| --- |
| license: apache-2.0 |
| pretty_name: USearch Molecules |
| size_categories: |
| - 10B<n<100B |
| task_categories: |
| - feature-extraction |
| tags: |
| - chemistry |
| - molecules |
| - drug-discovery |
| - cheminformatics |
| - smiles |
| - conformers |
| - molecular-fingerprints |
| - similarity-search |
| - vector-search |
| - 3d |
| - tabular |
| - pandas |
| - dask |
| - usearch |
| - rdkit |
| - numkong |
| configs: |
| - config_name: example |
| data_files: data/example/parquet/??????????-??????????.parquet |
| - config_name: example-3d |
| data_files: data/example/parquet/*.3D.parquet |
| - config_name: pubchem |
| data_files: data/pubchem/parquet/??????????-??????????.parquet |
| - config_name: pubchem-3d |
| data_files: data/pubchem/parquet/*.3D.parquet |
| - config_name: gdb13 |
| data_files: data/gdb13/parquet/??????????-??????????.parquet |
| - config_name: gdb13-3d |
| data_files: data/gdb13/parquet/*.3D.parquet |
| - config_name: real-3d |
| data_files: data/real/parquet/*.3D.parquet |
| --- |
| |
| # 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: |
|
|
| ```python |
| 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. |
|
|
| ```python |
| from datasets import load_dataset |
| |
| geometry = load_dataset("unum-cloud/USearchMolecules", "example-3d", split="train") |
| ``` |
|
|
| Searching the fingerprints is what [USearch](https://github.com/unum-cloud/USearch) is for, rebuilding chemistry from a SMILES string is [RDKit](https://www.rdkit.org), and the Kabsch and Umeyama kernels for comparing conformers come from [NumKong](https://github.com/ashvardanian/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](https://github.com/unum-science/USearchMolecules). |
|
|
| ## Citation |
|
|
| ```bibtex |
| @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} |
| } |
| ``` |
|
|
