Degree of labelling

manual.md

@@ -407,7 +407,7 @@ If a parameter is `None`, it will not be swept and will use default values.
 - peptide_motif
 - probe_distance_to_epitope
 - probe_steric_hindrance
-- probe_conjugation_efficiency
+- probe_DoL
 - probe_wobble_theta
 - labelling_efficiency
 - defect
@@ -449,7 +449,7 @@ If a parameter is `None`, it will not be swept and will use default values.
 | **probe_fluorophore** | Fluorophore name for emitters (e.g., "AF647") |
 | **probe_paratope** | If probe_model is defined, the paratope defines the anchor point of the probe |
 | **probe_conjugation_target_info** | If probe_model is defined, this dictionary specifies the sites to use as probe emitters |
-| **probe_conjugation_efficiency** | Efficiency of conjugation of emitters (float) |
+| **probe_DoL** | Efficiency of conjugation of emitters (float) |
 | **probe_seconday_epitope** | If probe is secondary, this amino acid sequence defines the epitope on the primary antibody model |
 | **probe_wobble_theta** | Enable probe wobbling (float or None) |
 | **probe_steric_hindrance** | Steric hindrance value or configuration (distance between epitopes) |

src/vlab4mic/analysis/sweep.py

@@ -868,7 +868,7 @@ def probe_parameters_sweep(
     probe_fluorophore: str = None,
     probe_paratope: str = None,
     probe_conjugation_target_info=None,
-    probe_conjugation_efficiency: list[float] = None,
+    probe_DoL: list[float] = None,
     probe_seconday_epitope=None,
     probe_wobbling=None,
     labelling_efficiency: list[float] = None,
@@ -885,7 +885,7 @@ def probe_parameters_sweep(
     probe_fluorophore : str, optional
     probe_paratope : str, optional
     probe_conjugation_target_info : any, optional
-    probe_conjugation_efficiency : list of float, optional
+    probe_DoL : list of float, optional
     probe_seconday_epitope : any, optional
     probe_wobbling : any, optional
     labelling_efficiency : list of float, optional

src/vlab4mic/configs/probes/Antibody.yaml

@@ -26,7 +26,7 @@ conjugation_sites:
       - CA
       residues:
       - LYS
-  efficiency: 1
+  DoL:
 epitope: # for secondary
   target:
     type: Sequence

src/vlab4mic/configs/probes/CCP_heavy_chain_Cterminal.yaml

@@ -22,5 +22,5 @@ conjugation_sites:
   target:
     type:
     value:
-  efficiency:
+  DoL:
 

src/vlab4mic/configs/probes/GFP.yaml

@@ -26,7 +26,7 @@ conjugation_sites:
       - C1
       residues: 
       - CRO
-  efficiency: 1
+  DoL:
 epitope: # for secondary
   target:
     type: 

src/vlab4mic/configs/probes/GFP_w_nanobody.yaml

@@ -28,7 +28,7 @@ conjugation_sites:
       - LYS
       chains: 
       - B
-  efficiency: 1
+  DoL:
 epitope: # for secondary
   target:
     type: 

src/vlab4mic/configs/probes/HIV_capsid_p24_direct.yaml

@@ -22,5 +22,5 @@ conjugation_sites:
   target:
     type:
     value:
-  efficiency:
+  DoL:
 

src/vlab4mic/configs/probes/Linker.yaml

@@ -22,5 +22,5 @@ conjugation_sites:
   target:
     type:
     value:
-  efficiency:
+  DoL:
 

src/vlab4mic/configs/probes/NHS_ester.yaml

@@ -26,5 +26,5 @@ conjugation_sites:
   target:
     type:
     value:
-  efficiency:
+  DoL:
 

src/vlab4mic/configs/probes/NPC_Nup96_Cterminal_direct.yaml

@@ -22,5 +22,5 @@ conjugation_sites:
   target:
     type:
     value:
-  efficiency:
+  DoL:
 

src/vlab4mic/configs/probes/Nanobody.yaml

@@ -26,7 +26,7 @@ conjugation_sites:
       - CA
       residues: 
       - LYS
-  efficiency: 1
+  DoL:
 epitope: # for secondary
   target:
     type: 

src/vlab4mic/configs/probes/SNAP-tag.yaml

@@ -26,7 +26,7 @@ conjugation_sites:
       - CAA
       residues: 
       - OGQ
-  efficiency: 1
+  DoL:
 epitope: # for secondary
   target:
     type: 

src/vlab4mic/configs/probes/_template_.yaml

@@ -21,7 +21,7 @@ conjugation_sites:
   target:
     type:
     value:
-  efficiency:
+  DoL:
   fluorophore:
 epitope: 
   target:

src/vlab4mic/configs/probes/anti-p24_primary_antibody_HIV.yaml

@@ -26,5 +26,5 @@ conjugation_sites:
       - CA
       residues: 
       - LYS
-  efficiency: 0.2
+  DoL:
 

src/vlab4mic/configs/probes/mMaple.yaml

@@ -26,7 +26,7 @@ conjugation_sites:
       - C1
       residues: 
       - PIA
-  efficiency: 1
+  DoL:
 epitope: # for secondary
   target:
     type: 

src/vlab4mic/experiments.py

@@ -934,7 +934,7 @@ def add_probe(
         probe_steric_hindrance=None,
         probe_paratope: str = None,
         probe_conjugation_target_info=None,
-        probe_conjugation_efficiency: float = None,
+        probe_DoL: float = None,
         probe_seconday_epitope=None,
         probe_wobble_theta: float = None,
         labelling_efficiency: float = 1.0,
@@ -972,7 +972,7 @@ def add_probe(
             Paratope identifier or information.
         :param probe_conjugation_target_info : Any, optional
             Information about the conjugation target.
-        :param probe_conjugation_efficiency : float, optional
+        :param probe_DoL : float, optional
             Efficiency of the probe conjugation.
         :param probe_seconday_epitope : Any, optional
             Information about a secondary epitope target.
@@ -1063,10 +1063,13 @@ def add_probe(
             probe_configuration["conjugation_sites"]["target"]["value"] = (
                 probe_conjugation_target_info["value"]
             )
-        if probe_conjugation_efficiency is not None:
-            probe_configuration["conjugation_efficiency"] = (
-                probe_conjugation_efficiency
+        if probe_DoL is not None:
+            print(f"Setting probe DoL to: {probe_DoL}")
+            probe_configuration["conjugation_sites"]["DoL"] = (
+                probe_DoL
             )
+        else:
+            print("Add_probe: Using default probe DoL from template")
         if probe_seconday_epitope is not None:
             probe_configuration["epitope_target_info"] = probe_seconday_epitope
         if probe_wobble_theta is not None:
@@ -1328,7 +1331,7 @@ def generate_virtual_sample(
     probe_fluorophore: str = "AF647",
     probe_paratope: str = None,
     probe_conjugation_target_info=None,
-    probe_conjugation_efficiency: float = None,
+    probe_DoL: float = None,
     probe_seconday_epitope=None,
     probe_wobble_theta=None,
     labelling_efficiency: float = 1.0,
@@ -1381,7 +1384,7 @@ def generate_virtual_sample(
         Sequence of the paratope site for when probe includes a model.
     :param probe_conjugation_target_info : Any, optional
         Information about the probe conjugation target.
-    :param probe_conjugation_efficiency : float, optional
+    :param probe_DoL : float, optional
         Efficiency of conjugation of emitters.
     :param probe_seconday_epitope : str, optional
         Sequence within probe model to be used as epitope for a secondary.
@@ -1421,6 +1424,21 @@ def generate_virtual_sample(
     myexperiment = ExperimentParametrisation()
     if clear_experiment:
         myexperiment.clear_experiment()
+    # select structure
+    if structure_is_path:
+        print(f"Selecting structure from path: {structure}")
+        myexperiment.select_structure(
+            structure_id=structure.split(".")[0], 
+            structure_path=structure,
+            build=True
+        )
+    else:
+        print("Selecting structure from ID:", structure)
+        myexperiment.select_structure(
+            structure_id=structure, 
+            structure_path=None,
+            build=True
+        )
     # load default configuration for probe
     if (primary_probe is not None) and (secondary_probe is not None):
         print("Adding primary and secondary probes")
@@ -1462,9 +1480,9 @@ def generate_virtual_sample(
                 probe_configuration["conjugation_target_info"] = (
                     probe_conjugation_target_info
                 )
-            if probe_conjugation_efficiency is not None:
-                probe_configuration["conjugation_efficiency"] = (
-                    probe_conjugation_efficiency
+            if probe_DoL is not None:
+                probe_configuration["probe_DoL"] = (
+                    probe_DoL
                 )
             if probe_seconday_epitope is not None:
                 probe_configuration["epitope_target_info"] = probe_seconday_epitope
@@ -1478,22 +1496,7 @@ def generate_virtual_sample(
         virtual_sample_template + ".yaml",
     )
     vsample_configuration = load_yaml(virtual_sample_template)
-    myexperiment.configuration_path
-    if structure_is_path:
-        print(f"Selecting structure from path: {structure}")
-        myexperiment.select_structure(
-            structure_id=structure.split(".")[0], 
-            structure_path=structure,
-            build=False
-        )
-    else:
-        print("Selecting structure from ID:", structure)
-        myexperiment.select_structure(
-            structure_id=structure, 
-            structure_path=None,
-            build=False
-        )
-
+    #myexperiment.configuration_path
     if defect and defect_large_cluster and defect_small_cluster:
         myexperiment.defect_eps["eps1"] = defect_small_cluster
         myexperiment.defect_eps["eps2"] = defect_large_cluster
@@ -1518,7 +1521,10 @@ def generate_virtual_sample(
     vsample_configuration["yz_orientations"] = yz_orientations
     vsample_configuration["axial_offset"] = axial_offset
     myexperiment.virtualsample_params = vsample_configuration
-    myexperiment.build(use_locals=True)
+    myexperiment.build(modules=[
+                "particle",
+                "coordinate_field",
+                "imager"], use_locals=True)
     if expansion_factor > 1:
         myexperiment.expand_virtual_sample(factor=expansion_factor)
     # myexperiment.coordinate_field_id = virtual_sample
@@ -1579,7 +1585,7 @@ def image_vsample(
     probe_fluorophore: str = "AF647",
     probe_paratope: str = None,
     probe_conjugation_target_info = None,
-    probe_conjugation_efficiency: float = None,
+    probe_DoL: float = None,
     probe_seconday_epitope = None,
     probe_wobble_theta = None,
     labelling_efficiency: float = 1.0,
@@ -1649,7 +1655,7 @@ def image_vsample(
         Sequence of the paratope site for when probe includes a model.
     :param probe_conjugation_target_info : any, optional
         Information about the probe conjugation target.
-    :param probe_conjugation_efficiency : float, optional
+    :param probe_DoL : float, optional
         Efficiency of conjugation of emitters.
     :param probe_seconday_epitope : str, optional
         Sequence within probe model to be used as epitope for a secondary.
@@ -1710,7 +1716,7 @@ def image_vsample(
             probe_fluorophore=probe_fluorophore,
             probe_paratope=probe_paratope,
             probe_conjugation_target_info=probe_conjugation_target_info,
-            probe_conjugation_efficiency=probe_conjugation_efficiency,
+            probe_DoL=probe_DoL,
             probe_seconday_epitope=probe_seconday_epitope,
             probe_wobble_theta=probe_wobble_theta,
             labelling_efficiency=labelling_efficiency,

src/vlab4mic/generate/labels.py

@@ -52,9 +52,9 @@ def _set_model_params(self, ID=None, format=None, database=None, **kwargs):
         for key, value in kwargs.items():
             self.model[key] = value
 
-    def _set_conjugation_params(self, target: dict, efficiency, **kwargs):
+    def _set_conjugation_params(self, target: dict, DoL=None, **kwargs):
         self.conjugation["target"] = target
-        self.conjugation["efficiency"] = efficiency
+        self.conjugation["DoL"] = DoL
         for key, value in kwargs.items():
             self.conjugation[key] = value
 
@@ -265,10 +265,12 @@ def construct_label(
         label_params["conjugation_sites"]["target"] = kwargs[
             "conjugation_target_info"
         ]
-    if "conjugation_efficiency" in kwargs.keys():
-        label_params["conjugation_sites"]["efficiency"] = kwargs[
-            "conjugation_efficiency"
-        ]
+    #if "probe_DoL" in label_params.keys():
+    #    label_params["conjugation_sites"]["DoL"] = kwargs[
+    #        "probe_DoL"
+    #    ]
+    #else:
+    #    print("No DoL provided, using default value. ########################")
     if "epitope_target_info" in kwargs.keys():
         label_params["epitope"]["target"] = kwargs["epitope_target_info"]
     if "wobble_theta" in label_params.keys():

src/vlab4mic/sweep_generator.py

@@ -537,7 +537,7 @@ def set_sweep_parameters(
             peptide_motif: dict = None,
             probe_distance_to_epitope= None,
             probe_steric_hindrance= None,
-            probe_conjugation_efficiency = None,
+            probe_DoL = None,
             probe_wobble_theta = None,
             labelling_efficiency = None,
             # defects
@@ -568,9 +568,9 @@ def set_sweep_parameters(
             self.set_parameter_values(
                 "probe", "probe_steric_hindrance", values=probe_steric_hindrance
             )
-        if probe_conjugation_efficiency is not None:
+        if probe_DoL is not None:
             self.set_parameter_values(
-                "probe", "probe_conjugation_efficiency", values=probe_conjugation_efficiency
+                "probe", "probe_DoL", values=probe_DoL
             )
         if probe_wobble_theta is not None:
             self.set_parameter_values(
@@ -1345,7 +1345,7 @@ def run_parameter_sweep(
     peptide_motif: dict = None,
     probe_distance_to_epitope = None,
     probe_steric_hindrance = None,
-    probe_conjugation_efficiency = None,
+    probe_DoL = None,
     probe_wobble_theta = None,
     labelling_efficiency = None,
     defect = None,
@@ -1424,7 +1424,7 @@ def run_parameter_sweep(
         - peptide_motif
         - probe_distance_to_epitope
         - probe_steric_hindrance
-        - probe_conjugation_efficiency
+        - probe_DoL
         - probe_wobble_theta
         - labelling_efficiency
         - defect
@@ -1484,7 +1484,7 @@ def run_parameter_sweep(
         peptide_motif=peptide_motif,
         probe_distance_to_epitope=probe_distance_to_epitope,
         probe_steric_hindrance=probe_steric_hindrance,
-        probe_conjugation_efficiency=probe_conjugation_efficiency,
+        probe_DoL=probe_DoL,
         probe_wobble_theta=probe_wobble_theta,
         labelling_efficiency=labelling_efficiency,
         defect=defect,

src/vlab4mic/utils/transform/cif_builder.py

@@ -151,7 +151,13 @@ def indirect_labelling(coords_nomrals, label_data, **kwargs):
         # select randomly, and according to labelling_efficiency
         # the places that will be labelled
         #efficiency = label_data["labelling_efficiency"]
-
+        if label_data["conjugation_sites"]["DoL"] is not None:
+            if label_data["conjugation_sites"]["DoL"] > 0:
+                dol=label_data["conjugation_sites"]["DoL"]
+            else:
+                dol = None
+        else:
+            dol = None
         epitopes, normals = binomial_epitope_sampling(
             epitopes=coords_nomrals["coordinates"],
             p=label_data["labelling_efficiency"],
@@ -178,7 +184,7 @@ def indirect_labelling(coords_nomrals, label_data, **kwargs):
             else:
                 normals_ft_epitopes = [normals, epitopes]
             indirect_realisation, list_reoriented_points_normals = decorate_epitopes_normals(
-                normals_ft_epitopes, label_data["emitters"]
+                normals_ft_epitopes, label_data["emitters"], dol=dol
             )
     else:
         print("No emitters defined in label. Using direct labelling")