抗体
互补决定区
肽库
计算生物学
抗原
免疫球蛋白轻链
核糖体
生物
分子生物学
亲和力成熟
噬菌体展示
核糖核酸
化学
生物化学
肽序列
遗传学
基因
作者
Benjamin T. Porebski,Matthew Balmforth,Gareth J. Browne,Aidan Riley,Kiarash Jamali,Maximillian J. L. J. Fürst,Mirko Velic,Andrew Buchanan,Ralph Minter,Tristan J. Vaughan,Philipp Holliger
标识
DOI:10.1038/s41551-023-01093-3
摘要
Abstract Developing therapeutic antibodies is laborious and costly. Here we report a method for antibody discovery that leverages the Illumina HiSeq platform to, within 3 days, screen in the order of 10 8 antibody–antigen interactions. The method, which we named ‘deep screening’, involves the clustering and sequencing of antibody libraries, the conversion of the DNA clusters into complementary RNA clusters covalently linked to the instrument’s flow-cell surface on the same location, the in situ translation of the clusters into antibodies tethered via ribosome display, and their screening via fluorescently labelled antigens. By using deep screening, we discovered low-nanomolar nanobodies to a model antigen using 4 × 10 6 unique variants from yeast-display-enriched libraries, and high-picomolar single-chain antibody fragment leads for human interleukin-7 directly from unselected synthetic repertoires. We also leveraged deep screening of a library of 2.4 × 10 5 sequences of the third complementarity-determining region of the heavy chain of an anti-human epidermal growth factor receptor 2 (HER2) antibody as input for a large language model that generated new single-chain antibody fragment sequences with higher affinity for HER2 than those in the original library.
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