Curated SPICE 1 OpenFF Dataset:

1000 conformer test set restricted to elements H, C, N, O, F, Cl, S, version "nc_1000_v1_HCNOFClS":

This provides a curated hdf5 file for a subset of the SPICE 1 OpenFF dataset (Open Force Field initiative default level of theory) designed to be compatible with modelforge, an infrastructure to implement and train NNPs. This subset is limited to molecules containing any of the following 7 elements: H, C, N, O, F, Cl, and S.  This datafile  includes 1000 total conformers for 100  unique molecules.

Changes: In this version, for each record `total_charge` is stored as an array of shape (N_conformers, 1), i.e., a value for each conformer; previously this was just a single value for each record as the charge state doesn't change for each conformer.  

When applicable, the units of properties are provided in the datafile,  encoded as strings compatible with the openff-units package.  For more information about the structure of the data file, please see the following:

• https://github.com/choderalab/modelforge/wiki/Dataset-and-curation#curation-module

This curated dataset was generated using the modelforge software at commit <add commit number>:

• Link to the source code at this commit: <add link to commit>
• Link to the script file used to generate the dataset: <add link to commit>

Source Dataset:

Small-molecule/Protein Interaction Chemical Energies (SPICE).

The SPICE dataset contains 1.1 million conformations for a diverse set of small molecules, dimers, dipeptides, and solvated amino acids. It includes 15 elements, charged and  uncharged molecules, and a wide range of covalent and non-covalent interactions.  It provides both forces and energies calculated using B3LYP-D3BJ/DZVP level of theory, using Psi4 1.4.1.
This is the default theory used for force field development by the Open Force Field Initiative.  

This does not include the following collections (which are part of the standard SPICE 1 dataset):

Citations:

Original SPICE 1 publication:

• Eastman, P., Behara, P.K., Dotson, D.L. et al. SPICE,  A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. Sci Data 10, 11 (2023). https://doi.org/10.1038/s41597-022-01882-6