Alternative initial models were generated from the initial model with additional template information via template-based modeling. A sequence profile was generated by searching sequences against the UniClust30 database 46 by using HHblits. Structure homologs were identified via the generated sequence profile from HHsearch with the Viterbi algorithm using the local alignment mode. The top 100 searched structures were compared with the initial model by using TM-align , and structures that had a similar fold to the initial model (TM-score > 0.6) were selected for further model building. For each selected structure, the sequence alignment between the target sequence and the template structure was generated by using HHalign with the MAC algorithm and using the global alignment mode. We allowed up to three alternative sequence alignments that had comparable alignment scores. Twelve models were generated for each sequence alignment by using MODELLER , and the best-scored model was selected as a final model for sequence alignment. Among the generated models, up to ten models were selected for further optimization based on a structure similarity cutoff, i.e. a TM-score of 0.6 or the best TM-score-0.2, whichever was greater. If less than two models were selected, we did not test the idea of alternative models for the target. Also, if there were any chain breaks, we did not try to build alternative models. During the benchmark, we identified experimental structures that were released after the first day of CASP of each target and removed them from the template list in order to generate refined models that can be compared to the performance of other groups during the respective rounds of CASP.