Construction of a rationally designed antibody platform for sequencing-assisted selection

Abstract

Antibody discovery platforms have become an important source of both therapeutic biomolecules and research reagents. Massively parallel DNA sequencing can be used to assist antibody selection by comprehensively monitoring libraries during selection, thus greatly expanding the power of these systems. We have therefore constructed a rationally designed, fully defined single-chain variable fragment (scFv) library and analysis platform optimized for analysis with short-read deep sequencing. Sequence-defined oligonucleotide libraries encoding three complementarity-determining regions (L3 from the light chain, H2 and H3 from the heavy chain) were synthesized on a programmable microarray and combinatorially cloned into a single scFv framework for molecular display. Our unique complementarity-determining region sequence design optimizes for protein binding by utilizing a hidden Markov model that was trained on all antibody-antigen cocrystal structures in the Protein Data Bank. The resultant ~10(12)-member library was produced in ribosome-display format, and comprehensively analyzed over four rounds of antigen selections by multiplex paired-end Illumina sequencing. The hidden Markov model scFv library generated multiple binders against an emerging cancer antigen and is the basis for a next-generation antibody production platform.