load_chembl214_ki#

skfp.datasets.moleculeace.load_chembl214_ki(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False, force_update: bool = False) → DataFrame | tuple[list[str], ndarray]#

Load the ChEMBL214 Ki dataset.

The task is to predict the inhibitor constant (Ki) of molecules against the 5-hydroxytryptamine receptor 1a target [1] [2].

Tasks

1

Task type

regression

Total samples

3317

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_chembl214_ki
>>> dataset = load_chembl214_ki()
>>> dataset  
(['COc1ccc(NC(=O)c2ccc(-c3ccc(-c4noc(C)n4)cc3C)cc2)cc1N1CCN(C)CC1, ..., 'O=S(=O)(NCCCCCCN1CCN(c2nsc3ccccc23)CC1)c1ccc2ccccc2c1'], \
array([-1.869, ..., -1.863]))

>>> dataset = load_chembl214_ki(as_frame=True)
>>> dataset.head() 
                                              SMILES        Ki
0  COc1ccc(NC(=O)c2ccc(-c3ccc(-c4noc(C)n4)cc3C)cc... -1.869232
1   Nc1cccc(-c2ccc(CCN3CCN(c4cccc5cccnc45)CC3)cc2)n1 -0.477121
2      COc1ccc(NS(=O)(=O)c2ccc(Br)cc2)cc1N1CCN(C)CC1 -2.400002
3  COc1ccc(NS(=O)(=O)c2sc3ccc(Cl)cc3c2C)cc1N1CCN(... -2.700002
4         CN1CCc2cccc3c2[C@H]1Cc1cccc(-c2ccccc2)c1-3 -0.255273