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Leak-CURBER IC50 Time

Summary

Leak-CURBER is a benchmark for enzymatic reaction tasks (NeurIPS 2026). This repository holds the leaderboard split IC50 Time at threshold time. It contains the paper's train and validation rows, merged and shuffled with seed 42. The test set is held out for the leaderboard.

Rows

1,309,913 rows in one train split.

Split

The Time split at threshold time: records are split by UniProt annotation date; test records belong to entries annotated after the training records.

Columns

Column Type Meaning
smiles string SMILES of the ligand (molecule input).
smiles_hash string SHA-256 of smiles_key (helper column).
smiles_key string Canonical SMILES used for grouping (helper column).
organism string Source organism of the target.
sequence string Amino acid sequence of the target protein (protein input).
uniprot_id string UniProt accession of the target.
value_type string Measured quantity (constant in this file).
monomer_id int64 BindingDB MonomerID (helper column).
ligand string Ligand name.
ligand_id string Ligand id in the source database (helper column).
target string BindingDB target name.
doi string DOI of the source article.
pmid string PubMed id of the source article.
ligand_target_complex_pdbs string PDB ids of ligand-target complexes.
pubchem_cid string PubChem compound id.
pubchem_sid string PubChem substance id (helper column).
chebi_id double ChEBI id.
chembl_id string ChEMBL id.
kegg_id string KEGG id.
zinc_id string ZINC id.
pdbs list<element: string> List of PDB ids.
unit string Unit of value (mM).
log10_value double Target: log10 of value in mM.
value double Raw value in mM.
uniprot_date timestamp[ns] UniProt entry creation date (helper column; used by the Time split).

Target

log10_value, the log10 of the half-maximal inhibitory concentration in mM.

Sources and license

This dataset is released for academic, non-commercial use under CC BY-NC-SA 4.0. The terms of each source database also apply. Users must follow them.

All rows come from BindingDB. The files have no per-row source column, so ChEMBL-imported records cannot be separated.

Citation

@inproceedings{ahmed2026leakcurber,
  title     = {Leak-CURBER: A Leakage-Controlled Multimodal Evaluation Benchmark for Enzymatic Reaction Tasks},
  author    = {Ahmed, Adhil and Balaji, Roshan and Bhatt, Nirav Pravinbhai},
  booktitle = {Advances in Neural Information Processing Systems},
  year      = {2026}
}

Code: https://github.com/bisect-group/Leak-CURBER

Please also cite the sources this dataset uses:

@article{liuBindingDB2024FAIR2025,
    title = {{BindingDB} in 2024: a {FAIR} knowledgebase of protein-small molecule binding data},
    volume = {53},
    issn = {1362-4962},
    url = {https://doi.org/10.1093/nar/gkae1075},
    doi = {10.1093/nar/gkae1075},
    number = {D1},
    journal = {Nucleic Acids Research},
    author = {Liu, Tiqing and Hwang, Linda and Burley, Stephen K and Nitsche, Carmen I and Southan, Christopher and Walters, W Patrick and Gilson, Michael K},
    month = jan,
    year = {2025},
    pages = {D1633--D1644},
}

@article{theuniprotconsortiumUniProtUniversalProtein2025,
    title = {{UniProt}: the {Universal} {Protein} {Knowledgebase} in 2025},
    volume = {53},
    issn = {1362-4962},
    url = {https://doi.org/10.1093/nar/gkae1010},
    doi = {10.1093/nar/gkae1010},
    number = {D1},
    journal = {Nucleic Acids Research},
    author = {{The UniProt Consortium}},
    month = jan,
    year = {2025},
    pages = {D609--D617},
}

@article{armstrongPDBeImprovedFindability2020,
    title = {{PDBe}: improved findability of macromolecular structure data in the {PDB}},
    volume = {48},
    issn = {0305-1048},
    url = {https://doi.org/10.1093/nar/gkz990},
    doi = {10.1093/nar/gkz990},
    number = {D1},
    journal = {Nucleic Acids Research},
    author = {Armstrong, David R and Berrisford, John M and Conroy, Matthew J and Gutmanas, Aleksandras and Anyango, Stephen and Choudhary, Preeti and Clark, Alice R and Dana, Jose M and Deshpande, Mandar and Dunlop, Roisin and Gane, Paul and Gáborová, Romana and Gupta, Deepti and Haslam, Pauline and Koča, Jaroslav and Mak, Lora and Mir, Saqib and Mukhopadhyay, Abhik and Nadzirin, Nurul and Nair, Sreenath and Paysan-Lafosse, Typhaine and Pravda, Lukas and Sehnal, David and Salih, Osman and Smart, Oliver and Tolchard, James and Varadi, Mihaly and Svobodova-Vařeková, Radka and Zaki, Hossam and Kleywegt, Gerard J and Velankar, Sameer},
    month = jan,
    year = {2020},
    pages = {D335--D343},
}

@article{varadiAlphaFoldProteinStructure2024,
    title = {{AlphaFold} {Protein} {Structure} {Database} in 2024: providing structure coverage for over 214 million protein sequences},
    volume = {52},
    issn = {0305-1048},
    url = {https://doi.org/10.1093/nar/gkad1011},
    doi = {10.1093/nar/gkad1011},
    number = {D1},
    journal = {Nucleic Acids Research},
    author = {Varadi, Mihaly and Bertoni, Damian and Magana, Paulyna and Paramval, Urmila and Pidruchna, Ivanna and Radhakrishnan, Malarvizhi and Tsenkov, Maxim and Nair, Sreenath and Mirdita, Milot and Yeo, Jingi and Kovalevskiy, Oleg and Tunyasuvunakool, Kathryn and Laydon, Agata and Žídek, Augustin and Tomlinson, Hamish and Hariharan, Dhavanthi and Abrahamson, Josh and Green, Tim and Jumper, John and Birney, Ewan and Steinegger, Martin and Hassabis, Demis and Velankar, Sameer},
    month = jan,
    year = {2024},
    pages = {D368--D375},
}

@article{zdrazil2023chembl,
  title = {The {ChEMBL} Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods},
  author = {Zdrazil, Barbara and Felix, Eloy and Hunter, Fiona and Manners, Emma J and Blackshaw, James and Corbett, Sybilla and de Veij, Marleen and Ioannidis, Harris and Lopez, David Mendez and Mosquera, Juan F and Magarinos, Maria Paula and Bosc, Nicolas and Arcila, Ricardo and Kizil{\"o}ren, Tevfik and Gaulton, Anna and Bento, A Patr{\'i}cia and Adasme, Melissa F and Monecke, Peter and Landrum, Gregory A and Leach, Andrew R},
  journal = {Nucleic Acids Research},
  volume = {52},
  number = {D1},
  pages = {D1180--D1192},
  year = {2023},
  doi = {10.1093/nar/gkad1004}
}
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