We explored a method of compound optimization based on the reconstruction of SMILES from Morgan fingerprints. In this methos, we used a vector of Morgan fingerprint (radius 2, 4096 bits) with the number of duplicate bits as input data (Fig. ), and trained the Transformer with the same SMILES sequence as output as above. After the Transformer training was finished, we computed the differences between the Morgan fingerprint (radius 2, 4096 bits, with the number of duplicate bits) of the original compounds and the converted compounds from the Matched Molecular Pair (MMP) analysis data 6) by He et al. to perform substructure conversion of the compounds needed for compound optimization. After excluding sequences containing negative values, we added the computed differences to the Morgan fingerprint of an arbitrary test compound, and created provisional sequences for new compounds (Fig. ). We used the trained Transformer to reconstruct SMILES strings from the input sequence and checked whether the compound conversion was performed correctly.