Preprocessing Script.py

## Script to sanitize and split AggregatorAdvisor dataset

# 1. Load modules

pip install rdkit
pip install molvs
import pandas as pd
import numpy as np
import urllib.request
import tqdm
import rdkit
from rdkit import Chem
import molvs

standardizer = molvs.Standardizer()
fragment_remover = molvs.fragment.FragmentRemover()

#3. Resolve SMILES parse error

# Smiles is 'None', found the compound on ChemSpider
# Smiles displayed 'Explicit valence for atom # 2 O, 3, is greater than permitted'
# https://www.chemspider.com/Chemical-Structure.17588253.html?rid=026abd00-5d7b-4c7a-b279-3ba43ab46203
AA.loc[AA['smiles'] == '[O-][N+](=[O-])C1=CC=CC(=C1)C2=NC(CO2)C3=CC=CC=C3' , 'smiles'] = 'c1ccc(cc1)C2COC(=N2)c3cccc(c3)[N+](=O)[O-]'

# Smiles is 'None', found the compound on ChemSpider
# Smiles displayed 'Explicit valence for atom # 2 O, 3, is greater than permitted'
# https://www.chemspider.com/Chemical-Structure.17588254.html?rid=0f94ced5-dee6-4274-b0c5-796500b40be7
AA.loc[AA['smiles'] == '[O-][N+](=[O-])C1=CC=CC(=C1)C2=NCCC(O2)C3=CC=CC=C3', 'smiles'] = 'c1ccc(cc1)C2CCN=C(O2)c3cccc(c3)[N+](=O)[O-]'

#4. Sanitize with MolVS and print problems

AA['X'] = [ \
    rdkit.Chem.MolToSmiles(
        fragment_remover.remove(
        standardizer.standardize(
        rdkit.Chem.MolFromSmiles(
        smiles))))
    for smiles in AA['smiles']]

problems = []
for index, row in tqdm.tqdm(AA.iterrows()):
    result = molvs.validate_smiles(row['X'])
    if len(result) == 0:
        continue
    problems.append( (row['substance_id'], result) )

# most are because it includes the salt form and/or it is not neutralized
for substance_id, alert in problems:
    print(f"substance_id: {substance_id}, problem: {alert[0]}")

#5. Select columns and rename the dataset

AA.rename(columns={'X': 'new SMILES'}, inplace=True)
AA[['new SMILES', 'substance_id', 'aggref_index', 'logP']].to_csv('AggregatorAdvisor.csv', index=False)