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SPICE_2023

SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical data for training potential functions. The emphasis is particularly on simulating drug-like small molecules interacting with proteins. Subsets of the dataset include the following: dipeptides: these provide comprehensive sampling of the covalent interactions found in proteins; solvated amino acids: these provide sampling of protein-water and water-water interactions; PubChem molecules: These sample a very wide variety of drug-like small molecules; monomer and dimer structures from DES370K: these provide sampling of a wide variety of non-covalent interactions; ion pairs: these provide further sampling of Coulomb interactions over a range of distances.

Dataset authors

Peter Eastman, Pavan Kumar Behara, David L. Dotson, Raimondas Galvelis, John E. Herr, Josh T. Horton, Yuezhi Mao, John D. Chodera, Benjamin P. Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E. Markland

Publication

https://doi.org/10.1038/s41597-022-01882-6

Original data link

https://doi.org/10.5281/zenodo.8222043

License

MIT

Number of unique molecular configurations

116504

Number of atoms

3382829

Elements included

Br, C, Ca, Cl, F, H, I, K, Li, N, Na, O, P, S

Properties included

energy, formation energy

Usage

ds.parquet : Aggregated dataset information.
co/ directory: Configuration rows each include a structure, calculated properties, and metadata.
cs/ directory : Configuration sets are subsets of configurations grouped by some common characteristic. If cs/ does not exist, no configurations sets have been defined for this dataset.
cs_co_map/ directory : The mapping of configurations to configuration sets (if defined).

ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:

Downloads last month: 33

Size of the auto-converted Parquet files (First 5GB per split):

3.14 GB

Number of rows (First 5GB per split):

189,630

Estimated number of rows:

189,628

Cite this dataset Eastman, P., Behara, P. K., Dotson, D. L., Galvelis, R., Herr, J. E., Horton, J. T., Mao, Y., Chodera, J. D., Pritchard, B. P., Wang, Y., Fabritiis, G. D., and Markland, T. E. SPICE 2023. ColabFit, 2023. https://doi.org/10.60732/a613a175

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