Integrating In Silico and In Vitro Tools for Optimized Antibody Development-Design of Therapeutic Anti-oxMIF Antibodies.

Background: Rigorous assessment of antibody developability is crucial for optimizing lead candidates before progressing to clinical studies. Recent advances in predictive tools for protein structures, surface properties, stability, and immunogenicity have streamlined the development of new biologics. However, accurate prediction of the impact of single amino acid substitutions on antibody structures remains challenging, due to the diversity of complementarity-determining regions (CDRs), particularly CDR3s.

Methods: In this study, we combined in silico tools with in vitro assessments to engineer improved antibodies against the oxidized isoform of the macrophage migration inhibitory factor (oxMIF), building on the first generation anti-oxMIF antibody imalumab.

Results: We identified hydrophobic hotspots conferring increased self-interaction and aggregation propensity on imalumab, which unravels its unusually short half-life in humans. By introducing mutations into the variable regions, we addressed these liabilities. Structural prediction tools and molecular dynamics simulations guided the selection of mutations, which were then experimentally validated. The lead candidate antibody, C0083, demonstrated reduced hydrophobicity and self-interaction due to the restructuring of its heavy chain CDR3 loop. Despite these structural changes, C0083 retained target specificity and binding affinity to oxMIF.

Conclusions: Altogether, this study shows that a small number of well-selected mutations was sufficient to substantially improve the biophysicochemical properties of imalumab.