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reformat.py
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reformat.py
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import argparse
import os
import pandas as pd
import subprocess
from rdkit import Chem
from src.utils import disable_rdkit_logging
from tqdm import tqdm
import csv
import numpy as np
import torch
def load_rdkit_molecule(xyz_path, obabel_path, scaf_sdf_path, true_sdf_path, true_scaf_smi_ori, true_mol_smi_ori):
supp = Chem.SDMolSupplier(obabel_path, sanitize=False)
mol = list(supp)[0]
mol_frags = Chem.GetMolFrags(mol, asMols=True, sanitizeFrags=False)
mol_filtered = max(mol_frags, default=mol, key=lambda m: m.GetNumAtoms())
try:
mol_smi = Chem.MolToSmiles(mol_filtered, canonical=True)
except RuntimeError:
mol_smi = Chem.MolToSmiles(mol_filtered, canonical=False)
supp = Chem.SDMolSupplier(scaf_sdf_path, sanitize=False)
true_scaf = list(supp)[0]
true_scaf_smi = Chem.MolToSmiles(true_scaf)
supp = Chem.SDMolSupplier(true_sdf_path, sanitize=False)
true_mol = list(supp)[0]
true_mol_smi = Chem.MolToSmiles(true_mol)
match = mol_filtered.GetSubstructMatch(true_scaf)
if len(match) == 0:
true_scaf = Chem.MolFromSmiles(true_scaf_smi_ori, sanitize=False)
try:
Chem.SanitizeMol(mol_filtered)
except Exception as e:
print(e)
mol_filtered_ = Chem.MolFromSmiles(mol_smi, sanitize=True)
if type(mol_filtered_) != Chem.rdchem.Mol:
mol_filtered_ = Chem.MolFromSmiles(mol_smi, sanitize=False)
match_ = mol_filtered_.GetSubstructMatch(true_scaf)
if len(match_) == 0:
rgroup_smi = ''
mol_smi = true_scaf_smi_ori
else:
rgroup = Chem.DeleteSubstructs(mol_filtered, true_scaf)
try:
Chem.Kekulize(rgroup, clearAromaticFlags=True)
except Exception:
pass
try:
rgroup_smi = Chem.MolToSmiles(rgroup)
except RuntimeError:
rgroup_smi = Chem.MolToSmiles(rgroup, canonical=False)
return mol_filtered, mol_smi, rgroup_smi, true_scaf_smi, true_mol_smi
else:
rgroup = Chem.DeleteSubstructs(mol_filtered, true_scaf)
try:
Chem.Kekulize(rgroup, clearAromaticFlags=True)
except Exception:
pass
try:
rgroup_smi = Chem.MolToSmiles(rgroup)
except RuntimeError:
rgroup_smi = Chem.MolToSmiles(rgroup, canonical=False)
return mol_filtered, mol_smi, rgroup_smi, true_scaf_smi, true_mol_smi
def load_molecules(folder, true_scaf_smi_ori, true_mol_smi_ori):
pred_mols = []
pred_mols_smi = []
pred_rgroup_smi = []
sample_num = 100
scaf_xyz_path = f'{folder}/scaf_.xyz'
scaf_sdf_path = f'{folder}/scaf_.sdf'
true_xyz_path = f'{folder}/true_.xyz'
true_sdf_path = f'{folder}/true_.sdf'
if not os.path.exists(scaf_sdf_path):
subprocess.run(f'obabel {scaf_xyz_path} -O {scaf_sdf_path} 2> /dev/null', shell=True)
if not os.path.exists(true_sdf_path):
subprocess.run(f'obabel {true_xyz_path} -O {true_sdf_path} 2> /dev/null', shell=True)
for i in range(sample_num):
pred_xyz_path = f'{folder}/{str(i)}_.xyz'
pred_sdf_path = f'{folder}/{str(i)}_.sdf'
mol, mol_smi, rgroup_smi, true_scaf_smi, true_mol_smi = load_rdkit_molecule(pred_xyz_path, pred_sdf_path, scaf_sdf_path, true_sdf_path, true_scaf_smi_ori, true_mol_smi_ori)
pred_mols.append(mol)
pred_mols_smi.append(mol_smi)
pred_rgroup_smi.append(rgroup_smi)
return pred_mols, pred_mols_smi, pred_rgroup_smi, true_scaf_smi, true_mol_smi
def load_sampled_dataset(folder, idx2true_mol_smi, idx2true_scaf_smi, idx2true_protein_filename):
pred_mols = []
pred_mols_smi = []
pred_rgroup_smi = []
true_mols_smi = []
true_scafs_smi = []
true_mols_smi_ori = []
true_scafs_smi_ori = []
protein_filename_list = []
max_num = 0
for fname in os.listdir(folder):
if fname.isdigit():
max_num = max(max_num, int(fname))
for i in range(max_num + 1):
true_mol_smi = idx2true_mol_smi[str(i)]
true_scaf_smi = idx2true_scaf_smi[str(i)]
protein_filename = idx2true_protein_filename[str(i)]
mols, mols_smi, rgroup_smi, true_scaf_smi_, true_mol_smi_ = load_molecules(f'{folder}/{str(i)}', true_scaf_smi, true_mol_smi)
pred_mols += mols
pred_mols_smi += mols_smi
pred_rgroup_smi += rgroup_smi
true_mols_smi += [true_mol_smi_] * len(mols)
true_scafs_smi += [true_scaf_smi_] * len(mols)
true_mols_smi_ori += [true_mol_smi] * len(mols)
true_scafs_smi_ori += [true_scaf_smi] * len(mols)
protein_filename_list += [protein_filename] * len(mols)
return pred_mols, pred_mols_smi, pred_rgroup_smi, true_mols_smi, true_scafs_smi, true_mols_smi_ori, true_scafs_smi_ori, protein_filename_list
def reformat(samples, formatted, true_smiles_path):
true_smiles_table = pd.read_csv(true_smiles_path, names=['uuid','molecule_name','molecule','scaffold','rgroups','anchor','pocket_full_size','pocket_bb_size','molecule_size','scaffold_size','rgroup_size', 'protein_filename'])
idx2true_mol_smi = dict(zip(true_smiles_table.uuid.values, true_smiles_table.molecule.values))
idx2true_scaf_smi = dict(zip(true_smiles_table.uuid.values, true_smiles_table.scaffold.values))
idx2true_protein_filename = dict(zip(true_smiles_table.uuid.values, true_smiles_table.protein_filename.values))
pred_mols, pred_mols_smi, pred_rgroup_smi, true_mols_smi, true_scafs_smi, true_mols_smi_ori, true_scafs_smi_ori, protein_filename_list = load_sampled_dataset(
folder = samples,
idx2true_mol_smi=idx2true_mol_smi,
idx2true_scaf_smi=idx2true_scaf_smi,
idx2true_protein_filename=idx2true_protein_filename,
)
formatted_output_dir = formatted
metric_out_smi_path = os.path.join(formatted_output_dir, 'crossdock_test_metric.smi')
vina_out_smi_path = os.path.join(formatted_output_dir, 'crossdock_test_vina.smi')
out_sdf_path = os.path.join(formatted_output_dir, 'crossdock_test.sdf')
os.makedirs(formatted_output_dir, exist_ok=True)
with open(metric_out_smi_path, 'w') as f:
for i in range(len(pred_mols_smi)):
f.write(f'{true_scafs_smi[i]} {true_mols_smi[i]} {pred_mols_smi[i]} {pred_rgroup_smi[i]} {protein_filename_list[i]}\n')
with open(vina_out_smi_path, 'w') as f:
for i in range(len(pred_mols_smi)):
f.write(f'{true_scafs_smi_ori[i]} {true_mols_smi_ori[i]} {pred_mols_smi[i]} {pred_rgroup_smi[i]} {protein_filename_list[i]}\n')
with Chem.SDWriter(open(out_sdf_path, 'w')) as writer:
for mol in pred_mols:
writer.write(mol)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--samples_path', action='store', type=str, required=False, default='')
parser.add_argument('--formatted_path', action='store', type=str, required=False, default='')
parser.add_argument('--true_smiles_path', action='store', type=str, required=False, default='')
args = parser.parse_args()
samples = args.samples_path
formatted = args.formatted_path
true_smiles_path = args.true_smiles_path
disable_rdkit_logging()
reformat(samples, formatted, true_smiles_path)