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

Bioorg Med Chem Lett. 2009 Jul 15;19(14):3744-7. doi: 10.1016/j.bmcl.2009.05.005. Epub 2009 May 7.


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 K(I) 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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acid Substitution
  • Animals
  • Antibodies / chemistry*
  • Antibodies / genetics
  • Antibodies / immunology
  • Computational Biology
  • Cross Reactions
  • Drug Design
  • Humans
  • Membrane Proteins
  • Mice
  • Mutation
  • Protein Engineering
  • Protein Structure, Tertiary
  • Serine Endopeptidases / chemistry
  • Serine Endopeptidases / metabolism
  • Serine Proteinase Inhibitors / chemistry*
  • Serine Proteinase Inhibitors / metabolism
  • Species Specificity
  • Thermodynamics


  • Antibodies
  • Membrane Proteins
  • Serine Proteinase Inhibitors
  • Serine Endopeptidases
  • ST14 protein, human
  • St14 protein, mouse