[gmx-users] Martini Lipid Bilayer Simulation

prithvi raj pandey pandeyprithviraj at gmail.com
Sat Sep 3 16:20:45 CEST 2016

Dear gmx users,

I am trying to perform Martini CG simulations containing peptide helices
embedded into POPC bilayer with Gromacs 5.1.2. I have prepared the system
using the insane.py script provided on the Martini website. I am running
the system using the mdp file (martini_v2.x_new.mdp) obtained from Martini
website. The entries of the mdp file are as follows -
; Updated 15 Jul 2015 by DdJ
; for use with GROMACS 5
; For a thorough comparison of different mdp options in combination with
the Martini force field, see:
; D.H. de Jong et al., Martini straight: boosting performance using a
shorter cutoff and GPUs, submitted.

title                    = Martini

; Most simulations are numerically stable with dt=40 fs,
; however better energy conservation is achieved using a
; 20-30 fs timestep.
; Time steps smaller than 20 fs are not required unless specifically stated
in the itp file.

integrator               = md
dt                       = 0.02
nsteps                   = 200000000
nstcomm                  = 100
comm-grps         = System

nstxout                  = 0
nstvout                  = 0
nstfout                  = 0
nstlog                   = 10000
nstenergy                = 1000
nstxout-compressed       = 10000
compressed-x-precision   = 100
compressed-x-grps        =
energygrps               = Protein POPC W

; To achieve faster simulations in combination with the Verlet-neighborlist
; scheme, Martini can be simulated with a straight cutoff. In order to
; do so, the cutoff distance is reduced 1.1 nm.
; Neighborlist length should be optimized depending on your hardware setup:
; updating ever 20 steps should be fine for classic systems, while updating
; every 30-40 steps might be better for GPU based systems.
; The Verlet neighborlist scheme will automatically choose a proper
; length, based on a energy drift tolerance.
; Coulomb interactions can alternatively be treated using a reaction-field,
; giving slightly better properties.
; Please realize that electrostVatic interactions in the Martini model are
; not considered to be very accurate to begin with, especially as the
; screening in the system is set to be uniform across the system with
; a screening constant of 15. When using PME, please make sure your
; system properties are still reasonable.
; With the polarizable water model, the relative electrostatic screening
; (epsilon_r) should have a value of 2.5, representative of a low-dielectric
; apolar solvent. The polarizable water itself will perform the explicit
; in aqueous environment. In this case, the use of PME is more realistic.

cutoff-scheme            = Verlet
nstlist                  = 20
ns_type                  = grid
pbc                      = xyz
verlet-buffer-tolerance  = 0.005

coulombtype              = cutoff
coulomb-modifier         = Potential-shift-verlet
rcoulomb                 = 1.1
epsilon_r                = 15    ; 2.5 (with polarizable water)
vdw_type                 = cutoff
vdw-modifier             = Potential-shift-verlet
rvdw                     = 1.1

; normal temperature and pressure coupling schemes can be used.
; It is recommended to couple individual groups in your system separately.
; Good temperature control can be achieved with the velocity rescale
; thermostat using a coupling constant of the order of 1 ps. Even better
; temperature control can be achieved by reducing the temperature coupling
; constant to 0.1 ps, although with such tight coupling (approaching
; the time step) one can no longer speak of a weak-coupling scheme.
; We therefore recommend a coupling time constant of at least 0.5 ps.
; The Berendsen thermostat is less suited since it does not give
; a well described thermodynamic ensemble.
; Pressure can be controlled with the Parrinello-Rahman barostat,
; with a coupling constant in the range 4-8 ps and typical compressibility
; in the order of 10e-4 - 10e-5 bar-1. Note that, for equilibration
; the Berendsen barostat probably gives better results, as the Parrinello-
; Rahman is prone to oscillating behaviour. For bilayer systems the
; coupling should be done semiisotropic.

tcoupl                   = v-rescale
tc-grps                  = Protein POPC W
tau_t                    = 1.0  1.0 1.0
ref_t                    = 310 310 310
Pcoupl                   = parrinello-rahman
Pcoupltype               = semiisotropic
tau_p                    = 12.0 ;12.0  ;parrinello-rahman is more stable
with larger tau-p, DdJ, 20130422
compressibility          = 3e-4  3e-4
ref_p                    = 1.0  1.0

gen_vel                  = no
gen_temp                 = 320
gen_seed                 = 473529

; for ring systems and stiff bonds constraints are defined
; which are best handled using Lincs.

constraints              = none
constraint_algorithm     = Lincs

As you may observe that I am running the simulation for 4 microseconds. The
system runs perfectly fine till 4 microsecond. But at the end of 4
microseconds I see that the POPC bilayer containing the peptide has moved
till to the end (along Z-axis) of the simulation box. I also tried changing
comm-grps = System to comm-grps     = Protein POPC W. The bilayer still
moved to the end of the box. Is it normal or is something not right?

Thanking you,

Prithvi Raj Pandey

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