haddock.modules.analysis.caprieval.capri module

CAPRI module.

class haddock.modules.analysis.caprieval.capri.CAPRI(identificator: int, model: PDBFile | Path, path: Path, reference: PDBFile | Path, params: MutableMapping[str, Any])

Bases: object

CAPRI class.

static add_chain_from_segid(pdb_path: PDBFile | Path) → Path

Replace the chainID with the segID.

Parameters:

pdb_path (PosixPath or haddock.libs.libontology.PDBFile) – PDB file to be replaced

calc_dockq() → None

Calculate the DockQ metric.

calc_fnat(cutoff: float = 5.0) → None

Calculate the frequency of native contacts.

Parameters:

cutoff (float) – The cutoff distance for the intermolecular contacts.

calc_global_rmsd() → None

Calculate the full structure RMSD.

calc_ilrmsd(cutoff: float = 10.0) → None

Calculate the Interface Ligand RMSD.

Parameters:

cutoff (float) – The cutoff distance for the intermolecular contacts.

calc_irmsd(cutoff: float = 5.0) → None

Calculate the I-RMSD.

Parameters:

cutoff (float) – The cutoff distance for the intermolecular contacts.

calc_lrmsd() → None

Calculate the L-RMSD.

has_cluster_info() → bool

Check wether this object contains cluster information.

Returns:

bool – True if this object contains cluster information.

static identify_interface(pdb_f: PDBFile | Path, cutoff: float = 5.0) → dict[str, list[int]]

Identify the interface.

Parameters:

• pdb_f (PosixPath or haddock.libs.libontology.PDBFile) – PDB file of the model to have its atoms identified

• cutoff (float, optional) – Cutoff distance for the interface identification.

Returns:

interface_resdic (dict[str, list[int]]) – Dictionary holding list of interface residues ids for each chains.

run() → None | CAPRI

Get the CAPRI metrics.

exception haddock.modules.analysis.caprieval.capri.CAPRIError(msg: str = '')

Bases: Exception

Raised when something goes wrong with the CAPRI class.

haddock.modules.analysis.caprieval.capri.calc_stats(data: list) → tuple[float, float]

Calculate the mean and stdev.

Parameters:

data (list) – List of values.

Returns:

• mean (float) – Mean of the values.

• stdev (float) – Standard deviation of the values.

haddock.modules.analysis.caprieval.capri.capri_cluster_analysis(capri_list: Iterable[CAPRI], model_list: Iterable[PDBFile], output_fname: str | Path, clt_threshold: int, sort_key: str, sort_ascending: bool, path: str | Path) → None

Consider the cluster results for the CAPRI evaluation.

haddock.modules.analysis.caprieval.capri.dump_weights(order: int) → None

haddock.modules.analysis.caprieval.capri.extract_data_from_capri_class(capri_objects: list[CAPRI], sort_key: str, sort_ascending: bool, output_fname: Path) → dict[int, dict[str, Any]] | None

Extracts data attributes from a list of CAPRI objects into a structured dictionary, optionally sorts the data based on a specified key, and writes the sorted data to a file.

Parameters:

• capri_objects (list[CAPRI]) – List of CAPRI objects containing data attributes to be extracted.

• sort_key (str) – Key by which to sort the extracted data. Must correspond to a valid attribute in the CAPRI object (e.g., ‘score’, ‘irmsd’).

• sort_ascending (bool) – If True, sorts the data in ascending order based on the sort_key; if False, sorts in descending order.

• output_fname (Path) – Path to the output file where the sorted data will be written.

Returns:

Optional[dict[int, ParamDict]] –

The sorted and structured data dictionary if

successful, None if no data was processed.

Raises:

(Include any specific exceptions the function may raise) –

haddock.modules.analysis.caprieval.capri.get_previous_cns_step(sel_steps: list, st_order: int) → str | None

Get the previous CNS step.

Parameters:

run_path (Path) – Path to the run folder.

Returns:

cns_step (str) – Name of the CNS step.

haddock.modules.analysis.caprieval.capri.load_contacts(pdb_f: Path | PDBFile, cutoff: float = 5.0, numbering_dic: dict[str, dict[int, int]] | None = None, model2ref_chain_dict: dict[str, str] | None = None) → set[tuple]

Load residue-based contacts.

Parameters:

• pdb_f (PosixPath or haddock.libs.libontology.PDBFile) – PDB file of the model to have its atoms identified

• cutoff (float, optional) – Cutoff distance for the interface identification.

Returns:

set(con_list) (set) – set of unique contacts

haddock.modules.analysis.caprieval.capri.rank_according_to_score(data: dict[int, dict[str, Any]], sort_key: str, sort_ascending: bool) → dict[int, dict[str, Any]]

Ranks a dictionary of data based on a specified sort key and sort order, and assigns a rank to each entry based on its ‘score’ attribute.

Parameters:

• data (dict[int, ParamDict]) – Dictionary where each key is an index and each value is a ParamDict containing data attributes.

• sort_key (str) – Key by which to sort the data within the ParamDict. Must correspond to a valid attribute in ParamDict.

• sort_ascending (bool) – If True, sorts the data in ascending order based on the sort_key; if False, sorts in descending order.

Returns:

dict[int, ParamDict] –

A new dictionary where entries are sorted according

to the sort_key and optionally sorted order. Each entry also includes a ‘caprieval_rank’ attribute indicating its rank based on the ‘score’.

haddock.modules.analysis.caprieval.capri.save_scoring_weights(cns_step: str) → Path

Save the scoring weights in a json file.

Parameters:

cns_step (str) – Name of the CNS step.

Returns:

scoring_params_fname (Path) – Path to the json file.