load_chembl234_ki#

skfp.datasets.moleculeace.load_chembl234_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 ChEMBL234 Ki dataset.

The task is to predict the inhibitor constant (Ki) of molecules against the D(3) dopamine receptor target [1] [2].

Tasks

1

Task type

regression

Total samples

3657

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_chembl234_ki
>>> dataset = load_chembl234_ki()
>>> dataset  
(['CN1C2CCC1CC(OC(c1ccc(F)cc1)c1ccc(F)cc1)C2, ..., 'CNc1cc(OC)c(C(=O)N[C@@H]2CCN(Cc3ccccc3)[C@@H]2C)cc1Cl'], \
array([-2.161, ..., -0.07188]))

>>> dataset = load_chembl234_ki(as_frame=True)
>>> dataset.head() 
                                              SMILES        Ki
0          CN1C2CCC1CC(OC(c1ccc(F)cc1)c1ccc(F)cc1)C2 -2.161368
1  O=C(NCCCN1CCN(c2cccc(Cl)c2Cl)CC1)c1cccc2c1-c1c... -1.556303
2         c1ccc(N2CCN(CCCn3c4ccccc4c4ccccc43)CC2)cc1 -3.383815
3             Oc1nc2c(N3CCN(Cc4ccccc4)CC3)cccc2[nH]1 -1.752048
4  O=C(NCCCN1CCN(c2ccccc2)CC1)c1cccc2c1-c1ccccc1C2=O -2.633468