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. 2022 Jan 31;38(7):1877–1880. doi: 10.1093/bioinformatics/btac016

Table 1.

Performance comparison between AlphaFold2, ABodyBuilder, DeepAb and ABlooper for both test sets

Method CDR-H1 CDR-H2 CDR-H3 CDR-L1 CDR-L2 CDR-L3
Rosetta Antibody Benchmark
 AlphaFold2a 0.84 0.99 2.87 0.53 0.49 0.95
 ABodyBuilder 1.08 0.99 2.77 0.69 0.50 1.12
 DeepAb 0.83 0.93 2.44 0.50 0.44 0.85
 ABlooper 0.92 1.01 2.49 0.62 0.52 0.97
 ABlooper unrelaxed 0.90 1.03 2.45 0.61 0.51 0.93
SAbDab latest structures
 ABodyBuilder 1.24 1.07 3.25 0.88 0.57 1.03
 DeepAba 1.00 0.82 2.49 0.59 0.45 0.90
 ABlooper 1.14 0.97 2.72 0.74 0.55 1.04
 ABlooper Unrelaxed 1.14 0.99 2.66 0.73 0.54 1.01

The mean RMSD to the crystal structure across each test set for the six CDRs is shown. RMSDs for each CDR are calculated after superimposing their corresponding chain to the crystal structure. RMSDs are given in Angstroms (Å).

a

It is likely that AlphaFold2 used at least some of the structures in the benchmark set during training. Similarly, structures in the SAbDab Latest Structures set may have been used for training DeepAb.