ArticlePLoS computational biology2025
An expandable synthetic library of human paired antibody sequences.
Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- From Molecular Precision to Clinical Practice: A Comprehensive Review of Bispecific and Trispecific Antibodies in Hematologic Malignancies.International journal of molecular sciences · 2025Review
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Authors and funding
6 authors.
Funding
Abstract
The potential diversity in the global repertoire of human antibody sequences is currently not well understood due to the limited existing paired antibody heavy-light chain sequence data that has been hindered by the low throughput and high costs of current single-cell sequencing methods. Here, we report IgHuAb, a large language model for high-throughput generation of paired human antibody sequences. Using IgHuAb, we created SynAbLib, a synthetic human antibody library that mimics population-level features of naturally occurring human antibody sequences, yet is associated with significantly greater diversity in sequence space. Further, experimental validation of a diverse set of antibodies from SynAbLib showed robust expression yields. IgHuAb and SynAbLib provide a readily expandable platform for human monoclonal antibody generation that can be efficiently mined for antibody sequences with target properties.
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