unum-cloud/USearchMolecules

USearch Molecules

7'132'507'184 small molecules with 2D fingerprints, 3D conformers and shape descriptors, indexed for real-time similarity search.

Start with example: 2 million molecules drawn from all three sources, 4 GB, carrying everything the larger subsets do.

Config	Molecules	Source
example	2'000'000	drawn from the three below, not additive
pubchem	115'627'267	NCBI PubChem
gdb13	977'468'267	University of Bern GDB13
real	6'039'411'650	Enamine REAL

Each subset has a -3d companion config holding three conformers per molecule.

Enamine REAL is the exception on this mirror: its conformers are here and still growing, while its fingerprint shards live on the S3 mirrors rather than the Hub.

Loading

The shards are plain Parquet, and pyarrow, pandas, polars and dask read both families directly:

import pyarrow.parquet as pq

molecules = pq.read_table("data/example/parquet/0000000000-0001000000.parquet")
geometry = pq.read_table("data/example/parquet/0000000000-0001000000.3D.parquet")

The datasets library loads the -3d configs, but not the fingerprint ones: MACCS, ECFP4, FCFP4 and PubChem are stored as fixed_size_binary, which has no datasets dtype equivalent.

from datasets import load_dataset

geometry = load_dataset("unum-cloud/USearchMolecules", "example-3d", split="train")

Searching the fingerprints is what USearch is for, rebuilding chemistry from a SMILES string is RDKit, and the Kabsch and Umeyama kernels for comparing conformers come from NumKong.

Columns

Fingerprint configs carry one row per molecule:

Column	Type	Description
smiles	utf8	Canonical graph: atoms, bonds, charges, stereochemistry
maccs	binary(21)	MACCS structural keys, 166 bits
pubchem	binary(111)	PubChem substructure fingerprint, 881 bits
ecfp4	binary(256)	Extended-connectivity fingerprint, radius 2, 2048 bits
fcfp4	binary(256)	Functional-class fingerprint, radius 2, 2048 bits

The -3d configs carry one row per conformer, three per molecule, lowest energy first:

Column	Type	Description
input_shard, input_row	utf8, uint64	Join keys back to the fingerprint row
smiles	utf8	Carried for convenience
conformer_index	uint8	Energy rank, 0 is lowest
status	uint8	0 is success; other codes mark why geometry is absent
n_heavy_atoms, n_atoms, n_bonds	uint16	Counts, with and without hydrogens
molecular_weight	float32	Exact mass in Daltons
conformer_coords	list<float16>	3 * n_atoms, row-major, centroid-centered
conformer_energy	float32	MMFF94 energy in kcal/mol
usrcat	list<float16>	60-dimensional shape descriptor; USR is its first 12 values

Geometry columns are null wherever status is non-zero. Conformers come from ETKDG embedding over RDKit's experimental torsion preferences, followed by MMFF94 relaxation.

Caveats

Conformer yield is not complete: PubChem reaches three conformers for 97.9 % of molecules, and the shortfall is concentrated above 100 atoms. A success status bounds the energy's finiteness rather than its magnitude, so filter on the gap to a molecule's own lowest conformer rather than on absolute energy.

Where a SMILES names more than one fragment, the geometry covers only the largest, while the smiles column keeps the whole string. Reproduce the choice with RDKit's LargestFragmentChooser under preferOrganic.

More

Pre-built USearch indexes, mirror choices, the SMARTS catalogs and the full methodology live in the GitHub repository.

Citation

@software{Vardanian_USearchMolecules,
  author = {Vardanian, Ash},
  title = {{USearchMolecules: A Multi-Modal Atlas of 7 Billion Small Molecules}},
  doi = {10.5281/zenodo.21613663},
  url = {https://github.com/unum-science/USearchMolecules},
  license = {Apache-2.0}
}