Datasets:
File size: 11,137 Bytes
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---
license: mit
pretty_name: Drug-Likeness RDKit Dataset
tags:
- cheminformatics
- rdkit
- drug-likeness
- AutoML
configs:
- config_name: default
data_files:
- split: train_rdkit
path: data/train_rdkit-*
- split: test_rdkit
path: data/test_rdkit-*
dataset_info:
features:
- name: label
dtype: int64
- name: Standardized_SMILES
dtype: string
- name: MaxAbsEStateIndex
dtype: float64
- name: MaxEStateIndex
dtype: float64
- name: MinAbsEStateIndex
dtype: float64
- name: MinEStateIndex
dtype: float64
- name: qed
dtype: float64
- name: SPS
dtype: float64
- name: MolWt
dtype: float64
- name: HeavyAtomMolWt
dtype: float64
- name: ExactMolWt
dtype: float64
- name: NumValenceElectrons
dtype: int64
- name: NumRadicalElectrons
dtype: int64
- name: MaxPartialCharge
dtype: float64
- name: MinPartialCharge
dtype: float64
- name: MaxAbsPartialCharge
dtype: float64
- name: MinAbsPartialCharge
dtype: float64
- name: FpDensityMorgan1
dtype: float64
- name: FpDensityMorgan2
dtype: float64
- name: FpDensityMorgan3
dtype: float64
- name: BCUT2D_MWHI
dtype: float64
- name: BCUT2D_MWLOW
dtype: float64
- name: BCUT2D_CHGHI
dtype: float64
- name: BCUT2D_CHGLO
dtype: float64
- name: BCUT2D_LOGPHI
dtype: float64
- name: BCUT2D_LOGPLOW
dtype: float64
- name: BCUT2D_MRHI
dtype: float64
- name: BCUT2D_MRLOW
dtype: float64
- name: AvgIpc
dtype: float64
- name: BalabanJ
dtype: float64
- name: BertzCT
dtype: float64
- name: Chi0
dtype: float64
- name: Chi0n
dtype: float64
- name: Chi0v
dtype: float64
- name: Chi1
dtype: float64
- name: Chi1n
dtype: float64
- name: Chi1v
dtype: float64
- name: Chi2n
dtype: float64
- name: Chi2v
dtype: float64
- name: Chi3n
dtype: float64
- name: Chi3v
dtype: float64
- name: Chi4n
dtype: float64
- name: Chi4v
dtype: float64
- name: HallKierAlpha
dtype: float64
- name: Ipc
dtype: float64
- name: Kappa1
dtype: float64
- name: Kappa2
dtype: float64
- name: Kappa3
dtype: float64
- name: LabuteASA
dtype: float64
- name: PEOE_VSA1
dtype: float64
- name: PEOE_VSA10
dtype: float64
- name: PEOE_VSA11
dtype: float64
- name: PEOE_VSA12
dtype: float64
- name: PEOE_VSA13
dtype: float64
- name: PEOE_VSA14
dtype: float64
- name: PEOE_VSA2
dtype: float64
- name: PEOE_VSA3
dtype: float64
- name: PEOE_VSA4
dtype: float64
- name: PEOE_VSA5
dtype: float64
- name: PEOE_VSA6
dtype: float64
- name: PEOE_VSA7
dtype: float64
- name: PEOE_VSA8
dtype: float64
- name: PEOE_VSA9
dtype: float64
- name: SMR_VSA1
dtype: float64
- name: SMR_VSA10
dtype: float64
- name: SMR_VSA2
dtype: float64
- name: SMR_VSA3
dtype: float64
- name: SMR_VSA4
dtype: float64
- name: SMR_VSA5
dtype: float64
- name: SMR_VSA6
dtype: float64
- name: SMR_VSA7
dtype: float64
- name: SMR_VSA8
dtype: float64
- name: SMR_VSA9
dtype: float64
- name: SlogP_VSA1
dtype: float64
- name: SlogP_VSA10
dtype: float64
- name: SlogP_VSA11
dtype: float64
- name: SlogP_VSA12
dtype: float64
- name: SlogP_VSA2
dtype: float64
- name: SlogP_VSA3
dtype: float64
- name: SlogP_VSA4
dtype: float64
- name: SlogP_VSA5
dtype: float64
- name: SlogP_VSA6
dtype: float64
- name: SlogP_VSA7
dtype: float64
- name: SlogP_VSA8
dtype: float64
- name: SlogP_VSA9
dtype: float64
- name: TPSA
dtype: float64
- name: EState_VSA1
dtype: float64
- name: EState_VSA10
dtype: float64
- name: EState_VSA11
dtype: float64
- name: EState_VSA2
dtype: float64
- name: EState_VSA3
dtype: float64
- name: EState_VSA4
dtype: float64
- name: EState_VSA5
dtype: float64
- name: EState_VSA6
dtype: float64
- name: EState_VSA7
dtype: float64
- name: EState_VSA8
dtype: float64
- name: EState_VSA9
dtype: float64
- name: VSA_EState1
dtype: float64
- name: VSA_EState10
dtype: float64
- name: VSA_EState2
dtype: float64
- name: VSA_EState3
dtype: float64
- name: VSA_EState4
dtype: float64
- name: VSA_EState5
dtype: float64
- name: VSA_EState6
dtype: float64
- name: VSA_EState7
dtype: float64
- name: VSA_EState8
dtype: float64
- name: VSA_EState9
dtype: float64
- name: FractionCSP3
dtype: float64
- name: HeavyAtomCount
dtype: int64
- name: NHOHCount
dtype: int64
- name: NOCount
dtype: int64
- name: NumAliphaticCarbocycles
dtype: int64
- name: NumAliphaticHeterocycles
dtype: int64
- name: NumAliphaticRings
dtype: int64
- name: NumAmideBonds
dtype: int64
- name: NumAromaticCarbocycles
dtype: int64
- name: NumAromaticHeterocycles
dtype: int64
- name: NumAromaticRings
dtype: int64
- name: NumAtomStereoCenters
dtype: int64
- name: NumBridgeheadAtoms
dtype: int64
- name: NumHAcceptors
dtype: int64
- name: NumHDonors
dtype: int64
- name: NumHeteroatoms
dtype: int64
- name: NumHeterocycles
dtype: int64
- name: NumRotatableBonds
dtype: int64
- name: NumSaturatedCarbocycles
dtype: int64
- name: NumSaturatedHeterocycles
dtype: int64
- name: NumSaturatedRings
dtype: int64
- name: NumSpiroAtoms
dtype: int64
- name: NumUnspecifiedAtomStereoCenters
dtype: int64
- name: Phi
dtype: float64
- name: RingCount
dtype: int64
- name: MolLogP
dtype: float64
- name: MolMR
dtype: float64
- name: fr_Al_COO
dtype: int64
- name: fr_Al_OH
dtype: int64
- name: fr_Al_OH_noTert
dtype: int64
- name: fr_ArN
dtype: int64
- name: fr_Ar_COO
dtype: int64
- name: fr_Ar_N
dtype: int64
- name: fr_Ar_NH
dtype: int64
- name: fr_Ar_OH
dtype: int64
- name: fr_COO
dtype: int64
- name: fr_COO2
dtype: int64
- name: fr_C_O
dtype: int64
- name: fr_C_O_noCOO
dtype: int64
- name: fr_C_S
dtype: int64
- name: fr_HOCCN
dtype: int64
- name: fr_Imine
dtype: int64
- name: fr_NH0
dtype: int64
- name: fr_NH1
dtype: int64
- name: fr_NH2
dtype: int64
- name: fr_N_O
dtype: int64
- name: fr_Ndealkylation1
dtype: int64
- name: fr_Ndealkylation2
dtype: int64
- name: fr_Nhpyrrole
dtype: int64
- name: fr_SH
dtype: int64
- name: fr_aldehyde
dtype: int64
- name: fr_alkyl_carbamate
dtype: int64
- name: fr_alkyl_halide
dtype: int64
- name: fr_allylic_oxid
dtype: int64
- name: fr_amide
dtype: int64
- name: fr_amidine
dtype: int64
- name: fr_aniline
dtype: int64
- name: fr_aryl_methyl
dtype: int64
- name: fr_azide
dtype: int64
- name: fr_azo
dtype: int64
- name: fr_barbitur
dtype: int64
- name: fr_benzene
dtype: int64
- name: fr_benzodiazepine
dtype: int64
- name: fr_bicyclic
dtype: int64
- name: fr_diazo
dtype: int64
- name: fr_dihydropyridine
dtype: int64
- name: fr_epoxide
dtype: int64
- name: fr_ester
dtype: int64
- name: fr_ether
dtype: int64
- name: fr_furan
dtype: int64
- name: fr_guanido
dtype: int64
- name: fr_halogen
dtype: int64
- name: fr_hdrzine
dtype: int64
- name: fr_hdrzone
dtype: int64
- name: fr_imidazole
dtype: int64
- name: fr_imide
dtype: int64
- name: fr_isocyan
dtype: int64
- name: fr_isothiocyan
dtype: int64
- name: fr_ketone
dtype: int64
- name: fr_ketone_Topliss
dtype: int64
- name: fr_lactam
dtype: int64
- name: fr_lactone
dtype: int64
- name: fr_methoxy
dtype: int64
- name: fr_morpholine
dtype: int64
- name: fr_nitrile
dtype: int64
- name: fr_nitro
dtype: int64
- name: fr_nitro_arom
dtype: int64
- name: fr_nitro_arom_nonortho
dtype: int64
- name: fr_nitroso
dtype: int64
- name: fr_oxazole
dtype: int64
- name: fr_oxime
dtype: int64
- name: fr_para_hydroxylation
dtype: int64
- name: fr_phenol
dtype: int64
- name: fr_phenol_noOrthoHbond
dtype: int64
- name: fr_phos_acid
dtype: int64
- name: fr_phos_ester
dtype: int64
- name: fr_piperdine
dtype: int64
- name: fr_piperzine
dtype: int64
- name: fr_priamide
dtype: int64
- name: fr_prisulfonamd
dtype: int64
- name: fr_pyridine
dtype: int64
- name: fr_quatN
dtype: int64
- name: fr_sulfide
dtype: int64
- name: fr_sulfonamd
dtype: int64
- name: fr_sulfone
dtype: int64
- name: fr_term_acetylene
dtype: int64
- name: fr_tetrazole
dtype: int64
- name: fr_thiazole
dtype: int64
- name: fr_thiocyan
dtype: int64
- name: fr_thiophene
dtype: int64
- name: fr_unbrch_alkane
dtype: int64
- name: fr_urea
dtype: int64
splits:
- name: train_rdkit
num_bytes: 14788191
num_examples: 8234
- name: test_rdkit
num_bytes: 12413665
num_examples: 6913
download_size: 10842785
dataset_size: 27201856
---
# Drug-Likeness Prediction Dataset (Based on DBPP-Predictor Data)
This dataset was created as part of a final project on drug-likeness prediction, based on the data from the DBPP-Predictor paper:
> Gu, Y., Wang, Y., Zhu, K. et al. DBPP-Predictor: a novel strategy for prediction of chemical drug-likeness based on property profiles. J Cheminform 16, 4 (2024). https://doi.org/10.1186/s13321-024-00800-9
It includes curated molecular data, preprocessed RDKit descriptors, and training/test splits suitable for training classification models to distinguish drug-like from non-drug-like molecules.
## Project Background
Drug-likeness refers to the potential of a small molecule to become a drug. Traditional rule-based approaches (e.g., Lipinski's Rule of Five) often fail to generalize across complex compounds. This project uses RDKit descriptors and AutoML (H2O) to construct a highly interpretable, generalizable classification model.
## Dataset Description
The dataset is derived from the DBPP GitHub repository (https://github.com/yxgu2353/DBPP-Predictor.git). It includes:
- 5,147 drug-like molecules (FDA and globally approved drugs)
- 10,000 non-drug-like molecules sampled from ZINC
All molecules were standardized using MolVS(clean_data.py), the datasets were split by sklearn(split_dataset.py), and RDKit descriptors (216 features) were computed (Rdkit_descriptor.py).
### Files:
- 'train_rdkit_descriptors.parquet'
- 'test_rdkit_descriptors.parquet'
Each file contains:
- 'label': 0 for non-drug, 1 for drug
- 'Standardized_SMILES'
- 216 numerical RDKit descriptors
## Model Development
All models were trained using H2O AutoML with 10-fold cross-validation(model_constrcution.py). The top 3 models were also evaluated using an independent test set, and SHAP analysis was used to interpret the top structural features contributing to drug-likeness(model_analysis.py).
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