openprotein.api.fold#

Create PDBs of your protein sequences via our folding models!

Note that for AlphaFold2 Models, you will also need to utilize our align. workflow.

Endpoints#

class openprotein.api.fold.FoldAPI[source]#

This class defines a high level interface for accessing the fold API.

esmfold: ESMFoldModel#

alphafold2: AlphaFold2Model#

__init__(session)[source]#

Parameters:: session (APISession)

property af2#: Alias for AlphaFold2

list_models()[source]#

list models available for creating folds of your sequences

Return type:: List[FoldModel]

get_model(model_id)[source]#

Get model by model_id.

FoldModel allows all the usual job manipulation: e.g. making POST and GET requests for this model specifically.

Parameters:: model_id (str) – the model identifier
Returns:: The model
Return type:: FoldModel
Raises:: HTTPError – If the GET request does not succeed.

get_results(job)[source]#

Retrieves the results of a fold job.

Parameters:: job (Job) – The fold job whose results are to be retrieved.
Returns:: An instance of FoldResultFuture
Return type:: FoldResultFuture

Models#

class openprotein.api.fold.ESMFoldModel[source]#

model_id = 'esmfold'#

__init__(session, model_id, metadata=None)[source]#

fold(sequences, num_recycles=1)[source]#

Fold sequences using this model.

Parameters:

sequences (List[bytes]) – sequences to fold
num_recycles (int) – number of times to recycle models

Return type:

FoldResultFuture

get_metadata()#

Get model metadata for this model.

Return type:: ModelMetadata

classmethod get_model()#

property metadata#

class openprotein.api.fold.AlphaFold2Model[source]#

__init__(session, model_id, metadata=None)[source]#

fold(msa, num_recycles=None, num_models=1, num_relax=0)[source]#

Post sequences to alphafold model.

Parameters:

msa (Union[str, MSAFuture]) – msa
num_recycles (int) – number of times to recycle models
num_models (int) – number of models to train - best model will be used
max_msa (Union[str, int]) – maximum number of sequences in the msa to use.
relax_max_iterations (int) – maximum number of iterations
num_relax (int | None)

Returns:

job

Return type:

Job

get_metadata()#

Get model metadata for this model.

Return type:: ModelMetadata

Results#

class openprotein.api.fold.FoldResultFuture[source]#

job_type: Any | None = ['/embeddings/fold']#: Future Job for manipulating results

__init__(session, job, sequences=None, max_workers=10)[source]#

Retrieve results from asynchronous, mapped endpoints. Use max_workers > 0 to enable concurrent retrieval of multiple pages.

Parameters:

session (APISession)
job (Job)

get_item(sequence)[source]#

Get fold results for specified sequence.

Parameters:: sequence (bytes) – sequence to fetch results for
Returns:: fold
Return type:: np.ndarray

classmethod get_job_type()#: Return the job type associated with this Future class.

refresh()#: refresh job status

wait(interval=5, timeout=None, verbose=False)#

Wait for job to complete, then fetch results.

Parameters:

interval (int, optional) – time between polling. Defaults to config.POLLING_INTERVAL.
timeout (int, optional) – max time to wait. Defaults to None.
verbose (bool, optional) – verbosity flag. Defaults to False.

Returns:

results of job

Return type:

results

wait_until_done(interval=5, timeout=None, verbose=False)#

Wait for job to complete. Do not fetch results (unlike wait())

Parameters:

interval (int, optional) – time between polling. Defaults to config.POLLING_INTERVAL.
timeout (int, optional) – max time to wait. Defaults to None.
verbose (bool, optional) – verbosity flag. Defaults to False.

Returns:

results of job

Return type:

results