Improving the species cross-reactivity of an antibody using computational design

The high degree of specificity displayed by antibodies often results in varying potencies against antigen orthologs, which can affect the efficacy of these molecules in different animal models of disease. We have used a computational design strategy to improve the species cross-reactivity of an antibody-based inhibitor of the cancer-associated serine protease MT-SP1. In silico predictions were tested in vitro, and the most effective mutation, T98R, was shown to improve antibody affinity for the mouse ortholog of the enzyme 14-fold, resulting in an inhibitor with a KI of 340 pM. This improved affinity will be valuable when exploring the role of MT-SP1 in mouse models of cancer, and the strategy outlined here could be useful in fine-tuning antibody specificity.

Small antigenic differences between the human and mouse versions of MT-SP1 greatly affect the binding of an anti-MT-SP1 antibody. The cross-reactivity of the antibody was improved by making computationally-designed point mutants of antibody residues that contact these divergent residues.Figure optionsDownload as PowerPoint slide