Delete MSTI Thiol Interference_preprocessing script.py

MSTI Thiol Interference_preprocessing script.py

@@ -1,104 +0,0 @@
-# 1. Load Modules
-
-pip install rdkit
-pip install molvs
-import pandas as pd
-import numpy as np
-import rdkit
-import molvs
-from rdkit import Chem
-
-standardizer = molvs.Standardizer()
-fragment_remover = molvs.fragment.FragmentRemover()
-
-
-# 2. Convert the SDF file from the original paper into data frame
-# Before running the code, please download SDF files from the original paper
-# https://pubs.acs.org/doi/10.1021/acs.jmedchem.3c00482
-
-from rdkit.Chem import PandasTools
-sdfFile = 'Thiol_training_set_curated.sdf'
-dataframe = PandasTools.LoadSDF(sdfFile)
-dataframe.to_csv('thiol.csv', index=False)
-df = pd.read_csv('thiol.csv')
-
-
-# 3. Resolve SMILES parse error
-# Some of the 'Raw_SMILES' rows contain TWO SMILES separated by ';'' and, they cause SMILES parse error (which means they cannot be read)
-# So we separated the SMILES and renamed the columns
-
-df.rename(columns = {'PUBCHEM_EXT_DATASOURCE_REGID': 'REGID_1'}, inplace = True)
-df.rename(columns = {'Other REGIDs': 'REGID_2'}, inplace = True)
-
-df.insert(2, 'REGID_3', np.NaN)
-
-df['REGID_3'] = df['REGID_2'].str.split(',').str[1]
-df['REGID_2'] = df['REGID_2'].str.split(',').str[0]
-
-df.insert(4, 'SMILES_2', np.NaN)
-df.insert(5, 'SMILES_3', np.NaN)
-
-df[['Raw_SMILES', 'SMILES_2', 'SMILES_3']] = df['Raw_SMILES'].str.split(';', expand=True)
-
-df.rename(columns= {'Raw_SMILES' : 'SMILES_1'}, inplace = True)
-
-
-# 4. Sanitize with MolVS and print problems
-
-df['X_1'] = [ \
-    rdkit.Chem.MolToSmiles(
-        fragment_remover.remove(
-        standardizer.standardize(
-        rdkit.Chem.MolFromSmiles(
-        smiles))))
-    for smiles in df['SMILES_1']]
-
-def process_smiles(smiles):
-    if pd.isna(smiles):
-        return None  
-    try:
-        return rdkit.Chem.MolToSmiles(
-            fragment_remover.remove(
-                standardizer.standardize(
-                    rdkit.Chem.MolFromSmiles(smiles))))
-    except Exception as e:
-        print(f"Error processing SMILES {smiles}: {e}")
-        return None  
-
-df['X_2'] = df['SMILES_2'].apply(process_smiles)
-
-def process_smiles(smiles):
-    if pd.isna(smiles):
-        return None  
-    try:
-        return rdkit.Chem.MolToSmiles(
-            fragment_remover.remove(
-                standardizer.standardize(
-                    rdkit.Chem.MolFromSmiles(smiles))))
-    except Exception as e:
-        print(f"Error processing SMILES {smiles}: {e}")
-        return None  
-
-df['X_3'] = df['SMILES_3'].apply(process_smiles)
-
-
-# 5. Rename the columns
-
-df.rename(columns={'X_1' : 'newSMILES_1', 'X_2' : 'newSMILES_2', 'X_3' : 'newSMILES_3'}, inplace = True)
-
-
-# 6. Create a file with sanitized SMILES
-
-df[['REGID_1',
- 'REGID_2',
- 'REGID_3',
- 'newSMILES_1',
- 'newSMILES_2',
- 'newSMILES_3',
- 'log_AC50_M',
- 'Efficacy',
- 'CC-v2',
- 'Outcome',
- 'InChIKey',
- 'ID',
- 'ROMol']].to_csv('thiol_sanitized.csv', index = False)