Name: SPICE_2023 Extended ID: SPICE_2023__Eastman-Behara-Dotson-Galvelis-Herr-Horton-Mao-Chodera-Pritchard-Wang-Fabritiis-Markland__DS_kg0dv12aiq97_0 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. 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 DOI: 10.60732/a613a175 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 Number of Configurations: 116,504 Number of Atoms: 3,382,829 Publication Link: https://doi.org/10.1038/s41597-022-01882-6 Data Source Link: https://doi.org/10.5281/zenodo.8222043