Information-Driven Antibody-Antigen Modelling with HADDOCK.
Antibody
HADDOCK
Information-driven docking
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2023
2023
Historique:
entrez:
8
11
2022
pubmed:
9
11
2022
medline:
11
11
2022
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 36346597
doi: 10.1007/978-1-0716-2609-2_14
doi:
Substances chimiques
Antigen-Antibody Complex
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
267-282Informations de copyright
© 2023. Springer Science+Business Media, LLC, part of Springer Nature.
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