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I have thousands of PDB files and I need to extract the following information from each of them: an ID or the name of the small molecule (ligand) present in the complex.
Is there a way to do that with BioPython or similar tools? Taking this PDB entry as an example, the tools should return 7FM.
I found out that the package PyPDB has the function get_ligands that does exactly what I'm looking for.
copying from How to download ligands for PDB structure one of the answers, one of mines, code :
import requests
import json
parsed_lig_dict = {}
def main(entry_id: str):
risposta = requests.get(f"https://data.rcsb.org/rest/v1/core/entry/{entry_id}/")
parsed = json.loads(risposta.content.decode())
# print(risposta.status_code)
# print((parsed))
# print(parsed["rcsb_entry_container_identifiers"]["non_polymer_entity_ids"])
# print('\n', type(parsed))
parsed_lig = parsed["rcsb_entry_container_identifiers"]["non_polymer_entity_ids"]
# print('\n\n',parsed_lig, type(parsed_lig))
# for i in parsed:
# print('\n', i , parsed[i])
for lig in parsed_lig:
risposta = requests.get(f"https://data.rcsb.org/rest/v1/core/nonpolymer_entity/{entry_id}/{lig}")
parsed = json.loads(risposta.content.decode())
# print('\n',risposta.status_code, risposta.content)
# print(parsed["rcsb_nonpolymer_entity_container_identifiers"]["asym_ids"],
# parsed["pdbx_entity_nonpoly"]["comp_id"])
parsed_lig_dict[lig] = [parsed["pdbx_entity_nonpoly"]["comp_id"] ,
dict.fromkeys(parsed["rcsb_nonpolymer_entity_container_identifiers"]["asym_ids"])]
for lig in parsed_lig_dict:
for chain in parsed_lig_dict[lig][1]:
risposta = requests.get(f"https://data.rcsb.org/rest/v1/core/nonpolymer_entity_instance/{entry_id}/{chain}")
# print(risposta.status_code)
parsed = json.loads(risposta.content.decode())
# print('\n',risposta.status_code, risposta.content)
# print(chain , '--> ',parsed["rcsb_nonpolymer_entity_instance_container_identifiers"]["auth_seq_id"])
parsed_lig_dict[lig][1][chain] = parsed["rcsb_nonpolymer_entity_instance_container_identifiers"]["auth_seq_id"]
# print(parsed_lig_dict)
# for i in parsed_lig_dict:
# print(parsed_lig_dict[i])
# for i in parsed_lig_dict:
# for y in parsed_lig_dict[i][1]:
# print(i,parsed_lig_dict[i][0], y , parsed_lig_dict[i][1][y])
cnt = 1
for i in parsed_lig_dict:
for y in parsed_lig_dict[i][1]:
seq_id = parsed_lig_dict[i][1][y]
chain = y
comp_id = parsed_lig_dict[i][0]
print(seq_id , y)
risposta = requests.get(f"https://models.rcsb.org/v1/{pdb_file}/ligand?auth_seq_id={seq_id}&label_asym_id={chain}&encoding=sdf" ,
allow_redirects=True)
print(risposta.status_code)
filename = f"lig_{comp_id}_{chain}_{seq_id}_{cnt}.sdf"
open(filename, 'wb').write(risposta.content)
cnt += 1
if __name__ == '__main__':
pdb_file = '5to8'
main(pdb_file)
output file : lig_7FM_B_701_1.sdf :
7FM
ModelServer 0.9.10
39 43 0 0 1 0 0 0 0 0 0
-2.0610 -10.3590 40.5700 C 0 0 0 0 0 0 0 0 0 0 0 0
-3.1170 -11.7950 42.6720 C 0 0 0 0 0 0 0 0 0 0 0 0
-3.8640 -12.6100 43.6800 C 0 0 0 0 0 0 0 0 0 0 0 0
-0.6970 -10.3290 36.5750 C 0 0 0 0 0 0 0 0 0 0 0 0
-1.8210 -10.9080 35.9890 C 0 0 0 0 0 0 0 0 0 0 0 0
-1.6600 -8.1940 35.9530 C 0 0 0 0 0 0 0 0 0 0 0 0
2.0300 -9.0340 41.4650 N 0 0 0 0 0 0 0 0 0 0 0 0
0.9390 -9.6680 41.0120 C 0 0 0 0 0 0 0 0 0 0 0 0
0.7980 -10.0800 39.7250 N 0 0 0 0 0 0 0 0 0 0 0 0
1.7720 -9.8430 38.8300 C 0 0 0 0 0 0 0 0 0 0 0 0
2.9200 -9.1930 39.2330 C 0 0 0 0 0 0 0 0 0 0 0 0
2.9910 -8.8020 40.5580 C 0 0 0 0 0 0 0 0 0 0 0 0
4.0340 -8.8690 38.3150 C 0 0 0 0 0 0 0 0 0 0 0 0
-0.0830 -9.8810 41.9510 N 0 0 0 0 0 0 0 0 0 0 0 0
-1.3380 -10.4670 41.7760 C 0 0 0 0 0 0 0 0 0 0 0 0
-3.3020 -10.9670 40.4240 C 0 0 0 0 0 0 0 0 0 0 0 0
-3.8290 -11.6870 41.4760 C 0 0 0 0 0 0 0 0 0 0 0 0
-1.8800 -11.1950 42.8370 C 0 0 0 0 0 0 0 0 0 0 0 0
-5.0400 -12.4130 41.5840 N 0 0 0 0 0 0 0 0 0 0 0 0
-5.2460 -12.6990 43.0180 C 0 0 0 0 0 0 0 0 0 0 0 0
1.5160 -10.2930 37.5490 N 0 0 0 0 0 0 0 0 0 0 0 0
0.4060 -11.1430 37.2090 C 0 0 0 0 0 0 0 0 0 0 0 0
-2.8420 -10.2200 35.4050 N 0 0 0 0 0 0 0 0 0 0 0 0
-2.7360 -8.8690 35.4000 C 0 0 0 0 0 0 0 0 0 0 0 0
-0.6240 -8.9330 36.5380 C 0 0 0 0 0 0 0 0 0 0 0 0
-1.9670 -12.3410 35.9950 N 0 0 0 0 0 0 0 0 0 0 0 0
-2.5680 -13.0870 37.1550 C 0 0 0 0 0 0 0 0 0 0 0 0
-1.4690 -13.1930 34.5670 S 0 0 0 0 0 0 0 0 0 0 0 0
-4.0440 -12.7310 37.3480 C 0 0 0 0 0 0 0 0 0 0 0 0
-5.9670 -12.8650 40.6430 C 0 0 0 0 0 0 0 0 0 0 0 0
-6.9720 -13.5050 40.9690 O 0 0 0 0 0 0 0 0 0 0 0 0
-4.6200 -13.4130 38.5900 C 0 0 0 0 0 0 0 0 0 0 0 0
-5.8010 -12.6200 39.1510 C 0 0 0 0 0 0 0 0 0 0 0 0
-0.5520 -12.3690 33.7940 O 0 0 0 0 0 0 0 0 0 0 0 0
-1.1430 -14.5640 34.8900 O 0 0 0 0 0 0 0 0 0 0 0 0
-3.0530 -13.2140 33.7590 C 0 0 0 0 0 0 0 0 0 0 0 0
5.0490 -8.1440 38.8710 F 0 0 0 0 0 0 0 0 0 0 0 0
4.6120 -9.9430 37.7390 F 0 0 0 0 0 0 0 0 0 0 0 0
3.5350 -8.1080 37.3100 F 0 0 0 0 0 0 0 0 0 0 0 0
1 16 2 0 0 0 0
1 15 1 0 0 0 0
2 17 2 0 0 0 0
2 18 1 0 0 0 0
2 3 1 0 0 0 0
3 20 1 0 0 0 0
4 5 2 0 0 0 0
4 25 1 0 0 0 0
4 22 1 0 0 0 0
5 23 1 0 0 0 0
5 26 1 0 0 0 0
6 24 1 0 0 0 0
6 25 2 0 0 0 0
7 12 2 0 0 0 0
7 8 1 0 0 0 0
8 9 2 0 0 0 0
8 14 1 0 0 0 0
9 10 1 0 0 0 0
10 21 1 0 0 0 0
10 11 2 0 0 0 0
11 13 1 0 0 0 0
11 12 1 0 0 0 0
13 39 1 0 0 0 0
13 38 1 0 0 0 0
13 37 1 0 0 0 0
14 15 1 0 0 0 0
15 18 2 0 0 0 0
16 17 1 0 0 0 0
17 19 1 0 0 0 0
19 30 1 0 0 0 0
19 20 1 0 0 0 0
21 22 1 0 0 0 0
23 24 2 0 0 0 0
26 28 1 0 0 0 0
26 27 1 0 0 0 0
27 29 1 0 0 0 0
28 36 1 0 0 0 0
28 34 2 0 0 0 0
28 35 2 0 0 0 0
29 32 1 0 0 0 0
30 33 1 0 0 0 0
30 31 2 0 0 0 0
32 33 1 0 0 0 0
M END
> <model_server_result.job_id>
RFDalM1AmREvgkv0PqdfQw
> <model_server_result.datetime_utc>
2023-10-27 22:13:14
> <model_server_result.server_version>
0.9.10
> <model_server_result.query_name>
ligand
> <model_server_result.source_id>
pdb-bcif
> <model_server_result.entry_id>
5to8
> <model_server_params.name>
atom_site
> <model_server_params.value>
{"label_asym_id":"B","auth_seq_id":701}
> <model_server_stats.io_time_ms>
5
> <model_server_stats.parse_time_ms>
76
> <model_server_stats.create_model_time_ms>
2
> <model_server_stats.query_time_ms>
244
> <model_server_stats.encode_time_ms>
0
> <model_server_stats.element_count>
39
$$$$
picture of .sdf file :
my attempt, will get only non water (H2O) or non aa (aminoacid) present in the PDB .... tricky if the ligand is an aa :
from Bio.PDB import PDBParser
from Bio.PDB import Selection
d = {'CYS': 'C', 'ASP': 'D', 'SER': 'S', 'GLN': 'Q', 'LYS': 'K',
'ILE': 'I', 'PRO': 'P', 'THR': 'T', 'PHE': 'F', 'ASN': 'N',
'GLY': 'G', 'HIS': 'H', 'LEU': 'L', 'ARG': 'R', 'TRP': 'W',
'ALA': 'A', 'VAL':'V', 'GLU': 'E', 'TYR': 'Y', 'MET': 'M'}
pdb_file = '5to8'
struct = PDBParser(QUIET = True).get_structure(pdb_file, pdb_file+'.pdb')
res_list = Selection.unfold_entities(struct , 'R')
for i in res_list :
if i.resname != 'HOH' and i.resname not in d :
print(i, i.resname)
output :
<Residue 7FM het=H_7FM resseq=701 icode= > 7FM