Antibodies are essential proteins that play a central role in immune recognition by binding specific antigen molecules. Although recent protein language models have enabled progress in single-chain protein modeling and generation, they often fall short in antigen-specific antibody design, where effective modeling requires explicit pairing between antibody and antigen, particularly at the epitope level.
arXiv:2606. 04154v1 Announce Type: cross Abstract: Antibodies neutralize foreign antigens by binding to specific surface regions called epitopes.
By Mansoor Ahmed, Huirong Chai, Haoxin Wang, Hemanth Venkateswara, Murray Patterson
arXiv:2603. 13431v3 Announce Type: replace-cross Abstract: Computational antibody design has seen rapid methodological progress, with dozens of deep generative methods proposed in the past three years, yet the field lacks a standardized benchmark for fair comparison and model development.
By Mansoor Ahmed, Nadeem Taj, Imdad Ullah Khan, Hemanth Venkateswara, Murray Patterson
arXiv:2605. 21610v2 Announce Type: replace Abstract: Antibody design methods condition on antigen structure to generate complementarity-determining regions (CDR), yet a systematic evaluation of baseline methods reveals that they largely ignore the antigen input.
By Mansoor Ahmed, Murray Patterson
arXiv:2605. 21600v2 Announce Type: replace Abstract: Computational antibody CDR design methods condition on antigen structure to generate binding loops.
By Mansoor Ahmed, Spencer VonBank, Nadeem Taj, Sujin Lee, Naila Jan, Murray Patterson
arXiv:2607. 05846v1 Announce Type: cross Abstract: Accurate ranking of antibody candidates according to their binding affinity is essential for therapeutic antibody discovery.
By Zhiyuan Chen, Jing Hu, Junzhe Wang, Yueyang Huang, Xinyi Yang, Zhaoyang Wang, Feng Zhu
Accurate ranking of antibody candidates according to their binding affinity is essential for therapeutic antibody discovery. However, existing methods treat affinity comparisons independently and ignore the contextual information encoded in other labeled comparisons, limiting their ability to capture antigen-specific binding landscapes.
arXiv:2609.00518v1 Announce Type: new
Abstract: Antibody-specific language models pretrained via masked language modeling (MLM) learn representations that are critical for downstream sequence design...
By Ayan Goel, Thomas A. Walton, Amirali Aghazadeh
DuaDeep-SeqAffinity is a sequence-only deep learning framework that predicts antibody–antigen binding affinity directly from primary amino acid sequences, eliminating the need for resolved 3D structures. The model processes the antigen and the antibody heavy and light chains as three independent streams, each embedded with a frozen ESM‑2 protein language model and passed through parallel Transformer and CNN branches before late fusion. On a sequence‑disjoint split of the AbRank benchmark, it achieves a Pearson correlation of 0.683, an R² of 0.460, and a pairwise ranking AUC of 0.895, outperforming single‑branch ablations and showing attention to CDR loops and epitope residues.
By Aicha Boutorh, Soumia Bouyahiaoui, Manel Kara Laouar, Sara Belhadj, Nour El Yakine Guendouz, Asma Boutorh
arXiv:2607. 18835v1 Announce Type: cross Abstract: Antibodies are essential therapeutic molecules, and their complementarity-determining regions (CDRs) form the primary antigen-recognition interface.
By Zhuo Yang, Jiaying He, Jiaqing Xie, Daolang Wang, Xipeng Qiu, Yuxin Wang, Tianfan Fu, Beilun Wang
arXiv:2607. 16263v1 Announce Type: new Abstract: Antibody expression ranking is a critical task in antibody design, yet its modelling is severely hindered by the scarcity of labeled experimental data.
By Josh Qixuan Sun, Morteza Babaie, Wenyang Hou, Mark Crowley, David Young
AbFlow is a one‑step flow‑matching framework that designs full‑atom antibodies end‑to‑end, focusing on the paratope region. It uses an equivariant Surface Multi‑channel Encoder to incorporate surface‑level antigen interaction data, refining especially the CDR‑H3 region. Experiments demonstrate that AbFlow generates superior antigen‑antibody complexes with improved binding affinity, particularly at the contact interface.
By Wenda Wang, Yang Zhang, Zhewei Wei, Wenbing Huang