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TitleEfficient generation of epitope-targeted antibodies with Germinal.
Journal, issue, pagesNat. Biotechnol., Year 2026
Publish dateMay 15, 2026
AuthorsLuis S Mille-Fragoso / Claudia L Driscoll / John N Wang / Haoyu Dai / Talal Widatalla / Jim L Zhang / Xiaowei Zhang / Bing Rao / Liang Feng / Brian L Hie / Xiaojing J Gao /
PubMed AbstractObtaining antibodies to specific protein targets is a widely important yet experimentally laborious process. Meanwhile, computational methods for antibody design have been limited by low success ...Obtaining antibodies to specific protein targets is a widely important yet experimentally laborious process. Meanwhile, computational methods for antibody design have been limited by low success rates that require resource-intensive screening. Here we introduce Germinal, a broadly enabling generative pipeline that designs antibodies against specific epitopes with nanomolar binding affinities while requiring only low-n experimental testing. Our method co-optimizes antibody structure and sequence by integrating a structure predictor with an antibody-specific protein language model to perform de novo design of functional complementarity-determining regions onto a user-specified structural framework. When tested against four diverse protein targets, Germinal designed functional antibodies across all targets and binder formats, testing only 43-101 designs for each antigen. Validated designs also exhibited robust expression in mammalian cells and high sequence and structural novelty. We provide open-source code and full computational and experimental protocols to facilitate wide adoption.
External linksNat. Biotechnol. / PubMed:42337361 / PubMed Central
MethodsEM (single particle)
Resolution3.93 Å
Structure data

77181
EMDB Unreleased entry

35tl

EMDB-77181, PDB-35tl:
PD-L1 complexed with Germinal-designed anti-PD-L1 scFv H5
Method: EM (single particle) / Resolution: 3.93 Å

Source
  • synthetic construct (others)
  • homo sapiens (human)
KeywordsDE NOVO PROTEIN / scfv / designed / binder

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