Datasets Overview¶

The torch-molecule provide easy access to a wide range of datasets (pre-cached or from Hugging Face Hub).

QM9

torch_molecule.datasets.load_qm9(local_dir: str = 'torchmol_data', target_cols: List[str] = ['gap'], return_local_data_path: bool = False)[source]¶

Load QM9 dataset from Hugging Face Hub.

Source: http://quantum-machine.org/datasets/

Parameters:

local_dir (str, optional) – Path where the data should be saved, by default “torchmol_data”
target_cols (List[str], optional) – List of target column names, by default [“gap”]
return_local_data_path (bool, optional) – Whether to return the local data path, by default False

Returns:

If return_local_data_path is False:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)

If return_local_data_path is True:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)
local_data_path: Path where the data is saved

Return type:

Tuple[List[str], np.ndarray] or Tuple[List[str], np.ndarray, str]

ChEMBL2k (a small subset from ChEMBL database)

torch_molecule.datasets.load_chembl2k(local_dir: str = 'torchmol_data', target_cols: List[str] = ['ABCB1', 'ABL1', 'ADRA1D', 'ADRA2B', 'ADRB2', 'CA12', 'CA2', 'CA9', 'CACNA1H', 'CDK2', 'CHRM1', 'CHRM3', 'CHRM4', 'CNR1', 'CYP1A2', 'CYP2C19', 'CYP2C9', 'CYP2D6', 'CYP3A4', 'DRD2', 'DRD3', 'DRD4', 'EGFR', 'ESR1', 'FLT1', 'HRH1', 'HTR1A', 'HTR2A', 'HTR2B', 'HTR2C', 'HTR6', 'KCNH2', 'KDR', 'LCK', 'MCL1', 'OPRK1', 'PPARG', 'PTGS1', 'SIGMAR1', 'SLC6A2', 'SLC6A4'], return_local_data_path: bool = False)[source]¶

Load ChEMBL2K dataset from Hugging Face Hub.

ChEMBL2K is introduced from “Learning Molecular Representation in a Cell” (ICLR 2025)

Parameters:

local_dir (str, optional) – Path where the data should be saved, by default “torchmol_data”
target_cols (List[str], optional) – List of target column names, by default [“ABCB1”, “ABL1”, “ADRA1D”, “ADRA2B”, “ADRB2”, “CA12”, “CA2”, “CA9”, “CACNA1H”, “CDK2”, “CHRM1”, “CHRM3”, “CHRM4”, “CNR1”, “CYP1A2”, “CYP2C19”, “CYP2C9”, “CYP2D6”, “CYP3A4”, “DRD2”, “DRD3”, “DRD4”, “EGFR”, “ESR1”, “FLT1”, “HRH1”, “HTR1A”, “HTR2A”, “HTR2B”, “HTR2C”, “HTR6”, “KCNH2”, “KDR”, “LCK”, “MCL1”, “OPRK1”, “PPARG”, “PTGS1”, “SIGMAR1”, “SLC6A2”, “SLC6A4”]
return_local_data_path (bool, optional) – Whether to return the local data path, by default False

Returns:

If return_local_data_path is False:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)

If return_local_data_path is True:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)
local_data_path: Path where the data is saved

Return type:

Tuple[List[str], np.ndarray] or Tuple[List[str], np.ndarray, str]

Broad6k

torch_molecule.datasets.load_broad6k(local_dir: str = 'torchmol_data', target_cols: List[str] = ['220_692', '221_693', '231_703', '233_706', '234_707', '235_708', '238_712', '239_713', '240_714', '241_715', '242_716', '243_717', '244_718', '246_720', '247_721', '248_722', '249_724', '251_727', '260_738', '264_742', '265_743', '267_745', '268_746', '269_747', '270_748', '274_752', '275_754', '276_755', '277_756', '278_757', '279_758', '280_759'], return_local_data_path: bool = False)[source]¶

Load Broad6K dataset from Hugging Face Hub.

Broad6K is introduced from “Learning Molecular Representation in a Cell” (ICLR 2025)

TODO: replace the column names with the original names

Parameters:

local_dir (str, optional) – Path where the data should be saved, by default “torchmol_data”
target_cols (List[str], optional) – List of target column names, by default all tasks
return_local_data_path (bool, optional) – Whether to return the local data path, by default False

Returns:

If return_local_data_path is False:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)

If return_local_data_path is True:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)
local_data_path: Path where the data is saved

Return type:

Tuple[List[str], np.ndarray] or Tuple[List[str], np.ndarray, str]

ToxCast (The US EPA Toxicity Forecaster program)

torch_molecule.datasets.load_toxcast(local_dir: str = 'torchmol_data', target_cols: List[str] = ['ACEA_T47D_80hr_Negative', 'ACEA_T47D_80hr_Positive', 'APR_HepG2_CellCycleArrest_24h_dn', 'APR_HepG2_CellCycleArrest_24h_up', 'APR_HepG2_CellCycleArrest_72h_dn', 'APR_HepG2_CellLoss_24h_dn', 'APR_HepG2_CellLoss_72h_dn', 'APR_HepG2_MicrotubuleCSK_24h_dn', 'APR_HepG2_MicrotubuleCSK_24h_up', 'APR_HepG2_MicrotubuleCSK_72h_dn', 'APR_HepG2_MicrotubuleCSK_72h_up', 'APR_HepG2_MitoMass_24h_dn', 'APR_HepG2_MitoMass_24h_up', 'APR_HepG2_MitoMass_72h_dn', 'APR_HepG2_MitoMass_72h_up', 'APR_HepG2_MitoMembPot_1h_dn', 'APR_HepG2_MitoMembPot_24h_dn', 'APR_HepG2_MitoMembPot_72h_dn', 'APR_HepG2_MitoticArrest_24h_up', 'APR_HepG2_MitoticArrest_72h_up', 'APR_HepG2_NuclearSize_24h_dn', 'APR_HepG2_NuclearSize_72h_dn', 'APR_HepG2_NuclearSize_72h_up', 'APR_HepG2_OxidativeStress_24h_up', 'APR_HepG2_OxidativeStress_72h_up', 'APR_HepG2_StressKinase_1h_up', 'APR_HepG2_StressKinase_24h_up', 'APR_HepG2_StressKinase_72h_up', 'APR_HepG2_p53Act_24h_up', 'APR_HepG2_p53Act_72h_up', 'APR_Hepat_Apoptosis_24hr_up', 'APR_Hepat_Apoptosis_48hr_up', 'APR_Hepat_CellLoss_24hr_dn', 'APR_Hepat_CellLoss_48hr_dn', 'APR_Hepat_DNADamage_24hr_up', 'APR_Hepat_DNADamage_48hr_up', 'APR_Hepat_DNATexture_24hr_up', 'APR_Hepat_DNATexture_48hr_up', 'APR_Hepat_MitoFxnI_1hr_dn', 'APR_Hepat_MitoFxnI_24hr_dn', 'APR_Hepat_MitoFxnI_48hr_dn', 'APR_Hepat_NuclearSize_24hr_dn', 'APR_Hepat_NuclearSize_48hr_dn', 'APR_Hepat_Steatosis_24hr_up', 'APR_Hepat_Steatosis_48hr_up', 'ATG_AP_1_CIS_dn', 'ATG_AP_1_CIS_up', 'ATG_AP_2_CIS_dn', 'ATG_AP_2_CIS_up', 'ATG_AR_TRANS_dn', 'ATG_AR_TRANS_up', 'ATG_Ahr_CIS_dn', 'ATG_Ahr_CIS_up', 'ATG_BRE_CIS_dn', 'ATG_BRE_CIS_up', 'ATG_CAR_TRANS_dn', 'ATG_CAR_TRANS_up', 'ATG_CMV_CIS_dn', 'ATG_CMV_CIS_up', 'ATG_CRE_CIS_dn', 'ATG_CRE_CIS_up', 'ATG_C_EBP_CIS_dn', 'ATG_C_EBP_CIS_up', 'ATG_DR4_LXR_CIS_dn', 'ATG_DR4_LXR_CIS_up', 'ATG_DR5_CIS_dn', 'ATG_DR5_CIS_up', 'ATG_E2F_CIS_dn', 'ATG_E2F_CIS_up', 'ATG_EGR_CIS_up', 'ATG_ERE_CIS_dn', 'ATG_ERE_CIS_up', 'ATG_ERRa_TRANS_dn', 'ATG_ERRg_TRANS_dn', 'ATG_ERRg_TRANS_up', 'ATG_ERa_TRANS_up', 'ATG_E_Box_CIS_dn', 'ATG_E_Box_CIS_up', 'ATG_Ets_CIS_dn', 'ATG_Ets_CIS_up', 'ATG_FXR_TRANS_up', 'ATG_FoxA2_CIS_dn', 'ATG_FoxA2_CIS_up', 'ATG_FoxO_CIS_dn', 'ATG_FoxO_CIS_up', 'ATG_GAL4_TRANS_dn', 'ATG_GATA_CIS_dn', 'ATG_GATA_CIS_up', 'ATG_GLI_CIS_dn', 'ATG_GLI_CIS_up', 'ATG_GRE_CIS_dn', 'ATG_GRE_CIS_up', 'ATG_GR_TRANS_dn', 'ATG_GR_TRANS_up', 'ATG_HIF1a_CIS_dn', 'ATG_HIF1a_CIS_up', 'ATG_HNF4a_TRANS_dn', 'ATG_HNF4a_TRANS_up', 'ATG_HNF6_CIS_dn', 'ATG_HNF6_CIS_up', 'ATG_HSE_CIS_dn', 'ATG_HSE_CIS_up', 'ATG_IR1_CIS_dn', 'ATG_IR1_CIS_up', 'ATG_ISRE_CIS_dn', 'ATG_ISRE_CIS_up', 'ATG_LXRa_TRANS_dn', 'ATG_LXRa_TRANS_up', 'ATG_LXRb_TRANS_dn', 'ATG_LXRb_TRANS_up', 'ATG_MRE_CIS_up', 'ATG_M_06_TRANS_up', 'ATG_M_19_CIS_dn', 'ATG_M_19_TRANS_dn', 'ATG_M_19_TRANS_up', 'ATG_M_32_CIS_dn', 'ATG_M_32_CIS_up', 'ATG_M_32_TRANS_dn', 'ATG_M_32_TRANS_up', 'ATG_M_61_TRANS_up', 'ATG_Myb_CIS_dn', 'ATG_Myb_CIS_up', 'ATG_Myc_CIS_dn', 'ATG_Myc_CIS_up', 'ATG_NFI_CIS_dn', 'ATG_NFI_CIS_up', 'ATG_NF_kB_CIS_dn', 'ATG_NF_kB_CIS_up', 'ATG_NRF1_CIS_dn', 'ATG_NRF1_CIS_up', 'ATG_NRF2_ARE_CIS_dn', 'ATG_NRF2_ARE_CIS_up', 'ATG_NURR1_TRANS_dn', 'ATG_NURR1_TRANS_up', 'ATG_Oct_MLP_CIS_dn', 'ATG_Oct_MLP_CIS_up', 'ATG_PBREM_CIS_dn', 'ATG_PBREM_CIS_up', 'ATG_PPARa_TRANS_dn', 'ATG_PPARa_TRANS_up', 'ATG_PPARd_TRANS_up', 'ATG_PPARg_TRANS_up', 'ATG_PPRE_CIS_dn', 'ATG_PPRE_CIS_up', 'ATG_PXRE_CIS_dn', 'ATG_PXRE_CIS_up', 'ATG_PXR_TRANS_dn', 'ATG_PXR_TRANS_up', 'ATG_Pax6_CIS_up', 'ATG_RARa_TRANS_dn', 'ATG_RARa_TRANS_up', 'ATG_RARb_TRANS_dn', 'ATG_RARb_TRANS_up', 'ATG_RARg_TRANS_dn', 'ATG_RARg_TRANS_up', 'ATG_RORE_CIS_dn', 'ATG_RORE_CIS_up', 'ATG_RORb_TRANS_dn', 'ATG_RORg_TRANS_dn', 'ATG_RORg_TRANS_up', 'ATG_RXRa_TRANS_dn', 'ATG_RXRa_TRANS_up', 'ATG_RXRb_TRANS_dn', 'ATG_RXRb_TRANS_up', 'ATG_SREBP_CIS_dn', 'ATG_SREBP_CIS_up', 'ATG_STAT3_CIS_dn', 'ATG_STAT3_CIS_up', 'ATG_Sox_CIS_dn', 'ATG_Sox_CIS_up', 'ATG_Sp1_CIS_dn', 'ATG_Sp1_CIS_up', 'ATG_TAL_CIS_dn', 'ATG_TAL_CIS_up', 'ATG_TA_CIS_dn', 'ATG_TA_CIS_up', 'ATG_TCF_b_cat_CIS_dn', 'ATG_TCF_b_cat_CIS_up', 'ATG_TGFb_CIS_dn', 'ATG_TGFb_CIS_up', 'ATG_THRa1_TRANS_dn', 'ATG_THRa1_TRANS_up', 'ATG_VDRE_CIS_dn', 'ATG_VDRE_CIS_up', 'ATG_VDR_TRANS_dn', 'ATG_VDR_TRANS_up', 'ATG_XTT_Cytotoxicity_up', 'ATG_Xbp1_CIS_dn', 'ATG_Xbp1_CIS_up', 'ATG_p53_CIS_dn', 'ATG_p53_CIS_up', 'BSK_3C_Eselectin_down', 'BSK_3C_HLADR_down', 'BSK_3C_ICAM1_down', 'BSK_3C_IL8_down', 'BSK_3C_MCP1_down', 'BSK_3C_MIG_down', 'BSK_3C_Proliferation_down', 'BSK_3C_SRB_down', 'BSK_3C_Thrombomodulin_down', 'BSK_3C_Thrombomodulin_up', 'BSK_3C_TissueFactor_down', 'BSK_3C_TissueFactor_up', 'BSK_3C_VCAM1_down', 'BSK_3C_Vis_down', 'BSK_3C_uPAR_down', 'BSK_4H_Eotaxin3_down', 'BSK_4H_MCP1_down', 'BSK_4H_Pselectin_down', 'BSK_4H_Pselectin_up', 'BSK_4H_SRB_down', 'BSK_4H_VCAM1_down', 'BSK_4H_VEGFRII_down', 'BSK_4H_uPAR_down', 'BSK_4H_uPAR_up', 'BSK_BE3C_HLADR_down', 'BSK_BE3C_IL1a_down', 'BSK_BE3C_IP10_down', 'BSK_BE3C_MIG_down', 'BSK_BE3C_MMP1_down', 'BSK_BE3C_MMP1_up', 'BSK_BE3C_PAI1_down', 'BSK_BE3C_SRB_down', 'BSK_BE3C_TGFb1_down', 'BSK_BE3C_tPA_down', 'BSK_BE3C_uPAR_down', 'BSK_BE3C_uPAR_up', 'BSK_BE3C_uPA_down', 'BSK_CASM3C_HLADR_down', 'BSK_CASM3C_IL6_down', 'BSK_CASM3C_IL6_up', 'BSK_CASM3C_IL8_down', 'BSK_CASM3C_LDLR_down', 'BSK_CASM3C_LDLR_up', 'BSK_CASM3C_MCP1_down', 'BSK_CASM3C_MCP1_up', 'BSK_CASM3C_MCSF_down', 'BSK_CASM3C_MCSF_up', 'BSK_CASM3C_MIG_down', 'BSK_CASM3C_Proliferation_down', 'BSK_CASM3C_Proliferation_up', 'BSK_CASM3C_SAA_down', 'BSK_CASM3C_SAA_up', 'BSK_CASM3C_SRB_down', 'BSK_CASM3C_Thrombomodulin_down', 'BSK_CASM3C_Thrombomodulin_up', 'BSK_CASM3C_TissueFactor_down', 'BSK_CASM3C_VCAM1_down', 'BSK_CASM3C_VCAM1_up', 'BSK_CASM3C_uPAR_down', 'BSK_CASM3C_uPAR_up', 'BSK_KF3CT_ICAM1_down', 'BSK_KF3CT_IL1a_down', 'BSK_KF3CT_IP10_down', 'BSK_KF3CT_IP10_up', 'BSK_KF3CT_MCP1_down', 'BSK_KF3CT_MCP1_up', 'BSK_KF3CT_MMP9_down', 'BSK_KF3CT_SRB_down', 'BSK_KF3CT_TGFb1_down', 'BSK_KF3CT_TIMP2_down', 'BSK_KF3CT_uPA_down', 'BSK_LPS_CD40_down', 'BSK_LPS_Eselectin_down', 'BSK_LPS_Eselectin_up', 'BSK_LPS_IL1a_down', 'BSK_LPS_IL1a_up', 'BSK_LPS_IL8_down', 'BSK_LPS_IL8_up', 'BSK_LPS_MCP1_down', 'BSK_LPS_MCSF_down', 'BSK_LPS_PGE2_down', 'BSK_LPS_PGE2_up', 'BSK_LPS_SRB_down', 'BSK_LPS_TNFa_down', 'BSK_LPS_TNFa_up', 'BSK_LPS_TissueFactor_down', 'BSK_LPS_TissueFactor_up', 'BSK_LPS_VCAM1_down', 'BSK_SAg_CD38_down', 'BSK_SAg_CD40_down', 'BSK_SAg_CD69_down', 'BSK_SAg_Eselectin_down', 'BSK_SAg_Eselectin_up', 'BSK_SAg_IL8_down', 'BSK_SAg_IL8_up', 'BSK_SAg_MCP1_down', 'BSK_SAg_MIG_down', 'BSK_SAg_PBMCCytotoxicity_down', 'BSK_SAg_PBMCCytotoxicity_up', 'BSK_SAg_Proliferation_down', 'BSK_SAg_SRB_down', 'BSK_hDFCGF_CollagenIII_down', 'BSK_hDFCGF_EGFR_down', 'BSK_hDFCGF_EGFR_up', 'BSK_hDFCGF_IL8_down', 'BSK_hDFCGF_IP10_down', 'BSK_hDFCGF_MCSF_down', 'BSK_hDFCGF_MIG_down', 'BSK_hDFCGF_MMP1_down', 'BSK_hDFCGF_MMP1_up', 'BSK_hDFCGF_PAI1_down', 'BSK_hDFCGF_Proliferation_down', 'BSK_hDFCGF_SRB_down', 'BSK_hDFCGF_TIMP1_down', 'BSK_hDFCGF_VCAM1_down', 'CEETOX_H295R_11DCORT_dn', 'CEETOX_H295R_ANDR_dn', 'CEETOX_H295R_CORTISOL_dn', 'CEETOX_H295R_DOC_dn', 'CEETOX_H295R_DOC_up', 'CEETOX_H295R_ESTRADIOL_dn', 'CEETOX_H295R_ESTRADIOL_up', 'CEETOX_H295R_ESTRONE_dn', 'CEETOX_H295R_ESTRONE_up', 'CEETOX_H295R_OHPREG_up', 'CEETOX_H295R_OHPROG_dn', 'CEETOX_H295R_OHPROG_up', 'CEETOX_H295R_PROG_up', 'CEETOX_H295R_TESTO_dn', 'CLD_ABCB1_48hr', 'CLD_ABCG2_48hr', 'CLD_CYP1A1_24hr', 'CLD_CYP1A1_48hr', 'CLD_CYP1A1_6hr', 'CLD_CYP1A2_24hr', 'CLD_CYP1A2_48hr', 'CLD_CYP1A2_6hr', 'CLD_CYP2B6_24hr', 'CLD_CYP2B6_48hr', 'CLD_CYP2B6_6hr', 'CLD_CYP3A4_24hr', 'CLD_CYP3A4_48hr', 'CLD_CYP3A4_6hr', 'CLD_GSTA2_48hr', 'CLD_SULT2A_24hr', 'CLD_SULT2A_48hr', 'CLD_UGT1A1_24hr', 'CLD_UGT1A1_48hr', 'NCCT_HEK293T_CellTiterGLO', 'NCCT_QuantiLum_inhib_2_dn', 'NCCT_QuantiLum_inhib_dn', 'NCCT_TPO_AUR_dn', 'NCCT_TPO_GUA_dn', 'NHEERL_ZF_144hpf_TERATOSCORE_up', 'NVS_ADME_hCYP19A1', 'NVS_ADME_hCYP1A1', 'NVS_ADME_hCYP1A2', 'NVS_ADME_hCYP2A6', 'NVS_ADME_hCYP2B6', 'NVS_ADME_hCYP2C19', 'NVS_ADME_hCYP2C9', 'NVS_ADME_hCYP2D6', 'NVS_ADME_hCYP3A4', 'NVS_ADME_hCYP4F12', 'NVS_ADME_rCYP2C12', 'NVS_ENZ_hAChE', 'NVS_ENZ_hAMPKa1', 'NVS_ENZ_hAurA', 'NVS_ENZ_hBACE', 'NVS_ENZ_hCASP5', 'NVS_ENZ_hCK1D', 'NVS_ENZ_hDUSP3', 'NVS_ENZ_hES', 'NVS_ENZ_hElastase', 'NVS_ENZ_hFGFR1', 'NVS_ENZ_hGSK3b', 'NVS_ENZ_hMMP1', 'NVS_ENZ_hMMP13', 'NVS_ENZ_hMMP2', 'NVS_ENZ_hMMP3', 'NVS_ENZ_hMMP7', 'NVS_ENZ_hMMP9', 'NVS_ENZ_hPDE10', 'NVS_ENZ_hPDE4A1', 'NVS_ENZ_hPDE5', 'NVS_ENZ_hPI3Ka', 'NVS_ENZ_hPTEN', 'NVS_ENZ_hPTPN11', 'NVS_ENZ_hPTPN12', 'NVS_ENZ_hPTPN13', 'NVS_ENZ_hPTPN9', 'NVS_ENZ_hPTPRC', 'NVS_ENZ_hSIRT1', 'NVS_ENZ_hSIRT2', 'NVS_ENZ_hTrkA', 'NVS_ENZ_hVEGFR2', 'NVS_ENZ_oCOX1', 'NVS_ENZ_oCOX2', 'NVS_ENZ_rAChE', 'NVS_ENZ_rCNOS', 'NVS_ENZ_rMAOAC', 'NVS_ENZ_rMAOAP', 'NVS_ENZ_rMAOBC', 'NVS_ENZ_rMAOBP', 'NVS_ENZ_rabI2C', 'NVS_GPCR_bAdoR_NonSelective', 'NVS_GPCR_bDR_NonSelective', 'NVS_GPCR_g5HT4', 'NVS_GPCR_gH2', 'NVS_GPCR_gLTB4', 'NVS_GPCR_gLTD4', 'NVS_GPCR_gMPeripheral_NonSelective', 'NVS_GPCR_gOpiateK', 'NVS_GPCR_h5HT2A', 'NVS_GPCR_h5HT5A', 'NVS_GPCR_h5HT6', 'NVS_GPCR_h5HT7', 'NVS_GPCR_hAT1', 'NVS_GPCR_hAdoRA1', 'NVS_GPCR_hAdoRA2a', 'NVS_GPCR_hAdra2A', 'NVS_GPCR_hAdra2C', 'NVS_GPCR_hAdrb1', 'NVS_GPCR_hAdrb2', 'NVS_GPCR_hAdrb3', 'NVS_GPCR_hDRD1', 'NVS_GPCR_hDRD2s', 'NVS_GPCR_hDRD4.4', 'NVS_GPCR_hH1', 'NVS_GPCR_hLTB4_BLT1', 'NVS_GPCR_hM1', 'NVS_GPCR_hM2', 'NVS_GPCR_hM3', 'NVS_GPCR_hM4', 'NVS_GPCR_hNK2', 'NVS_GPCR_hOpiate_D1', 'NVS_GPCR_hOpiate_mu', 'NVS_GPCR_hTXA2', 'NVS_GPCR_p5HT2C', 'NVS_GPCR_r5HT1_NonSelective', 'NVS_GPCR_r5HT_NonSelective', 'NVS_GPCR_rAdra1B', 'NVS_GPCR_rAdra1_NonSelective', 'NVS_GPCR_rAdra2_NonSelective', 'NVS_GPCR_rAdrb_NonSelective', 'NVS_GPCR_rNK1', 'NVS_GPCR_rNK3', 'NVS_GPCR_rOpiate_NonSelective', 'NVS_GPCR_rOpiate_NonSelectiveNa', 'NVS_GPCR_rSST', 'NVS_GPCR_rTRH', 'NVS_GPCR_rV1', 'NVS_GPCR_rabPAF', 'NVS_GPCR_rmAdra2B', 'NVS_IC_hKhERGCh', 'NVS_IC_rCaBTZCHL', 'NVS_IC_rCaDHPRCh_L', 'NVS_IC_rNaCh_site2', 'NVS_LGIC_bGABARa1', 'NVS_LGIC_h5HT3', 'NVS_LGIC_hNNR_NBungSens', 'NVS_LGIC_rGABAR_NonSelective', 'NVS_LGIC_rNNR_BungSens', 'NVS_MP_hPBR', 'NVS_MP_rPBR', 'NVS_NR_bER', 'NVS_NR_bPR', 'NVS_NR_cAR', 'NVS_NR_hAR', 'NVS_NR_hCAR_Antagonist', 'NVS_NR_hER', 'NVS_NR_hFXR_Agonist', 'NVS_NR_hFXR_Antagonist', 'NVS_NR_hGR', 'NVS_NR_hPPARa', 'NVS_NR_hPPARg', 'NVS_NR_hPR', 'NVS_NR_hPXR', 'NVS_NR_hRAR_Antagonist', 'NVS_NR_hRARa_Agonist', 'NVS_NR_hTRa_Antagonist', 'NVS_NR_mERa', 'NVS_NR_rAR', 'NVS_NR_rMR', 'NVS_OR_gSIGMA_NonSelective', 'NVS_TR_gDAT', 'NVS_TR_hAdoT', 'NVS_TR_hDAT', 'NVS_TR_hNET', 'NVS_TR_hSERT', 'NVS_TR_rNET', 'NVS_TR_rSERT', 'NVS_TR_rVMAT2', 'OT_AR_ARELUC_AG_1440', 'OT_AR_ARSRC1_0480', 'OT_AR_ARSRC1_0960', 'OT_ER_ERaERa_0480', 'OT_ER_ERaERa_1440', 'OT_ER_ERaERb_0480', 'OT_ER_ERaERb_1440', 'OT_ER_ERbERb_0480', 'OT_ER_ERbERb_1440', 'OT_ERa_EREGFP_0120', 'OT_ERa_EREGFP_0480', 'OT_FXR_FXRSRC1_0480', 'OT_FXR_FXRSRC1_1440', 'OT_NURR1_NURR1RXRa_0480', 'OT_NURR1_NURR1RXRa_1440', 'TOX21_ARE_BLA_Agonist_ch1', 'TOX21_ARE_BLA_Agonist_ch2', 'TOX21_ARE_BLA_agonist_ratio', 'TOX21_ARE_BLA_agonist_viability', 'TOX21_AR_BLA_Agonist_ch1', 'TOX21_AR_BLA_Agonist_ch2', 'TOX21_AR_BLA_Agonist_ratio', 'TOX21_AR_BLA_Antagonist_ch1', 'TOX21_AR_BLA_Antagonist_ch2', 'TOX21_AR_BLA_Antagonist_ratio', 'TOX21_AR_BLA_Antagonist_viability', 'TOX21_AR_LUC_MDAKB2_Agonist', 'TOX21_AR_LUC_MDAKB2_Antagonist', 'TOX21_AR_LUC_MDAKB2_Antagonist2', 'TOX21_AhR_LUC_Agonist', 'TOX21_Aromatase_Inhibition', 'TOX21_AutoFluor_HEK293_Cell_blue', 'TOX21_AutoFluor_HEK293_Media_blue', 'TOX21_AutoFluor_HEPG2_Cell_blue', 'TOX21_AutoFluor_HEPG2_Cell_green', 'TOX21_AutoFluor_HEPG2_Media_blue', 'TOX21_AutoFluor_HEPG2_Media_green', 'TOX21_ELG1_LUC_Agonist', 'TOX21_ERa_BLA_Agonist_ch1', 'TOX21_ERa_BLA_Agonist_ch2', 'TOX21_ERa_BLA_Agonist_ratio', 'TOX21_ERa_BLA_Antagonist_ch1', 'TOX21_ERa_BLA_Antagonist_ch2', 'TOX21_ERa_BLA_Antagonist_ratio', 'TOX21_ERa_BLA_Antagonist_viability', 'TOX21_ERa_LUC_BG1_Agonist', 'TOX21_ERa_LUC_BG1_Antagonist', 'TOX21_ESRE_BLA_ch1', 'TOX21_ESRE_BLA_ch2', 'TOX21_ESRE_BLA_ratio', 'TOX21_ESRE_BLA_viability', 'TOX21_FXR_BLA_Antagonist_ch1', 'TOX21_FXR_BLA_Antagonist_ch2', 'TOX21_FXR_BLA_agonist_ch2', 'TOX21_FXR_BLA_agonist_ratio', 'TOX21_FXR_BLA_antagonist_ratio', 'TOX21_FXR_BLA_antagonist_viability', 'TOX21_GR_BLA_Agonist_ch1', 'TOX21_GR_BLA_Agonist_ch2', 'TOX21_GR_BLA_Agonist_ratio', 'TOX21_GR_BLA_Antagonist_ch2', 'TOX21_GR_BLA_Antagonist_ratio', 'TOX21_GR_BLA_Antagonist_viability', 'TOX21_HSE_BLA_agonist_ch1', 'TOX21_HSE_BLA_agonist_ch2', 'TOX21_HSE_BLA_agonist_ratio', 'TOX21_HSE_BLA_agonist_viability', 'TOX21_MMP_ratio_down', 'TOX21_MMP_ratio_up', 'TOX21_MMP_viability', 'TOX21_NFkB_BLA_agonist_ch1', 'TOX21_NFkB_BLA_agonist_ch2', 'TOX21_NFkB_BLA_agonist_ratio', 'TOX21_NFkB_BLA_agonist_viability', 'TOX21_PPARd_BLA_Agonist_viability', 'TOX21_PPARd_BLA_Antagonist_ch1', 'TOX21_PPARd_BLA_agonist_ch1', 'TOX21_PPARd_BLA_agonist_ch2', 'TOX21_PPARd_BLA_agonist_ratio', 'TOX21_PPARd_BLA_antagonist_ratio', 'TOX21_PPARd_BLA_antagonist_viability', 'TOX21_PPARg_BLA_Agonist_ch1', 'TOX21_PPARg_BLA_Agonist_ch2', 'TOX21_PPARg_BLA_Agonist_ratio', 'TOX21_PPARg_BLA_Antagonist_ch1', 'TOX21_PPARg_BLA_antagonist_ratio', 'TOX21_PPARg_BLA_antagonist_viability', 'TOX21_TR_LUC_GH3_Agonist', 'TOX21_TR_LUC_GH3_Antagonist', 'TOX21_VDR_BLA_Agonist_viability', 'TOX21_VDR_BLA_Antagonist_ch1', 'TOX21_VDR_BLA_agonist_ch2', 'TOX21_VDR_BLA_agonist_ratio', 'TOX21_VDR_BLA_antagonist_ratio', 'TOX21_VDR_BLA_antagonist_viability', 'TOX21_p53_BLA_p1_ch1', 'TOX21_p53_BLA_p1_ch2', 'TOX21_p53_BLA_p1_ratio', 'TOX21_p53_BLA_p1_viability', 'TOX21_p53_BLA_p2_ch1', 'TOX21_p53_BLA_p2_ch2', 'TOX21_p53_BLA_p2_ratio', 'TOX21_p53_BLA_p2_viability', 'TOX21_p53_BLA_p3_ch1', 'TOX21_p53_BLA_p3_ch2', 'TOX21_p53_BLA_p3_ratio', 'TOX21_p53_BLA_p3_viability', 'TOX21_p53_BLA_p4_ch1', 'TOX21_p53_BLA_p4_ch2', 'TOX21_p53_BLA_p4_ratio', 'TOX21_p53_BLA_p4_viability', 'TOX21_p53_BLA_p5_ch1', 'TOX21_p53_BLA_p5_ch2', 'TOX21_p53_BLA_p5_ratio', 'TOX21_p53_BLA_p5_viability', 'Tanguay_ZF_120hpf_AXIS_up', 'Tanguay_ZF_120hpf_ActivityScore', 'Tanguay_ZF_120hpf_BRAI_up', 'Tanguay_ZF_120hpf_CFIN_up', 'Tanguay_ZF_120hpf_CIRC_up', 'Tanguay_ZF_120hpf_EYE_up', 'Tanguay_ZF_120hpf_JAW_up', 'Tanguay_ZF_120hpf_MORT_up', 'Tanguay_ZF_120hpf_OTIC_up', 'Tanguay_ZF_120hpf_PE_up', 'Tanguay_ZF_120hpf_PFIN_up', 'Tanguay_ZF_120hpf_PIG_up', 'Tanguay_ZF_120hpf_SNOU_up', 'Tanguay_ZF_120hpf_SOMI_up', 'Tanguay_ZF_120hpf_SWIM_up', 'Tanguay_ZF_120hpf_TRUN_up', 'Tanguay_ZF_120hpf_TR_up', 'Tanguay_ZF_120hpf_YSE_up'], return_local_data_path: bool = False)[source]¶

Load ToxCast dataset from Hugging Face Hub.

Source: https://www.epa.gov/comptox-tools/exploring-toxcast-data

Parameters:

local_dir (str, optional) – Path where the data should be saved, by default “torchmol_data”
target_cols (List[str], optional) – List of target column names, by default all tasks
return_local_data_path (bool, optional) – Whether to return the local data path, by default False

Returns:

If return_local_data_path is False:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)

If return_local_data_path is True:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)
local_data_path: Path where the data is saved

Return type:

Tuple[List[str], np.ndarray] or Tuple[List[str], np.ndarray, str]

ADMET (absorption-distribution-metabolism-excretion-toxicity)

torch_molecule.datasets.load_admet(local_dir: str = 'torchmol_data', target_cols: List[str] = ['AMES', 'BBB_Martins', 'Bioavailability_Ma', 'CYP1A2_Veith', 'CYP2C19_Veith', 'CYP2C9_Substrate_CarbonMangels', 'CYP2C9_Veith', 'CYP2D6_Substrate_CarbonMangels', 'CYP2D6_Veith', 'CYP3A4_Substrate_CarbonMangels', 'CYP3A4_Veith', 'Caco2_Wang', 'Carcinogens_Lagunin', 'Clearance_Hepatocyte_AZ', 'Clearance_Microsome_AZ', 'ClinTox', 'DILI', 'HIA_Hou', 'Half_Life_Obach', 'HydrationFreeEnergy_FreeSolv', 'LD50_Zhu', 'Lipophilicity_AstraZeneca', 'NR-AR-LBD', 'NR-AR', 'NR-AhR', 'NR-Aromatase', 'NR-ER-LBD', 'NR-ER', 'NR-PPAR-gamma', 'PAMPA_NCATS', 'PPBR_AZ', 'Pgp_Broccatelli', 'SR-ARE', 'SR-ATAD5', 'SR-HSE', 'SR-MMP', 'SR-p53', 'Skin_Reaction', 'Solubility_AqSolDB', 'VDss_Lombardo', 'hERG'], return_local_data_path: bool = False)[source]¶

Load ADMET dataset from Hugging Face Hub.

Source: https://github.com/swansonk14/admet_ai/blob/main/admet_ai/resources/data/admet.csv

Parameters:

local_dir (str, optional) – Path where the data should be saved, by default “torchmol_data”
target_cols (List[str], optional) – List of target column names, by default all tasks
return_local_data_path (bool, optional) – Whether to return the local data path, by default False

Returns:

If return_local_data_path is False:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)

If return_local_data_path is True:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)
local_data_path: Path where the data is saved

Return type:

Tuple[List[str], np.ndarray] or Tuple[List[str], np.ndarray, str]

Gas Permeability for polymers

torch_molecule.datasets.load_gasperm(target_cols: List[str] = ['CH4', 'CO2', 'H2', 'N2', 'O2']) → Tuple[List[str], ndarray][source]¶

Load gas permeability dataset from local CSV.gz file within torch_molecule package.

Parameters:

target_cols (List[str]) – List of target column names. Default is [“CH4”, “CO2”, “H2”, “N2”, “O2”]

Returns:

smiles_list: List of SMILES strings
property_numpy: 2D numpy array with properties (rows=molecules, cols=targets)

Return type:

Tuple[List[str], np.ndarray]