Installation instructions and usage examples are available in the repository README at github.com/openforcefie...

Pablo v0.2.0 includes expanded custom residue definition capabilities, including the ability to define "anonymous" residues that don't rely on atom names. The workflow demonstrates parameterizing a post-translationally modified protein system and running a short OpenMM simulation.

The updated workflow uses a new tool (openff-pablo v0.2.0) for loading modified proteins from PDB files and the new prototype Rosemary force field (OpenFF 3.0.0 alpha 0) for a self-consistent treatment of both canonical and noncanonical protein residues.

The scientific work is still ongoing, but we’re releasing a prototype version so you can try it out now and learn how it will fit into your workflow once it’s fully ready for production.

Years of research on modeling proteins are beginning to pay off in a new force field that can do something no other publicly available force field can do: accurately model proteins, peptides, and general organic molecules with one consistent set of parameters.

Compared to Sage 2.2.1, Sage 2.3.0-rc2 splits torsions so that a single torsional parameter only covers a central bond with a single multiplicity. It also adds some bond and angle types to improve performance of targeted chemistries, such as small rings.

Sage 2.3.0-rc2 is applicable to drug-like molecules consisting of the elements C, H, O, N, P, S, F, Cl, Br, and I, atomic Xe, and the monoatomic ions Li+, Na+, K+, Rb+, Cs+, F-, Cl-, Br-, and I-.

Sage 2.3.0-rc2 is the second force field candidate in Open Force Field using AshGC v1.0. Both vdW and valence parameters have been re-fit, using AshGC charges, to a dataset of physical properties and QM data.

AshGC supports most small-molecule chemistries with elements C, O, H, N, S, F, Br, Cl, I, P; a list of excluded SMARTS patterns is included in the documentation. docs.openforcefield.org/projects/nag...

Then, in a workflow, you can load Sage 2.3.0 rc2 with

`ff = ForceField("openff-2.3.0-rc2.offxml")`

Or you can update an existing environment:
```
mamba install -c conda-forge "openff-toolkit>=0.17" "openff-interchange>=0.4.6" "openff-nagl>=0.5.3" "openff-nagl-models>=2025.09" "openff-forcefields>=2025.10"
```

The easiest way to try Sage 2.3.0 rc2 out is by making a new environment:
```
mamba create -n openff -c conda-forge "openff-toolkit>=0.17"
mamba activate openff
```

2. Warnings are sometimes emitted about protons/stereo/charges, those are from a performance heuristic and don’t change the chemistry of the inputs (we’re working on silencing these)

Two notes on the example:

1. The first time NAGL is used in a new environment, there may be a few seconds of extra runtime due to pytorch initialization.

...
for idx, mol in enumerate(tqdm(mols, desc="Processing molecules")):
interchange = ff.create_interchange(mol.to_topology())
interchange.minimize()
mol.conformers[0] = interchange.positions
mol.to_file(f"minimized_mol_{idx}.sdf", file_format="sdf")
```

```
from openff.toolkit import Molecule, ForceField
from tqdm import tqdm # for progress bars
mols = Molecule.from_file("inputs.sdf") # loads 50 different molecules
ff = ForceField("openff_unconstrained-2.3.0-rc2.offxml")
...

Because AshGC assigns charges so quickly, use cases like quick conformer minimization are now practical. The following python code will minimize 50 different molecules from an input SDF, saving each minimized structure to an SDF file, in about 1 minute:

Please try it out and let us know if you find any substantial improvements, regressions, or other issues in comparison to Sage 2.2.1. If all goes well, we plan to make the full release in a few weeks! See the thread for an example: