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Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening. 2023

Benjamin T Porebski, and Matthew Balmforth, and Gareth Browne, and Aidan Riley, and Kiarash Jamali, and Maximillian J L J Fürst, and Mirko Velic, and Andrew Buchanan, and Ralph Minter, and Tristan Vaughan, and Philipp Holliger
MRC Laboratory of Molecular Biology, Cambridge, UK.

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 108 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 × 106 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 × 105 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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