Name: solvated_protein_fragments_JCTC_2019 Extended ID: solvated_protein_fragments_JCTC_2019__Unke-Meuwly__DS_ctjgc03xdauc_0 Description: The solvated protein fragments dataset was generated as a partner benchmark dataset, along with SN2, for measuring the performance of machine learning models, in particular PhysNet, at describing chemical reactions, long-range interactions, and condensed phase systems. The dataset contains structures for all possible "amons" (hydrogen-saturated covalently bonded fragments) of up to eight heavy atoms (C, N, O, S) that can be derived from chemical graphs of proteins containing the 20 natural amino acids connected via peptide bonds or disulfide bridges. For amino acids that can occur in different charge states due to (de)protonation (i.e., carboxylic acids that can be negatively charged or amines that can be positively charged), all possible structures with up to a total charge of +-2e are included. In total, the dataset provides reference energies, forces, and dipole moments for 2,731,180 structures calculated at the revPBE-D3(BJ)/def2-TZVP level of theory using ORCA 4.0.1. Authors: Oliver T. Unke Markus Meuwly DOI: 10.60732/c4731f07 Calculated Property Types: atomic_forces energy Elements: C (19.27%) H (63.04%) N (4.88%) O (11.69%) S (1.13%) Methods: DFT-revPBE+D3(BJ) Software: ORCA 4.0.1 Number of Configurations: 2,730,942 Number of Atoms: 58,390,211 Publication Link: https://doi.org/10.1021/acs.jctc.9b00181 Data Source Link: https://doi.org/10.5281/zenodo.2605372