modelforge curated dataset: SPICE 1

Modelforge Curated SPICE 1 Dataset:-1000 configuration test set-Version: nc_1000_v1.1 This provides a curated hdf5 file for the SPICE 1 dataset (release v1.1.4) designed to be compatible with modelforge, an infrastructure to implement and train NNPs. This dataset contains 100 unique records for 1000 total configurations, with a maximum of 10 configurations per record. When applicable, the units of properties are provided in the datafile, encoded as strings compatible with the openff-units package. This is compatible with modelforge HDF5 schema 2. 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 Properties Included: atomic_numbers positions "per_atom" "nanometer" dft_total_force "per_atom" "kilojoule_per_mole / nanometer" mbis_charges "per_atom" "elementary_charge" mbis_dipoles "per_atom" "elementary_charge * nanometer" mbis_quadrupoles "per_atom" "elementary_charge * nanometer ** 2" mbis_octupoles "per_atom" "elementary_charge * nanometer ** 3" mayer_indices "per_atom" "dimensionless" wiberg_lowdin_indices "per_atom" "dimensionless" total_charge "per_system" "elementary_charge" dft_total_energy "per_system" "kilojoule_per_mole" formation_energy "per_system" "kilojoule_per_mole" scf_dipole "per_system" "elementary_charge * nanometer" scf_quadrupole "per_system" "elementary_charge * nanometer ** 2" smiles "meta_data" 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