---
configs:
- config_name: default
  data_files: "co/*.parquet"
- config_name: info
  data_files: "ds.parquet"
- config_name: configuration_sets
  data_files: "cs/*.parquet"
- config_name: config_set_mapping
  data_files: "cs_co_map/*.parquet"
license: mit
tags:
- molecular dynamics
- mlip
- interatomic potential
pretty_name: SPICE 2023
---
### <details><summary>Cite this dataset </summary>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</details>  
#### This dataset has been curated and formatted for the ColabFit Exchange  
#### This dataset is also available on the ColabFit Exchange:  
https://materials.colabfit.org/id/DS_kg0dv12aiq97_0  
#### Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.  
https://materials.colabfit.org
<br><hr>  
# Dataset  Name  
SPICE 2023  
### Description  
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  
<br>
<hr>  

# 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).  
<br>
#### ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:  
- [Parquet parsing: example code](https://materials.colabfit.org/docs/how_to_use_parquet)  
- [Dataset info schema](https://materials.colabfit.org/docs/dataset_schema)  
- [Configuration schema](https://materials.colabfit.org/docs/configuration_schema)  
- [Configuration set schema](https://materials.colabfit.org/docs/configuration_set_schema)  
- [Configuration set to configuration mapping schema](https://materials.colabfit.org/docs/cs_co_mapping_schema)