Massive sampling strategy for antibody-antigen targets in CAPRI Round 55
with MassiveFold
Abstract
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 AlphaFold 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 does provide the best models in
most cases.
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