  We consider the problem of antibody sequence design given 3D structural
information. Building on previous work, we propose a fine-tuned inverse folding
model that is specifically optimised for antibody structures and outperforms
generic protein models on sequence recovery and structure robustness when
applied on antibodies, with notable improvement on the hypervariable CDR-H3
loop. We study the canonical conformations of complementarity-determining
regions and find improved encoding of these loops into known clusters. Finally,
we consider the applications of our model to drug discovery and binder design
and evaluate the quality of proposed sequences using physics-based methods.
