#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# This file is part of the `pypath` python module
#
# Copyright 2014-2023
# EMBL, EMBL-EBI, Uniklinik RWTH Aachen, Heidelberg University
#
# Authors: see the file `README.rst`
# Contact: Dénes Türei (turei.denes@gmail.com)
#
# Distributed under the GPLv3 License.
# See accompanying file LICENSE.txt or copy at
# https://www.gnu.org/licenses/gpl-3.0.html
#
# Website: https://pypath.omnipathdb.org/
#
from __future__ import annotations
import csv
import collections
import itertools
import pypath.share.curl as curl
import pypath.share.common as common
import pypath_common._constants as _const
import pypath.resources.urls as urls
import pypath.utils.mapping as mapping
import pypath.utils.taxonomy as taxonomy
import pypath.internals.intera as intera
[docs]
def guide2pharma_download(
organism: str | int = 'human',
endogenous: bool = True,
process_interactions: bool = True,
process_complexes: bool = True,
) -> tuple[list, dict]:
"""
Downloads and processes Guide to Pharmacology data.
Returns list of dicts.
Args:
organism
Name of the organism, e.g. `human`.
endogenous
Whether to include only endogenous ligands interactions.
"""
get_taxid = lambda x: (
_const.NOT_ORGANISM_SPECIFIC
if x in {'', 'None'} else
taxonomy.ensure_ncbi_tax_id(x)
)
organism_ = None
ncbi_tax_id = None
if isinstance(organism, str):
ncbi_tax_id = get_taxid(organism)
try:
organism_ = taxonomy.ensure_common_name(ncbi_tax_id)
organism_ = organism_.capitalize() if organism_ else None
except KeyError:
pass # no organism specified
positives = {
'agonist', 'activator', 'potentiation', 'partial agonist',
'inverse antagonist', 'full agonist', 'activation',
'irreversible agonist', 'positive',
}
negatives = {
'inhibitor', 'antagonist', 'inhibition', 'irreversible inhibition',
'inverse agonist', 'negative', 'weak inhibition',
'reversible inhibition',
}
GuideToPharmacologyInteraction = collections.namedtuple(
'GuideToPharmacologyInteraction',
[
'ligand',
'ligand_id_type',
'target',
'target_id_type',
'target_is_ligand',
'ligand_organism',
'target_organism',
'effect',
'ligand_location',
'target_type',
'ligand_endogenous',
'pubmed_ids',
]
)
def is_positive(term):
return term.lower().strip() in positives
def is_negative(term):
return term.lower().strip() in negatives
interactions = []
complexes = {}
url = urls.urls['gtp']['url']
c = curl.Curl(url, silent = False, large = True, encoding = 'utf-8')
line0 = next(c.result)
if line0[:2] != '"#':
c.fileobj.seek(0)
data = csv.DictReader(c.result)
if organism_ is not None:
data = [
d for d in data
if (
get_taxid(d['Target Species']) == ncbi_tax_id and
ncbi_tax_id in set(
get_taxid(t)
for t in d['Ligand Species'].split('|')
)
)
]
if endogenous:
data = [d for d in data if d['Endogenous'].strip() == 'true']
for d in data:
if is_positive(d['Type']) or is_positive(d['Action']):
effect = 1
elif is_negative(d['Type']) or is_negative(d['Action']):
effect = -1
else:
effect = 0
ligands = d['Ligand Gene Symbol'] or d['Ligand PubChem SID']
ligands = ligands.split('|')
ligand_taxons = [get_taxid(l) for l in d['Ligand Species'].split('|')]
for ligand_taxon in zip(ligands, ligand_taxons):
targets = (
d['Target UniProt ID'] or
d['Target Ligand UniProt ID'] or
d['Target Ligand PubChem SID']
)
targets = targets.split('|')
references = d['PubMed ID'].split('|') if d['PubMed ID'] else []
if process_interactions:
for ligand, target in itertools.product(ligands, targets):
interactions.append(
GuideToPharmacologyInteraction(
ligand = ligand,
ligand_id_type = (
'genesymbol'
if d['Ligand Gene Symbol'] else
'pubchem_sid'
if d['Ligand PubChem SID'] else
None
),
target = target,
target_id_type = (
'uniprot'
if (
d['Target UniProt ID'] or
d['Target Ligand UniProt ID']
) else
'pubchem_sid'
if d['Target Ligand PubChem SID'] else
None
),
target_is_ligand = bool(d['Target Ligand']),
ligand_organism = ligand_taxon,
target_organism = get_taxid(d['Target Species']),
effect = effect,
ligand_location = (
d['Ligand Context'].strip().lower() or None
),
target_type = (
d['Receptor Site'].strip().lower() or None
),
ligand_endogenous = (
d['Endogenous'].strip() == 't'
),
pubmed_ids = references,
)
)
if process_complexes:
if (
len(targets) > 1 and (
d['Target UniProt ID'] or
d['Target Ligand UniProt ID']
)
):
cplex = intera.Complex(
components = targets,
sources = 'Guide2Pharma',
references = references,
)
key = cplex.__str__()
if key in complexes:
complexes[key] += cplex
else:
complexes[key] = cplex
if (
len(ligands) > 1 and
d['Ligand Gene Symbol']
):
ligand_uniprots = [
mapping.map_name0(ligand, 'genesymbol', 'uniprot')
for ligand in ligands
]
ligand_uniprots = [u for u in ligand_uniprots if u]
if len(ligand_uniprots) > 1:
cplex = intera.Complex(
components = ligand_uniprots,
sources = 'Guide2Pharma',
references = references,
)
key = cplex.__str__()
if key in complexes:
complexes[key] += cplex
else:
complexes[key] = cplex
return interactions, complexes
[docs]
def guide2pharma_interactions(**kwargs):
interactions, complexes = guide2pharma_download(
process_complexes = False,
**kwargs
)
return interactions
[docs]
def guide2pharma_complexes(**kwargs):
interactions, complexes = guide2pharma_download(
process_interactions = False,
**kwargs
)
return complexes
