Leash-Biosciences/papyrus-decoy-eval

Papyrus Decoy Evaluation Set

A protein-ligand binding benchmark dataset derived from the Papyrus bioactivity database, augmented with property-matched decoy molecules for evaluating virtual screening and binding prediction models.

What is this dataset?

This dataset pairs known protein-ligand binders (actives) with synthetically selected decoy molecules — compounds that are physicochemically similar to the actives but are assumed to be non-binders. This setup enables evaluation of models on a realistic discrimination task: can the model distinguish true binders from plausible-looking non-binders?

Source Data

• Actives: Extracted from the Papyrus 05.5++ combined dataset (human proteins only, pChEMBL > 7 threshold for binding)
• Decoys: Selected from the GuacaMol training set (~1M drug-like molecules)

Decoy Generation

Decoys are generated using a KNN-first, similarity-filtered strategy:

1. Property matching: For each active molecule, K nearest neighbors are retrieved from the GuacaMol library based on five normalized molecular properties (molecular weight, Bertz complexity, LogP, TPSA, ring count).
2. Structural filtering: Candidates with Tanimoto similarity > 0.30 (Morgan fingerprints, radius=2, 2048 bits) to any active for that target are discarded, ensuring decoys are physicochemically similar but structurally distinct.
3. Sampling: From the filtered pool, decoys are randomly sampled at the target ratio.

Dataset Splits

Split	Description
papyrus_decoy_v4_val.parquet	Validation set (~60% of targets)
papyrus_decoy_v4_test.parquet	Test set (~40% of targets)

The decoy-to-binder ratio is 100:1 (100 decoys per active).

Filtering Criteria

All molecules (actives and decoys) satisfy:

• Molecular weight: 400–900 Da
• LogP: 0–8
• Rotatable bonds: ≤ 12
• Largest ring size: ≤ 11

Proteins are restricted to Homo sapiens sequences with length ≤ 1024 amino acids. Per-target actives are diversity-subsampled to a maximum of 250 using fingerprint-based average-distance sampling.

Key Columns

Column	Description
smiles	SMILES string of the molecule
amino_acid_sequence	Protein amino acid sequence
protein_name	HGNC gene symbol
binds	Binary label (1 = active binder, 0 = decoy)
molecule_lib	Source library (papyrus or guacamol)
pchembl_value_Mean	Mean pChEMBL value (actives only)
UniProtID	UniProt accession
moldesc_*	Precomputed molecular descriptors (MW, LogP, TPSA, ECFP4, etc.)

Intended Use

Benchmarking protein-ligand binding prediction models, virtual screening methods, and molecular representation learning. The high decoy ratio (100:1) provides a challenging, realistic class imbalance setting.

Citation

If you use this dataset, please cite the underlying Papyrus database:

Béquignon OJM, Bongers BJ, Jespers W, et al. Papyrus: a large-scale curated dataset aimed at bioactivity predictions. J Cheminform. 2023;15(1):3.