Massive Sampling Strategy for Antibody–Antigen Targets in <scp>CAPRI</scp> Round 55 With <scp>MassiveFold</scp>

Massive sampling with AlphaFold2 improves protein-protein complex predictions. This has been shown during the last CASP15-CAPRI blind prediction round by the AFsample tool. However, more difficult targets including antibody-antigen binding remain challenging. CAPRI Round 55 consisted of three antibody-antigen targets and one heterotrimer. We used our AlphaFold2-based MassiveFold, running 6 prediction pools, each with their own set of parameters, to produce in total more than 6000 predictions per target. We show here that massive sampling categorically produces acceptable to high quality predictions, however it is clear that the AlphaFold2 confidence score cannot be used to identify the best models in the set. We also show that, contrary to what was done before for CASP15-CAPRI with AFsample, increasing the sampling without activating the dropout provides the best models for most of the targets of Round 55.