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).
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.