We downloaded ZINC dataset from here and canonicalized it. We used the following function to canonicalize the data and removed some SMILES that cannot be read by RDKit.
from rdkit import Chem
def canonicalize(mol):
mol = Chem.MolToSmiles(Chem.MolFromSmiles(mol),True)
return mol
We randomly split the preprocessed data into train and validation. The ratio is 9 : 1.
We downloaded ZINC dataset from here and canonicalized it. We used the following function to canonicalize the data and removed some SMILES that cannot be read by RDKit.
from rdkit import Chem
def canonicalize(mol):
mol = Chem.MolToSmiles(Chem.MolFromSmiles(mol),True)
return mol
We randomly split the preprocessed data into train and validation. The ratio is 9 : 1.