Approaches in literature are divided into two general approaches: using manually curated substructure lists to identify FGs or automatic identification methods. Ertl's algorithm 34 is a most recent example of the latter, which automatically extracts FGs iterating through atoms in a molecule, and is easily implemented in cheminformatics libraries such as CDK and RDKit. The RDKit implemented algorithm was thus adapted in this approach to account for bonded hydrogens as well as the first degree environment (nearest neighbors) around the functional group. For instance, 1 contains hydroxyl (OH) and amine (NH2) functional groups (highlighted in blue in Figure ) which were expanded to include the aromatic carbons (highlighted in green in Figure ), forming FG fragments Car-OH and Car-NH2. These are henceforth referred to as carrier fragments. It is important to note that the user is not restricted to first-degree environments but can employ higher-degree environments to capture more molecular context. However, keeping in mind that there is an inherent trade-off between template specificity and generalizability, the first-degree environment is used in this work. The final output of this step is a list of carrier fragments that belong to each query species, in this case: aromatic hydroxyl (belonging to 1 and 3), aromatic amine (belonging to , anhydride (belonging to , acetamido (belonging to and carboxylic (belonging to fragments.