gh-k-dense-ai-claude-scientific-skills-scientific-skills/skills/pytdc/references/datasets.md

TDC Datasets Comprehensive Catalog

This document provides a comprehensive catalog of all available datasets in the Therapeutics Data Commons, organized by task category.

Single-Instance Prediction Datasets

ADME (Absorption, Distribution, Metabolism, Excretion)

Absorption:

• Caco2_Wang - Caco-2 cell permeability (906 compounds)
• Caco2_AstraZeneca - Caco-2 permeability from AstraZeneca (700 compounds)
• HIA_Hou - Human intestinal absorption (578 compounds)
• Pgp_Broccatelli - P-glycoprotein inhibition (1,212 compounds)
• Bioavailability_Ma - Oral bioavailability (640 compounds)
• F20_edrug3d - Oral bioavailability F>=20% (1,017 compounds)
• F30_edrug3d - Oral bioavailability F>=30% (1,017 compounds)

Distribution:

• BBB_Martins - Blood-brain barrier penetration (1,975 compounds)
• PPBR_AZ - Plasma protein binding rate (1,797 compounds)
• VDss_Lombardo - Volume of distribution at steady state (1,130 compounds)

Metabolism:

• CYP2C19_Veith - CYP2C19 inhibition (12,665 compounds)
• CYP2D6_Veith - CYP2D6 inhibition (13,130 compounds)
• CYP3A4_Veith - CYP3A4 inhibition (12,328 compounds)
• CYP1A2_Veith - CYP1A2 inhibition (12,579 compounds)
• CYP2C9_Veith - CYP2C9 inhibition (12,092 compounds)
• CYP2C9_Substrate_CarbonMangels - CYP2C9 substrate (666 compounds)
• CYP2D6_Substrate_CarbonMangels - CYP2D6 substrate (664 compounds)
• CYP3A4_Substrate_CarbonMangels - CYP3A4 substrate (667 compounds)

Excretion:

• Half_Life_Obach - Half-life (667 compounds)
• Clearance_Hepatocyte_AZ - Hepatocyte clearance (1,020 compounds)
• Clearance_Microsome_AZ - Microsome clearance (1,102 compounds)

Solubility & Lipophilicity:

• Solubility_AqSolDB - Aqueous solubility (9,982 compounds)
• Lipophilicity_AstraZeneca - Lipophilicity (logD) (4,200 compounds)
• HydrationFreeEnergy_FreeSolv - Hydration free energy (642 compounds)

Toxicity

Organ Toxicity:

• hERG - hERG channel inhibition/cardiotoxicity (648 compounds)
• hERG_Karim - hERG blockers extended dataset (13,445 compounds)
• DILI - Drug-induced liver injury (475 compounds)
• Skin_Reaction - Skin reaction (404 compounds)
• Carcinogens_Lagunin - Carcinogenicity (278 compounds)
• Respiratory_Toxicity - Respiratory toxicity (278 compounds)

General Toxicity:

• AMES - Ames mutagenicity (7,255 compounds)
• LD50_Zhu - Acute toxicity LD50 (7,385 compounds)
• ClinTox - Clinical trial toxicity (1,478 compounds)
• SkinSensitization - Skin sensitization (278 compounds)
• EyeCorrosion - Eye corrosion (278 compounds)
• EyeIrritation - Eye irritation (278 compounds)

Environmental Toxicity:

• Tox21-AhR - Nuclear receptor signaling (8,169 compounds)
• Tox21-AR - Androgen receptor (9,362 compounds)
• Tox21-AR-LBD - Androgen receptor ligand binding (8,343 compounds)
• Tox21-ARE - Antioxidant response element (6,475 compounds)
• Tox21-aromatase - Aromatase inhibition (6,733 compounds)
• Tox21-ATAD5 - DNA damage (8,163 compounds)
• Tox21-ER - Estrogen receptor (7,257 compounds)
• Tox21-ER-LBD - Estrogen receptor ligand binding (8,163 compounds)
• Tox21-HSE - Heat shock response (8,162 compounds)
• Tox21-MMP - Mitochondrial membrane potential (7,394 compounds)
• Tox21-p53 - p53 pathway (8,163 compounds)
• Tox21-PPAR-gamma - PPAR gamma activation (7,396 compounds)

HTS (High-Throughput Screening)

SARS-CoV-2:

• SARSCoV2_Vitro_Touret - In vitro antiviral activity (1,484 compounds)
• SARSCoV2_3CLPro_Diamond - 3CL protease inhibition (879 compounds)
• SARSCoV2_Vitro_AlabdulKareem - In vitro screening (5,953 compounds)

Other Targets:

• Orexin1_Receptor_Butkiewicz - Orexin receptor screening (4,675 compounds)
• M1_Receptor_Agonist_Butkiewicz - M1 receptor agonist (1,700 compounds)
• M1_Receptor_Antagonist_Butkiewicz - M1 receptor antagonist (1,700 compounds)
• HIV_Butkiewicz - HIV inhibition (40,000+ compounds)
• ToxCast - Environmental chemical screening (8,597 compounds)

QM (Quantum Mechanics)

• QM7 - Quantum mechanics properties (7,160 molecules)
• QM8 - Electronic spectra and excited states (21,786 molecules)
• QM9 - Geometric, energetic, electronic, thermodynamic properties (133,885 molecules)

Yields

• Buchwald-Hartwig - Reaction yield prediction (3,955 reactions)
• USPTO_Yields - Yield prediction from USPTO (853,879 reactions)

Epitope

• IEDBpep-DiseaseBinder - Disease-associated epitope binding (6,080 peptides)
• IEDBpep-NonBinder - Non-binding peptides (24,320 peptides)

Develop (Development)

• Manufacturing - Manufacturing success prediction
• Formulation - Formulation stability

CRISPROutcome

• CRISPROutcome_Doench - Gene editing efficiency prediction (5,310 guide RNAs)

Multi-Instance Prediction Datasets

DTI (Drug-Target Interaction)

Binding Affinity:

• BindingDB_Kd - Dissociation constant (52,284 pairs, 10,665 drugs, 1,413 proteins)
• BindingDB_IC50 - Half-maximal inhibitory concentration (991,486 pairs, 549,205 drugs, 5,078 proteins)
• BindingDB_Ki - Inhibition constant (375,032 pairs, 174,662 drugs, 3,070 proteins)

Kinase Binding:

• DAVIS - Davis kinase binding dataset (30,056 pairs, 68 drugs, 442 proteins)
• KIBA - KIBA kinase binding dataset (118,254 pairs, 2,111 drugs, 229 proteins)

Binary Interaction:

• BindingDB_Patent - Patent-derived DTI (8,503 pairs)
• BindingDB_Approval - FDA-approved drug DTI (1,649 pairs)

DDI (Drug-Drug Interaction)

• DrugBank - Drug-drug interactions (191,808 pairs, 1,706 drugs)
• TWOSIDES - Side effect-based DDI (4,649,441 pairs, 645 drugs)

PPI (Protein-Protein Interaction)

• HuRI - Human reference protein interactome (52,569 interactions)
• STRING - Protein functional associations (19,247 interactions)

GDA (Gene-Disease Association)

• DisGeNET - Gene-disease associations (81,746 pairs)
• PrimeKG_GDA - Gene-disease from PrimeKG knowledge graph

DrugRes (Drug Response/Resistance)

• GDSC1 - Genomics of Drug Sensitivity in Cancer v1 (178,000 pairs)
• GDSC2 - Genomics of Drug Sensitivity in Cancer v2 (125,000 pairs)

DrugSyn (Drug Synergy)

• DrugComb - Drug combination synergy (345,502 combinations)
• DrugCombDB - Drug combination database (448,555 combinations)
• OncoPolyPharmacology - Oncology drug combinations (22,737 combinations)

PeptideMHC

• MHC1_NetMHCpan - MHC class I binding (184,983 pairs)
• MHC2_NetMHCIIpan - MHC class II binding (134,281 pairs)

AntibodyAff (Antibody Affinity)

• Protein_SAbDab - Antibody-antigen affinity (1,500+ pairs)

MTI (miRNA-Target Interaction)

• miRTarBase - Experimentally validated miRNA-target interactions (380,639 pairs)

Catalyst

• USPTO_Catalyst - Catalyst prediction for reactions (11,000+ reactions)

TrialOutcome

• TrialOutcome_WuXi - Clinical trial outcome prediction (3,769 trials)

Generation Datasets

MolGen (Molecular Generation)

• ChEMBL_V29 - Drug-like molecules from ChEMBL (1,941,410 molecules)
• ZINC - ZINC database subset (100,000+ molecules)
• GuacaMol - Goal-directed benchmark molecules
• Moses - Molecular sets benchmark (1,936,962 molecules)

RetroSyn (Retrosynthesis)

• USPTO - Retrosynthesis from USPTO patents (1,939,253 reactions)
• USPTO-50K - Curated USPTO subset (50,000 reactions)

PairMolGen (Paired Molecule Generation)

• Prodrug - Prodrug to drug transformations (1,000+ pairs)
• Metabolite - Drug to metabolite transformations

Using retrieve_dataset_names

To programmatically access all available datasets for a specific task:

from tdc.utils import retrieve_dataset_names

# Get all datasets for a specific task
adme_datasets = retrieve_dataset_names('ADME')
tox_datasets = retrieve_dataset_names('Tox')
dti_datasets = retrieve_dataset_names('DTI')
hts_datasets = retrieve_dataset_names('HTS')

Dataset Statistics

Access dataset statistics directly:

from tdc.single_pred import ADME
data = ADME(name='Caco2_Wang')

# Print basic statistics
data.print_stats()

# Get label distribution
data.label_distribution()

Loading Datasets

All datasets follow the same loading pattern:

from tdc.<problem_type> import <TaskType>
data = <TaskType>(name='<DatasetName>')

# Get full dataset
df = data.get_data(format='df')  # or 'dict', 'DeepPurpose', etc.

# Get train/valid/test split
split = data.get_split(method='scaffold', seed=1, frac=[0.7, 0.1, 0.2])

Notes

• Dataset sizes and statistics are approximate and may be updated
• New datasets are regularly added to TDC
• Some datasets may require additional dependencies
• Check the official TDC website for the most up-to-date dataset list: https://tdcommons.ai/overview/