uniref30 [46G]

wget -bqc http://wwwuser.gwdg.de/~compbiol/uniclust/2020_06/UniRef30_2020_06_hhsuite.tar.gz

BFD [272G]

wget -bqc https://bfd.mmseqs.com/bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt.tar.gz

structure templates (including *_a3m.ffdata, *_a3m.ffindex) [over 100G]

wget -bqc https://files.ipd.uw.edu/pub/RoseTTAFold/pdb100_2021Mar03.tar.gz

for CASP14 benchmarks, we used this one: https://files.ipd.uw.edu/pub/RoseTTAFold/pdb100_2020Mar11.tar.gz

tar xfz weights.tar.gz mkdir -p bfd tar xfz bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt.tar.gz -C ./bfd

tar xfz pdb100_2021Mar03.tar.gz

mkdir -p UniRef30_2020_06 tar xfz UniRef30_2020_06_hhsuite.tar.gz -C ./UniRef30_2020_06

resources

Cores: 1
CPU Utilized: 01:15:07
CPU Efficiency: 45.94% of 02:43:30 core-walltime
Memory Utilized: 39.91 GB
Memory Efficiency: 99.77% of 40.00 GB

first time running forget the setting of anaconda environment end at the final end2end step