Hello GROMACS users
I want to analyse a coarse-grained system of 2 RNA strands using GROMACS. I have several issues with running the simulation, so maybe you have some suggestions and ideas. Thanks for your help.
My goal is to understand conformational changes upon binding of two RNA strands. They have a length of 350 nt and 150 nt and are in a simulation box. Since the system is kind of big and I want to see formation of bonds between this two strands, coarse graining seems to be the best method to get long simulations. I used Martini RNA cg. I added water as solvent and NA,CL ions. The simulation was run using a modified Martini tutorial (RNA) for single stranded RNA.
When running the energy minimisation and the equilibration of the system I am getting LINCS warnings and the system is blowing up.
1. Which salvation method do you recommend to setup a system for cg Martini simulation?
When doing it manually, i. e. adding the ions to the topology file as suggested in the tutorial, the ions are not equally distributed.
When using insane.py the simulation is not running through.
2. How can I solve LINCS errors and blowing up of the system?
I tried to increase the tilmestep, but it did not help.
3. Do you have any suggestions to generate a .pdb or .gro input file from a plane RNA sequence?
I am looking for a program that does not make use of Machine Learning or fragment libraries. So far I was using RNAcomposer to generate just a helix of my RNA based on secondary structure constraints. But the resulting .pdb file does not contain information on bonds. Only atom positions in x,y,z coordinates are given. So ideally I am looking for a program that generates me a tertiary structure inform of a simple strand without any constraints. I know, this is not so much related to GROMACS, but maybe you have a suggestion.
Thanks a lot and have a nice day!
————————— md.mdp ————————————————-
integrator = md
dt = 0.020
nsteps = 50000 ; 1us 50000000
nstcomm = 100
nstxout = 0
nstvout = 0
nstfout = 0
nstlog = 1000
nstenergy = 0
nstxout-compressed = 50000 ; 1ns
compressed-x-precision = 100
compressed-x-grps = RNA
cutoff-scheme = Verlet
nstlist = 20
ns_type = grid
pbc = xyz
verlet-buffer-tolerance = 0.005
coulombtype = reaction-field
rcoulomb = 1.1
epsilon_r = 15 ; 2.5 (with polarizable water)
epsilon_rf = 0
vdw_type = cutoff
vdw-modifier = Potential-shift-verlet
rvdw = 1.1
tcoupl = v-rescale
tc-grps = RNA W_WF_ION
tau_t = 1.0 1.0
ref_t = 300 300
Pcoupl = parrinello-rahman
Pcoupltype = semiisotropic
tau_p = 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 = 300
gen_seed = -1
constraints = none
constraint_algorithm = Lincs
GROMACS version: 2020.1-Ubuntu-2020.1-1
GROMACS modification: No
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