load_chembl2147_ki#

skfp.datasets.moleculeace.load_chembl2147_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 ChEMBL2147 Ki dataset.

The task is to predict the inhibitor constant (Ki) of molecules against the Serine/threonine-protein kinase pim-1 target [1] [2].

Tasks

1

Task type

regression

Total samples

1456

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_chembl2147_ki
>>> dataset = load_chembl2147_ki()
>>> dataset  
(['FC(F)(F)c1cccc(-c2nnc3ccc(NC4CCCCC4)cn23)c1, ..., 'NC(=O)c1cc(Cl)c2c(Cl)c(C#CC3CNCCO3)n([C@H]3CCCNC3)c2n1'], \
array([-1.041, ..., 0.04576]))

>>> dataset = load_chembl2147_ki(as_frame=True)
>>> dataset.head() 
                                              SMILES        Ki
0        FC(F)(F)c1cccc(-c2nnc3ccc(NC4CCCCC4)cn23)c1 -1.041393
1         Cc1ccc2[nH]c(=O)c(CC(=O)O)c(-c3ccccc3)c2c1 -3.653213
2            O=C(O)c1cccc(Nc2nc(-c3ccc(O)cc3O)cs2)c1 -3.531479
3       O=C(O)c1cccc2c(-c3ccccc3)c(-c3ccccc3)[nH]c12 -2.740363
4  CCc1ccc(C2C(C(C)=O)=C(O)C(=O)N2CCc2c[nH]c3cccc... -3.322219