Frequently asked questions (FAQ)

What kinds of input files can I apply SMIRNOFF parameters to?

SMIRNOFF force fields use direct chemical perception meaning that, unlike many molecular mechanics (MM) force fields, they apply parameters based on substructure searches acting directly on molecules. This creates unique opportunities and allows them to encode a great deal of chemistry quite simply, but it also means that the starting point for parameter assignment must be well-defined chemically, giving not just the elements and connectivity for all of the atoms of all of the components of your system, but also providing the formal charges and bond orders.

Specifically, to apply SMIRNOFF to a system, you must either:

  1. Provide Open Force Field Toolkit Molecule objects corresponding to the components of your system, or

  2. Provide an OpenMM Topology which includes bond orders and thus can be converted to molecules corresponding to the components of your system

Without this information, our direct chemical perception cannot be applied to your molecule, as it requires the chemical identity of the molecules in your system – that is, bond order and formal charge as well as atoms and connectivity. Unless you provide the full chemical identity in this sense, we must attempt to guess or infer the chemical identity of your molecules, which is a recipe for trouble. Different molecules can have the same chemical graph but differ in bond order and formal charge, or different resonance structures may be treated rather differently by some force fields (e.g. c1cc(ccc1c2cc[nH+]cc2)[O-] vs C1=CC(C=CC1=C2C=CNC=C2)=O, where the central bond is rotatable in one resonance structure but not in the other) even though they have identical formal charge and connectivity (chemical graph). A force field which uses the chemical identity of molecules to assign parameters needs to know the exact chemical identity of the molecule you are intending to parameterize.

Can I use an AMBER (or GROMACS) topology/coordinate file as a starting point for applying a SMIRNOFF force field?

In a word, “no”.

Parameter files used by typical molecular dynamics simulation packages do not currently encode enough information to identify the molecules chemically present, or at least not without drawing inferences. For example, one could take a structure file and infer bond orders based on bond lengths, or attempt to infer bond orders from force constants in a parameter file. Such inference work is outside the scope of SMIRNOFF.

What about starting from a PDB file?

PDB files do not in general provide the chemical identity of small molecules contained therein, and thus do not provide suitable starting points for applying SMIRNOFF to small molecules. This is especially problematic for PDB files from X-ray crystallography which typically do not include proteins, making the problem even worse. For our purposes here, however, we assume you begin with the coordinates of all atoms present and the full topology of your system.

Given a PDB file of a hypothetical biomolecular system of interest containing a small molecule, there are several routes available to you for treating the small molecule present:

  • Use a cheminformatics toolkit (see below) to infer bond orders

  • Identify your ligand from a database; e.g. if it is in the Protein Data Bank (PDB), it will be present in the Ligand Expo meaning that it has a database entry and code you can use to look up its putative chemical identity

  • Identify your ligand by name or SMILES string (or similar) from the literature or your collaborators

What about starting from an XYZ file?

XYZ files generally only contain elements and positions, and are therefore similar in content to PDB files. See the above section “What about starting from a PDB file?” for more information.

What do you recommend as a starting point?

For application of SMIRNOFF force fields, we recommend that you begin your work with formats which provide the chemical identity of your small molecule (including formal charge and bond order). This means we recommend one of the following or equivalent:

  • A .sdf, .mol, or .mol2 file or files for the molecules comprising your system, with correct bond orders and formal charges. (Note: Do NOT generate this from a simulation package or tool which does not have access to bond order information; you may end up with a correct-seeming file, but the bond orders will be incorrect)

  • Isomeric SMILES strings for the components of your system

  • InChi strings for the components of your system

  • Chemical Identity Registry numbers for the components of your system

  • IUPAC names for the components of your system

Essentially, anything which provides the full identity of what you want to simulate (including stereochemistry) should work, though it may require more or less work to get it into an acceptable format.

I understand the risks and want to perform bond and formal charge inference anyway

If you are unable to provide a molecule in the formats recommended above and want to attempt to infer the bond orders and atomic formal charges, there are tools available elsewhere that can provide guesses for this problem. These tools are not perfect, and the inference problem itself is poorly defined, so you should review each output closely (see our Core Concepts for an explanation of what information is needed to construct an OpenFF Molecule). Some tools we know of include:

I’m getting stereochemistry errors when loading a molecule from a SMILES string.

By default, the OpenFF Toolkit throws an error if a molecule with undefined stereochemistry is loaded. This is because the stereochemistry of a molecule may affect its partial charges, and assigning parameters using direct chemical perception may require knowing the stereochemistry of chiral centers. In addition, coordinates generated by the Toolkit for undefined chiral centers may have any combination of stereochemistries; the toolkit makes no guarantees about consistency, uniformity, or randomness. Note that the main-line OpenFF force fields currently use a stereochemistry-dependent charge generation method, but do not include any other stereospecific parameters.

This behavior is in line with OpenFF’s general attitude of requiring users to explicitly acknowledge actions that may cause silent errors later on. If you’re confident a Molecule with unassigned stereochemistry is acceptable, pass allow_undefined_stereo=True to molecule loading methods like Molecule.from_smiles to downgrade the exception to a warning. For an example, see the “SMILES without stereochemistry” section in the Molecule cookbook. Where possible, our parameter assignment infrastructure will gracefully handle molecules with undefined stereochemistry that are loaded this way, though they will be missing any stereospecific parameters.

I’m having troubles installing the OpenFF Toolkit on my Apple Silicon Mac.

As of August 2022, some upstreams (at least AmberTools, possibly more) are not built on osx-arm64, so installing the OpenFF stack is only possible with Rosetta. See the platform support section of the installation documentation for more.

(Keywords osx-arm64, M1 Mac, M2 Mac)

My mamba/conda installation of the toolkit doesn’t appear to work. What should I try next?

We recommend that you install the toolkit in a fresh environment, explicitly passing the channels to be used, in-order:

mamba create -n <my_new_env> -c conda-forge openff-toolkit
mamba activate <my_new_env>

Installing into a new environment avoids forcing mamba to satisfy the dependencies of both the toolkit and all existing packages in that environment. Taking the approach that conda/mamba environments are generally disposable, even ephemeral, minimizes the chances for hard-to-diagnose dependency issues.

My mamba/conda installation of the toolkit STILL doesn’t appear to work.

Many of our users encounter issues that are ultimately due to their terminal finding a different conda at higher priority in their PATH than the conda deployment where OpenFF is installed. To fix this, find the conda deployment where OpenFF is installed. Then, if that folder is something like ~/miniconda3, run in the terminal:

source ~/miniconda3/etc/profile.d/

and then try rerunning and/or reinstalling the Toolkit.

How are partial charges assigned in a SMIRNOFF force field?

There are many charge methods supported by the SMIRNOFF specification. With the exception of water, mainline OpenFF force fields only use AM1-BCC (through ToolkitAM1BCC) to assign partial charges. (A future biopolymer force field will likely use library charges for standard residues.)

If OpenEye Toolkits are installed and licensed, the ELF10 variant of AM1-BCC is used. OpenEye’s Quacpac (oequacpac.OEAM1BCCELF10Charges) is used to generate partial charges.

Otherwise, RDKit is used to generate a conformer which is passed to AmberTool’s sqm (with -c bcc).

Note that, because of differences with the ELF10 variant and other subtle differences between OpenEye Toolkits and RDKit/AmberTools, assigned partial charges can be expected to differ based on the available toolkit(s). These numerical differences are often minor but in some molecules or use cases can be significant.

A future charge method may use NAGL to assign partial charges from a graph-convolutional neural network instead of an underlying semi-empirical method. This approach is anticipated to be faster, more scalable, and more consistent than current approaches. As of March 2024, this is under development and not released for general use.

The partial charges generated by the toolkit don’t seem to depend on the molecule’s conformation! Is this a bug?

No! This is the intended behavior. The force field parameters of a molecule should be independent of both their chemical environment and conformation so that they can be used and compared across different contexts. When applying AM1BCC partial charges, the toolkit achieves a deterministic output by ignoring the input conformation and producing several new conformations for the same molecule. Partial charges are then computed based on these conformations. This behavior can be controlled with the use_conformers argument to Molecule.assign_partial_charges().

Parameterizing my system, which contains a large molecule, is taking forever. What’s wrong?

The mainline OpenFF force fields use AM1-BCC to assign partial charges (via the <ToolkitAM1BCCHandler> tag in the OFFXML file). This method unfortunately scales poorly with the size of a molecule and ligands roughly 100 atoms (about 40 heavy atoms) or larger may take so long (i.e. 10 minutes or more) that it seems like your code is simply hanging indefinitely. If you have an OpenEye license and OpenEye Toolkits installed, the OpenFF Toolkit will instead use quacpac, which can offer better performance on large molecules. Otherwise, it uses AmberTools’ sqm, which is free to use.

In the future, the use of AM1-BCC in OpenFF force fields may be replaced with method(s) that perform better and scale better with molecule size, but (as of April 2022) these are still in an experimental phase.

How can I distribute my own force fields in SMIRNOFF format?

We support conda data packages for distribution of force fields in .offxml format! Just add the relevant entry point to and distribute via a conda (or PyPI) package:

    'openforcefield.smirnoff_forcefield_directory' : [
        'my_new_force_field_paths = my_package:get_my_new_force_field_paths',

Where get_my_new_force_field_paths is a function in the my_package module providing a list of strings holding the paths to the directories to search. You should also rename my_new_force_field_paths to suit your force field. See openff-forcefields for an example.

What does “unconstrained” mean in a force field name?

Each release of an OpenFF force field has two associated .offxml files: one unadorned (for example, openff-2.0.0.offxml) and one labeled “unconstrained” (openff_unconstrained-2.0.0.offxml). This reflects the presence or absence of holonomic constraints on hydrogen-involving bonds in the force field specification.

Typically, OpenFF force fields treat bonds with a harmonic potential according to Hooke’s law. With this treatment, bonds involving hydrogen atoms have a much higher vibration frequency than any other part of a typical biochemical system. By constraining these bonds to a fixed length, MD time steps can be increased past 1 fs, improving simulation performance. These bond vibrations are not structurally important to proteins so can usually be ignored.

While we recommend hydrogen-involving bond constraints and a time step of 2 fs for ordinary use, some other specialist uses require a harmonic treatment. The unconstrained force fields are provided for these uses.

Use the constrained force field:

  • When running MD with a time step greater than 1 fs

Use the unconstrained force field:

  • When computing single point energy calculations or energy minimization

  • When running MD with a time step of 1 fs (or less)

  • When bond lengths may deviate from equilibrium

  • When fitting a force field, both because many fitting techniques require continuity and because deviations from equilibrium bond length may be important

  • Any other circumstance when forces or energies must be defined or continuous for any possible position of a hydrogen atom

Starting with v2.0.0 (Sage), TIP3P water is included in OpenFF force fields. The geometry of TIP3P water is always constrained, even in the unconstrained force fields.

How do I add or remove constraints from my own force field?

To make applying or removing bond constraints easy, constrained force fields released by OpenFF always include full bond parameters. Constraints on Hydrogen-involving bonds inherit their lengths from the harmonic parameters also included in the force field. To restore the harmonic treatment, simply remove the appropriate constraint entry from the force field.

Hydrogen-involving bonds are constrained with a single constraint entry in a .offxml file:

<Constraints version="0.3">
    <!-- constrain all bonds to hydrogen to their equilibrium bond length -->
    <Constraint smirks="[#1:1]-[*:2]" id="c1"></Constraint>

Adding or removing the inner <Constraint... line will convert a force field between being constrained and unconstrained. A ForceField object can constrain its bonds involving hydrogen by adding the relevant parameter to its 'Constraints' parameter handler:

ch = force_field.get_parameter_handler('Constraints')

Constraints can be removed from bonds involving hydrogen by removing the corresponding parameter:

del forcefield['Constraints']["[#1:1]-[*:2]"]