PocketFinder¶

Find pockets in a Protein using the Deep Origin Pocket Finder.

Creating pockets¶

First, create a protein, for example:

from deeporigin.drug_discovery import Protein, BRD_DATA_DIR

protein = Protein.from_file(BRD_DATA_DIR / "brd.pdb")
protein.remove_water()

Using Pocket Finder¶

Use the PocketFinder class from deeporigin.drug_discovery.pocket_finder to find pockets. PocketFinder supports synchronous and asynchronous execution.

Estimating cost¶

To estimate cost without starting the run, pass quote=True to run() or start(). This populates pf.estimate and leaves the execution in a quoted state.

from deeporigin.drug_discovery import PocketFinder

pf = PocketFinder(protein, pocket_count=1)
pf.run(quote=True)
pf.estimate

When you are ready to proceed, confirm the quoted execution:

pf.confirm()
pockets = pf.get_results()

Synchronous¶

Use run() when you want to submit the execution and wait for the result in the same cell or script.

from deeporigin.drug_discovery import PocketFinder

pf = PocketFinder(protein, pocket_count=1)
pockets = pf.run()

pf.run() returns a list of Pocket objects. You will be charged for each run unless you request a quote first.

Asynchronous¶

For longer runs, or when you want to keep the notebook responsive, submit the execution asynchronously with start():

pf = PocketFinder(protein, pocket_count=5)
pf.start()

pf.wait()
pockets = pf.get_results()

In a notebook, you can use watch() to display progress while the execution is running:

pf = PocketFinder(protein, pocket_count=5)
pf.start()
task = await pf.watch()
pf.wait()
pockets = pf.get_results()

To cancel an asynchronous execution that is queued or running, call cancel():

pf.cancel()

Existing executions¶

You can reconstruct a PocketFinder object from an existing tools execution ID. This is useful when reconnecting to an in-progress run, inspecting estimate or cost, or fetching results in a later session.

pf = PocketFinder.from_id("<executionId>")
pf.sync()
pockets = pf.get_results()

If you already have the execution payload from client.executions.get, use PocketFinder.from_dto(dto) instead.

You can also list previous PocketFinder executions:

executions = PocketFinder.list()
succeeded = PocketFinder.list(status=["Succeeded"])

Using PDB files¶

Create a pocket directly from a PDB file:

from deeporigin.drug_discovery import Pocket

pocket = Pocket.from_pdb_file("path/to/pocket.pdb", name="my_pocket")

Other ways to define a pocket¶

To define pockets from a residue number, a crystal ligand, or a standalone ligand file, see Work with Pockets.

From a result-explorer record ID¶

Load a single pocket by its result-explorer record ID, such as an ID from a previous pocket-finder run or from the platform UI:

from deeporigin.drug_discovery import Pocket

pocket = Pocket.from_id("your-pocket-record-id")

This fetches the record, downloads the pocket PDB file, and returns a Pocket with properties populated from the record. Optionally pass a client if you do not want to use the default:

pocket = Pocket.from_id("your-pocket-record-id", client=my_client)

If no record exists for the given ID, ValueError is raised.

Visualization¶

Inspecting pocket data¶

View pocket properties by simply inspecting the object:

pocket

You should see a table similar to:

    Pocket:
    ╭─────────────────────────┬──────────────╮
    │ Name                    │ pocket_1     │
    ├─────────────────────────┼──────────────┤
    │ Color                   │ red          │
    ├─────────────────────────┼──────────────┤
    │ Volume                  │ 545.0 Å³     │
    ├─────────────────────────┼──────────────┤
    │ Total SASA              │ 1560.474 Å²  │
    ├─────────────────────────┼──────────────┤
    │ Polar SASA              │ 762.11224 Å² │
    ├─────────────────────────┼──────────────┤
    │ Polar/Apolar SASA ratio │ 0.95459515   │
    ├─────────────────────────┼──────────────┤
    │ Hydrophobicity          │ 15.903226    │
    ├─────────────────────────┼──────────────┤
    │ Polarity                │ 17.0         │
    ├─────────────────────────┼──────────────┤
    │ Drugability score       │ 0.83243614   │
    ╰─────────────────────────┴──────────────╯

3D visualization in a protein¶

Pockets can be visualized using:

protein.show(pockets=pockets)

You should see something like: