load_chembl235_ec50#

skfp.datasets.moleculeace.load_chembl235_ec50(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False, force_update: bool = False) → DataFrame | tuple[list[str], ndarray]#

Load the ChEMBL235 EC50 dataset.

The task is to predict the half maximal effective concentration (EC50) of molecules against the Peroxisome proliferator-activated receptor gamma target [1] [2].

Tasks

1

Task type

regression

Total samples

2349

Recommended split

activity_cliff

Recommended metric

RMSE
Parameters:

  • data_dir ({None, str, path-like}, default=None) – Path to the root data directory. If None, currently set scikit-learn directory is used, by default $HOME/scikit_learn_data.

  • as_frame (bool, default=False) – If True, returns the raw DataFrame with columns: “SMILES”, “label”. Otherwise, returns SMILES as list of strings, and labels as a NumPy array (1D integer binary vector).

  • verbose (bool, default=False) – If True, progress bar will be shown for downloading or loading files.

  • force_update (bool, default=False) – If True, always re-download the dataset from HuggingFace Hub, even if it is already present locally. If False, the dataset is downloaded only if it is not yet available locally.

Returns:

data – Depending on the as_frame argument, one of: - Pandas DataFrame with columns: “SMILES”, “label” - tuple of: list of strings (SMILES), NumPy array (labels)

Return type:

pd.DataFrame or tuple(list[str], np.ndarray)

References

Examples

>>> from skfp.datasets.moleculeace import load_chembl235_ec50
>>> dataset = load_chembl235_ec50()
>>> dataset  
(['CC(/C=C/C(F)=C(/C)c1cc(C(C)(C)C)cc(C(C)(C)C)c1OCC(F)(F)F)=C\C(=O)O, ..., 'O=C(O)Cc1cc(Br)c(Oc2cc(I)c(O)c(I)c2)c(I)c1'], \
array([-1.324, ..., -2.477]))

>>> dataset = load_chembl235_ec50(as_frame=True)
>>> dataset.head() 
                                              SMILES      EC50
0  CC(/C=C/C(F)=C(/C)c1cc(C(C)(C)C)cc(C(C)(C)C)c1... -1.324282
1  CCCOc1c(/C(C)=C\C=C\C(C)=C\C(=O)O)cc(C(C)C)cc1... -1.343409
2  C/C(=C/C=C/C(C)=C/C(=O)O)c1cc(-c2cccs2)cc(C(C)... -0.993436
3  CCC(Cc1ccc(OC)c(C(=O)NCc2ccc(OCCc3ccccc3)cc2)c... -3.477121
4  CCCCC(Cc1ccc(OC)c(C(=O)NCc2ccc(C(F)(F)F)cc2)c1... -3.397940