Cited by 342Monoclonal and Polyclonal Antibodies ResearchProtein Structure and Dynamicsvaccines and immunoinformatics approaches

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Computational design of antibody-affinity improvement beyond in vivo maturation

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Lippow, Shaun M, Wittrup, K Dane, Tidor, Bruce·2007·Nature Biotechnology

DOI 10.1038/nbt1336PMC PMC2803018

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Abstract

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 potency, 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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Authors: Lippow, S. M., Wittrup, K. D., & Tidor, B.
Affiliations: Massachusetts Institute of Technology (US)
Corresponding author: Wittrup, K Dane
Tidor, Bruce
ORCID: Wittrup, K Dane
Tidor, Bruce
Venue: Nature Biotechnology
Publisher: Springer Science and Business Media LLC
Published: 2007-09-23
Volume: 25
Issue: 10
Pages: 1171-1176
ISSN: 0733-222X (ISSN-L)
1087-0156
1546-1696
DOI: 10.1038/nbt1336
PMC: PMC2803018
OpenAlex: W2083028331
Cited by: 342
References: 30
Citations by year: 2026: 9 · 2025: 11 · 2024: 14 · 2023: 17 · 2022: 24 · 2021: 14 · 2020: 22 · 2019: 15 · 2018: 23 · 2017: 18 · 2016: 15 · 2015: 24 · 2014: 23 · 2013: 21 · 2012: 21
FWCI: 14.05
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.springer.com/tdm (tdm)
Locations: Nature Biotechnology (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Science Foundation
National Institutes of Health
National Cancer Institute (CA96504, R01CA096504)
National Institute of General Medical Sciences (GM65418, R56GM065418, R01GM065418)
Topics: Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
Keywords: affinity maturation, computational antibody design, point mutations, cetuximab, anti-EGFR monoclonal antibody, bevacizumab, anti-fluorescein antibody, anti-lysozyme antibody, therapeutic antibodies, directed evolution, binding affinity enhancement
MeSH terms: Antibodies, Antibody Affinity, Antigens, Genetic Engineering, Models, Biological, Models, Molecular, Muramidase, Mutation, Protein Binding, Protein Conformation, Yeasts, Computer-Aided Design

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Computational design of antibody-affinity improvement beyond in vivo maturation

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