{"url":"/dataset/spice","name":"SPICE","full_name":"Small-Molecule/Protein Interaction Chemical Energies","description_markdown":"**SPICE** is a collection of quantum mechanical data for training potential functions. The emphasis is particularly on simulating drug-like small molecules interacting with proteins. It is designed to achieve the following goals:\r\n\r\n- Cover a wide range of chemical space\r\n- Cover a wide range of conformations\r\n- Include forces as well as energies\r\n- Include a variety of other information\r\n- Use an accurate level of theory\r\n- Be a dynamic, growing dataset\r\n- Be freely available under a non-restrictive licence","description_withheld":null,"homepage":"https://github.com/openmm/spice-dataset","introduced_date":"2022-09-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/spice-a-dataset-of-drug-like-molecules-and","title":"SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials","first_author":"Peter Eastman","url":null},"license":{"name":"MIT license","url":"https://github.com/openmm/spice-dataset/blob/main/LICENSE"},"modalities":[],"tasks":[],"languages":[],"variants":["SPICE"],"data_loaders":[],"num_papers_in_archive":17,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}