A fundamental problem in computational chemistry is to find a set of reactants to synthesize
a target molecule, aka retrosynthesis prediction. Existing state-of-the-art methods rely on
matching the target molecule with a large set of reaction templates, which are very
computationally expensive and also suffer from the problem of coverage. In this paper, we
propose a novel template-free approach called G2Gs by transforming a target molecular
graph into a set of reactant molecular graphs. G2Gs first splits the target molecular graph …