It is important to remember that we are using two AI components in our computational workflow, which can be trained jointly or independently from each other. In this proof-of-principle work, we started with an existing generative MLM model that originally targeted the generation of drug candidates for molecular therapeutics , while the GCNN surrogate for the prediction of HOMO-LUMO gaps was specifically trained as part of this work.