Mockup protocol

.gitignore

 A0A1B0GTU1-O75152*
-.*~
\ No newline at end of file
+.*~
+.docker-bash-history
+.DS_Store

translate2modelcif.py

@@ -16,6 +16,7 @@ import modelcif
 import modelcif.associated
 import modelcif.dumper
 import modelcif.model
+import modelcif.protocol
 import modelcif.reference
 
 from ost import io
@@ -218,6 +219,69 @@ def _get_audit_authors():
     return ("Foo B", "Bar F")
 
 
+def _get_protocol_steps_and_software(trg_ents):
+    """Create the list of protocol steps with software and parameters used."""
+    protocol = []
+
+    # modelling step
+    step = {
+        "method_type": "modeling",
+        "name": "ma_protocol_step.step_name",
+        "details": "ma_protocol_step.details",
+    }
+    # get input data
+    # Must refer to data already in the JSON, so we try keywords
+    step["input"] = "target_sequences"
+    # get output data
+    # Must refer to existing data, so we try keywords
+    step["output"] = "model"
+    # get software
+    step["software"] = {
+        "name": "ColabFold",
+        "classification": "model building",
+        "description": "software.description",
+        "citation": {
+            "pmid": None,
+            "title": "ColabFold - Making protein folding accessible to all",
+            "journal": "bioRxiv",
+            "volume": None,
+            "page_range": None,
+            "year": 2022,
+            "authors": [
+                "Mirdita M",
+                "Schütze K",
+                "Moriwaki Y",
+                "Heo L",
+                "Ovchinnikov S",
+                "Steinegger M",
+            ],
+            "doi": "10.1101/2021.08.15.456425",
+        },
+        "location": "https://github.com/sokrypton/ColabFold",
+        "type": "package",
+        "version": "software.version",
+    }
+    # get parameters
+    step["software_parameters"] = {}
+    protocol.append(step)
+
+    # model selection step
+    # ToDo [input/ internal]: model selection step on a single model is a bit
+    # silly, how do we get a list of models?
+    step = {
+        "method_type": "model selection",
+        "name": "ma_protocol_step.step_name",
+        "details": "ma_protocol_step.details",
+    }
+    step["input"] = "model"
+    step["output"] = "model"
+    step["software"] = {}
+    step["software_parameters"] = {}
+    protocol.append(step)
+
+    return protocol
+
+
 def _get_title():
     """Get a title for this modelling experiment."""
     # ToDo [input]: Add title
@@ -379,28 +443,9 @@ def _get_scores(data, prfx):
     data.update(scrs_json)
 
 
-def _store_as_modelcif(interaction_name, data_json, ost_ent, file_prfx):
-    """Mix all the data into a ModelCIF file."""
-    print("    generating ModelCIF objects...", end="")
-    pstart = timer()
-    # ToDo [internal]: Get protocol/ software
-    # ToDo [internal]: Get QA metrics
-    # create system to gather all the data
-    system = modelcif.System(
-        title=data_json["title"],
-        id=interaction_name.upper(),
-        model_details=data_json["model_details"],
-    )
-    # create target entities, references, source, asymmetric units & assembly
-    # for source we assume all chains come from the same taxon
-    source = ihm.source.Natural(
-        ncbi_taxonomy_id=data_json["target_entities"][0]["up_ncbi_taxid"],
-        scientific_name=data_json["target_entities"][0]["up_organism"],
-    )
-
-    # create an asymmetric unit and an entity per target sequence
-    asym_units = {}
-    for cif_ent in data_json["target_entities"]:
+def _get_modelcif_entities(target_ents, source, asym_units, system):
+    """Create ModelCIF entities and asymmetric units."""
+    for cif_ent in target_ents:
         # ToDo [input]: Get entity description
         mdlcif_ent = modelcif.Entity(
             cif_ent["pdb_sequence"],
@@ -430,6 +475,31 @@ def _store_as_modelcif(interaction_name, data_json, ost_ent, file_prfx):
         )
         system.target_entities.append(mdlcif_ent)
 
+
+def _store_as_modelcif(interaction_name, data_json, ost_ent, file_prfx):
+    """Mix all the data into a ModelCIF file."""
+    print("    generating ModelCIF objects...", end="")
+    pstart = timer()
+    # ToDo [internal]: Get protocol/ software
+    # create system to gather all the data
+    system = modelcif.System(
+        title=data_json["title"],
+        id=interaction_name.upper(),
+        model_details=data_json["model_details"],
+    )
+    # create target entities, references, source, asymmetric units & assembly
+    # for source we assume all chains come from the same taxon
+    source = ihm.source.Natural(
+        ncbi_taxonomy_id=data_json["target_entities"][0]["up_ncbi_taxid"],
+        scientific_name=data_json["target_entities"][0]["up_organism"],
+    )
+
+    # create an asymmetric unit and an entity per target sequence
+    asym_units = {}
+    _get_modelcif_entities(
+        data_json["target_entities"], source, asym_units, system
+    )
+
     # ToDo [input]: Get Assembly name
     assembly = modelcif.Assembly(
         asym_units.values(), name="ma_struct_assembly_details.assembly_name"
@@ -460,6 +530,56 @@ def _store_as_modelcif(interaction_name, data_json, ost_ent, file_prfx):
     )
     system.model_groups.append(model_group)
 
+    # Add protocol
+    protocol = modelcif.protocol.Protocol()
+    for js_step in data_json["protocol"]:
+        sftwre = None
+        # ToDo [input]: Turn into software group if parameters are available
+        # ToDo [input]: Get software.description
+        # ToDo [input]: Get software.version
+        if js_step["software"]:
+            sftwre = modelcif.Software(
+                js_step["software"]["name"],
+                js_step["software"]["classification"],
+                js_step["software"]["description"],
+                js_step["software"]["location"],
+                js_step["software"]["type"],
+                js_step["software"]["version"],
+                citation=ihm.Citation(
+                    pmid=js_step["software"]["citation"]["pmid"],
+                    title=js_step["software"]["citation"]["title"],
+                    journal=js_step["software"]["citation"]["journal"],
+                    volume=js_step["software"]["citation"]["volume"],
+                    page_range=js_step["software"]["citation"]["page_range"],
+                    year=js_step["software"]["citation"]["year"],
+                    authors=js_step["software"]["citation"]["authors"],
+                    doi=js_step["software"]["citation"]["doi"],
+                ),
+            )
+        if js_step["input"] == "target_sequences":
+            input_data = modelcif.data.DataGroup(system.target_entities)
+        elif js_step["input"] == "model":
+            input_data = model
+        else:
+            raise RuntimeError(f"Unknown protocol input: '{js_step['input']}'")
+        if js_step["output"] == "model":
+            output_data = model
+        else:
+            raise RuntimeError(
+                f"Unknown protocol output: '{js_step['output']}'"
+            )
+        protocol.steps.append(
+            modelcif.protocol.Step(
+                input_data=input_data,
+                output_data=output_data,
+                name=js_step["name"],
+                details=js_step["details"],
+                software=sftwre,
+            )
+        )
+        protocol.steps[-1].method_type = js_step["method_type"]
+    system.protocols.append(protocol)
+
     # write modelcif System to file
     print("    write to disk...", end="", flush=True)
     pstart = timer()
@@ -484,6 +604,7 @@ def _create_model_json(data, pdb_file, up_acs):
     """Create a dictionary (mimicking JSON) that contains all the data."""
 
     data["target_entities"], ost_ent = _get_entities(pdb_file, up_acs)
+    data["protocol"] = _get_protocol_steps_and_software(data["target_entities"])
     return ost_ent