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deeporigin.drug_discovery.docking

This module encapsulates methods to run docking and show docking results on Deep Origin

Attributes

LOCAL_BASE module-attribute 

LOCAL_BASE = home() / '.deeporigin'

Number module-attribute 

Number = float | int

Classes

Docking

Bases: WorkflowStep

class to handle Docking-related tasks within the Complex class.

Objects instantiated here are meant to be used within the Complex class.

Attributes

tool_version class-attribute instance-attribute 
tool_version = '0.4.0'

Functions

get_results 
get_results(
    *, file_type: str = "csv"
) -> DataFrame | None | list[str]

return a list of paths to CSV files that contain the results from docking

run 
run(
    *,
    pocket: Optional[Pocket] = None,
    box_size: Optional[
        tuple[Number, Number, Number]
    ] = None,
    pocket_center: Optional[
        tuple[Number, Number, Number]
    ] = None,
    batch_size: Optional[int] = 32,
    n_workers: Optional[int] = None,
    _output_dir_path: Optional[str] = None,
    use_parallel: bool = True
)

Run bulk docking on Deep Origin. Ligands will be split into batches based on the batch_size argument, and will run in parallel on Deep Origin clusters.

Parameters:

Name Type Description Default
box_size tuple[float, float, float]

box size

 None
pocket_center tuple[float, float, float]

pocket center

 None
batch_size int

batch size. Defaults to 30.

 32
n_workers int

number of workers. Defaults to None.

 None
use_parallel bool

whether to run jobs in parallel. Defaults to True.

 True
show_poses 
show_poses()

show docked ligands with protein in 3D

show_results 
show_results()

show results of bulk Docking run in a table, rendering 2D structures of molecules