DisAb: Self-Consistent Antibody Sequence–Structure Co-Design with Multi-Chain All-Atom Discrete Diffusion

Antibody design requires amino-acid sequence and 3D structure to remain mutually compatible under antigen conditions. Existing generative methods often model sequence in a discrete space but structure in continuous geometric spaces, resulting in heterogeneous generation processes that are difficult to synchronize and reuse across different design tasks. We introduce DisAb (Discrete Diffusion for Antibody), a unified framework that represents antibody sequence and multi-chain all-atom structure as residue-aligned discrete tokens and jointly generates them through a single masked discrete diffusion process. To enable this formulation, we develop DisAb-VQ, to our knowledge the first residue-level VQ-VAE that tokenizes multi-chain atom14 protein geometry while preserving intra-chain structure and relative inter-chain placement. We further introduce Boltz-2-based sequence–structure self-consistency as a reference-free potential for sequential Monte Carlo (SMC) guidance at inference time. We evaluate DisAb in both bound-antigen design and the more challenging unbound setting, where the complete bound antigen–VH–VL complex is generated from an isolated antigen monomer. DisAb-VQ accurately reconstructs multi-chain all-atom structures, while DisAb achieves an Aligned DockQ of $0.692$ in the bound setting, improved to $0.711$ with SMC guidance. In the unbound setting, SMC improves raw DockQ from $0.129$ to $0.149$ while also improving VH–VL geometry, CDR sequence recovery, and sequence–structure self-consistency. These results demonstrate that unified discrete modeling provides a flexible framework for antibody design.