Small molecule MD with openMM #MD #Openforcefield

I updated openforcefield from ver 0.5 to ver 0.6. ForceField of SMIRNOFF is also updated.

I tried to use new version of OpenFF.
At first, I calculated partial charge with semi empirical method ‘AM1-BCC’. Ambertools is used for the calculation, it is easy.

from openforcefield.topology import Molecule
from openforcefield.utils.toolkits import RDKitToolkitWrapper, AmberToolsToolkitWrapper
from openforcefield.topology import Topology
from openforcefield.typing.engines.smirnoff import ForceField
biar = Molecule.from_smiles('c1ccccc1-c1c(C)ccnc1')
#Gerates conformers, default number of generated conformers is 10.
biar.generate_conformers()
biar.compute_partial_charges_am1bcc()

Just finished, check the result. Nitrogen has the most negative charge and neighbor aromatic carbons has positive charges.

for i, atm in enumerate(biar.atoms):
    print(pc[i], atm)
-0.1175 e 
-0.1305 e 
-0.125 e 
-0.1305 e 
-0.1175 e 
-0.036 e 
-0.1543 e 
-0.0243 e 
-0.0648 e 
-0.2513 e 
0.3952 e 
-0.668 e 
0.4062 e 
0.136 e 
0.1335 e 
0.133 e 
0.1335 e 
0.136 e 
0.0527 e 
0.0527 e 
0.0527 e 
0.143 e 
0.0221 e 
0.0251 e 

It seems work fine. OK let’s try to MD calculation.

For convenience, I wrote simple script and config file for calculation.
Following code calculate MD with SMILES as sys.argv[1]

#small_mol_md.py
import yaml
import sys
import os
import time
import matplotlib.pyplot as plt
from openforcefield.topology import Molecule
from openforcefield.topology import Topology
from openforcefield.typing.engines.smirnoff import ForceField
from openforcefield.utils.toolkits import RDKitToolkitWrapper
from openforcefield.utils.toolkits import AmberToolsToolkitWrapper
from simtk import openmm
from simtk import unit
from rdkit import Chem

def run_md(molecule, confId=0):
    off_topology = molecule.to_topology()
    omm_topology = off_topology.to_openmm()
    system = forcefield.create_openmm_system(off_topology)

    time_step = config["time_step"] * unit.femtoseconds
    temperature = config["temperature"] * unit.kelvin
    friction = 1 / unit.picosecond
    integrator = openmm.LangevinIntegrator(temperature, friction, time_step)
    
    conf = molecule.conformers[confId]
    simulation = openmm.app.Simulation(omm_topology,
                                       system,
                                       integrator)
    simulation.context.setPositions(conf)
    if not os.path.isdir('./log'):
        os.mkdir('./log')
    pdb_reporter = openmm.app.PDBReporter('./log/trj.pdb', config["trj_freq"])
    state_data_reporter = openmm.app.StateDataReporter("./log/data.csv",
                                                       config["data_freq"],
                                                       step=True,
                                                       potentialEnergy=True,
                                                       temperature=True,
                                                       density=True)
    simulation.reporters.append(pdb_reporter)
    simulation.reporters.append(state_data_reporter)
    start = time.process_time()
    simulation.step(config["num_steps"])
    end = time.process_time()
    print(f"Elapsed time {end-start:.2f} sec")
    print("Done")

if __name__=="__main__":
    forcefield = ForceField("openff-1.0.0.offxml")
    config = yaml.load(open("mdconf.yml", "r"), yaml.Loader)
    molecule = Molecule.from_smiles(sys.argv[1])
    molecule.generate_conformers()
    run_md(molecule)

And calculation configuration is below.

#mdconfig.yml
time_step: 2
temperature: 300
friction: 1
trj_freq: 1
data_freq: 1
num_steps: 1000

Run calculation.
$ python small_mol_md.py ‘c1ccc(C)cc1-c2c(OC)nccc2’

After the calculation, I could get pdb and csv file.
Pdb file has 1000 states. And CSV file has calculated data.

blue shows energy and red shows temperature

It took ~10 sec for the molecule, it will take long time for large scale calculation.

MD calculation requires many parameters. I’m not familiar for the calculation so started to learn it. Now I installed GROMACS in my PC.

There are lots of things what I would like to learn….

Published by iwatobipen

I'm medicinal chemist in mid size of pharmaceutical company. I love chemoinfo, cording, organic synthesis, my family.

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