Efficient generation of epitope-targeted antibodies with Germinal

Obtaining antibodies to specific protein targets is a widely important yet experimentally laborious process. Computational methods for antibody design have been limited by low success rates that require resource-intensive screening. Germinal is a generative pipeline that designs antibodies against specific epitopes with nanomolar binding affinities while requiring only low-n experimental testing. The 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. Germinal was tested against four diverse protein targets, resulting in functional antibodies across all targets and binder formats. Only 43-101 designs were tested for each antigen, demonstrating the method's efficiency. The validated designs exhibited robust expression in mammalian cells and high sequence and structural novelty. The open-source code and full computational and experimental protocols are available to facilitate wide adoption. Germinal has the potential to revolutionize the field of antibody design, enabling researchers to quickly and efficiently generate high-quality antibodies for various applications. However, it is essential to note that Germinal is a research-use-only (RUO) laboratory peptide supplier, and the peptides generated through this method should only be used for research purposes and not for human therapeutic use. Further testing and validation are required to ensure the safety and efficacy of these antibodies in humans.