load_pgp_broccatelli#
- skfp.datasets.tdc.adme.load_pgp_broccatelli(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False) DataFrame | tuple[list[str]] | ndarray #
Load the P-gp (P-glycoprotein) Inhibition dataset.
The task is to predict whether a molecule inhibits the P-glycoprotein. P-glycoprotein (P-gp) is an ABC transporter protein involved in intestinal absorption, drug metabolism, and brain penetration, and its inhibition can seriously alter a drug’s bioavailability and safety [1] [2].
This dataset is a part of “absorption” subset of ADME tasks.
Tasks
1
Task type
classification
Total samples
1218
Recommended split
scaffold
Recommended metric
AUROC
- 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.
- 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