license: cc0-1.0
language:
- en
tags:
- bioassay
pretty_name: CHAFF
size_categories:
- 10K<n<100K
dataset_info:
config_name: CHAFF
features:
- name: AID
dtype: int64
- name: CID
dtype: int64
- name: AssayOutcome
dtype: string
- name: SMILES
dtype: string
splits:
- name: train
num_bytes: 4985084
num_examples: 69777
download_size: 1909242
dataset_size: 4985084
configs:
- config_name: CHAFF
data_files:
- split: train
path: CHAFF/train-*
Dataset description
This dataset collection contains curated active compound lists from various PubChem BioAssay (AID) datasets, focusing on known assay interference artifacts. We downloaded raw assay results from PubChem using their AID identifiers and extracted only the compounds labeled as "Active."
Then We applied SMILES standardization using RDKit and MolVS, including molecule sanitization and fragment removal.
Each dataset includes the following columns:
- Task: Interference type (e.g., Autofluorescence, REDOX)
- AID: PubChem Assay ID
- CID: PubChem Compound ID
- SMILES: Curated chemical representation
The final dataset is suitable for training and evaluating machine learning models.
List of PubChem AIDs included:
632, 1641, 1730, 1857, 1926, 435026, 504689, 720541, 1159604, 587, 588, 589, 590, 591, 592, 593, 594, 709, 923, 1480, 1483, 1696, 1775, 1776, 2124, 2757, 588517, 588620, 624483, 720675, 720678, 720680, 720681, 720682, 720686, 720687, 584, 585, 1476, 1478, 485294, 485341, 411, 1006, 1269, 1379, 1891, 2515, 2530, 366887, 366889, 366891, 488838, 493175, 588342, 588498, 602357, 602358, 602364, 602474, 602475, 602476, 602477, 624030, 652016, 720522, 720835, 1224835, 1347047, 672, 682, 936, 878, 888, 929, 1234
Dataset processing
st1_download_pubchem.py
Download bioassay datasets from PubChem using a single AID (Assay ID) and save them in CSV format.
st2_run_download_pubchem.py
Automate the download process for multiple AIDs by allowing you to input a list of AIDs, sequentially downloading each dataset.
st3_extract_active_compounds.py
Parse each dataset and filters rows labeled as "Active".
st4_smiles_curation.py
Standardize and validate 'CanonicalSMILES' column. Apply sanitization, standardization, and fragment removal using RDKit and MolVS.
st5_detergent_smiles_curation.py
Special handling for AIDs 585, 584, 1476, 1478, 485341, 485294 These datasets are processed to remove overlapping compounds based on detergent-related assay pairs. (Without detergent - With detergent). This ensures non-specific binders (likely aggregators) are excluded.
- AID 585 → remove compounds also active in AID 584
- AID 1476 → remove compounds also active in AID 1478
- AID 485341 → remove compounds also active in AID 485294