Datasets:
File size: 1,158 Bytes
24fff69 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | import json
import pandas as pd
from tqdm import tqdm
from rdkit import Chem
natural_list = set(json.load(open('./all_natural_metabolite_names.json')))
metabolite_inchi_smiles_dic = pd.read_csv('../datasets/metabolite_inchi_smiles_brenda_pubchem.tsv',sep='\t',index_col='metabolite')
name_to_smiles = {}
for ind, row in tqdm(metabolite_inchi_smiles_dic.iterrows()):
try:
name_to_smiles[row.name] = Chem.MolToSmiles(Chem.MolFromSmiles(row.smiles))
except:
continue
natural_smi_list = [name_to_smiles[name] for name in natural_list if name in name_to_smiles]
for parameter in ['kcat','km','ki']:
print(parameter)
datafile = f'./data/processed/splits_wpdbs/{parameter}-random_trainvaltest.csv'
if parameter=='kcat':
subcol = 'reactant_smiles'
else:
subcol = 'substrate_smiles'
df = pd.read_csv(datafile)
count = 0
for ind, row in tqdm(df.iterrows()):
natural = True
substrates = row[subcol].split('.')
for sub in substrates:
if not sub in natural_smi_list:
natural = False
if natural: count+=1
print(count)
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