Datasets:

ailab-bio
/

AutoTPDplus

license: cc-by-4.0
language:
  - en
pretty_name: AutoTPD+
tags:
  - targeted-protein-degradation
  - protac
  - molecular-glue
  - drug-discovery
  - tabular
arxiv: 2605.11221
configs:
  - config_name: autotpdplus-protac
    data_files:
      - split: train
        path: AutoTPDplus-PROTAC.csv
  - config_name: autotpdplus-mg
    data_files:
      - split: train
        path: AutoTPDplus-MG.csv
  - config_name: autotpd-protac
    data_files:
      - split: train
        path: AutoTPD-PROTAC.csv
  - config_name: autotpd-mg
    data_files:
      - split: train
        path: AutoTPD-MG.csv

AutoTPD+

AutoTPD+ is a living database of PROTAC and molecular glue degradation assays mined from the literature using an agentic LLM workflow.

It contains standardized compound, target, recruiter, assay, cell-line, DC50, and Dmax information. AutoTPD+ combines literature extracted records with PROTAC-DB 3.0 and MolGlueDB and is designed for monthly updates.

7,622 assay records
1,008 source publications
2,408 unique chemical structures
2 modalities: PROTAC and molecular glue

Files

File	Description	Records
`AutoTPDplus-PROTAC.csv`	Living PROTAC dataset	6,766
`AutoTPDplus-MG.csv`	Living molecular glue dataset	856
`AutoTPD-PROTAC.csv`	Frozen PROTAC benchmark	714
`AutoTPD-MG.csv`	Frozen molecular glue benchmark	246

Data format

Each row represents one degradation assay record.

All columns

Column	Description
IDENTIFIERS
`AutoTPD_ID`	Stable row identifier, unchanged across monthly releases
`Record_ID`	Record ID in the source database; empty for LLM-extracted records
`Compound_ID`	Compound ID in the source database; empty for LLM-extracted records
`DOI`	Source publication
COMPOUND
`Compound_Name`	Compound name or label as reported in the paper
`IUPAC_Name`	IUPAC name
`IUPAC_Name_Source`	Where the IUPAC name came from (PAPER, PUBCHEM)
`SMILES`	RDKit canonical SMILES
`SMILES_Source`	Where the SMILES came from (PAPER, PUBCHEM, OPSIN, source database)
`StdInChIKey`	Standard InChIKey computed by RDKit from the standardized canonical SMILES
`Connectivity_Key`	First block of the InChIKey (connectivity only, ignores stereochemistry)
DEGRADATION TARGET
`Degradation_Target`	Target as reported in the paper
`Degradation_Target_Gene`	HGNC gene symbol
`Degradation_Target_Uniprot`	UniProt accession
`Degradation_Target_Uniprot_MutationID`	UniProt variant ID when a specific mutant is targeted
`Degradation_Target_Sequence`	UniProt protein sequence
RECRUITER
`Recruiter`	Recruiter (usually an E3 ligase) as reported
`Recruiter_Gene`	Gene symbol
`Recruiter_Uniprot`	UniProt accession
`Recruiter_Sequence`	UniProt protein sequence
ASSAY CONTEXT
`Assay`	Assay as described in the paper
`Assay_STD`	Standardized assay family
`Cell_Line`	Cell line as reported, or cell-free
`Cell_Line_STD`	Cellosaurus recommended name
`Cell_Line_STD_Accession`	Cellosaurus accession (RRID)
`Cell_Line_Modification`	Engineered construct, e.g. a HiBiT knock-in
`Cell_Line_Species`	Species of the cell line
DC50
`DC50`	Concentration giving 50% degradation
`DC50_units`	Units of DC50
`DC50_h`	Treatment time in hours
`DC50_operator`	Qualifier: `<`, `>`, `~`, `<=`, `>=`
`DC50_range_min`	Range low end, or mean − error
`DC50_range_max`	Range high end, or mean + error
DMAX
`Dmax`	Maximal degradation, in %
`Dmax_h`	Treatment time in hours
`Dmax_operator`	Qualifier: `<`, `>`, `~`, `<=`, `>=`
`Dmax_range_min`	Range low end, or mean − error
`Dmax_range_max`	Range high end, or mean + error
DMAX CONCENTRATION
`Dmax_conc`	Concentration at which Dmax was measured
`Dmax_conc_units`	Units of Dmax_conc
`Dmax_conc_operator`	Qualifier for Dmax_conc
`Dmax_conc_range_min`	Range low end
`Dmax_conc_range_max`	Range high end

Usage

from datasets import load_dataset

protac = load_dataset(
    "ailab-bio/AutoTPDplus",
    "autotpdplus-protac",
    token=True,
)

molecular_glue = load_dataset(
    "ailab-bio/AutoTPDplus",
    "autotpdplus-mg",
    token=True,
)

Citation

@misc{rao2026agenticliteratureextractionaugments,
      title={Agentic Literature Extraction Augments Targeted Protein Degradation Databases}, 
      author={Yaochen Rao and Farzaneh Jalalypour and N. M. Anoop Krishnan and Rocío Mercado},
      year={2026},
      eprint={2605.11221},
      archivePrefix={arXiv},
      primaryClass={q-bio.QM},
      url={https://arxiv.org/abs/2605.11221}, 
}

License

The structured datasets are released under CC BY 4.0. Original publications, PROTAC-DB, MolGlueDB, and other upstream resources remain subject to their respective licenses.