add 2d conformers
Browse files- data/pdb.parquet +2 -2
- parse_complexes.py +24 -4
- pdb_protein_ligand_complexes.py +4 -3
data/pdb.parquet
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3cbbee08b3cd8659d95f45643d8a053c29a4d6017c9d563721a5b7b4707e5f1b
|
3 |
+
size 412327231
|
parse_complexes.py
CHANGED
@@ -88,7 +88,17 @@ def tokenize_ligand(mol):
|
|
88 |
else:
|
89 |
token_pos.append((np.nan, np.nan, np.nan))
|
90 |
|
91 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
92 |
|
93 |
def read_ligand_expo():
|
94 |
"""
|
@@ -191,15 +201,17 @@ def process_entry(df_dict, pdb_fn):
|
|
191 |
|
192 |
ligand_smiles = []
|
193 |
ligand_xyz = []
|
|
|
194 |
|
195 |
for mol, name in zip(ligand_mols, ligand_names):
|
196 |
print('Processing {} and {}'.format(pdb_name, name))
|
197 |
-
smi, xyz = tokenize_ligand(mol)
|
198 |
ligand_smiles.append(smi)
|
199 |
ligand_xyz.append(xyz)
|
|
|
200 |
|
201 |
seq, receptor_xyz = get_protein_sequence_and_coords(protein)
|
202 |
-
return pdb_name, seq, receptor_xyz, ligand_names, ligand_smiles, ligand_xyz
|
203 |
except Exception as e:
|
204 |
print(repr(e))
|
205 |
|
@@ -225,7 +237,15 @@ if __name__ == '__main__':
|
|
225 |
lig_id = [l for r in result if r is not None for l in r[3]]
|
226 |
lig_smiles = [s for r in result if r is not None for s in r[4]]
|
227 |
lig_xyz = [xyz for r in result if r is not None for xyz in r[5]]
|
|
|
228 |
|
229 |
import pandas as pd
|
230 |
-
df = pd.DataFrame({
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
231 |
df.to_parquet('data/pdb.parquet',index=False)
|
|
|
88 |
else:
|
89 |
token_pos.append((np.nan, np.nan, np.nan))
|
90 |
|
91 |
+
k = 0
|
92 |
+
conf_2d = AllChem.Compute2DCoords(mol)
|
93 |
+
token_pos_2d = []
|
94 |
+
for i,token in enumerate(masked_tokens):
|
95 |
+
if token != '':
|
96 |
+
token_pos_2d.append(tuple(mol.GetConformer(conf_2d).GetAtomPosition(atom_order[k])))
|
97 |
+
k += 1
|
98 |
+
else:
|
99 |
+
token_pos_2d.append((0.,0.,0.))
|
100 |
+
|
101 |
+
return smi, token_pos, token_pos_2d
|
102 |
|
103 |
def read_ligand_expo():
|
104 |
"""
|
|
|
201 |
|
202 |
ligand_smiles = []
|
203 |
ligand_xyz = []
|
204 |
+
ligand_xyz_2d = []
|
205 |
|
206 |
for mol, name in zip(ligand_mols, ligand_names):
|
207 |
print('Processing {} and {}'.format(pdb_name, name))
|
208 |
+
smi, xyz, xyz_2d = tokenize_ligand(mol)
|
209 |
ligand_smiles.append(smi)
|
210 |
ligand_xyz.append(xyz)
|
211 |
+
ligand_xyz_2d.append(xyz_2d)
|
212 |
|
213 |
seq, receptor_xyz = get_protein_sequence_and_coords(protein)
|
214 |
+
return pdb_name, seq, receptor_xyz, ligand_names, ligand_smiles, ligand_xyz, ligand_xyz_2d
|
215 |
except Exception as e:
|
216 |
print(repr(e))
|
217 |
|
|
|
237 |
lig_id = [l for r in result if r is not None for l in r[3]]
|
238 |
lig_smiles = [s for r in result if r is not None for s in r[4]]
|
239 |
lig_xyz = [xyz for r in result if r is not None for xyz in r[5]]
|
240 |
+
lig_xyz_2d = [xyz for r in result if r is not None for xyz in r[6]]
|
241 |
|
242 |
import pandas as pd
|
243 |
+
df = pd.DataFrame({
|
244 |
+
'pdb_id': pdb_id,
|
245 |
+
'lig_id': lig_id,
|
246 |
+
'seq': seq,
|
247 |
+
'smiles': lig_smiles,
|
248 |
+
'receptor_xyz': receptor_xyz,
|
249 |
+
'ligand_xyz': lig_xyz,
|
250 |
+
'ligand_xyz_2d': lig_xyz_2d})
|
251 |
df.to_parquet('data/pdb.parquet',index=False)
|
pdb_protein_ligand_complexes.py
CHANGED
@@ -54,10 +54,10 @@ _URLs = {name: _URL+_file_names[name] for name in _file_names}
|
|
54 |
|
55 |
|
56 |
# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
|
57 |
-
class
|
58 |
-
"""List of protein sequences, ligand SMILES, and complex
|
59 |
|
60 |
-
VERSION = datasets.Version("1.
|
61 |
|
62 |
def _info(self):
|
63 |
# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
|
@@ -78,6 +78,7 @@ class ProteinLigandContacts(datasets.ArrowBasedBuilder):
|
|
78 |
"seq": datasets.Value("string"),
|
79 |
"smiles": datasets.Value("string"),
|
80 |
"ligand_xyz": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
|
|
|
81 |
"receptor_xyz": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
|
82 |
# These are the features of your dataset like images, labels ...
|
83 |
}
|
|
|
54 |
|
55 |
|
56 |
# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
|
57 |
+
class PDBProteinLigandComplexes(datasets.ArrowBasedBuilder):
|
58 |
+
"""List of protein sequences, ligand SMILES, and complex coordinates."""
|
59 |
|
60 |
+
VERSION = datasets.Version("1.3.0")
|
61 |
|
62 |
def _info(self):
|
63 |
# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
|
|
|
78 |
"seq": datasets.Value("string"),
|
79 |
"smiles": datasets.Value("string"),
|
80 |
"ligand_xyz": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
|
81 |
+
"ligand_xyz_2d": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
|
82 |
"receptor_xyz": datasets.Sequence(datasets.Sequence(datasets.Value('float32'))),
|
83 |
# These are the features of your dataset like images, labels ...
|
84 |
}
|