"""Compute contacts between chains in complexes.
The ``[contactmap]`` module aims at generating heatmaps and chordcharts of
the contacts observed in the input complexes.
If complexes are clustered, the analysis of contacts will be performed
based on all structures from each cluster.
**Heatmaps** are describing the probability of contacts (<5A) between two
residues (both intramolecular and intermolecular).
**Chordcharts** are describing only intermolecular contacts in circles,
connecting with *chords* the two residues that are contacting.
"""
from copy import deepcopy
from pathlib import Path
from haddock.core.defaults import MODULE_DEFAULT_YAML
from haddock.core.typing import Any, FilePath, SupportsRunT
from haddock.modules import BaseHaddockModule
from haddock.modules import get_engine
from haddock.modules.analysis import get_analysis_exec_mode
from haddock.modules.analysis.contactmap.contmap import (
ContactsMap,
ContactsMapJob,
ClusteredContactMap,
get_clusters_sets,
make_contactmap_report,
topX_models,
)
RECIPE_PATH = Path(__file__).resolve().parent
DEFAULT_CONFIG = Path(RECIPE_PATH, MODULE_DEFAULT_YAML)
[docs]
class HaddockModule(BaseHaddockModule):
"""HADDOCK3 module to compute complexes contacts and generate heatmap."""
name = RECIPE_PATH.name
def __init__(
self,
order: int,
path: Path,
*ignore: Any,
init_params: FilePath = DEFAULT_CONFIG,
**everything: Any,
) -> None:
"""Initialize class."""
super().__init__(order, path, init_params)
[docs]
@classmethod
def confirm_installation(cls) -> None:
"""Confirm if contact executable is compiled."""
return
def _run(self) -> None:
"""Execute module."""
# Get the models generated in previous step
if type(self.previous_io) == iter:
_e = "This module cannot come after one that produced an iterable."
self.finish_with_error(_e)
try:
models = self.previous_io.retrieve_models(individualize=True)
except AttributeError as e:
self.finish_with_error(e)
# Obtain clusters
clusters_sets = get_clusters_sets(models)
# Initiate holder of all jobs to be run by the `Scheduler`
contact_jobs: list[SupportsRunT] = []
# Loop over clusters
for clustid, clt_models in clusters_sets.items():
# In case of unclustered models
if clustid is None:
# Obtain subset of top models
top_models = topX_models(clt_models, topX=self.params["topX"])
# Create single model analysis params
single_models_params = deepcopy(self.params)
single_models_params["single_model_analysis"] = True
# Loop over models to analyse
for model in top_models:
modelfname = Path(model.file_name).stem
# Create a job object
contmap_job = ContactsMapJob(
Path(f"Unclustered_contmap_{modelfname}"),
single_models_params,
modelfname,
# Create a contact map object
ContactsMap(
Path(model.rel_path),
Path(f"Unclustered_contmap_{modelfname}"),
single_models_params,
),
)
contact_jobs.append(contmap_job)
# For clustered models
else:
# Create a job object
contmap_job = ContactsMapJob(
Path(f"cluster{clustid}_contmap"),
self.params,
f"Cluster_{clustid}",
# Create a contact map object
ClusteredContactMap(
[Path(model.rel_path) for model in clt_models],
Path(f"cluster{clustid}_contmap"),
self.params,
),
)
contact_jobs.append(contmap_job)
# Find execution engine
exec_mode = get_analysis_exec_mode(self.params["mode"])
Engine = get_engine(exec_mode, self.params)
engine = Engine(contact_jobs)
engine.run()
# Generate report
make_contactmap_report(contact_jobs, "ContactMapReport.html")
# Send models to the next step, no operation is done on them
self.output_models = models
self.export_io_models()