Dataset

SPICE_2023




Species content of dataset


Name :
SPICE_2023
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
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.
Cite As :
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.
ColabFit ID :
Date Added :
2023-12-11
License :
MIT
Downloads :
51
Num. Configurations :
116,504
Num. Atoms :
3,382,829
Calculated Property Types :
energy formation_energy
Elements :
Br (0.28%) C (36.34%) Ca (0.0%) Cl (0.78%) F (1.07%) H (45.83%) I (0.05%) K (0.02%) Li (0.0%) N (6.88%) Na (0.01%) O (6.77%) P (0.14%) S (1.83%)
Methods :
DFT-ωB97M+D3(BJ)
Software :
Psi4 1.4.1
Spec File :
Configuration Sets by Name :
Configuration Sets by ID :
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