The HLD I-II dataset for training models used in the third round of experiments was created by a similar protocol. As input sequences, only DhlA and LinB were selected together with all 19 sequences in the "Other known sequences" input field. The resulting dataset was composed of 4053 sequences (job ID d6cv1o). As a query for MSA preprocessing, the DhaA sequence (Uniprot ID P0A3G3) was selected. Experimental results from rounds 1 and 2 indicated that the poor solubility might stem from many deletions suggested in the reconstructed sequences. Therefore, we adjusted parameters of MSA preprocessing to lower the number of gaps. In addition to the previous preprocessing steps, we implemented a further refinement by excluding columns from the MSA where amino acid symbols were present in the query if the column contained more than 80% gaps (>70% for Model 3). These excluded query amino acids were stored separately and reintegrated into their original positions in the generated sequence. Also, we did not perform 90% identity sequence clustering.