Google Summer of Code 2022

These SMILES can be analysed using the RDKit library to get information about the atoms and bonds in the molecules. Molecular fingerprinting is a vectorized representation of molecules capturing precise details of atomic configurations. During the featurization process, a molecule is decomposed into substructures (e.g., fragments) of a fixed-length binary fingerprint assembled into an array whose each element is either 1 or 0. For this project, I implemented atomic and bond-level featurization and molecule-level (global) featurization in DeepChem, specific to D-MPNN model requirements. The D-MPNN paper [1] suggested 133 features for each atom and 14 features for each bond in a molecule. The individual features are extracted from SMILES using RDKit library and one-hot encoded to get vectorized representation.