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Computational design of antibody-affinity improvement beyond in vivo maturation


Antibodies are used extensively in diagnostics and as therapeutic agents. Achieving high-affinity binding is important for expanding detection limits, extending dissociation half-times, decreasing drug dosages and increasing drug efficacy. However, antibody-affinity maturation in vivo often fails to produce antibody drugs of the targeted potency1, making further affinity maturation in vitro by directed evolution or computational design necessary. Here we present an iterative computational design procedure that focuses on electrostatic binding contributions and single mutants. By combining multiple designed mutations, a tenfold affinity improvement to 52 pM was engineered into the anti–epidermal growth factor receptor drug cetuximab (Erbitux), and a 140-fold improvement in affinity to 30 pM was obtained for the anti-lysozyme model antibody D44.1. The generality of the methods was further demonstrated through identification of known affinity-enhancing mutations in the therapeutic antibody bevacizumab (Avastin) and the model anti-fluorescein antibody 4-4-20. These results demonstrate computational capabilities for enhancing and accelerating the development of protein reagents and therapeutics.

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Figure 1: Designed high-affinity mutations in D44.1.
Figure 2: Designed high-affinity cetuximab mutant.
Figure 3: Comparison of calculated and experimental binding free energies.


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We thank S.L. Sazinsky for the gift of the 404SG material, and D. Lipovsek and R.T. Sauer for comments on the manuscript. This work was supported by a National Science Foundation Graduate Fellowship to S.M.L. and grants from the National Institutes of Health (CA96504 and GM65418).

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Authors and Affiliations



B.T. oversaw all computational aspects of the work, and K.D.W. oversaw all experimental aspects of the work. S.M.L. developed and adopted the design methods and software and carried out all computational and experimental studies. The authors as a group interpreted the results of the calculations and selected the mutants to create experimentally. S.M.L. drafted the manuscript, and all authors contributed to its editing.

Corresponding authors

Correspondence to K Dane Wittrup or Bruce Tidor.

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Supplementary Table 1–3, Supplementary Methods, Supplementary Figures 1–4 (PDF 131 kb)

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Lippow, S., Wittrup, K. & Tidor, B. Computational design of antibody-affinity improvement beyond in vivo maturation. Nat Biotechnol 25, 1171–1176 (2007).

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