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Antibody Affinity Maturation Using Computational Methods: From an Initial Hit to Small-Scale Expression of Optimized Binders

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Computer-Aided Antibody Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2552))

Abstract

Nanobodies (VHHs) are engineered fragments of the camelid single-chain immunoglobulins. The VHH domain contains the highly variable segments responsible for antigen recognition. VHHs can be easily produced as recombinant proteins. Their small size is a good advantage for in silico approaches. Computer methods represent a valuable strategy for the optimization and improvement of their binding affinity. They also allow for epitope selection offering the possibility to design new VHHs for regions of a target protein that are not naturally immunogenic. Here we present an in silico mutagenic protocol developed to improve the binding affinity of nanobodies together with the first step of their in vitro production. The method, already proven successful in improving the low Kd of a nanobody hit obtained by panning, can be employed for the ex novo design of antibody fragments against selected protein target epitopes.

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Acknowledgments

This work has been funded by the Italian Association for Cancer Research (AIRC) through the grant “My First AIRC grant” Rif.18510 (PI: Fortuna) and the CINECA Awards N. HP10C70TG1, 2018, for the availability of high performance computing resources and support.

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Authors and Affiliations

  1. Department of Chemical and Pharmaceutical Sciences, University of Trieste, Trieste, Italy

    Barbara Medagli, Rita De Zorzi & Sara Fortuna

  2. CONCEPT Lab, Istituto Italiano di Tecnologia, Genova, Italy

    Miguel A. Soler & Sara Fortuna

  3. Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy

    Miguel A. Soler

Authors
  1. Barbara Medagli
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  2. Miguel A. Soler
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  3. Rita De Zorzi
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  4. Sara Fortuna
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Corresponding authors

Correspondence to Barbara Medagli or Sara Fortuna .

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Editors and Affiliations

  1. School of Engineering, The University of Tokyo, Tokyo, Japan

    Kouhei Tsumoto

  2. School of Engineering, The University of Tokyo, Tokyo, Japan

    Daisuke Kuroda

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Medagli, B., Soler, M.A., De Zorzi, R., Fortuna, S. (2023). Antibody Affinity Maturation Using Computational Methods: From an Initial Hit to Small-Scale Expression of Optimized Binders. In: Tsumoto, K., Kuroda, D. (eds) Computer-Aided Antibody Design. Methods in Molecular Biology, vol 2552. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2609-2_19

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  • DOI: https://doi.org/10.1007/978-1-0716-2609-2_19

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2608-5

  • Online ISBN: 978-1-0716-2609-2

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