| Literature DB >> 23872324 |
Brian D Harms1, Jeffrey D Kearns2, Sergio Iadevaia2, Alexey A Lugovskoy3.
Abstract
Antibodies are essential components of the adaptive immune system that provide protection from extracellular pathogens and aberrant cells in the host. Immunoglobulins G, which have been adapted for therapeutic use due to their exquisite specificity of target recognition, are bivalent homodimers composed of two antigen binding Fab arms and an immune cell recruiting Fc module. In recent years significant progress has been made in optimizing properties of both Fab and Fc components to derive antibodies with improved affinity, stability, and effector function. However, systematic analyses of the efficiency with which antibodies crosslink their targets have lagged, despite the well-recognized importance of this cross-arm binding for optimal antigen engagement. Such an understanding is particularly relevant given the variety of next-generation multispecific antibody scaffolds under development. In this manuscript we attempt to fill this gap by presenting a framework for analysis and optimization of antibody cross-arm engagement. We illustrate the power of this integrated approach by presenting case studies for rational multispecific antibody design based on quantitative assessment of the interplay between antibody valency, target expression, and cross-arm binding efficiency. We conclude that optimal design parameters for cross-arm binding strongly depend on the biological context of the disease, and that cross-arm binding efficiency needs to be considered for successful application of multispecific antibodies.Entities:
Keywords: Avidity; Bispecific antibody; Computational modeling; Cross-arm binding; HER2; HER3; HRG; IGF-1; IGF-1R; Immunoglobulin; Multispecific antibodies; dsIgG; dual-specific IgG; heregulin; human epidermal growth factor receptor 2; human epidermal growth factor receptor 3; insulin-like growth factor-1; insulin-like growth factor-1 receptor; pAKT; phosphorylated AKT
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Year: 2013 PMID: 23872324 DOI: 10.1016/j.ymeth.2013.07.017
Source DB: PubMed Journal: Methods ISSN: 1046-2023 Impact factor: 3.608