load_chembl204_ki#

skfp.datasets.moleculeace.load_chembl204_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 ChEMBL204 Ki dataset.

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

Tasks

1

Task type

regression

Total samples

2754

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_chembl204_ki
>>> dataset = load_chembl204_ki()
>>> dataset  
(['CC(=N)N1CCC(Oc2ccc3nc(CCC(=O)O)n(Cc4ccc5ccc(C(=N)N)cc5c4)c3c2)CC1, ..., 'CCC(=O)N1CCC[C@H]1C(=O)NCc1ccc(C(=N)N)cc1'], \
array([-3.427, ..., -4.146]))

>>> dataset = load_chembl204_ki(as_frame=True)
>>> dataset.head() 
                                              SMILES        Ki
0  CC(=N)N1CCC(Oc2ccc3nc(CCC(=O)O)n(Cc4ccc5ccc(C(... -3.426511
1  CC(=N)N1CCC(Oc2ccc3c(c2)nc(C(C)C)n3Cc2ccc3ccc(... -2.939519
2  CCC(C)c1nc2cc(OC3CCN(C(C)=N)CC3)ccc2n1Cc1ccc2c... -3.361728
3  COC(=O)C(C)CN(c1ccc2c(c1)nc(C)n2Cc1ccc2ccc(C(=... -3.698970
4  CCCCc1nc2cc(OC3CCN(C(C)=N)CC3)ccc2n1Cc1ccc2ccc... -3.301030