NAGL-MBIS

A collection of models to predict conformation independent MBIS charges and volumes of molecules, built on the NAGL package by SimonBoothroyd.

Installation

The required dependencies to run these models can be installed using mamba and the provided environment file:

mamba env create -f devtools/conda-envs/env.yaml

You will then need to install this package from source, first clone the repository from github:

git clone https://github.com/jthorton/nagl-mbis.git
cd nagl-mbis

With the nagl environment activate install the models via:

pip install -e . --no-build-isolation 

Quick start

NAGL-MBIS offers some pre-trained models to compute conformation independent MBIS charges, these can be loaded using the following code in a script

from naglmbis.models import load_charge_model

# load two pre-trained charge models
charge_model = load_charge_model(charge_model="nagl-v1-mbis")
# load a model trained to scf dipole and mbis charges
charge_model_2 = load_charge_model(charge_model="nagl-v1-mbis-dipole")

we can then use these models to predict the corresponding properties for a given openff-toolkit Molecule object or rdkit Chem.Mol.

from openff.toolkit.topology import Molecule

# create ethanol
ethanol = Molecule.from_smiles("CCO")
# predict the charges (in e) and atomic volumes in (bohr ^3)
charges = charge_model.compute_properties(ethanol.to_rdkit())["mbis-charges"]
volumes = charge_model_2.compute_properties(ethanol.to_rdkit())["mbis-volumes"]

This is currently broken, due to plugins changing in the openff stack!

Alternatively we provide an openff-toolkit parameter handler plugin which allows you to create an openmm system using the normal python pathway with a modified force field which requests that the NAGMBIS model be used to predict charges and LJ parameters. We provide a function which can modify any offxml to add the custom handler

from naglmbis.plugins import modify_force_field
from openff.toolkit.topology import Molecule

nagl_sage = modify_force_field(force_field="openff_unconstrained-2.0.0.offxml")
# write out the force field to file
nagl_sage.to_file("nagl_sage.offxml")
# or use it to create an openmm system
methanol = Molecule.from_smiles("CO")
openmm_system = nagl_sage.create_openmm_system(topology=methanol.to_topology())

Models

MBISGraphMode

This model uses a minimal set of basic atomic features including

• one hot encoded element
• the number of bonds
• ring membership of size 3-8
• n_gcn_layers 5
• n_gcn_hidden_features 128
• n_mbis_layers 2
• n_mbis_hidden_features 64
• learning_rate 0.001
• n_epochs 1000

These models were trained on the OpenFF ESP Fragment Conformers v1.0 dataset which is on QCArchive. The dataset was computed using HF/6-31G* with PSI4 and was split 80:10:10 using the deepchem maxmin spliter.