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Remove screening pipeline section
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---
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: p_bbb
dtype: float64
- name: score_total
dtype: float64
splits:
- name: train
num_examples: 924220136
dataset_size: 126000000000
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: 924M Compound BBB Permeability Screen"
size_categories:
- 1B<n<10B
---
# BBB-Nuke: 924M Compound Blood-Brain Barrier Permeability Screen
## Overview
924 million small molecules screened for blood-brain barrier (BBB) permeability using the [BBB-Nuke](https://github.com/ATTN-Lab) pipeline.
## Data Sources
| Source | Files | Compounds |
|--------|-------|-----------|
| Enamine REAL | 2,000 | ~199M |
| Existing (ZINC/ChEMBL) | 7,384 | ~666M |
| PubChem | 625 | ~59M |
| **Total** | **10,009** | **924,220,136** |
## Key Columns
- - Canonical SMILES
- - BBB permeability probability (0-1)
- - CNS multi-parameter optimization score
- , , - Key physicochemical descriptors
- - Predicted pKa
- - Data source (enamine_real, existing, pubchem)
## Compute
Screened on Azure ML using 8x NVIDIA A100 80GB GPUs (Standard_ND96amsr_A100_v4).
## Citation
If you use this dataset, please cite the ATTN-Lab BBB-Nuke project.
## License
CC BY-NC 4.0