Efficient generation of epitope-targeted de novo antibodies with Germinal
Автор: Valence Labs
Загружено: 2025-11-25
Просмотров: 360
Paper: Efficient generation of epitope-targeted de novo antibodies with Germinal
https://www.biorxiv.org/content/10.11...
Abstract: Obtaining novel antibodies against 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 currently require resource-intensive screening. Here, we introduce Germinal, a broadly enabling generative framework 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 (CDRs) onto a user-specified structural framework. When tested against four diverse protein targets, Germinal achieved an experimental success rate of 4-22% across all targets, testing only 43-101 designs for each antigen. Validated nanobodies also exhibited robust expression in mammalian cells and nanomolar binding affinities. We provide open-source code and full computational and experimental protocols to facilitate wide adoption. Germinal represents a milestone in efficient, epitope-targeted de novo antibody design, with notable implications for the development of molecular tools and therapeutics.
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