Datasets:

yoonholee
/

MoleculeBench

license: mit
task_categories:
  - tabular-classification
  - tabular-regression
tags:
  - chemistry
  - drug-discovery
  - molecules
  - ADMET
  - SMILES
  - molecular-properties
size_categories:
  - 100K<n<1M

MoleculeBench

Pre-computed molecular property scores for 417,500 unique drug-like molecules from ZINC250K and dockstring, scored with three computational chemistry tools.

Quick Start

import pandas as pd

df = pd.read_parquet("hf://datasets/yoonholee/MoleculeBench/all_results.parquet")
print(df.shape)  # (417500, 126)

# Filter drug-like molecules
druglike = df[
    (df["admet_ai.QED"] > 0.5) &
    (df["rdkit_properties.LipinskiViolations"] == 0) &
    (df["admet_ai.BBB_Martins"] > 0.8)
]

Dataset Details


Molecules	417,500 unique canonical SMILES
Sources	ZINC250K (249K) + dockstring (260K), deduplicated
Columns	126 (1 SMILES + 98 ADMET-AI + 24 RDKit + 3 similarity)
Format	Parquet (291 MB)

Column Reference

ADMET-AI (98 columns)

Predicted with ADMET-AI (Chemprop-RDKit models trained on TDC datasets). Each property has a raw prediction and a DrugBank-approved percentile.

Physicochemical: molecular_weight, logP, hydrogen_bond_acceptors, hydrogen_bond_donors, Lipinski, QED, stereo_centers, tpsa

Absorption: HIA_Hou, Bioavailability_Ma, Caco2_Wang, PAMPA_NCATS, Pgp_Broccatelli, Solubility_AqSolDB, HydrationFreeEnergy_FreeSolv, Lipophilicity_AstraZeneca

Distribution: BBB_Martins, PPBR_AZ, VDss_Lombardo

Metabolism: CYP1A2_Veith, CYP2C9_Veith, CYP2C9_Substrate_CarbonMangels, CYP2C19_Veith, CYP2D6_Veith, CYP2D6_Substrate_CarbonMangels, CYP3A4_Veith, CYP3A4_Substrate_CarbonMangels

Excretion: Clearance_Hepatocyte_AZ, Clearance_Microsome_AZ, Half_Life_Obach

Toxicity: AMES, Carcinogens_Lagunin, ClinTox, DILI, hERG, LD50_Zhu, Skin_Reaction, NR-AR, NR-AR-LBD, NR-AhR, NR-Aromatase, NR-ER, NR-ER-LBD, NR-PPAR-gamma, SR-ARE, SR-ATAD5, SR-HSE, SR-MMP, SR-p53

Each property also has a *_drugbank_approved_percentile column (49 total).

RDKit Properties (24 columns)

Computed with RDKit. Prefixed with rdkit_properties.:

MolWt, LogP, QED, TPSA, HBondDonorCount, HBondAcceptorCount, RotatableBondCount, RingCount, AromaticRingCount, HeavyAtomCount, FractionCSP3, MolarRefractivity, FormalCharge, BasicAmineCount, AccessibleSurfaceArea, SlogP_VSA5, PEOE_VSA6, Kappa1, BalabanJ, BertzCT, SyntheticAccessibility, PAINS, LipinskiViolations, MurckoScaffold

Similarity Search (3 columns)

Nearest neighbors from a FAISS index over ChEMBL/PubChem/BindingDB (~2M compounds):

similarity.similar_compounds — JSON list of top-k neighbors with SMILES, Tanimoto similarity, source database, and metadata
similarity.count — number of neighbors returned
similarity.error — error message if search failed (rare)

Source Datasets

ZINC250K: 249,455 drug-like molecules from ZINC via the chemical_vae paper
dockstring: 260,155 molecules from the dockstring benchmark (ExCAPE-DB subset with docking scores for 58 protein targets)

After canonicalization and deduplication, 1,041 overlapping molecules were removed.

Generation

Scored using MoleculeBench, which runs each tool as an isolated HTTP worker service:

uv run moleculebench --start-services
uv run python benchmark_all.py