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Information-Driven Antibody–Antigen Modelling with HADDOCK

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Computer-Aided Antibody Design

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

Abstract

In the recent years, therapeutic use of antibodies has seen a huge growth, "due to their inherent proprieties and technological advances in the methods used to study and characterize them. Effective design and engineering of antibodies for therapeutic purposes are heavily dependent on knowledge of the structural principles that regulate antibody–antigen interactions. Several experimental techniques such as X-ray crystallography, cryo-electron microscopy, NMR, or mutagenesis analysis can be applied, but these are usually expensive and time-consuming. Therefore computational approaches like molecular docking may offer a valuable alternative for the characterization of antibody–antigen complexes.

Here we describe a protocol for the prediction of the 3D structure of antibody–antigen complexes using the integrative modelling platform HADDOCK. The protocol consists of (1) the identification of the antibody residues belonging to the hypervariable loops which are known to be crucial for the binding and can be used to guide the docking and (2) the detailed steps to perform docking with the HADDOCK 2.4 webserver following different strategies depending on the availability of information about epitope residues.

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Acknowledgments

This work is supported by the European Union Horizon 2020 BioExcel (grant # 675728 and 823830), EOSC-hub (grant # 777536) and EGI-ACE (grant # 101017567) projects.

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Correspondence to Alexandre M. J. J. Bonvin .

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Ambrosetti, F., Jandova, Z., Bonvin, A.M.J.J. (2023). Information-Driven Antibody–Antigen Modelling with HADDOCK. 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_14

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  • DOI: https://doi.org/10.1007/978-1-0716-2609-2_14

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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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