load_chembl237_ec50#

skfp.datasets.moleculeace.load_chembl237_ec50(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False, force_update: bool = False) → DataFrame | tuple[list[str], ndarray]#

Load the ChEMBL237 EC50 dataset.

The task is to predict the half maximal effective concentration (EC50) of molecules against the Kappa-type opioid receptor target [1] [2].

Tasks

1

Task type

regression

Total samples

955

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_chembl237_ec50
>>> dataset = load_chembl237_ec50()
>>> dataset  
(['C=CCN1CC[C@]23c4c5ccc(O)c4O[C@H]2C(=O)CC[C@@]3(O)[C@H]1C5, ..., 'Oc1ccc2c3c1O[C@H]1c4ncc(-c5ccccc5)cc4C[C@@]4(OCCCC5CCCCC5)[C@@H](C2)N(CC2CC2)CC[C@]314'], \
array([-0.9191, ..., -1.538]))

>>> dataset = load_chembl237_ec50(as_frame=True)
>>> dataset.head() 
                                              SMILES      EC50
0  CC[C@H](C)[C@H](NC(=O)[C@H](CCCN=C(N)N)NC(=O)[...  0.130768
1  C=CCN1CC[C@]23c4c5ccc(O)c4O[C@H]2C(=O)CC[C@@]3... -0.919078
2  CN1CC[C@]23c4c5ccc(O)c4O[C@H]2[C@@]24CC[C@@]3(... -1.320146
3  CO[C@@]12CCC3(C[C@H]1[C@@](C)(O)C(C)(C)C)[C@H]... -0.380211
4  Nc1nc2cc3c(cc2s1)C[C@@H]1[C@@H]2CCCC[C@]32CCN1... -0.380211