README.md

metadata

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 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