openprotein.models#

Unified access to models on the OpenProtein AI platform. Use them to work at a lower level to craft your own workflows.

Note that the Models API is a WIP interface, but we are working hard on bringing all models here for a consistent and simple developer experience.

Interface#

class openprotein.models.ModelsAPI(session)[source]#

API-like accessor that groups all available protein models.

This class is attached to the main APISession and provides a single, consistent entry point for accessing various models.

Parameters:

session (APISession)

Models#

RFdiffusion#

class openprotein.models.foundation.rfdiffusion.RFdiffusionModel(session, model_id='rfdiffusion')[source]#

RFdiffusion model for generating de novo protein structures.

This model supports functionalities like unconditional design, scaffolding, and binder design.

Parameters:
get_metadata()[source]#

Get model metadata for this model.

Returns:

The metadata associated with this model.

Return type:

ModelMetadata

generate(n=1, structure_file=None, contigs=None, inpaint_seq=None, provide_seq=None, hotspot=None, T=None, partial_T=None, use_active_site_model=None, use_beta_model=None, symmetry=None, order=None, add_potential=None, scaffold_target_structure_file=None, scaffold_target_use_struct=False, **kwargs)[source]#

Run a protein structure generate job using RFdiffusion.

Parameters:

  • n (int, optional) – The number of unique design trajectories to run (default is 1).

  • structure_file (BinaryIO, optional) – An input PDB file (as a file-like object) used for inpainting or other guided design tasks where parts of an existing structure are provided.

  • contigs (int, str, optional) – Defines the lengths and connectivity of chain segments for the desired structure, specified in RFdiffusion’s contig string format. Required for most design tasks. Example: 150, ‘10-20/A100-110/10-20’ for a binder design.

  • inpaint_seq (str, optional) – A string specifying the regions in the input structure to mask for in-painting. Example: ‘A1-A10/A30-40’.

  • provide_seq (str, optional) – A string specifying which segments of the contig have a provided sequence. Example: ‘A1-A10/A30-40’.

  • hotspot (str, optional) – A string specifying hotspot residues to constrain during design, typically for functional sites. Example: ‘A10,A12,A14’.

  • T (int, optional) – The number of timesteps for the diffusion process.

  • partial_T (int, optional) – The number of timesteps for partial diffusion.

  • use_active_site_model (bool, optional) – If True, uses the active site model checkpoint, which has been finetuned to better keep very small motifs in place in the output for motif scaffolding (default is False).

  • use_beta_model (bool, optional) – If True, uses the complex beta model checkpoint, which generates a greater diversity of topologies but has not been extensively experimentally validated (default is False).

  • symmetry ({"cyclic", "dihedral", "tetrahedral"}, optional) – The type of symmetry to apply to the design.

  • order (int, optional) – The order of the symmetry (e.g., 3 for C3 or D3 symmetry). Must be provided if symmetry is set.

  • add_potential (bool, optional) – A flag to toggle an additional potential to guide the design. This defaults to true in the case of symmetric design.

  • scaffold_target_structure_file (str, bytes, BinaryIO, optional) – A PDB file (which can be the text string or bytes or the file-like object) containing a scaffold structure to be used as a structural guide. It could also be used as a target when doing scaffold guided binder design with scaffold_target_use_struct.

  • scaffold_target_use_struct (bool, optional) – Whether or not to use the provided scaffold structure as a target. Otherwise, it is used only as a topology guide.

  • **kwargs (dict) – Additional keyword args that are passed directly to the rfdiffusion inference script. Overwrites any preceding options.

Returns:

A future object that can be used to retrieve the results of the design job upon completion.

Return type:

RFdiffusionFuture

predict(n=1, structure_file=None, contigs=None, inpaint_seq=None, provide_seq=None, hotspot=None, T=None, partial_T=None, use_active_site_model=None, use_beta_model=None, symmetry=None, order=None, add_potential=None, scaffold_target_structure_file=None, scaffold_target_use_struct=False, **kwargs)#

Run a protein structure generate job using RFdiffusion.

Parameters:

  • n (int, optional) – The number of unique design trajectories to run (default is 1).

  • structure_file (BinaryIO, optional) – An input PDB file (as a file-like object) used for inpainting or other guided design tasks where parts of an existing structure are provided.

  • contigs (int, str, optional) – Defines the lengths and connectivity of chain segments for the desired structure, specified in RFdiffusion’s contig string format. Required for most design tasks. Example: 150, ‘10-20/A100-110/10-20’ for a binder design.

  • inpaint_seq (str, optional) – A string specifying the regions in the input structure to mask for in-painting. Example: ‘A1-A10/A30-40’.

  • provide_seq (str, optional) – A string specifying which segments of the contig have a provided sequence. Example: ‘A1-A10/A30-40’.

  • hotspot (str, optional) – A string specifying hotspot residues to constrain during design, typically for functional sites. Example: ‘A10,A12,A14’.

  • T (int, optional) – The number of timesteps for the diffusion process.

  • partial_T (int, optional) – The number of timesteps for partial diffusion.

  • use_active_site_model (bool, optional) – If True, uses the active site model checkpoint, which has been finetuned to better keep very small motifs in place in the output for motif scaffolding (default is False).

  • use_beta_model (bool, optional) – If True, uses the complex beta model checkpoint, which generates a greater diversity of topologies but has not been extensively experimentally validated (default is False).

  • symmetry ({"cyclic", "dihedral", "tetrahedral"}, optional) – The type of symmetry to apply to the design.

  • order (int, optional) – The order of the symmetry (e.g., 3 for C3 or D3 symmetry). Must be provided if symmetry is set.

  • add_potential (bool, optional) – A flag to toggle an additional potential to guide the design. This defaults to true in the case of symmetric design.

  • scaffold_target_structure_file (str, bytes, BinaryIO, optional) – A PDB file (which can be the text string or bytes or the file-like object) containing a scaffold structure to be used as a structural guide. It could also be used as a target when doing scaffold guided binder design with scaffold_target_use_struct.

  • scaffold_target_use_struct (bool, optional) – Whether or not to use the provided scaffold structure as a target. Otherwise, it is used only as a topology guide.

  • **kwargs (dict) – Additional keyword args that are passed directly to the rfdiffusion inference script. Overwrites any preceding options.

Returns:

A future object that can be used to retrieve the results of the design job upon completion.

Return type:

RFdiffusionFuture

class openprotein.models.foundation.rfdiffusion.RFdiffusionFuture(session, job)[source]#

Future for handling the results of an RFdiffusion job.

Parameters:
get_pdb(replicate=0)[source]#

Retrieve the PDB file for a specific design.

Parameters:

  • design_index (int) – The 0-based index of the design to retrieve.

  • replicate (int)

Returns:

The content of the PDB file as a string.

Return type:

str

get(replicate=0)[source]#

Default result accessor, returns the first PDB.

Parameters:

replicate (int)

cancelled()#

Check if the job has been cancelled.

Returns:

True if the job is cancelled, False otherwise.

Return type:

bool

property created_date: datetime#

The creation timestamp of the job.

done()#

Check if the job has completed.

Returns:

True if the job is done, False otherwise.

Return type:

bool

property end_date: datetime | None#

The end timestamp of the job.

property id: str#

The unique identifier of the job.

property job_id: str#

The unique identifier of the job.

property job_type: str#

The type of the job.

property progress_counter: int#

The progress counter of the job.

refresh()#

Refresh the job status and internal job object.

property start_date: datetime | None#

The start timestamp of the job.

property status: JobStatus#

The current status of the job.

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

Wait for the job to complete, then fetch results.

Parameters:

  • interval (int, optional) – Time in seconds between polling. Defaults to config.POLLING_INTERVAL.

  • timeout (int | None, optional) – Maximum time in seconds to wait. Defaults to None.

  • verbose (bool, optional) – Verbosity flag. Defaults to False.

Returns:

The results of the job.

Return type:

Any

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

Wait for the job to complete.

Parameters:

  • interval (float, optional) – Time in seconds between polling. Defaults to config.POLLING_INTERVAL.

  • timeout (int, optional) – Maximum time in seconds to wait. Defaults to None.

  • verbose (bool, optional) – Verbosity flag. Defaults to False.

Returns:

True if the job completed successfully.

Return type:

bool

Notes

This method does not fetch the job results, unlike wait().