File size: 3,242 Bytes
622ba61 a6ddc5b 622ba61 a6ddc5b 622ba61 a6ddc5b 622ba61 a6ddc5b 622ba61 a6ddc5b 622ba61 a6ddc5b 622ba61 a6ddc5b 34a983c a6ddc5b 622ba61 34a983c 622ba61 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 | ---
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
|