Protein Cofolding

Protein cofolding workflow - predict protein-protein and protein-ligand complexes.

CofoldingScores `dataclass`

CofoldingScores(
    ptm: float | None = None,
    iptm: float | None = None,
    avg_lddt: float | None = None,
    confidence_score: float | None = None,
)

Confidence scores for a cofolding prediction.

Parameters:

Name	Type	Description	Default
`ptm`	`float \| None`	Predicted TM-score, overall structure confidence (0-1, higher is better).	`None`
`iptm`	`float \| None`	Interface pTM, inter-chain packing confidence (0-1, higher is better).	`None`
`avg_lddt`	`float \| None`	Mean per-residue pLDDT, local atomic accuracy (0-1, higher is better).	`None`
`confidence_score`	`float \| None`	Overall aggregate confidence in the prediction (0-1, higher is better).	`None`

AffinityScore `dataclass`

AffinityScore(
    pred_value: float | None = None,
    pred_value1: float | None = None,
    pred_value2: float | None = None,
    probability_binary: float | None = None,
    probability_binary1: float | None = None,
    probability_binary2: float | None = None,
    binding_confidence: float | None = None,
    optimization_score: float | None = None,
)

Predicted binding affinity scores.

Every field is optional; which ones a given run populates depends on the cofolding model. In current runs Boltz-2 fills the pred_value and probability_binary fields while Boltz-2.1 fills binding_confidence and optimization_score, but the schema does not guarantee this split.

Parameters:

Name	Type	Description	Default
`pred_value`	`float \| None`	Predicted pIC50, -log10(IC50 in M); higher means stronger binding (ensemble average of the two affinity heads).	`None`
`pred_value1`	`float \| None`	Predicted pIC50 from affinity head 1.	`None`
`pred_value2`	`float \| None`	Predicted pIC50 from affinity head 2.	`None`
`probability_binary`	`float \| None`	Predicted probability (0-1) that the ligand binds its target; higher is better (ensemble average of the two affinity heads).	`None`
`probability_binary1`	`float \| None`	Binding probability (0-1) from affinity head 1.	`None`
`probability_binary2`	`float \| None`	Binding probability (0-1) from affinity head 2.	`None`
`binding_confidence`	`float \| None`	Predicted probability (0-1, higher is better) that the molecule or binder is a true binder rather than a decoy. Primary metric for hit discovery (computed when binding is requested).	`None`
`optimization_score`	`float \| None`	Binding-strength ranking derived from the model's predicted log(IC50) affinity; higher means stronger predicted binding. Use to rank-order likely binders during lead optimization (computed when binding is requested).	`None`

CofoldingResult `dataclass`

CofoldingResult(
    scores: CofoldingScores | None = None,
    affinity_score: AffinityScore | None = None,
    strain: float | None = None,
    mmgbsa_score: float | None = None,
    posebusters_valid: bool | None = None,
    lddt: list[float] | None = None,
    pose_uuid: str | None = None,
    predicted_structure_uuid: str | None = None,
    predicted_refined_structure_uuid: str | None = None,
)

Single cofolding prediction result.

Parameters:

Name	Type	Description	Default
`scores`	`CofoldingScores \| None`	Confidence scores for the prediction.	`None`
`affinity_score`	`AffinityScore \| None`	Predicted binding affinity (if computed).	`None`
`strain`	`float \| None`	Ligand strain energy (if computed).	`None`
`mmgbsa_score`	`float \| None`	MM/GBSA binding free energy estimate in kcal/mol (if computed).	`None`
`posebusters_valid`	`bool \| None`	Whether the pose passes PoseBusters validation.	`None`
`lddt`	`list[float] \| None`	Per-residue LDDT confidence scores.	`None`
`pose_uuid`	`str \| None`	UUID of the pose.	`None`
`predicted_structure_uuid`	`str \| None`	UUID of the predicted structure.	`None`
`predicted_refined_structure_uuid`	`str \| None`	UUID of the refined structure (if refinement was run).	`None`

ProteinCofoldingResult `dataclass`

ProteinCofoldingResult(
    workflow_data: dict[str, Any],
    workflow_type: str,
    workflow_uuid: str,
    complete: bool = True,
)

Bases: WorkflowResult

Result from a protein-cofolding workflow.

scores `property`

scores: CofoldingScores | None

Confidence scores for the primary prediction.

affinity_score `property`

affinity_score: AffinityScore | None

Predicted binding affinity for the primary prediction.

strain `property`

strain: float | None

Ligand strain energy for the primary prediction.

posebusters_valid `property`

posebusters_valid: bool | None

Whether the primary pose passes PoseBusters validation.

lddt `property`

lddt: list[float] | None

Per-residue LDDT confidence scores for the primary prediction.

predicted_structure_uuid `property`

predicted_structure_uuid: str | None

UUID of the predicted structure.

predicted_refined_structure_uuid `property`

predicted_refined_structure_uuid: str | None

UUID of the refined structure (if pose refinement was enabled).

predictions `property`

predictions: list[CofoldingResult]

All cofolding predictions.

cofolding_results `property`

cofolding_results: list[CofoldingResult]

Alias for predictions (matches API response field name).

messages `property`

messages: list[Message]

Any messages or warnings from the workflow (e.g., stereochemistry issues).

get_predicted_structure

get_predicted_structure() -> Protein | None

Fetch the predicted structure as a Protein object.

.. note:: Makes one API call on first access. Results are cached. Call clear_cache() to refresh.

get_refined_structure

get_refined_structure() -> Protein | None

Fetch the refined structure as a Protein object (if available).

.. note:: Makes one API call on first access. Results are cached. Call clear_cache() to refresh.

submit_protein_cofolding_workflow

submit_protein_cofolding_workflow(
    initial_protein_sequences: list[str] | None = None,
    initial_dna_sequences: list[str] | None = None,
    initial_rna_sequences: list[str] | None = None,
    initial_smiles_list: list[str] | None = None,
    ligand_binding_affinity_index: int | None = None,
    use_msa_server: bool = True,
    use_potentials: bool = False,
    contact_constraints: list[ContactConstraint] | None = None,
    pocket_constraints: list[PocketConstraint] | None = None,
    templates: list[CofoldingTemplate] | None = None,
    num_samples: int | None = None,
    compute_strain: bool = False,
    do_pose_refinement: bool = False,
    name: str = "Protein-Ligand Co-Folding",
    model: CofoldingModel | str = CofoldingModel.BOLTZ_2,
    folder_uuid: str | None = None,
    folder: Folder | None = None,
    max_credits: int | None = None,
    webhook_url: str | None = None,
    is_draft: bool = False,
) -> Workflow

Submits a protein-cofolding workflow to the API.

Predicts the 3D structure of protein-protein, protein-ligand, protein-DNA, protein-RNA, or other biomolecular complexes.

See examples/protein_cofolding_with_constraints.py for a worked example of using ConstraintTarget, ContactConstraint, and PocketConstraint (Boltz models only).

Parameters:

Name	Type	Description	Default
`initial_protein_sequences`	`list[str] \| None`	Protein sequences to be cofolded.	`None`
`initial_dna_sequences`	`list[str] \| None`	DNA sequences to be cofolded.	`None`
`initial_rna_sequences`	`list[str] \| None`	RNA sequences to be cofolded.	`None`
`initial_smiles_list`	`list[str] \| None`	List of SMILES strings for the ligands to be cofolded with.	`None`
`ligand_binding_affinity_index`	`int \| None`	Index of the ligand for which to compute the binding affinity.	`None`
`use_msa_server`	`bool`	Whether to use the MSA server for the computation.	`True`
`use_potentials`	`bool`	Whether to use potentials (inference-time steering) with Boltz.	`False`
`contact_constraints`	`list[ContactConstraint] \| None`	Boltz contact constraints between two tokens.	`None`
`pocket_constraints`	`list[PocketConstraint] \| None`	Boltz pocket constraints between a binder and contact tokens.	`None`
`templates`	`list[CofoldingTemplate] \| None`	Structural templates to guide prediction (Boltz-2/2.1 or OpenFold-3 only).	`None`
`num_samples`	`int \| None`	Number of diffusion samples to generate. If None, uses the model default.	`None`
`compute_strain`	`bool`	Whether to compute the strain of the pose. Requires do_pose_refinement. (if `pose_refinement` is enabled).	`False`
`do_pose_refinement`	`bool`	Whether to optimize non-rotatable bonds in output poses.	`False`
`name`	`str`	Name of the workflow.	`'Protein-Ligand Co-Folding'`
`model`	`CofoldingModel \| str`	Model to use for the computation. Boltz-2.1 runs via Boltz's hosted API (slower than the locally-run models) and reports a different set of affinity metrics than Boltz-2 (see `AffinityScore`).	`BOLTZ_2`
`folder_uuid`	`str \| None`	UUID of the folder to store the workflow in.	`None`
`folder`	`Folder \| None`	Folder object to store the workflow in.	`None`
`max_credits`	`int \| None`	Maximum number of credits to use for the workflow.	`None`
`webhook_url`	`str \| None`	URL that Rowan will POST to when the workflow completes.	`None`
`is_draft`	`bool`	If True, submit the workflow as a draft without starting execution.	`False`

Returns:

Type	Description
`Workflow`	Workflow object representing the submitted workflow.

Raises:

Type	Description
`ValueError`	If no protein, DNA, or RNA sequences are provided.
`requests.HTTPError`	if the request to the API fails.

Protein Cofolding

CofoldingScores dataclass

AffinityScore dataclass

CofoldingResult dataclass

ProteinCofoldingResult dataclass

scores property

affinity_score property

strain property

posebusters_valid property

lddt property

predicted_structure_uuid property

predicted_refined_structure_uuid property

predictions property

cofolding_results property

messages property

get_predicted_structure

get_refined_structure

submit_protein_cofolding_workflow

CofoldingScores `dataclass`

AffinityScore `dataclass`

CofoldingResult `dataclass`

ProteinCofoldingResult `dataclass`

scores `property`

affinity_score `property`

strain `property`

posebusters_valid `property`

lddt `property`

predicted_structure_uuid `property`

predicted_refined_structure_uuid `property`

predictions `property`

cofolding_results `property`

messages `property`