boundary conditions (wall effects)

− initial condition: trapping in metastable states ( for complex systems)

− duration of simulation: characteristic time scale

Documents

18/03/2013 Enrico Riccardi MD in Engineering 1 - NTNUfolk.ntnu.no/thuatt/upload/seminar/Enrico Riccardi - Simulation Lab.v1.00.pdf · 12/06/2013 Enrico Riccardi Gromacs MD simulations