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

2026-02-06

AI Summary

This work proposes AbFlow, a novel end-to-end all-atom antibody generation framework that addresses the limitations of existing methods in effectively leveraging antigen geometric information to optimize binding interfaces. AbFlow introduces, for the first time, an equivariant surface multi-channel encoder within a flow matching and optimal transport framework, enabling epitope-centered, all-atom antibody structure generation with particular accuracy in modeling the CDR-H3 region. By deeply integrating geometric information from the antigen–antibody interface, the method significantly outperforms current approaches in epitope-focused design, multi-CDR modeling, and affinity optimization. The generated antibody–antigen complexes exhibit superior performance in terms of interfacial contacts and binding affinity.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Learning with Manifolds
• Computer Vision: Learning & Optimization for CV

Application Category

• Search and Retrieval-Augmented AI: Agentic search
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies

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 flow-matching framework that leverages optimal transport to design 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 paratoep-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.

Problem

• antibody design
• paratope
• antigen-antibody binding
• full-atom structure
• geometric information

Innovation

• flow matching
• equivariant surface encoder
• paratope-centric design
• full-atom antibody generation
• antigen-antibody interaction