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.ipynb_checkpoints/3-run-and-customized-checkpoint.ipynb
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%% Cell type:markdown id:fba6117b tags:
%% Cell type:markdown id:024005b4 tags:
# Learn to run simulation and implement customized coarsed-grained polymer models
As we've dived into the polymer objects in arbd and learned the basic usage of arbd, now it's time to put everything together and run coarsed-grained protein model using arbd!
We will constructing a polymer model by coarse-graining the HpsModel.
## Step 1: Model Construction testing
## Step 1: Model Construction
We will begin with
We will start with the Hps Model we just saw in section 2 following and run the initial conformation with the same procedures.
%% Cell type:code id:60d287ac tags:
%% Cell type:code id:04d59bef tags:
``` python
import numpy as np
from pathlib import Path
from arbdmodel import ArbdEngine
from arbdmodel.coords import readArbdCoords
from arbdmodel.polymer import PolymerSection
from arbdmodel.hps_polymer_model import _types
from arbdmodel.hps_polymer_model import HpsModel as NupModel
#from info import NupModel, create_arbd_polymer_objects, dimensions
temperature = 298.15
ion_concentration = 250 # in mM
gpu = 0
decomp_period = 50
skin_depth = 8
## 3.2
model_name = 'HPS'
step = 1
## units "sqrt(80 epsilon0 k K /(2 * (mM/particle) * e**2))" AA
debye_length = 10
polymers, sequences = create_arbd_polymer_objects()
model = NupModel( polymers, sequences,
debye_length = debye_length,
temperature=temperature,
damping_coefficient = 50000, # units of 1/ns
decomp_period = decomp_period,
pairlist_distance = 50+skin_depth,
dimensions = dimensions
)
engine = ArbdEngine( integrator = 'Langevin',
num_steps=1e7,
output_period=1e4,
gpu = 0
)
directory = f'1-one_bead_per_res-{model_name}'
outname = 'run'
if not Path(f'{directory}/output/{outname}.dcd').exists():
# """ "Minimization" """
# add_restraints(model,restraints)
# model.simulate(output_name='{}-min-{}'.format(model_name,step),
# num_steps=1e3, output_period=500,
# gpu=gpu,
# )
# coords = readArbdCoords('output/{}-min-{}.restart'.format(model_name,step))
# model.update_splines(coords)
""" Production """
model.set_damping_coefficient( 100 )
engine.simulate(model, output_name=outname,
directory = directory
)
```
%% Cell type:markdown id:5fb80332 tags:
Then we can run the simulation with
%% Cell type:code id:28a28e18 tags:
``` python
_seq = 'GLFG' * 8 # 10 repeats per polymer
## We're going to tile polymers along x and y in a square lattice
Nx = 5
Ny = 5
N_polymers = Nx*Ny
density = 55 # mg / mL
""" Calculated parameters """
polymer_mass = sum( [_types[aa].mass for aa in _seq] ) # in daltons
## units "mg/ml" "dalton/AA**3"
_conversion = 0.0006022142
dimensions = (Nx*Ny*polymer_mass/(density*_conversion))**(1/3) # in Angstroms, the unit of length in ARBD
dimensions = [dimensions]*3 # along x,y,z
xs = np.linspace( -dimensions[0]*0.5, dimensions[0]*0.5, Nx+1 ) # row edges (one extra value)
ys = np.linspace( -dimensions[1]*0.5, dimensions[1]*0.5, Ny+1 ) # column edges
xs = (xs[1:] + xs[:-1])*0.5 # row centers
ys = (ys[1:] + ys[:-1])*0.5 # column centers
z = np.arange(len(_seq))*3.8*0.5 # times coordinate for every amino acid in a polymer, compressed a bit
""" Build peptide list consisting of sequence, coordinates"""
peptides = []
for x in xs:
for y in ys:
r = np.empty( (len(_seq),3) ) # allocate array for coordinates of each amino acid in polymer
r[:,0] = x
r[:,1] = y
r[:,2] = z
peptides.append( (_seq, r ) )
```
%% Cell type:markdown id:e0987f4a tags:
Then we can run the simulation with
%% Cell type:code id:1ad8de8d tags:
``` python
from pathlib import Path
from arbdmodel import ArbdEngine
from arbdmodel.coords import readArbdCoords
#from info import NupModel, create_arbd_polymer_objects, dimensions
temperature = 298.15
ion_concentration = 250 # in mM
gpu = 0
decomp_period = 50
skin_depth = 8
## 3.2
model_name = 'HPS'
step = 1
## units "sqrt(80 epsilon0 k K /(2 * (mM/particle) * e**2))" AA
debye_length = 10
polymers, sequences = create_arbd_polymer_objects()
model = NupModel( polymers, sequences,
debye_length = debye_length,
temperature=temperature,
damping_coefficient = 50000, # units of 1/ns
decomp_period = decomp_period,
pairlist_distance = 50+skin_depth,
dimensions = dimensions
)
```
%% Cell type:code id:6942a0b7 tags:
%% Cell type:code id:b5aef887 tags:
``` python
```
......
3-run-and-customized.ipynb
+ 76
− 52
View file @ cfa59271
%% Cell type:markdown id:fba6117b tags:
%% Cell type:markdown id:024005b4 tags:
# Learn to run simulation and implement customized coarsed-grained polymer models
As we've dived into the polymer objects in arbd and learned the basic usage of arbd, now it's time to put everything together and run coarsed-grained protein model using arbd!
We will constructing a polymer model by coarse-graining the HpsModel.
## Step 1: Model Construction testing
## Step 1: Model Construction
We will begin with
We will start with the Hps Model we just saw in section 2 following and run the initial conformation with the same procedures.
%% Cell type:code id:60d287ac tags:
%% Cell type:code id:04d59bef tags:
``` python
import numpy as np
from pathlib import Path
from arbdmodel import ArbdEngine
from arbdmodel.coords import readArbdCoords
from arbdmodel.polymer import PolymerSection
from arbdmodel.hps_polymer_model import _types
from arbdmodel.hps_polymer_model import HpsModel as NupModel
#from info import NupModel, create_arbd_polymer_objects, dimensions
temperature = 298.15
ion_concentration = 250 # in mM
gpu = 0
decomp_period = 50
skin_depth = 8
## 3.2
model_name = 'HPS'
step = 1
## units "sqrt(80 epsilon0 k K /(2 * (mM/particle) * e**2))" AA
debye_length = 10
polymers, sequences = create_arbd_polymer_objects()
model = NupModel( polymers, sequences,
debye_length = debye_length,
temperature=temperature,
damping_coefficient = 50000, # units of 1/ns
decomp_period = decomp_period,
pairlist_distance = 50+skin_depth,
dimensions = dimensions
)
engine = ArbdEngine( integrator = 'Langevin',
num_steps=1e7,
output_period=1e4,
gpu = 0
)
directory = f'1-one_bead_per_res-{model_name}'
outname = 'run'
if not Path(f'{directory}/output/{outname}.dcd').exists():
# """ "Minimization" """
# add_restraints(model,restraints)
# model.simulate(output_name='{}-min-{}'.format(model_name,step),
# num_steps=1e3, output_period=500,
# gpu=gpu,
# )
# coords = readArbdCoords('output/{}-min-{}.restart'.format(model_name,step))
# model.update_splines(coords)
""" Production """
model.set_damping_coefficient( 100 )
engine.simulate(model, output_name=outname,
directory = directory
)
```
%% Cell type:markdown id:5fb80332 tags:
Then we can run the simulation with
%% Cell type:code id:28a28e18 tags:
``` python
_seq = 'GLFG' * 8 # 10 repeats per polymer
## We're going to tile polymers along x and y in a square lattice
Nx = 5
Ny = 5
N_polymers = Nx*Ny
density = 55 # mg / mL
""" Calculated parameters """
polymer_mass = sum( [_types[aa].mass for aa in _seq] ) # in daltons
## units "mg/ml" "dalton/AA**3"
_conversion = 0.0006022142
dimensions = (Nx*Ny*polymer_mass/(density*_conversion))**(1/3) # in Angstroms, the unit of length in ARBD
dimensions = [dimensions]*3 # along x,y,z
xs = np.linspace( -dimensions[0]*0.5, dimensions[0]*0.5, Nx+1 ) # row edges (one extra value)
ys = np.linspace( -dimensions[1]*0.5, dimensions[1]*0.5, Ny+1 ) # column edges
xs = (xs[1:] + xs[:-1])*0.5 # row centers
ys = (ys[1:] + ys[:-1])*0.5 # column centers
z = np.arange(len(_seq))*3.8*0.5 # times coordinate for every amino acid in a polymer, compressed a bit
""" Build peptide list consisting of sequence, coordinates"""
peptides = []
for x in xs:
for y in ys:
r = np.empty( (len(_seq),3) ) # allocate array for coordinates of each amino acid in polymer
r[:,0] = x
r[:,1] = y
r[:,2] = z
peptides.append( (_seq, r ) )
```
%% Cell type:markdown id:e0987f4a tags:
Then we can run the simulation with
%% Cell type:code id:1ad8de8d tags:
``` python
from pathlib import Path
from arbdmodel import ArbdEngine
from arbdmodel.coords import readArbdCoords
#from info import NupModel, create_arbd_polymer_objects, dimensions
temperature = 298.15
ion_concentration = 250 # in mM
gpu = 0
decomp_period = 50
skin_depth = 8
## 3.2
model_name = 'HPS'
step = 1
## units "sqrt(80 epsilon0 k K /(2 * (mM/particle) * e**2))" AA
debye_length = 10
polymers, sequences = create_arbd_polymer_objects()
model = NupModel( polymers, sequences,
debye_length = debye_length,
temperature=temperature,
damping_coefficient = 50000, # units of 1/ns
decomp_period = decomp_period,
pairlist_distance = 50+skin_depth,
dimensions = dimensions
)
```
%% Cell type:code id:6942a0b7 tags:
%% Cell type:code id:b5aef887 tags:
``` python
```
......
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