Source code for gdsctools.drugs


Small functionalities to retrive chembl/chemspider identifiers
based on a drug name

from easydev import Progress
from gdsctools import DrugDecode
import pandas as pd

__all__ = ["ChemSpiderSearch"]

[docs]class ChemSpiderSearch(object): """This class uses ChemSpider and ChEMBL to identify drug name .. warning:: this is a draft version in dev mode :: c = ChemSpiderSearch() c.search_in_chemspider() c.search_from_smile_inchembl() df = c.find_chembl_ids() It happens that most of public names can be found and almost none of non-public are found. As expected... If chemspider, chembl and pubchem are empty, search for the drug name in chemspider. CHEMSPIDER search: if no identifier found, the search if DROPPED if 1 identifier found, we keep going using the SMILE identifier If more than 1 identifier found, this is AMBIGUOUS. If chembl and pubchem, check with unichem If chembl, check smiles If chembl and chemspider, check smiles ? SMILES are not unique """ def __init__(self, drug_decode): print("ChemSpiderSearch is still in progress, please do not use") self.dd = DrugDecode(drug_decode) self.dd_filled = DrugDecode(drug_decode) from bioservices.chemspider import ChemSpider from bioservices import ChEMBL from bioservices import UniChem try: print('Loading PubChem') from bioservices.pubchem import PubChem self.puchem = PubChem() except: # Pubchem was introduced only in dec 2015 pass print('Loading ChEMBL service') self.chembl = ChEMBL(cache=True) print('Loading ChemSpider service') self.chemspider = ChemSpider(cache=True) print('Loading UniChem service') # in unichem db number is 22 and chembl is 1 self.unichem = UniChem() print('Settings some data aliases') self._cs_find = self.chemspider.find self._cs_get = self.chemspider.GetExtendedCompoundInfo self.drug_ids = sorted(list(self.dd.df.index.values)) self.drug_names = sorted(list(self.dd.df.DRUG_NAME.values))
[docs] def filling_chembl_pubchem_using_unichem(self): """ """ N = len(self.drug_ids) pb = Progress(N) for i, this in enumerate(self.drug_ids): entry = self.dd.df.loc[this] # if no information is provided, we will need to get it # from chemspider # From the database, when chembl is provided, it is unique # same for chemspider and pubchem and CAS select = entry[['CHEMSPIDER', 'CHEMBL', 'PUBCHEM']] if select.count() == 0: name = self.dd.df.loc[this].DRUG_NAME results = self._cs_find(name) if len(results) == 0: # nothing found pass elif len(results) == 1: self.dd_filled.df.loc[this].loc['CHEMSPIDER'] = results[0] else: # non unique #chemspider = ",".join([str(x) for x in results]) self.dd_filled.df.loc[this].loc['CHEMSPIDER'] = results pb.animate(i+1) # Search in chemspider systematically for i, this in enumerate(self.drug_ids): entry = self.dd.df.loc[this] if select.count() == 1: res = self._cs_find(drug) pb.animate(i+1)
[docs] def find_chembl_ids(self): """ """ # don't know how to search for a chembl id given the drug name... # so we use chemspider #self.search_in_chemspider() # but chemspider returns molecular information (not chembl id) # so given the smile string, we look back in chembl for valid entries #self.search_from_smile_inchembl() # finally, get the chembl identifiers drugs = [] chembl_ids = [] chemspider_ids = [] smiles_c = [] smiles_cs = [] for drug in self.drug_ids: try: entry = self.results_chembl[drug] ids = ",".join([x['chemblId'] for x in entry]) drugs.append(drug) chembl_ids.append(ids) ids = ",".join([str(x) for x in self.results[drug]]) except: print('skipping' + drug) ids = ",".join([drug, '', '', '', '', '']) chemspider_ids.append(ids) for drug in self.drug_ids: try: smiles_c.append(",".join([x['smiles'] for x in self.results_chembl[drug]])) except: smiles_c.append('') try: smiles_cs.append(self.results_chemspider[drug]['smiles']) except: smiles_cs.append('') df = pd.DataFrame([drugs, chembl_ids, chemspider_ids, smiles_c, smiles_cs], index=['DRUG_NAME','CHEMBL_ID','CHEMSPIDER_ID', 'SMILE_CHEMBL', 'SMILE_CHEMSPIDER']) df = df.T return df
[docs] def get_chemspider_ids(self, drug_name): res = self._cs_find(drug) return res
[docs] def search_in_chemspider(self): # Fill results attribute as a dictionary. Keys being the drug id # and values are list of chemspider identifiers # # SB52334 --> SB-52334 N = len(self.dd) pb = Progress(N) self.results = {} results = [] for i, index in enumerate(self.dd.df.index): drug = self.dd.df.index[i] drug_name = self.dd.df.loc[drug].DRUG_NAME try: res = self._cs_find(drug_name) except: print("This drug index (%s) / drug name (%s) was not found" % (index, drug_name)) res = [] self.results[drug] = res pb.animate(i+1) results.append(res) self.dd_filled.df['CHEMSPIDER_SEARCHED'] = results
[docs] def search_from_smile_inchembl(self): N = len(self.drug_ids) pb = Progress(N) self.results_chembl = {} self.results_chemspider = {} for i in range(0, N): drug = self.drug_ids[i] self.results_chembl[drug] = [] if self.results[drug]: for chemspider_id in self.results[drug]: chemspider_entry = self._cs_get(chemspider_id) self.results_chemspider[drug] = chemspider_entry smile = chemspider_entry['smiles'] # now search in chembl res_chembl = self.chembl.get_compounds_by_SMILES(smile) try: res_chembl['compounds'] self.results_chembl[drug].extend(res_chembl['compounds']) except: pass pb.animate(i+1)