fix inference_app.py

inference_app.py

@@ -898,12 +898,12 @@ def predict (input_seq_1, input_msa_1, input_protein_1, input_seq_2,input_msa_2,
     mat = mat.to(device)
     vect = vect.to(device)
     ligand1 = torch.tensor(extract_coordinates_from_pdb(input_protein_1),dtype=torch.float).to(device)
-    receptor1 = torch.tensor(extract_coordinates_from_pdb(input_protein_2),dtype=torch.float).to(device)
+    # receptor1 = torch.tensor(extract_coordinates_from_pdb(input_protein_2),dtype=torch.float).to(device)
     transformed_ligand = torch.matmul(ligand1, mat) + vect
-    transformed_receptor = torch.matmul(receptor1, mat) + vect
+    # transformed_receptor = torch.matmul(receptor1, mat) + vect
     file1 = update_pdb_coordinates_from_tensor(input_protein_1, "holo_ligand.pdb", transformed_ligand)
-    file2 = update_pdb_coordinates_from_tensor(input_protein_2, "holo_receptor.pdb", transformed_receptor)
-    out_pdb = merge_pdb_files(file1,file2,"output.pdb")
+    # file2 = update_pdb_coordinates_from_tensor(input_protein_2, "holo_receptor.pdb", transformed_receptor)
+    out_pdb = merge_pdb_files(file1,input_protein_2,"output.pdb")
     # return an output pdb file with the protein and two chains A and B.  
     # also return a JSON with any metrics you want to report
     metrics = {"mean_plddt": 80, "binding_affinity": 2}