Modeling Antibody-Antigen Complexes by Information-Driven Docking.
ClusPro
H3 modeling
HADDOCK
LightDock
ZDOCK
antibody
binding sites
conformational changes
docking
Journal
Structure (London, England : 1993)
ISSN: 1878-4186
Titre abrégé: Structure
Pays: United States
ID NLM: 101087697
Informations de publication
Date de publication:
07 01 2020
07 01 2020
Historique:
received:
22
03
2019
revised:
03
07
2019
accepted:
18
10
2019
pubmed:
16
11
2019
medline:
2
10
2020
entrez:
16
11
2019
Statut:
ppublish
Résumé
Antibodies are Y-shaped proteins essential for immune response. Their capability to recognize antigens with high specificity makes them excellent therapeutic targets. Understanding the structural basis of antibody-antigen interactions is therefore crucial for improving our ability to design efficient biological drugs. Computational approaches such as molecular docking are providing a valuable and fast alternative to experimental structural characterization for these complexes. We investigate here how information about complementarity-determining regions and binding epitopes can be used to drive the modeling process, and present a comparative study of four different docking software suites (ClusPro, LightDock, ZDOCK, and HADDOCK) providing specific options for antibody-antigen modeling. Their performance on a dataset of 16 complexes is reported. HADDOCK, which includes information to drive the docking, is shown to perform best in terms of both success rate and quality of the generated models in both the presence and absence of information about the epitope on the antigen.
Identifiants
pubmed: 31727476
pii: S0969-2126(19)30352-1
doi: 10.1016/j.str.2019.10.011
pii:
doi:
Substances chimiques
Antigen-Antibody Complex
0
Epitopes
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
119-129.e2Informations de copyright
Copyright © 2019 Elsevier Ltd. All rights reserved.