An application of RNN to the inverse-QSAR problem

RNN model was used in solution of inverse QSAR problem. Authors demonstrate an efficient approach in generating new molecules de nova with desired Activity values. They used SMILES representations of given set and trained a network capable of producing new series of symbols.