Dear valued scientists,
I am trying to write a simple python script which parses certain uniprot entries using the biopython module. this is what I got so far:
from Bio import SeqIO
import urllib
handle = urllib.urlopen("http://www.uniprot.org/uniprot/P12345.xml")
record = SeqIO.read(handle, "uniprot-xml")
#print(record)
print(record.name)
This script will simply print the Entry Name of "P12345". Now I would like to extract information like subcellular location, which is included in the Uniprot entry.
Can anyone give an advice on how to proceed?
Thank you and best regards,
Helge
Looks like this module for xml parsing is not that neat. If you let me know which information you like to get, I can write a python script for you.
Yes, I've also run into this problem with Biopython and Uniprot entry parsing before. In the end, it was easier to skip Biopython entirely and just use beautifulsoup4 to handle the xml. Check out the Bioservices package, too (linked below). It seems to fill some of the gaps in Biopython but may be more than you need.
https://pythonhosted.org/bioservices/
Dear Harry,
thank you for your advice. I will have a look at Bioservices.
Best regards
Helge
Despite the very helpful comments , I do not want to give up on SeqIO entirely, becausye it seems to provide a complete data structure for uniprot entries already. If you look at the example below, all the info I need is actually stored. There should be some why to access individual fields, right?
E.g. how could I print only
"/comment_subcellularlocation_location=['Mitochondrion matrix', 'Cell membrane']"
instead of the whole entry (see below).
Best regards
Helge
CODE:
from Bio import SeqIO
import urllib
handle = urllib.urlopen("http://www.uniprot.org/uniprot/P12345.xml")
record = SeqIO.read(handle, "uniprot-xml")
print(record)
OUTPUT:
ID: P12345
Name: AATM_RABIT
Description: Aspartate aminotransferase, mitochondrial
Database cross-references: CTD:2806, EC:2.6.1.1, EC:2.6.1.7,
[...]
PANTHER:PTHR11879, PIR:B27103, PRINTS:PR00799, PROSITE:PS00105, Pfam:PF00155, Proteomes:UP000001811, PubMed:4030726, RefSeq:XP_002711597.1, STRING:9986.ENSOCUP00000003357, SUPFAM:SSF53383, Swiss-Prot:AATM_RABIT, Swiss-Prot:G1SKL2, Swiss-Prot:P12345, TreeFam:TF300641, eggNOG:COG1448, eggNOG:KOG1411
Number of features: 42
[...]
/sequence_version=2
/comment_function=['Catalyzes the irreversible transamination of the L-tryptophan metabolite L-kynurenine to form kynurenic acid (KA). Plays a key role in amino acid metabolism. Important for metabolite exchange between mitochondria and cytosol. Facilitates cellular uptake of long-chain free fatty acids (By similarity).']
/key=['1', '2', '3', '4', '5', '6']
/sequence_length=430
/recommendedName_fullName=['Aspartate aminotransferase, mitochondrial']
/created=1989-10-01
/modified=2015-11-11
/comment_miscellaneous=['In eukaryotes there are cytoplasmic, mitochondrial and chloroplastic isozymes.']
/comment_subcellularlocation_location=['Mitochondrion matrix', 'Cell membrane']
/accessions=['P12345', 'G1SKL2']
Try this at the end of your script.
print record.annotations['comment_subcellularlocation_location']
SwissProt XML Parser class
ID: P09616
Name: HLA_STAAU
Description: Alpha-hemolysin
Database cross-references: ChEMBL:CHEMBL1075259, DIP:DIP-59322N, DOI:10.1074/jbc.270.39.23065, DOI:10.1126/science.274.5294.1859, EMBL:M90536, EMBL:X01645, EvolutionaryTrace:P09616, GO:GO:0005576, GO:GO:0042802, GO:GO:0044179, GO:GO:0090729, IntAct:P09616, InterPro:IPR003963, InterPro:IPR005831, InterPro:IPR016183, InterPro:IPR036435, NCBI Taxonomy:1280, PDB:3M2L, PDB:3M3R, PDB:3M4D, PDB:3M4E, PDB:4IDJ, PDB:4YHD, PDB:7AHL, PDBsum:3M2L, PDBsum:3M3R, PDBsum:3M4D, PDBsum:3M4E, PDBsum:4IDJ, PDBsum:4YHD, PDBsum:7AHL, PIR:S69209, PMAP-CutDB:P09616, PRINTS:PR01468, PRO:PR:P09616, PROSITE:PS00274, Pfam:PF07968, ProteinModelPortal:P09616, PubMed:1400487, PubMed:1587866, PubMed:6500704,
I have above swissprot format which I have read, could you please help me to know, how to read PDB id's from here.
PDB:3M2L, PDB:3M3R, PDB:3M4D, PDB:3M4E, PDB:4IDJ, PDB:4YHD, PDB:7AHL
thanks
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