Bispecific antibody target pair discovery by high-throughput phenotypic screening using in vitro combinatorial Fab libraries.

Bispecific antibodies can uniquely influence cellular responses, but selecting target combinations for optimal functional activity remains challenging. Here we describe a high-throughput, combinatorial, phenotypic screening approach using a new bispecific antibody target discovery format, allowing screening of hundreds of target combinations. Simple in vitro mixing of Fab-fusion proteins from a diverse library enables the generation of thousands of screen-ready bispecific antibodies for high-throughput, biologically relevant assays. We identified an obligate bispecific co-targeting CD79a/b and CD22 as a potent inhibitor of human B cell activation from a short-term flow cytometry signaling assay. A long-term, high-content imaging assay identified anti-integrin bispecific inhibitors of human cell matrix accumulation targeting integrins ß1 and ß6 or αV and ß1. In all cases, functional activity was conserved from the bispecific screening format to a therapeutically relevant format. We also introduce a broader type of mechanistic screen whereby functional modulation of different cell subsets in peripheral blood mononuclear cells was evaluated simultaneously. We identified bispecific antibodies capable of activating different T cell subsets of potential interest for applications in oncology or infectious disease, as well as bispecifics abrogating T cell activity of potential interest to autoimmune or inflammatory disease. The bispecific target pair discovery technology described herein offers access to new target biology and unique bispecific therapeutic opportunities in diverse disease indications.

Structurally Mapping Antibody Repertoires.

Every human possesses millions of distinct antibodies. It is now possible to analyze this diversity via next-generation sequencing of immunoglobulin genes (Ig-seq). This technique produces large volume sequence snapshots of B-cell receptors that are indicative of the antibody repertoire. In this paper, we enrich these large-scale sequence datasets with structural information. Enriching a sequence with its structural data allows better approximation of many vital features, such as its binding site and specificity. Here, we describe the structural annotation of antibodies pipeline that maps the outputs of large Ig-seq experiments to known antibody structures. We demonstrate the viability of our protocol on five separate Ig-seq datasets covering ca. 35 m unique amino acid sequences from ca. 600 individuals. Despite the great theoretical diversity of antibodies, we find that the majority of sequences coming from such studies can be reliably mapped to an existing structure.