To extend the D-MPNN architecture for reaction property prediction, Chemprop incorporates the CGR method, which enables users to input SMARTS, an efficient notation for concatenating the SMILES of reactants, solvents, and products. CGR represents chemical reactions by combining the reactant(s) and product(s) into a single molecular graph. A key advantage of CGR is its ability to connect disjoint parts between reactant and product graphs, facilitating message passing among all atoms. As a result, the model architecture remains consistent and can be directly applied to reaction tasks.