| --- |
| dataset_info: |
| features: |
| - name: compound_id |
| dtype: string |
| - name: smiles_input |
| dtype: string |
| - name: smiles_standardized |
| dtype: string |
| - name: source |
| dtype: string |
| - name: provenance |
| dtype: string |
| - name: passed_mpo_filter |
| dtype: bool |
| - name: mw |
| dtype: float64 |
| - name: logp |
| dtype: float64 |
| - name: tpsa |
| dtype: float64 |
| - name: hbd |
| dtype: float64 |
| - name: hba |
| dtype: float64 |
| - name: heavy_atoms |
| dtype: float64 |
| - name: fsp3 |
| dtype: float64 |
| - name: pka_representative |
| dtype: float64 |
| - name: cns_mpo_score |
| dtype: float64 |
| - name: efflux_MDR1_HUMAN |
| dtype: float64 |
| - name: efflux_A4D1D2_HUMAN |
| dtype: float64 |
| - name: efflux_ABCG2_HUMAN |
| dtype: float64 |
| - name: efflux_MRP1_HUMAN |
| dtype: float64 |
| - name: efflux_MRP2_HUMAN |
| dtype: float64 |
| - name: efflux_MRP4_HUMAN |
| dtype: float64 |
| - name: efflux_S47A1_HUMAN |
| dtype: float64 |
| - name: efflux_S22A8_HUMAN |
| dtype: float64 |
| - name: p_bbb |
| dtype: float64 |
| - name: heuristic_reason |
| dtype: string |
| - name: heuristic_veto |
| dtype: string |
| - name: score_total |
| dtype: float64 |
| splits: |
| - name: train |
| num_examples: 1023158502 |
| dataset_size: 140000000000 |
| license: cc-by-nc-4.0 |
| task_categories: |
| - tabular-classification |
| tags: |
| - chemistry |
| - drug-discovery |
| - blood-brain-barrier |
| - bbb |
| - cns |
| - molecular-properties |
| - screening |
| pretty_name: "BBB-Nuke: 1B Compound BBB Permeability Screen" |
| size_categories: |
| - 1B<n<10B |
| --- |
| |
| # BBB-Nuke: 1 Billion Compound Blood-Brain Barrier Permeability Screen |
|
|
| ## Overview |
|
|
| 1.02 billion small molecules screened for blood-brain barrier (BBB) permeability using the [BBB-Nuke](https://github.com/ATTN-Lab) pipeline (v0.12.0). |
|
|
| ## Screening Pipeline |
|
|
| Each compound was scored through: |
| 1. **Standardization** - SMILES canonicalization via RDKit |
| 2. **Physicochemical properties** - MW, LogP, TPSA, HBD, HBA, Fsp3, heavy atom count |
| 3. **pKa prediction** - Representative pKa via MolGpKa (batched GCN inference) |
| 4. **CNS-MPO scoring** - Multi-parameter optimization (6 properties) |
| 5. **Efflux transporter prediction** - 8 efflux proteins (S1 fingerprint RF classifiers) |
| 6. **Classifier + heuristic** - Final P_BBB probability score (5-fold CV AUROC 0.933) |
| |
| ## Data Sources |
| |
| | Source | Parquet Dir | Compounds | |
| |--------|-------------|-----------| |
| | Enamine REAL | data/enamine_real/ | ~199M | |
| | Existing (ZINC/ChEMBL) | data/existing/ | ~666M | |
| | PubChem | data/pubchem/ | ~59M | |
| | CPU Screen (ZINC) | data/existing_cpu/ | ~99M | |
| | **Total** | | **1,023,158,502** | |
| |
| ## Key Columns |
| |
| - `smiles_standardized` - Canonical SMILES |
| - `p_bbb` - BBB permeability probability (0-1) |
| - `cns_mpo_score` - CNS multi-parameter optimization score |
| - `mw`, `logp`, `tpsa` - Key physicochemical descriptors |
| - `pka_representative` - Predicted pKa |
| - `efflux_*` - Efflux transporter affinity scores (8 proteins) |
| - `provenance` - Data source (enamine_real, existing, pubchem) |
| - `score_total` - Composite heuristic score |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite the ATTN-Lab BBB-Nuke project. |
|
|
| ## License |
|
|
| CC BY-NC 4.0 |
|
|
