get_target_smi_df

get_target_smi_df(target_id: str, *, version: VersionHint | None = None, prefix: Sequence[str] | None = None, refresh: bool = False, standard_relation: str | None = None, standard_type: str | None = None, aggregate: Literal['mean', 'gmean'] | None = 'mean', **kwargs: Any) → pandas.DataFrame[source]

Get bioactivities for compounds against the given target (from get_target_sql()).

Parameters:

  • target_id – ChEMBL identifier for the target. For example, use CHEMBL1867 for the human A2A receptor.

  • version – The version of ChEMBL to use. If not given, uses the latest version.

  • aggregate – The aggregation to use (either “mean” or “gmean” for geometric mean). If none, do not do aggregation.

  • refresh – If true, rebuild the cached file.

  • standard_relation – Relation type filter, applied before aggregation. For example, can be “=”

  • standard_type – Assay type filter, applied before aggregation. For example, can be “IC50”

  • kwargs – Remaining keyword arguments to pass through to get_target_sql()

Returns:

A dataframe

Raises:

ValueError – If an unknown aggregate value is given

Note, this caches the unfiltered, unaggregated data as a SMI file for later reuse.