AbFlow: End-to-end Paratope-Centric Antibody Design by Interaction Enhanced Flow Matching

Abstract:Antigen-antibody binding is a critical process in the immune response. Although recent progress has advanced antibody design, current methods lack a generative framework for end-to-end modeling of full-atom antibody structures and struggle to fully exploit antigen-specific geometric information for optimizing local binding interfaces and global structures. To overcome these limitations, we introduce AbFlow, a paratope-restricted one-step flow-matching framework for designing full-atom antibodies end-to-end. AbFlow incorporates an extended velocity field network featuring an equivariant Surface Multi-channel Encoder, which uses surface-level antigen interaction data to refine the antibody structure, particularly the CDR-H3 region. Extensive experiments in paratope-centric antibody design, multi-CDRs and full-atom antibody design, binding affinity optimization, and complex structure prediction show that AbFlow produces superior antigen-antibody complexes, especially at the contact interface, and markedly improves the binding affinity of generated antibodies.

Quantitative Methods (q-bio.QM); Artificial Intelligence (cs.AI); Computational Engineering, Finance, and Science (cs.CE)

arXiv:2602.07084 [q-bio.QM]

(or arXiv:2602.07084v2 [q-bio.QM] for this version)

https://doi.org/10.48550/arXiv.2602.07084 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.1145/3770854.3780296 Focus to learn more DOI(s) linking to related resources

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