Simulate an Interchange with Amber

▼ Click here for dependency installation instructions The simplest way to install dependencies is to use the Interchange examples environment. From the root of the cloned openff-interchange repository: 
conda env create --name interchange-examples --file devtools/conda-envs/examples_env.yaml 
conda activate interchange-examples
pip install -e .
cd examples/amber
jupyter notebook amber.ipynb

In this example, we’ll quickly construct an Interchange and then run a simulation in Amber.

We need an Interchange to get started, so let’s put that together quickly. For more explanation on this process, take a look at the packed_box and protein_ligand examples.

import mdtraj
import nglview
import openmm.app
from openff.toolkit import ForceField, Molecule, Topology
from openff.toolkit.utils import get_data_file_path

from openff.interchange import Interchange

# Read a structure from the Toolkit's test suite into a Topology
pdbfile = openmm.app.PDBFile(get_data_file_path("systems/packmol_boxes/propane_methane_butanol_0.2_0.3_0.5.pdb"))
molecules = [Molecule.from_smiles(smi) for smi in ["CCC", "C", "CCCCO"]]
off_topology = Topology.from_openmm(pdbfile.topology, unique_molecules=molecules)

# Construct the Interchange with the OpenFF "Sage" force field
interchange = Interchange.from_smirnoff(
    force_field=ForceField("openff-2.0.0.offxml"),
    topology=off_topology,
)
interchange.positions = pdbfile.positions

Tada! A beautiful solvent system:

interchange.visualize("nglview")

Run a simulation

We need Amber input files to run our simulation. Interchange.to_amber takes a (string) prefix as an argument and wraps three other methods that each write out a file needed for running a simulation in Amber:

  • mysim.prmtop stores the chemical topology and physics paramaters

  • mysim.inpcrd file stores coordinates

  • mysim_pointenergy.in tells sander how a single-point energy “simulation” should be run

interchange.to_amber("mysim")

!ls mysim*

mysim.inpcrd  mysim.prmtop  mysim_pointenergy.in

/home/runner/micromamba/envs/openff-docs-examples/lib/python3.10/site-packages/openff/interchange/components/mdconfig.py:402: SwitchingFunctionNotImplementedWarning: A switching distance 8.0 angstrom was specified by the force field, but Amber does not implement a switching function. Using a hard cut-off instead. Non-bonded interactions will be affected.
  warnings.warn(

To get a proper simulation with a trajectory, we’ll also need an input file to describe the simulation parameters a a few other details, like a thermostat and what information to write to files:

amber_in = """Basic Amber control file
&cntrl
  imin=0,                ! Run molecular dynamics.
  ntx=1,                 ! Take positions from input and generate velocities
  nstlim=500,            ! Number of MD-steps to be performed.
  dt=0.001,              ! Time step (ps), use a low 1 ps timestep to be safe
  tempi=300.0,           ! Initial temperature for velocity generation
  temp0=300.0,           ! Thermostat temperature
  cut=9.0,               ! vdW cutoff (Å)
  fswitch=8.0            ! vdW switching function start point (Å)
  igb=0,                 ! Don't use a Generalized Born model
  ntt=3, gamma_ln=2.0,   ! Temperature scaling using Langevin dynamics with the collision frequency in gamma_ln (1/ps)
  ntp=0,                 ! No pressure scaling
  iwrap=1,               ! Wrap trajectory coordinates to stay in box
  ioutfm=1,              ! Write out netcdf trajectory
  ntwx=10,               ! Frequency to write coordinates
  ntpr=50,               ! Frequency to log energy info
  ntc=2,                 ! Constraints on Hydrogen-involving bonds
/
"""
with open("amber.in", "w") as f:
    f.write(amber_in)

Run the simulation with Sander:

!sander                 \
    -O                  \
    -i amber.in         \
    -p mysim.prmtop     \
    -c mysim.inpcrd     \
    -x trajectory.nc

And finally we can visualize!

traj = mdtraj.load("trajectory.nc", top=mdtraj.load_prmtop("mysim.prmtop"))
nglview.show_mdtraj(traj)

/home/runner/micromamba/envs/openff-docs-examples/lib/python3.10/site-packages/mdtraj/formats/netcdf.py:154: UserWarning: Warning: The 'netCDF4' Python package is not installed. MDTraj is using the 'scipy' implementation to read and write netCDF files,which can be significantly slower.
For improved performance, consider installing netCDF4. See installation instructions at:
https://unidata.github.io/netcdf4-python/#quick-install
  warnings.warn(warning_message)