Curated SPICE 1 Dataset:

Full dataset restricted to elements H, C, N, O, F, Cl, S, version "full_dataset_v1_HCNOFClS":

This provides a curated hdf5 file for a subset of the SPICE 1 dataset (release v1.1.4) 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  dataset contains 976,408 total conformers, for 16,565 unique molecules. 

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:

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 c5c7153:

• Link to the source code at this commit: 
  • <add commit>
• Link to the script file used to generate the dataset: 
  • <add 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 at the ωB97M-D3(BJ)/def2-TZVPPD level of theory, using Psi4 1.4.1 along with other useful quantities such as multipole moments and bond orders.

Citations:

Original 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

Source dataset, released with CCO 1.0 Universal license:

• Eastman, P., Behara, P. K., Dotson, D., Galvelis, R., Herr, J., Horton, J., Mao, Y., Chodera, J., Pritchard, B., Wang, Y., De Fabritiis, G., & Markland, T. (2022). SPICE 1.1.4 (1.1.4) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8222043