changes for the release

EAPM/EAPM.py

@@ -95,13 +95,21 @@ def createPlugin():
 
     eapmPlugin.addBlock(epPredBlock)
 
-    from Blocks.testBlock import testBlock  # type: ignore
+    # from Blocks.testBlock import testBlock  # type: ignore
 
-    eapmPlugin.addBlock(testBlock)
+    # eapmPlugin.addBlock(testBlock)
 
-    from Blocks.AnalyseGlideGPX import AnalyseGPXBlock  # type: ignore
+    from Blocks.AnalyseGlide import AnalyseGBlock  # type: ignore
 
-    eapmPlugin.addBlock(AnalyseGPXBlock)
+    eapmPlugin.addBlock(AnalyseGBlock)
+
+    # from Blocks.Rbcavity import rbCavityBlock  # type: ignore
+
+    # eapmPlugin.addBlock(rbCavityBlock)
+
+    # from Blocks.Rbdock import rbDockBlock  # type: ignore
+
+    # eapmPlugin.addBlock(rbDockBlock)
 
     # Add the configs
     from Configs.mafftConfig import mafftExecutableConfig  # type: ignore

EAPM/Include/Blocks/Ahatool.py

@@ -1,7 +1,3 @@
-import datetime
-import os
-import subprocess
-
 from HorusAPI import PluginBlock, PluginVariable, VariableList, VariableTypes
 
 # TODO Add to the documentation
@@ -85,6 +81,10 @@
 
 def initialAction(block: PluginBlock):
 
+    import datetime
+    import os
+    import subprocess
+
     container_name = block.inputs.get("container_name", "bsceapm/ahatool:2.2")
     input_fasta = block.inputs.get("input_fasta", None)
     fasta = os.path.basename(input_fasta)

EAPM/Include/Blocks/AlignPdbEAPM.py

@@ -124,26 +124,30 @@ def initialAlign(block: PluginBlock):
     alignmentMode = block.variables.get("alignment_mode", "aligned")
     referenceResidues = block.variables.get("reference_residues", [])
 
+    import prepare_proteins
+
+    print("Loading PDB files...")
+
+    models = prepare_proteins.proteinModels(inputFolder)
+
     # Parse the chain indexes
     if chainIndexes is not None:
         chainIndexes = [x["chain_index"] for x in chainIndexes]
     else:
         chainIndexes = [0]
 
+    trajectory_chain_indexes = None
     # Parse the trajectory chain indexes
     if trajectoryChainIndexes is not None:
         trajectoryChainIndexes = [x["trajectory_chain_index"] for x in trajectoryChainIndexes]
+        trajectory_chain_indexes = {}
+        for i, model in enumerate(models.models_names):
+            trajectory_chain_indexes[model] = trajectoryChainIndexes[i]
 
     # Parse the reference residues
     if referenceResidues is not None:
         referenceResidues = [x["reference_residues"] for x in referenceResidues]
 
-    import prepare_proteins
-
-    print("Loading PDB files...")
-
-    models = prepare_proteins.proteinModels(inputFolder)
-
     print("Aligning models...")
 
     import subprocess
@@ -163,7 +167,7 @@ def hookSubprocessMafft(command, **kwargs):
             pdbReference,
             outputFolder,
             chain_indexes=chainIndexes,
-            trajectory_chain_indexes=trajectoryChainIndexes,
+            trajectory_chain_indexes=trajectory_chain_indexes,
             aligment_mode=alignmentMode,
             reference_residues=referenceResidues,
             verbose=True,

EAPM/Include/Blocks/AlphaFoldEAPM.py

@@ -2,8 +2,6 @@
 Module containing the AlphaFold block for the EAPM plugin
 """
 
-import os
-
 from HorusAPI import PluginVariable, SlurmBlock, VariableTypes
 
 # ==========================#
@@ -72,6 +70,8 @@ def initialAlphafold(block: SlurmBlock):
         print("Alphafold requires an accelerated partition. Changing to acc_bscls.")
         block.variables["partition"] = "acc_bscls"
 
+    import os
+
     # If folder already exists, raise exception
     if removeExisting and os.path.exists(folderName):
         os.system("rm -rf " + folderName)
@@ -107,6 +107,8 @@ def finalAlhafoldAction(block: SlurmBlock):
 
     resultsFolder = block.extraData["folder_name"]
 
+    import os
+
     output_models_folder = os.path.join(downloaded_path, resultsFolder, "output_models")
 
     block.setOutput(outputModelsVariable.id, output_models_folder)

EAPM/Include/Blocks/AnalyseGlideGPX.py → EAPM/Include/Blocks/AnalyseGlide.py

@@ -1,11 +1,3 @@
-import json
-import os
-import shutil
-
-import bsc_calculations
-import pandas as pd
-import prepare_proteins
-
 from HorusAPI import PluginBlock, PluginVariable, VariableGroup, VariableTypes
 
 # TODO  Configure the inputs correctly
@@ -28,10 +20,16 @@
     defaultValue=None,
 )
 residueProtein = PluginVariable(
-    name="Atom Protein", id="resi_id1", description="atom1", type=VariableTypes.ATOM
+    name="Atom Protein",
+    id="resi_id1",
+    description="Atom of the protein to calculate the distance to",
+    type=VariableTypes.ATOM,
 )
 residueLigand = PluginVariable(
-    name="Atom Ligand", id="resi_id2", description="atom2", type=VariableTypes.ATOM
+    name="Atom Ligand",
+    id="resi_id2",
+    description="Atom of the ligand to calculate the distance to",
+    type=VariableTypes.ATOM,
 )
 resNameProt = PluginVariable(
     name="Protein residue name",
@@ -40,10 +38,10 @@
     type=VariableTypes.STRING,
     defaultValue="CYS",
 )
-resNameLig = PluginVariable(
-    name="Ligand residue name",
-    id="res_name_lig",
-    description="The ligand residue name",
+atomNameProt = PluginVariable(
+    name="Protein atomname",
+    id="atom_name_prot",
+    description="The protein atom name",
     type=VariableTypes.STRING,
     defaultValue="SG",
 )
@@ -54,12 +52,26 @@
     type=VariableTypes.STRING,
     defaultValue="GSH",
 )
+atomNameLig = PluginVariable(
+    name="Ligand atom name",
+    id="atom_name_ligand",
+    description="The atom name of the ligand",
+    type=VariableTypes.STRING,
+    defaultValue="S1",
+)
 
 stringGroup = VariableGroup(
     id="string_input",
     name="Input String",
     description="The input are in string",
-    variables=[conservedResidues, glideOutputVariable, resNameProt, resNameLig, ligandName],
+    variables=[
+        conservedResidues,
+        glideOutputVariable,
+        resNameProt,
+        atomNameProt,
+        ligandName,
+        atomNameLig,
+    ],
 )
 atomGroup = VariableGroup(
     id="atom_input",
@@ -70,12 +82,18 @@
 
 # Output variables
 outputModelsVariable = PluginVariable(
-    id="models",
-    name="Alphafold models",
-    description="The output models",
+    id="best_poses",
+    name="Best poses",
+    description="The best poses from the analysis",
     type=VariableTypes.FOLDER,
 )
-
+analyseGlideOutputVariable = PluginVariable(
+    id="glide_results_output",
+    name="Glide results output",
+    description="Output results of the Glide analysis",
+    type=VariableTypes.CUSTOM,
+    allowedValues=["glide_output"],
+)
 
 # ==========================#
 # Variable
@@ -87,54 +105,85 @@
     type=VariableTypes.STRING,
     defaultValue="SG_S",
 )
+removePreviousVar = PluginVariable(
+    name="Remove previous models",
+    id="remove_previous",
+    description="Remove previous",
+    type=VariableTypes.BOOLEAN,
+    defaultValue=False,
+)
+separatorVar = PluginVariable(
+    name="Separator",
+    id="separator",
+    description="The separator",
+    type=VariableTypes.STRING,
+    defaultValue="@",
+)
 
 
 def finalAction(block: PluginBlock):
 
+    import prepare_proteins
+
     bsc_result = block.inputs.get(glideOutputVariable.id, None)
     folder_to_analyse = bsc_result["dock_folder"]
     model_folder = bsc_result["model_folder"]
 
     conserved_indexes = block.inputs.get(conservedResidues.id, None)
 
     metrics = block.variables.get("metrics", "SG_S")
+    remove_previous = block.variables.get("remove_previous", False)
+    separator = block.variables.get("separator", "@")
 
     if block.selectedInputGroup == stringGroup.id:
         res_name_prot = block.inputs.get(resNameProt.id, "CYS")
-        res_name_lig = block.inputs.get(resNameLig.id, "SG")
+        atom_name_prot = block.inputs.get(atomNameProt.id, "SG")
         ligand_name = block.inputs.get(ligandName.id, "GSH")
+        atom_name_lig = block.inputs.get(atomNameLig.id, "S1")
     else:
         residue_protein = block.inputs.get(residueProtein.id, None)
+        res_name_prot = residue_protein["auth_comp_id"]
+        atom_name_prot = residue_protein["auth_atom_id"]
         residue_ligand = block.inputs.get(residueLigand.id, None)
+        ligand_name = residue_ligand["auth_comp_id"]
+        atom_name_lig = residue_ligand["auth_atom_id"]
+        metrics = f"{atom_name_prot}_{atom_name_lig}"
 
     models = prepare_proteins.proteinModels(model_folder)
 
+    if conserved_indexes is None:
+        raise ValueError("Conserved residues must be provided")
+    if not isinstance(conserved_indexes, dict):
+        try:
+            conserved_indexes = int(conserved_indexes)
+        except ValueError:
+            raise ValueError("Conserved indexes must be an integer or a dictionary of integers")
+        conserved_indexes_f = {}
+        for model in models:
+            conserved_indexes_f[model] = [conserved_indexes]
+        conserved_indexes = conserved_indexes_f
+
     center_atom = {}  # Create dictionary to store the atom 3-element tuple for each model
     for model in models:  # Iterate the models inside the library
         # Iterate the residues for each Bio.PDB.Structure object
         for r in models.structures[model].get_residues():
             # Check that the residue matches the defined index
-            aa = conserved_indexes[model]
             # for cons_ind in conserved_indexes[model]:
             if r.id[1] in conserved_indexes[model]:
                 # Assert that the residue has the correct residue identity
                 if r.resname == res_name_prot:
                     # Store the corresponsing tuple.
-                    center_atom[model] = (r.get_parent().id, r.id[1], res_name_lig)
+                    center_atom[model] = (r.get_parent().id, r.id[1], atom_name_prot)
                     break
 
-    print(f"center_atom: {center_atom}")
-
     atom_pairs = {}  # Define the dictionary containing the atom pairs for each model
     for model in models:
         atom_pairs[model] = {}
         for ligand in [ligand_name]:
             atom_pairs[model][ligand] = []
-            atom_pairs[model][ligand].append((center_atom[model], "S1"))
+            atom_pairs[model][ligand].append((center_atom[model], atom_name_lig))
 
-    print(f"Atom pairs: {atom_pairs}")
-
-    models.analyseDocking(folder_to_analyse, atom_pairs=atom_pairs)
+    models.analyseDocking(folder_to_analyse, atom_pairs=atom_pairs, separator=separator)
 
     metric_distances = {}  # Define the global dictionary
     metric_distances[metrics] = {}  # Define the metric nested dictionary
@@ -144,24 +193,38 @@ def finalAction(block: PluginBlock):
             # Define the ligand nested dictionary with all the docking distances list
             metric_distances[metrics][model][ligand] = models.getDockingDistances(model, ligand)
 
-    print(f"metric_distances: {metric_distances}")
-
     models.combineDockingDistancesIntoMetrics(metric_distances)
 
-    print(f"models.docking_data: {models.docking_data}")
-
     best_poses = models.getBestDockingPosesIteratively(metric_distances)
 
-    models.extractDockingPoses(best_poses, folder_to_analyse, "best_docking_poses", separator="@")
+    models.extractDockingPoses(
+        best_poses,
+        folder_to_analyse,
+        "best_docking_poses",
+        separator=separator,
+        remove_previous=remove_previous,
+    )
 
     block.setOutput(outputModelsVariable.id, "best_docking_poses")
 
+    glideOutput = {
+        "poses_folder": "best_docking_poses",
+        "models_folder": model_folder,  # "prepared_proteins",
+        "atom_pairs": atom_pairs,
+    }
+    import pickle
+
+    with open("glide_output.pkl", "wb") as f:
+        pickle.dump(glideOutput, f)
+
+    block.setOutput(analyseGlideOutputVariable.id, glideOutput)
+
 
-AnalyseGPXBlock = PluginBlock(
-    name="Analyse Glide GPX",
-    description="To analyse Glide GPX results",
+AnalyseGBlock = PluginBlock(
+    name="Analyse Glide",
+    description="To analyse Glide results",
     action=finalAction,
-    variables=[metricsVar],
-    inputGroups=[stringGroup, atomGroup],
-    outputs=[outputModelsVariable],
+    variables=[metricsVar, removePreviousVar, separatorVar],
+    inputGroups=[atomGroup, stringGroup],
+    outputs=[outputModelsVariable, analyseGlideOutputVariable],
 )

EAPM/Include/Blocks/AnalyseGlideDocking.py

@@ -1,6 +1,3 @@
-import datetime
-import os
-
 from HorusAPI import (
     Extensions,
     PluginBlock,
@@ -133,6 +130,10 @@
 
 
 def analyseDockingAction(block: PluginBlock):
+
+    import datetime
+    import os
+
     if block.selectedInputGroup == "folder_variable_group":
         folder_to_analyse = block.inputs.get("docking_folder", "docking")
         model_folder = block.inputs.get("model_folder", "models")
@@ -391,6 +392,7 @@ def analyseDocking(
     """
 
     import json
+    import os
 
     import pandas as pd
     import prepare_proteins
@@ -529,6 +531,7 @@ def extractDockingPoses(
         Remove all content in the output folder
     """
 
+    import os
     import shutil
 
     # Check the separator is not in model or ligand names