New version of openforcefield supports RDKit! #RDKit #chemoinformatics #openforcefield

In this morning I found great news on my tiwtter TL that openforcefield supports RDKit! Older version of openforcefiled is required openeyeTK which is commercial license for industry. I had interested in the package but could not install because I’m not academia and our company does not OETK license now.

https://open-forcefield-toolkit.readthedocs.io/en/latest/releasehistory.html

I can’t wait to use it so I installed the package and check it immediately.
Following code is ran on google colab. If would like to run on local env, you can skip several steps.

# install conda
!wget https://repo.continuum.io/miniconda/Miniconda3-4.4.10-Linux-x86_64.sh
!chmod ./Miniconda3-4.4.10-Linux-x86_64.sh
!time bash ./Miniconda3-4.4.10-Linux-x86_64.sh -b -f -p /usr/local
# install rdkit via conda command
!time conda install -c conda-forge rdkit -y

import sys
import os
sys.path.append('/usr/local/lib/python3.6/site-packages/')
from rdkit import Chem
from rdkit import rdBase
print(rdBase.rdkitVersion)

Then install openforcefield. Openforcefield is required openmm. Cuda version of colab was 10.0 so I did not need change of openmm install version. So, just type install ‘conda install openforcefield’. ;)

! conda config --add channels omnia --add channels conda-forge
! conda install -y openforcefield

Now ready, let’s call openforcefield.

from openforcefield.topology import Molecule
from openforcefield.topology import Topology
from openforcefield.utils import RDKitToolkitWrapper
from openforcefield.typing.engines.smirnoff import ForceField
from simtk import openmm
from simtk import unit

Following code was borrowed from original repo.

def get_energy(system, positions):
    """
    Return the potential energy.

    Parameters
    ----------
    system : simtk.openmm.System
        The system to check
    positions : simtk.unit.Quantity of dimension (natoms,3) with units of length
        The positions to use
    Returns
    ---------
    energy
    """

    integrator = openmm.VerletIntegrator(1.0 * unit.femtoseconds)
    context = openmm.Context(system, integrator)
    context.setPositions(positions)
    state = context.getState(getEnergy=True)
    energy = state.getPotentialEnergy().in_units_of(unit.kilocalories_per_mole)
    return energy

Load molecule with openFF method and calculate energy.

mol = Molecule.from_smiles('CCO')
mol.generate_conformers()
positions = mol.conformers[0]
#load Force Field
ff = ForceField('smirnoff99Frosst.offxml')
topology = mol.to_topology()
orginal_system = ff.create_openmm_system(topology)
orig_energy = get_energy(orginal_system, positions)
print(orig_energy)
> 2.3399880921635527 kcal/mol

Next calculate energy from rdkit mol object.

mol = Chem.MolFromSmiles('c1ccccc1')
rdw = RDKitToolkitWrapper()
ofmol = rdw.from_rdkit(mol)
ofmol.generate_conformers()
positions = ofmol.conformers[0]
topology = ofmol.to_topology()
orginal_system = ff.create_openmm_system(topology)
orig_energy = get_energy(orginal_system, positions)
print(orig_energy)
>7.987402593200566 kcal/mol

This is very simple example of OpenFF usage with RDKit. The package seems powerful for CADD. I would like to learn the package more and molecular dynamics.

Whole code of the post can check from my repo.

And I really thank to developer of RDKit, Openforcefield and many open source chemoinformatics tools.

https://nbviewer.jupyter.org/github/iwatobipen/playground/blob/master/OpenFF_test.ipynb

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