add 2d conformers

data/pdb.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2f6ef36582e7e9e8a29ac07976da378194216ad2144d33daa8a639e93300fcb9
-size 396814137
+oid sha256:3cbbee08b3cd8659d95f45643d8a053c29a4d6017c9d563721a5b7b4707e5f1b
+size 412327231

parse_complexes.py

@@ -88,7 +88,17 @@ def tokenize_ligand(mol):
         else:
             token_pos.append((np.nan, np.nan, np.nan))
 
-    return smi, token_pos
+    k = 0
+    conf_2d = AllChem.Compute2DCoords(mol)
+    token_pos_2d = []
+    for i,token in enumerate(masked_tokens):
+        if token != '':
+            token_pos_2d.append(tuple(mol.GetConformer(conf_2d).GetAtomPosition(atom_order[k])))
+            k += 1
+        else:
+            token_pos_2d.append((0.,0.,0.))
+
+    return smi, token_pos, token_pos_2d
 
 def read_ligand_expo():
     """
@@ -191,15 +201,17 @@ def process_entry(df_dict, pdb_fn):
 
         ligand_smiles = []
         ligand_xyz = []
+        ligand_xyz_2d = []
 
         for mol, name in zip(ligand_mols, ligand_names):
             print('Processing {} and {}'.format(pdb_name, name))
-            smi, xyz = tokenize_ligand(mol)
+            smi, xyz, xyz_2d = tokenize_ligand(mol)
             ligand_smiles.append(smi)
             ligand_xyz.append(xyz)
+            ligand_xyz_2d.append(xyz_2d)
 
         seq, receptor_xyz = get_protein_sequence_and_coords(protein)
-        return pdb_name, seq, receptor_xyz, ligand_names, ligand_smiles, ligand_xyz
+        return pdb_name, seq, receptor_xyz, ligand_names, ligand_smiles, ligand_xyz, ligand_xyz_2d
     except Exception as e:
         print(repr(e))
 
@@ -225,7 +237,15 @@ if __name__ == '__main__':
             lig_id = [l for r in result if r is not None for l in r[3]]
             lig_smiles = [s for r in result if r is not None for s in r[4]]
             lig_xyz = [xyz for r in result if r is not None for xyz in r[5]]
+            lig_xyz_2d = [xyz for r in result if r is not None for xyz in r[6]]
 
             import pandas as pd
-            df = pd.DataFrame({'pdb_id': pdb_id, 'lig_id': lig_id, 'seq': seq, 'smiles': lig_smiles, 'receptor_xyz': receptor_xyz, 'ligand_xyz': lig_xyz})
+            df = pd.DataFrame({
+                'pdb_id': pdb_id,
+                'lig_id': lig_id,
+                'seq': seq,
+                'smiles': lig_smiles,
+                'receptor_xyz': receptor_xyz,
+                'ligand_xyz': lig_xyz,
+                'ligand_xyz_2d': lig_xyz_2d})
             df.to_parquet('data/pdb.parquet',index=False)

pdb_protein_ligand_complexes.py

@@ -54,10 +54,10 @@ _URLs = {name: _URL+_file_names[name] for name in _file_names}
 
 
 # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
-class ProteinLigandContacts(datasets.ArrowBasedBuilder):
-    """List of protein sequences, ligand SMILES, and complex contacts."""
+class PDBProteinLigandComplexes(datasets.ArrowBasedBuilder):
+    """List of protein sequences, ligand SMILES, and complex coordinates."""
 
-    VERSION = datasets.Version("1.2.0")
+    VERSION = datasets.Version("1.3.0")
 
     def _info(self):
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
@@ -78,6 +78,7 @@ class ProteinLigandContacts(datasets.ArrowBasedBuilder):
                 "seq": datasets.Value("string"),
                 "smiles": datasets.Value("string"),
                 "ligand_xyz": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
+                "ligand_xyz_2d": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
                 "receptor_xyz": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
                 # These are the features of your dataset like images, labels ...
             }