Fig. 1. Overview of SMILES augmentation methods. (a) SMILES enumeration28 (used as a baseline in this work), where multiple SMILES strings are obtained by starting the graph traversal from different non-hydrogen atoms and/or by proceeding in different directions. (b) Token deletion, where new SMILES strings are generated by randomly removing tokens from the original string. (c) Atom masking, where atoms are randomly replaced with dummy tokens (‘[*]’). (d) Bioisosteric substitution, where pre-defined functional groups are substituted with their reported bioisosteres. (e) Self-training, where novel SMILES are generated by a trained CLM and used in turn to the initial set for the next training phase.
