This workflow provides a practical route from immune-repertoire discovery to binding-positive humanized antibodies and applied the workflow to antibodies against amyloid-β (Aβ)-derived preparations.
Abstract
Therapeutic antibody development requires workflows that integrate antigen-reactive clone discovery with efficient humanization and early developability assessment. Here, we combined immune yeast fragment antigen-binding (Fab) display with single-round focused humanization and applied the workflow to antibodies against amyloid-β (Aβ)-derived preparations. Immunization with Aβ1-42 aggregate preparations generated a Fab-display library with a diversity of approximately 3.5 × 108. Magnetic enrichment followed by fluorescence-activated cell sorting (FACS) identified three sequence-distinct immunoglobulin G (IgG)-format candidates, of which CLAB17 and CLAB45 were advanced to humanization. Structure-guided libraries sampled framework positions predicted to support complementarity-determining regions (CDRs) or heavy-and light-chain variable-domain packing, and a single FACS round recovered binding-positive variants CLAB17-h2 and CLAB45-h8. Both retained the parental CDRs and showed increased predicted humanness, favorable computational developability triage profiles, and high purity by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). By enzyme-linked immunosorbent assay (ELISA), CLAB17-h2 showed a lower apparent half-maximal effective concentration (EC50) for Aβ1-42AggreSure, whereas CLAB45-h8 showed a lower apparent EC50 for pyroglutamate-modified Aβ3-42 (AβpE3-42). Because the preparations were not resolved into defined assembly states, these antibodies are considered Aβ-preparation-binding rather than aggregate-state-selective candidates. This workflow provides a practical route from immune-repertoire discovery to binding-positive humanized antibodies.
The findings support the feasibility of this workflow for research-grade and diagnostic antibody discovery, while broader evaluation will require larger candidate cohorts, independent biological validation, and additional antigen classes.
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